A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape.

PubMed

Lausch, Angela; Pause, Marion; Merbach, Ines; Zacharias, Steffen; Doktor, Daniel; Volk, Martin; Seppelt, Ralf

2013-02-01

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the "One Sensor at Different Scales" (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R (2) of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.

Multi-scale variation in spatial heterogeneity for microbial community structure in an eastern Virginia agricultural field

NASA Technical Reports Server (NTRS)

Franklin, Rima B.; Mills, Aaron L.

2003-01-01

To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of community structure in a wheat field in eastern Virginia (USA). Nearly 200 soil samples were collected at a variety of separation distances ranging from 2.5 cm to 11 m. Whole-community DNA was extracted from each sample, and community structure was compared using amplified fragment length polymorphism (AFLP) DNA fingerprinting. Relative similarity was calculated between each pair of samples and compared using geostatistical variogram analysis to study autocorrelation as a function of separation distance. Spatial autocorrelation was found at scales ranging from 30 cm to more than 6 m, depending on the sampling extent considered. In some locations, up to four different correlation length scales were detected. The presence of nested scales of variability suggests that the environmental factors regulating the development of the communities in this soil may operate at different scales. Kriging was used to generate maps of the spatial organization of communities across the plot, and the results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot, and this is thought to be due to the variable response of individual populations to spatial heterogeneity associated with soil properties. c2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

Beta diversity at different spatial scales: plant communities in organic and conventional agriculture.

PubMed

Gabriel, Doreen; Roschewitz, Indra; Tscharntke, Teja; Thies, Carsten

2006-10-01

Biodiversity studies that guide agricultural subsidy policy have generally compared farming systems at a single spatial scale: the field. However, diversity patterns vary across spatial scales. Here, we examined the effects of farming system (organic vs. conventional) and position in the field (edge vs. center) on plant species richness in wheat fields at three spatial scales. We quantified alpha-, beta-, and gamma-diversity at the microscale in 800 plots, at the mesoscale in 40 fields, and at the macroscale in three regions using the additive partitioning approach, and evaluated the relative contribution of beta-diversity at each spatial scale to total observed species richness. We found that alpha-, beta-, and gamma-diversity were higher in organic than conventional fields and higher at the field edge than in the field center at all spatial scales. In both farming systems, beta-diversity at the meso- and macroscale explained most of the overall species richness (up to 37% and 25%, respectively), indicating considerable differences in community composition among fields and regions due to environmental heterogeneity. The spatial scale at which beta-diversity contributed the most to overall species richness differed between rare and common species. Total richness of rare species (present in < or = 5% of total samples) was mainly explained by differences in community composition at the meso- and macroscale (up to 27% and 48%, respectively), but only in organic fields. Total richness of common species (present in > or = 25% of total samples) was explained by differences in community composition at the micro- and mesoscale (up to 29% and 47%, respectively), i.e., among plots and fields, independent of farming system. Our results show that organic farming made the greatest contribution to total species richness at the meso (among fields) and macro (among regions) scale due to environmental heterogeneity. Hence, agri-environment schemes should exploit this large-scale contribution of beta-diversity by tailoring schemes at regional scales to maximize dissimilarity between conservation areas using geographic information systems rather than focusing entirely at the classical local-field scale, which is the current practice.

Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales

NASA Astrophysics Data System (ADS)

Abiodun, Olanrewaju O.; Guan, Huade; Post, Vincent E. A.; Batelaan, Okke

2018-05-01

In most hydrological systems, evapotranspiration (ET) and precipitation are the largest components of the water balance, which are difficult to estimate, particularly over complex terrain. In recent decades, the advent of remotely sensed data based ET algorithms and distributed hydrological models has provided improved spatially upscaled ET estimates. However, information on the performance of these methods at various spatial scales is limited. This study compares the ET from the MODIS remotely sensed ET dataset (MOD16) with the ET estimates from a SWAT hydrological model on graduated spatial scales for the complex terrain of the Sixth Creek Catchment of the Western Mount Lofty Ranges, South Australia. ET from both models was further compared with the coarser-resolution AWRA-L model at catchment scale. The SWAT model analyses are performed on daily timescales with a 6-year calibration period (2000-2005) and 7-year validation period (2007-2013). Differences in ET estimation between the SWAT and MOD16 methods of up to 31, 19, 15, 11 and 9 % were observed at respectively 1, 4, 9, 16 and 25 km2 spatial resolutions. Based on the results of the study, a spatial scale of confidence of 4 km2 for catchment-scale evapotranspiration is suggested in complex terrain. Land cover differences, HRU parameterisation in AWRA-L and catchment-scale averaging of input climate data in the SWAT semi-distributed model were identified as the principal sources of weaker correlations at higher spatial resolution.

Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images.

PubMed

Al-Khafaji, Suhad Lateef; Jun Zhou; Zia, Ali; Liew, Alan Wee-Chung

2018-02-01

Spectral-spatial feature extraction is an important task in hyperspectral image processing. In this paper we propose a novel method to extract distinctive invariant features from hyperspectral images for registration of hyperspectral images with different spectral conditions. Spectral condition means images are captured with different incident lights, viewing angles, or using different hyperspectral cameras. In addition, spectral condition includes images of objects with the same shape but different materials. This method, which is named spectral-spatial scale invariant feature transform (SS-SIFT), explores both spectral and spatial dimensions simultaneously to extract spectral and geometric transformation invariant features. Similar to the classic SIFT algorithm, SS-SIFT consists of keypoint detection and descriptor construction steps. Keypoints are extracted from spectral-spatial scale space and are detected from extrema after 3D difference of Gaussian is applied to the data cube. Two descriptors are proposed for each keypoint by exploring the distribution of spectral-spatial gradient magnitude in its local 3D neighborhood. The effectiveness of the SS-SIFT approach is validated on images collected in different light conditions, different geometric projections, and using two hyperspectral cameras with different spectral wavelength ranges and resolutions. The experimental results show that our method generates robust invariant features for spectral-spatial image matching.

River eutrophication: irrigated vs. non-irrigated agriculture through different spatial scales.

PubMed

Monteagudo, Laura; Moreno, José Luis; Picazo, Félix

2012-05-15

The main objective of this study was to determine how spatial scale may affect the results when relating land use to nutrient enrichment of rivers and, secondly, to investigate which agricultural practices are more responsible for river eutrophication in the study area. Agriculture was split into three subclasses (irrigated, non-irrigated and low-impact agriculture) which were correlated to stream nutrient concentration on four spatial scales: large scale (drainage area of total subcatchment and 100 m wide subcatchment corridors) and local scale (5 and 1 km radius buffers). Nitrate, ammonium and orthophosphate concentrations and land use composition (agriculture, urban and forest) were measured at 130 river reaches in south-central Spain during the 2001-2009 period. Results suggested that different spatial scales may lead to different conclusions. Spatial autocorrelation and the inadequate representation of some land uses produced unreal results on large scales. Conversely, local scales did not show data autocorrelation and agriculture subclasses were well represented. The local scale of 1 km buffer was the most appropriate to detect river eutrophication in central Spanish rivers, with irrigated cropland as the main cause of river pollution by nitrate. As regards river management, a threshold of 50% irrigated cropland within a 1 km radius buffer has been obtained using breakpoint regression analysis. This means that no more than 50% of irrigation croplands should be allowed near river banks in order to avoid river eutrophication. Finally, a methodological approach is proposed to choose the appropriate spatial scale when studying river eutrophication caused by diffuse pollution like agriculture. Copyright © 2012 Elsevier Ltd. All rights reserved.

Design and implementation of a distributed large-scale spatial database system based on J2EE

NASA Astrophysics Data System (ADS)

Gong, Jianya; Chen, Nengcheng; Zhu, Xinyan; Zhang, Xia

2003-03-01

With the increasing maturity of distributed object technology, CORBA, .NET and EJB are universally used in traditional IT field. However, theories and practices of distributed spatial database need farther improvement in virtue of contradictions between large scale spatial data and limited network bandwidth or between transitory session and long transaction processing. Differences and trends among of CORBA, .NET and EJB are discussed in details, afterwards the concept, architecture and characteristic of distributed large-scale seamless spatial database system based on J2EE is provided, which contains GIS client application, web server, GIS application server and spatial data server. Moreover the design and implementation of components of GIS client application based on JavaBeans, the GIS engine based on servlet, the GIS Application server based on GIS enterprise JavaBeans(contains session bean and entity bean) are explained.Besides, the experiments of relation of spatial data and response time under different conditions are conducted, which proves that distributed spatial database system based on J2EE can be used to manage, distribute and share large scale spatial data on Internet. Lastly, a distributed large-scale seamless image database based on Internet is presented.

Effects of spatial scale of sampling on food web structure

PubMed Central

Wood, Spencer A; Russell, Roly; Hanson, Dieta; Williams, Richard J; Dunne, Jennifer A

2015-01-01

This study asks whether the spatial scale of sampling alters structural properties of food webs and whether any differences are attributable to changes in species richness and connectance with scale. Understanding how different aspects of sampling effort affect ecological network structure is important for both fundamental ecological knowledge and the application of network analysis in conservation and management. Using a highly resolved food web for the marine intertidal ecosystem of the Sanak Archipelago in the Eastern Aleutian Islands, Alaska, we assess how commonly studied properties of network structure differ for 281 versions of the food web sampled at five levels of spatial scale representing six orders of magnitude in area spread across the archipelago. Species (S) and link (L) richness both increased by approximately one order of magnitude across the five spatial scales. Links per species (L/S) more than doubled, while connectance (C) decreased by approximately two-thirds. Fourteen commonly studied properties of network structure varied systematically with spatial scale of sampling, some increasing and others decreasing. While ecological network properties varied systematically with sampling extent, analyses using the niche model and a power-law scaling relationship indicate that for many properties, this apparent sensitivity is attributable to the increasing S and decreasing C of webs with increasing spatial scale. As long as effects of S and C are accounted for, areal sampling bias does not have a special impact on our understanding of many aspects of network structure. However, attention does need be paid to some properties such as the fraction of species in loops, which increases more than expected with greater spatial scales of sampling. PMID:26380704

Soil moisture dynamics and dominant controls at different spatial scales over semiarid and semi-humid areas

NASA Astrophysics Data System (ADS)

Suo, Lizhu; Huang, Mingbin; Zhang, Yongkun; Duan, Liangxia; Shan, Yan

2018-07-01

Soil moisture dynamics plays an active role in ecological and hydrological processes, and it depends on a large number of environmental factors, such as topographic attributes, soil properties, land use types, and precipitation. However, studies must still clarify the relative significance of these environmental factors at different soil depths and at different spatial scales. This study aimed: (1) to characterize temporal and spatial variations in soil moisture content (SMC) at four soil layers (0-40, 40-100, 100-200, and 200-500 cm) and three spatial scales (plot, hillslope, and region); and (2) to determine their dominant controls in diverse soil layers at different spatial scales over semiarid and semi-humid areas of the Loess Plateau, China. Given the high co-dependence of environmental factors, partial least squares regression (PLSR) was used to detect relative significance among 15 selected environmental factors that affect SMC. Temporal variation in SMC decreased with increasing soil depth, and vertical changes in the 0-500 cm soil profile were divided into a fast-changing layer (0-40 cm), an active layer (40-100 cm), a sub-active layer (100-200 cm), and a relatively stable layer (200-500 cm). PLSR models simulated SMC accurately in diverse soil layers at different scales; almost all values for variation in response (R2) and goodness of prediction (Q2) were >0.5 and >0.0975, respectively. Upper and lower layer SMCs were the two most important factors that influenced diverse soil layers at three scales, and these SMC variables exhibited the highest importance in projection (VIP) values. The 7-day antecedent precipitation and 7-day antecedent potential evapotranspiration contributed significantly to SMC only at the 0-40 cm soil layer. VIP of soil properties, especially sand and silt content, which influenced SMC strongly, increased significantly after increasing the measured scale. Mean annual precipitation and potential evapotranspiration also influenced SMC at the regional scale significantly. Overall, this study indicated that dominant controls of SMC varied among three spatial scales on the Loess Plateau, and VIP was a function of spatial scale and soil depth.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ~ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-07-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ∼ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-07-02

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonablemore » fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ~ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Zooming in on Spatial Scaling: Preschool Children and Adults Use Mental Transformations to Scale Spaces

ERIC Educational Resources Information Center

Möhring, Wenke; Newcombe, Nora S.; Frick, Andrea

2014-01-01

Spatial scaling is an important prerequisite for many spatial tasks and involves an understanding of how distances in different-sized spaces correspond. Previous studies have found evidence for such an understanding in preschoolers; however, the mental processes involved remain unclear. In the present study, we investigated whether children and…

Process scales in catchment science: a new synthesis

EPA Science Inventory

Concerns surrounding data resolution, choice of spatial and temporal scales in research design, and problems with extrapolation of processes across spatial and temporal scales differ greatly between scientific process-elucidation research and scenario exploration for watershed ma...

Snow depth spatial structure from hillslope to basin scale

NASA Astrophysics Data System (ADS)

Deems, J. S.

2017-12-01

Knowledge of spatial patterns of snow accumulation is required for understanding the hydrology, climatology, and ecology of mountain regions. Spatial structure in snow accumulation patterns changes with the scale of observation, a feature that has been characterized using fractal dimensions calculated from lidar-derived snow depth maps: fractal scaling structure at short length scales, with a `scale break' transition to more stochastic patterns at longer separation distances. Previous work has shown that this fractal structure of snow depth distributions differs between sites with different vegetation and terrain characteristics. Forested areas showed a transition to a nearly random spatial distribution at a much shorter lag distance than do unforested sites, enabling a statistical characterization. Alpine areas, however, showed strong spatial structure for a much wider scale range, and were the source of the dominant spatial pattern observable over a wider area. These spatial structure characteristics suggest that the choice of measurement or model resolution (satellite sensor, DEM, field survey point spacing, etc.) will strongly affect the estimates of snow volume or mass, as well as the magnitude of spatial variability. These prior efforts used data sets that were high resolution ( 1 m laser point spacing) but of limited extent ( 1 km2), constraining detection of scale features such as fractal dimension or scale breaks to areas of relatively similar characteristics and to lag distances of under 500 m. New datasets available from the NASA JPL Airborne Snow Observatory (ASO) provide similar resolution but over large areas, enabling assessment of snow spatial structure across an entire watershed, or in similar vegetation or physiography but in different parts of the basin. Additionally, the multi-year ASO time series allows an investigation into the temporal stability of these scale characteristics, within a single snow season and between seasons of strongly varying accumulation totals and patterns. This presentation will explore initial results from this study, using data from the Tuolumne River Basin in California, USA. Fractal scaling characteristics derived from ASO lidar snow depth measurements are examined at the basin scale, as well as in varying topographic and forest cover environments.

Mushroom biomass and diversity are driven by different spatio-temporal scales along Mediterranean elevation gradients

NASA Astrophysics Data System (ADS)

Alday, Josu G.; Martínez de Aragón, Juan; de-Miguel, Sergio; Bonet, José Antonio

2017-04-01

Mushrooms are important non-wood-forest-products in many Mediterranean ecosystems, being highly vulnerable to climate change. However, the ecological scales of variation of mushroom productivity and diversity, and climate dependence has been usually overlooked due to a lack of available data. We determined the spatio-temporal variability of epigeous sporocarps and the climatic factors driving their fruiting to plan future sustainable management of wild mushrooms production. We collected fruiting bodies in Pinus sylvestris stands along an elevation gradient for 8 consecutive years. Overall, sporocarp biomass was mainly dependent on inter-annual variations, whereas richness was more spatial-scale dependent. Elevation was not significant, but there were clear elevational differences in biomass and richness patterns between ectomycorrhizal and saprotrophic guilds. The main driver of variation was late-summer-early-autumn precipitation. Thus, different scale processes (inter-annual vs. spatial-scale) drive sporocarp biomass and diversity patterns; temporal effects for biomass and ectomycorrhizal fungi vs. spatial scale for diversity and saprotrophic fungi. The significant role of precipitation across fungal guilds and spatio-temporal scales indicates that it is a limiting resource controlling sporocarp production and diversity in Mediterranean regions. The high spatial and temporal variability of mushrooms emphasize the need for long-term datasets of multiple spatial points to effectively characterize fungal fruiting patterns.

A microstructural model of motion of macro-twin interfaces in Ni-Mn-Ga 10 M martensite

NASA Astrophysics Data System (ADS)

Seiner, Hanuš; Straka, Ladislav; Heczko, Oleg

2014-03-01

We present a continuum-based model of microstructures forming at the macro-twin interfaces in thermoelastic martensites and apply this model to highly mobile interfaces in 10 M modulated Ni-Mn-Ga martensite. The model is applied at three distinct spatial scales observed in the experiment: meso-scale (modulation twinning), micro-scale (compound a-b lamination), and nano-scale (nanotwining in the concept of adaptive martensite). We show that two mobile interfaces (Type I and Type II macro-twins) have different micromorphologies at all considered spatial scales, which can directly explain their different twinning stress observed in experiments. The results of the model are discussed with respect to various experimental observations at all three considered spatial scales.

Predictor variable resolution governs modeled soil types

USDA-ARS?s Scientific Manuscript database

Soil mapping identifies different soil types by compressing a unique suite of spatial patterns and processes across multiple spatial scales. It can be quite difficult to quantify spatial patterns of soil properties with remotely sensed predictor variables. More specifically, matching the right scale...

[Spatial scale effect of land use landscape pattern in Yongdeng County, Gansu Province, China.

PubMed

Liu, Yuan Yuan; Liu, Xue Lu

2016-04-22

Based on "patch-corridor-matrix" pattern, spatial scale effect of landscape pattern was studied in Yongdeng County of Lanzhou City, Gansu Province, China. The results showed that the grassland was the matrix of landscape structure in the studied area, road and river played the corridor role, and the other landscape elements (cultivated land, forest land, garden land, residential land, industrial and mineral land, public management and service land, and the other land) acted as patches. The patch level index and the landscape level index all showed obvious dependence on spatial extent. The scale effect of patch index of different landscape elements existed differently in different extent intervals, so did the scale effect of the landscape level index. Within the extent of 1-20 km, the scale effect showed the most obvious difference between the element types and the index types, while it became smaller in 21-90 km, and disappeared beyond 90 km. 90 km×90 km might be the effective extent to study the dependence of spatial extent of landscape structure.

Describing a multitrophic plant-herbivore-parasitoid system at four spatial scales

NASA Astrophysics Data System (ADS)

Cuautle, M.; Parra-Tabla, V.

2014-02-01

Herbivore-parasitoid interactions must be studied using a multitrophic and multispecies approach. The strength and direction of multiple effects through trophic levels may change across spatial scales. In this work, we use the herbaceous plant Ruellia nudiflora, its moth herbivore Tripudia quadrifera, and several parasitoid morphospecies that feed on the herbivore to answer the following questions: Do herbivore and parasitoid attack levels vary depending on the spatial scale considered? With which plant characteristics are the parasitoid and the herbivore associated? Do parasitoid morphospecies vary in the magnitude of their positive indirect effect on plant reproduction? We evaluated three approximations of herbivore and parasitoid abundance (raw numbers, ratios, and attack rates) at four spatial scales: regional (three different regions which differ in terms of abiotic and biotic characteristics); population (i.e. four populations within each region); patch (four 1 m2 plots in each population); and plant level (using a number of plant characteristics). Finally, we determined whether parasitoids have a positive indirect effect on plant reproductive success (seed number). Herbivore and parasitoid numbers differed at three of the spatial scales considered. However, herbivore/fruit ratio and attack rates did not differ at the population level. Parasitoid/host ratio and attack rates did not differ at any scale, although there was a tendency of a higher attack in one region. At the plant level, herbivore and parasitoid abundances were related to different plant traits, varying the importance and the direction (positive or negative) of those traits. In addition, only one parasitoid species (Bracon sp.) had a positive effect on plant fitness saving up to 20% of the seeds in a fruit. These results underline the importance of knowing the scales that are relevant to organisms at different trophic levels and distinguish between the specific effects of species.

Scaling effect of fraction of vegetation cover retrieved by algorithms based on linear mixture model

NASA Astrophysics Data System (ADS)

Obata, Kenta; Miura, Munenori; Yoshioka, Hiroki

2010-08-01

Differences in spatial resolution among sensors have been a source of error among satellite data products, known as a scaling effect. This study investigates the mechanism of the scaling effect on fraction of vegetation cover retrieved by a linear mixture model which employs NDVI as one of the constraints. The scaling effect is induced by the differences in texture, and the differences between the true endmember spectra and the endmember spectra assumed during retrievals. A mechanism of the scaling effect was analyzed by focusing on the monotonic behavior of spatially averaged FVC as a function of spatial resolution. The number of endmember is limited into two to proceed the investigation analytically. Although the spatially-averaged NDVI varies monotonically along with spatial resolution, the corresponding FVC values does not always vary monotonically. The conditions under which the averaged FVC varies monotonically for a certain sequence of spatial resolutions, were derived analytically. The increasing and decreasing trend of monotonic behavior can be predicted from the true and assumed endmember spectra of vegetation and non-vegetation classes regardless the distributions of the vegetation class within a fixed area. The results imply that the scaling effect on FVC is more complicated than that on NDVI, since, unlike NDVI, FVC becomes non-monotonic under a certain condition determined by the true and assumed endmember spectra.

Cross-scale analysis of fire regimes

Treesearch

Donald A. Falk; Carol Miller; Donald McKenzie; Anne E. Black

2007-01-01

Cross-scale spatial and temporal perspectives are important for studying contagious landscape disturbances such as fire, which are controlled by myriad processes operating at different scales. We examine fire regimes in forests of western North America, focusing on how observed patterns of fire frequency change across spatial scales. To quantify changes in fire...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, U.; Riley, W. J.

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Spatial variation in the climatic predictors of species compositional turnover and endemism.

PubMed

Di Virgilio, Giovanni; Laffan, Shawn W; Ebach, Malte C; Chapple, David G

2014-08-01

Previous research focusing on broad-scale or geographically invariant species-environment dependencies suggest that temperature-related variables explain more of the variation in reptile distributions than precipitation. However, species-environment relationships may exhibit considerable spatial variation contingent upon the geographic nuances that vary between locations. Broad-scale, geographically invariant analyses may mask this local variation and their findings may not generalize to different locations at local scales. We assess how reptile-climatic relationships change with varying spatial scale, location, and direction. Since the spatial distributions of diversity and endemism hotspots differ for other species groups, we also assess whether reptile species turnover and endemism hotspots are influenced differently by climatic predictors. Using New Zealand reptiles as an example, the variation in species turnover, endemism and turnover in climatic variables was measured using directional moving window analyses, rotated through 360°. Correlations between the species turnover, endemism and climatic turnover results generated by each rotation of the moving window were analysed using multivariate generalized linear models applied at national, regional, and local scales. At national-scale, temperature turnover consistently exhibited the greatest influence on species turnover and endemism, but model predictive capacity was low (typically r (2) = 0.05, P < 0.001). At regional scales the relative influence of temperature and precipitation turnover varied between regions, although model predictive capacity was also generally low. Climatic turnover was considerably more predictive of species turnover and endemism at local scales (e.g., r (2) = 0.65, P < 0.001). While temperature turnover had the greatest effect in one locale (the northern North Island), there was substantial variation in the relative influence of temperature and precipitation predictors in the remaining four locales. Species turnover and endemism hotspots often occurred in different locations. Climatic predictors had a smaller influence on endemism. Our results caution against assuming that variability in temperature will always be most predictive of reptile biodiversity across different spatial scales, locations and directions. The influence of climatic turnover on the species turnover and endemism of other taxa may exhibit similar patterns of spatial variation. Such intricate variation might be discerned more readily if studies at broad scales are complemented by geographically variant, local-scale analyses.

[Spatial point patterns of Antarctic krill fishery in the northern Antarctic Peninsula].

PubMed

Yang, Xiao Ming; Li, Yi Xin; Zhu, Guo Ping

2016-12-01

As a key species in the Antarctic ecosystem, the spatial distribution of Antarctic krill (thereafter krill) often tends to present aggregation characteristics, which therefore reflects the spatial patterns of krill fishing operation. Based on the fishing data collected from Chinese krill fishing vessels, of which vessel A was professional krill fishing vessel and Vessel B was a fishing vessel which shifted between Chilean jack mackerel (Trachurus murphyi) fishing ground and krill fishing ground. In order to explore the characteristics of spatial distribution pattern and their ecological effects of two obvious different fishing fleets under a high and low nominal catch per unit effort (CPUE), from the viewpoint of spatial point pattern, the present study analyzed the spatial distribution characteristics of krill fishery in the northern Antarctic Peninsula from three aspects: (1) the two vessels' point pattern characteristics of higher CPUEs and lower CPUEs at different scales; (2) correlation of the bivariate point patterns between these points of higher CPUE and lower CPUE; and (3) correlation patterns of CPUE. Under the analysis derived from the Ripley's L function and mark correlation function, the results showed that the point patterns of the higher/lo-wer catch available were similar, both showing an aggregation distribution in this study windows at all scale levels. The aggregation intensity of krill fishing was nearly maximum at 15 km spatial scale, and kept stably higher values at the scale of 15-50 km. The aggregation intensity of krill fishery point patterns could be described in order as higher CPUE of vessel A > lower CPUE of vessel B >higher CPUE of vessel B > higher CPUE of vessel B. The relationship of the higher and lo-wer CPUEs of vessel A showed positive correlation at the spatial scale of 0-75 km, and presented stochastic relationship after 75 km scale, whereas vessel B showed positive correlation at all spatial scales. The point events of higher and lower CPUEs were synchronized, showing significant correlations at most of spatial scales because of the dynamics nature and complex of krill aggregation patterns. The distribution of vessel A's CPUEs was positively correlated at scales of 0-44 km, but negatively correlated at the scales of 44-80 km. The distribution of vessel B's CPUEs was negatively correlated at the scales of 50-70 km, but no significant correlations were found at other scales. The CPUE mark point patterns showed a negative correlation, which indicated that intraspecific competition for space and prey was significant. There were significant differences in spatial point pattern distribution between vessel A with higher fishing capacity and vessel B with lower fishing capacity. The results showed that the professional krill fishing vessel is suitable to conduct the analysis of spatial point pattern and scientific fishery survey.

[Spatial patterns of dominant tree species in sub-alpine Betula-Abies forest in West Sichuan of China].

PubMed

Miao, Ning; Liu, Shi-Rong; Shi, Zuo-Min; Yu, Hong; Liu, Xing-Liang

2009-06-01

Based on the investigation in a 4 hm2 Betula-Abies forest plot in sub-alpine area in West Sichuan of China, and by using point pattern analysis method in terms of O-ring statistics, the spatial patterns of dominant species Betula albo-sinensis and Abies faxoniana in different age classes in study area were analyzed, and the intra- and inter-species associations between these age classes were studied. B. albo-sinensis had a unimodal distribution of its DBH frequency, indicating a declining population, while A. faxoniana had a reverse J-shaped pattern, showing an increasing population. All the big trees of B. albo-sinensis and A. faxoniana were spatially in random at all scales, while the medium age and small trees were spatially clumped at small scales and tended to be randomly or evenly distributed with increasing spatial scale. The maximum aggregation degree decreased with increasing age class. Spatial association mainly occurred at small scales. A. faxoniana generally showed positive intra-specific association, while B. albo-sinensis generally showed negative intra-specific association. For the two populations, big and small trees had no significant spatial association, but middle age trees had negative spatial association. Negative inter-specific associations of the two populations were commonly found in different age classes. The larger the difference of age class, the stronger the negative inter-specific association.

Density dependence, spatial scale and patterning in sessile biota.

PubMed

Gascoigne, Joanna C; Beadman, Helen A; Saurel, Camille; Kaiser, Michel J

2005-09-01

Sessile biota can compete with or facilitate each other, and the interaction of facilitation and competition at different spatial scales is key to developing spatial patchiness and patterning. We examined density and scale dependence in a patterned, soft sediment mussel bed. We followed mussel growth and density at two spatial scales separated by four orders of magnitude. In summer, competition was important at both scales. In winter, there was net facilitation at the small scale with no evidence of density dependence at the large scale. The mechanism for facilitation is probably density dependent protection from wave dislodgement. Intraspecific interactions in soft sediment mussel beds thus vary both temporally and spatially. Our data support the idea that pattern formation in ecological systems arises from competition at large scales and facilitation at smaller scales, so far only shown in vegetation systems. The data, and a simple, heuristic model, also suggest that facilitative interactions in sessile biota are mediated by physical stress, and that interactions change in strength and sign along a spatial or temporal gradient of physical stress.

Frugivory and Spatial Patterns of Seed Deposition by Carnivorous Mammals in Anthropogenic Landscapes: A Multi-Scale Approach

PubMed Central

López-Bao, José V.; González-Varo, Juan P.

2011-01-01

Background Knowledge about how frugivory and seed deposition are spatially distributed is valuable to understand the role of dispersers on the structure and dynamics of plant populations. This may be particularly important within anthropogenic areas, where either the patchy distribution of wild plants or the presence of cultivated fleshy-fruits may influence plant-disperser interactions. Methodology/Principal Findings We investigated frugivory and spatial patterns of seed deposition by carnivorous mammals in anthropogenic landscapes considering two spatial scales: ‘landscape’ (∼10 km2) and ‘habitat type’ (∼1–2 km2). We sampled carnivore faeces and plant abundance at three contrasting habitats (chestnut woods, mosaics and scrublands), each replicated within three different landscapes. Sixty-five percent of faeces collected (n = 1077) contained seeds, among which wild and cultivated seeds appeared in similar proportions (58% and 53%) despite that cultivated fruiting plants were much less abundant. Seed deposition was spatially structured among both spatial scales being different between fruit types. Whereas the most important source of spatial variation in deposition of wild seeds was the landscape scale, it was the habitat scale for cultivated seeds. At the habitat scale, seeds of wild species were mostly deposited within mosaics while seeds of cultivated species were within chestnut woods and scrublands. Spatial concordance between seed deposition and plant abundance was found only for wild species. Conclusions/Significance Spatial patterns of seed deposition by carnivores differed between fruit types and seemed to be modulated by the fleshy-fruited plant assemblages and the behaviour of dispersers. Our results suggest that a strong preference for cultivated fruits by carnivores may influence their spatial foraging behaviour and lower their dispersal services to wild species. However, the high amount of seeds removed within and between habitats suggests that carnivores must play an important role – often overlooked – as ‘restorers’ and ‘habitat shapers’ in anthropogenic areas. PMID:21297861

Study of satellite retrieved aerosol optical depth spatial resolution effect on particulate matter concentration prediction

NASA Astrophysics Data System (ADS)

Strandgren, J.; Mei, L.; Vountas, M.; Burrows, J. P.; Lyapustin, A.; Wang, Y.

2014-10-01

The Aerosol Optical Depth (AOD) spatial resolution effect is investigated for the linear correlation between satellite retrieved AOD and ground level particulate matter concentrations (PM2.5). The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) for obtaining AOD with a high spatial resolution of 1 km and provides a good dataset for the study of the AOD spatial resolution effect on the particulate matter concentration prediction. 946 Environmental Protection Agency (EPA) ground monitoring stations across the contiguous US have been used to investigate the linear correlation between AOD and PM2.5 using AOD at different spatial resolutions (1, 3 and 10 km) and for different spatial scales (urban scale, meso-scale and continental scale). The main conclusions are: (1) for both urban, meso- and continental scale the correlation between PM2.5 and AOD increased significantly with increasing spatial resolution of the AOD, (2) the correlation between AOD and PM2.5 decreased significantly as the scale of study region increased for the eastern part of the US while vice versa for the western part of the US, (3) the correlation between PM2.5 and AOD is much more stable and better over the eastern part of the US compared to western part due to the surface characteristics and atmospheric conditions like the fine mode fraction.

[Multiple time scales analysis of spatial differentiation characteristics of non-point source nitrogen loss within watershed].

PubMed

Liu, Mei-bing; Chen, Xing-wei; Chen, Ying

2015-07-01

Identification of the critical source areas of non-point source pollution is an important means to control the non-point source pollution within the watershed. In order to further reveal the impact of multiple time scales on the spatial differentiation characteristics of non-point source nitrogen loss, a SWAT model of Shanmei Reservoir watershed was developed. Based on the simulation of total nitrogen (TN) loss intensity of all 38 subbasins, spatial distribution characteristics of nitrogen loss and critical source areas were analyzed at three time scales of yearly average, monthly average and rainstorms flood process, respectively. Furthermore, multiple linear correlation analysis was conducted to analyze the contribution of natural environment and anthropogenic disturbance on nitrogen loss. The results showed that there were significant spatial differences of TN loss in Shanmei Reservoir watershed at different time scales, and the spatial differentiation degree of nitrogen loss was in the order of monthly average > yearly average > rainstorms flood process. TN loss load mainly came from upland Taoxi subbasin, which was identified as the critical source area. At different time scales, land use types (such as farmland and forest) were always the dominant factor affecting the spatial distribution of nitrogen loss, while the effect of precipitation and runoff on the nitrogen loss was only taken in no fertilization month and several processes of storm flood at no fertilization date. This was mainly due to the significant spatial variation of land use and fertilization, as well as the low spatial variability of precipitation and runoff.

Spatial distribution of enzyme driven reactions at micro-scales

NASA Astrophysics Data System (ADS)

Kandeler, Ellen; Boeddinghaus, Runa; Nassal, Dinah; Preusser, Sebastian; Marhan, Sven; Poll, Christian

2017-04-01

Studies of microbial biogeography can often provide key insights into the physiologies, environmental tolerances, and ecological strategies of soil microorganisms that dominate in natural environments. In comparison with aquatic systems, soils are particularly heterogeneous. Soil heterogeneity results from the interaction of a hierarchical series of interrelated variables that fluctuate at many different spatial and temporal scales. Whereas spatial dependence of chemical and physical soil properties is well known at scales ranging from decimetres to several hundred metres, the spatial structure of soil enzymes is less clear. Previous work has primarily focused on spatial heterogeneity at a single analytical scale using the distribution of individual cells, specific types of organisms or collective parameters such as bacterial abundance or total microbial biomass. There are fewer studies that have considered variations in community function and soil enzyme activities. This presentation will give an overview about recent studies focusing on spatial pattern of different soil enzymes in the terrestrial environment. Whereas zymography allows the visualization of enzyme pattern in the close vicinity of roots, micro-sampling strategies followed by MUF analyses clarify micro-scale pattern of enzymes associated to specific microhabitats (micro-aggregates, organo-mineral complexes, subsoil compartments).

Biodiversity in canopy-forming algae: Structure and spatial variability of the Mediterranean Cystoseira assemblages

NASA Astrophysics Data System (ADS)

Piazzi, L.; Bonaviri, C.; Castelli, A.; Ceccherelli, G.; Costa, G.; Curini-Galletti, M.; Langeneck, J.; Manconi, R.; Montefalcone, M.; Pipitone, C.; Rosso, A.; Pinna, S.

2018-07-01

In the Mediterranean Sea, Cystoseira species are the most important canopy-forming algae in shallow rocky bottoms, hosting high biodiverse sessile and mobile communities. A large-scale study has been carried out to investigate the structure of the Cystoseira-dominated assemblages at different spatial scales and to test the hypotheses that alpha and beta diversity of the assemblages, the abundance and the structure of epiphytic macroalgae, epilithic macroalgae, sessile macroinvertebrates and mobile macroinvertebrates associated to Cystoseira beds changed among scales. A hierarchical sampling design in a total of five sites across the Mediterranean Sea (Croatia, Montenegro, Sardinia, Tuscany and Balearic Islands) was used. A total of 597 taxa associated to Cystoseira beds were identified with a mean number per sample ranging between 141.1 ± 6.6 (Tuscany) and 173.9 ± 8.5(Sardinia). A high variability at small (among samples) and large (among sites) scale was generally highlighted, but the studied assemblages showed different patterns of spatial variability. The relative importance of the different scales of spatial variability should be considered to optimize sampling designs and propose monitoring plans of this habitat.

Measuring spatial patterns in floodplains: A step towards understanding the complexity of floodplain ecosystems: Chapter 6

USGS Publications Warehouse

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.; Gilvear, David J.; Greenwood, Malcolm T.; Thoms, Martin C.; Wood, Paul J.

2016-01-01

Floodplains can be viewed as complex adaptive systems (Levin, 1998) because they are comprised of many different biophysical components, such as morphological features, soil groups and vegetation communities as well as being sites of key biogeochemical processing (Stanford et al., 2005). Interactions and feedbacks among the biophysical components often result in additional phenomena occuring over a range of scales, often in the absence of any controlling factors (sensu Hallet, 1990). This emergence of new biophysical features and rates of processing can lead to alternative stable states which feed back into floodplain adaptive cycles (cf. Hughes, 1997; Stanford et al., 2005). Interactions between different biophysical components, feedbacks, self emergence and scale are all key properties of complex adaptive systems (Levin, 1998; Phillips, 2003; Murray et al., 2014) and therefore will influence the manner in which we study and view spatial patterns. Measuring the spatial patterns of floodplain biophysical components is a prerequisite to examining and understanding these ecosystems as complex adaptive systems. Elucidating relationships between pattern and process, which are intrinsically linked within floodplains (Ward et al., 2002), is dependent upon an understanding of spatial pattern. This knowledge can help river scientists determine the major drivers, controllers and responses of floodplain structure and function, as well as the consequences of altering those drivers and controllers (Hughes and Cass, 1997; Whited et al., 2007). Interactions and feedbacks between physical, chemical and biological components of floodplain ecosystems create and maintain a structurally diverse and dynamic template (Stanford et al., 2005). This template influences subsequent interactions between components that consequently affect system trajectories within floodplains (sensu Bak et al., 1988). Constructing and evaluating models used to predict floodplain ecosystem responses to natural and anthropogenic disturbances therefore require quantification of spatial pattern (Asselman and Middelkoop, 1995; Walling and He, 1998). Quantifying these patterns also provides insights into the spatial and temporal domains of structuring processes as well as enabling the detection of self-emergent phenomena, environmental constraints or anthropogenic interference (Turner et al., 1990; Holling, 1992; De Jager and Rohweder, 2012). Thus, quantifying spatial pattern is an important building block on which to examine floodplains as complex adaptive systems (Levin, 1998). Approaches to measuring spatial pattern in floodplains must be cognisant of scale, self-emergent phenomena, spatial organisation, and location. Fundamental problems may arise when patterns observed at a site or transect scale are scaled-up to infer processes and patterns over entire floodplain surfaces (Wiens, 2002; Thorp et al., 2008). Likewise, patterns observed over the entire spatial extent of a landscape can mask important variation and detail at finer scales (Riitters et al., 2002). Indeed, different patterns often emerge at different scales (Turner et al., 1990) because of hierarchical structuring processes (O'Neill et al., 1991). Categorising data into discrete, homogeneous and predefined spatial units at a particular scale (e.g. polygons) creates issues and errors associated with scale and subjective classification (McGarigal et al., 2009; Cushman et al., 2010). These include, loss of information within classified ‘patches’, as well as the ability to detect the emergence of new features that do not fit the original classification scheme. Many of these issues arise because floodplains are highly heterogeneous and have complex spatial organizations (Carbonneau et al., 2012; Legleiter, 2013). As a result, the scale and location at which measurements are made can influence the observed spatial patterns; and patterns may not be scale independent or applicable in different geomorp

Multi-scale Slip Inversion Based on Simultaneous Spatial and Temporal Domain Wavelet Transform

NASA Astrophysics Data System (ADS)

Liu, W.; Yao, H.; Yang, H. Y.

2017-12-01

Finite fault inversion is a widely used method to study earthquake rupture processes. Some previous studies have proposed different methods to implement finite fault inversion, including time-domain, frequency-domain, and wavelet-domain methods. Many previous studies have found that different frequency bands show different characteristics of the seismic rupture (e.g., Wang and Mori, 2011; Yao et al., 2011, 2013; Uchide et al., 2013; Yin et al., 2017). Generally, lower frequency waveforms correspond to larger-scale rupture characteristics while higher frequency data are representative of smaller-scale ones. Therefore, multi-scale analysis can help us understand the earthquake rupture process thoroughly from larger scale to smaller scale. By the use of wavelet transform, the wavelet-domain methods can analyze both the time and frequency information of signals in different scales. Traditional wavelet-domain methods (e.g., Ji et al., 2002) implement finite fault inversion with both lower and higher frequency signals together to recover larger-scale and smaller-scale characteristics of the rupture process simultaneously. Here we propose an alternative strategy with a two-step procedure, i.e., firstly constraining the larger-scale characteristics with lower frequency signals, and then resolving the smaller-scale ones with higher frequency signals. We have designed some synthetic tests to testify our strategy and compare it with the traditional one. We also have applied our strategy to study the 2015 Gorkha Nepal earthquake using tele-seismic waveforms. Both the traditional method and our two-step strategy only analyze the data in different temporal scales (i.e., different frequency bands), while the spatial distribution of model parameters also shows multi-scale characteristics. A more sophisticated strategy is to transfer the slip model into different spatial scales, and then analyze the smooth slip distribution (larger scales) with lower frequency data firstly and more detailed slip distribution (smaller scales) with higher frequency data subsequently. We are now implementing the slip inversion using both spatial and temporal domain wavelets. This multi-scale analysis can help us better understand frequency-dependent rupture characteristics of large earthquakes.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales.

PubMed

Rueckl, Martin; Lenzi, Stephen C; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca 2+ -imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca 2+ imaging datasets, particularly when these have been acquired at different spatial scales.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales

PubMed Central

Rueckl, Martin; Lenzi, Stephen C.; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W.

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca2+-imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca2+ imaging datasets, particularly when these have been acquired at different spatial scales. PMID:28706482

Community structure of aquatic insects in the Esparza River, Costa Rica.

PubMed

Herrera-Vásquez, Jonathan

2009-01-01

This study focused on the structure of the aquatic insect community in spatial and temporal scales in the Esparza River. The river was sampled for one full year throughout 2007. During the dry season low flow months, five sampling points were selected in two different habitats (currents and pools), with five replicates per sample site. During the wet season with peak rain, only the data in the "current habitat" were sampled at each site. Specimens present in the different substrates were collected and preserved in situ. A nested ANOVA was then applied to the data to determine richness and density as the response variables. The variations in temporal and spatial scales were analyzed using width, depth and discharge of the river, and then analyzed using a nested ANOVA. Only a correlation of 51% similarity in richness was found, while in spatial scale, richness showed significant variation between sampling sites, but not between habitats. However, the temporal scale showed significant differences between habitats. Density showed differences between sites and habitats during the dry season in the spatial scale, while in the temporal scale significant variation was found between sampling sites. Width varied between habitats during the dry season, but not between sampling points. Depth showed differences between sampling sites and season. This work studies the importance of community structure of aquatic insects in rivers, and its relevance for the quality of water in rivers and streams.

Effect of spatial and temporal scales on habitat suitability modeling: A case study of Ommastrephes bartramii in the northwest pacific ocean

NASA Astrophysics Data System (ADS)

Gong, Caixia; Chen, Xinjun; Gao, Feng; Tian, Siquan

2014-12-01

Temporal and spatial scales play important roles in fishery ecology, and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution. The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling, with the western stock of winter-spring cohort of neon flying squid ( Ommastrephes bartramii) in the northwest Pacific Ocean as an example. In this study, the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature (SST) from remote sensing during August to October of 2003-2008 were used. We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales (0.5°, 1° and 2°), four longitude scales (0.5°, 1°, 2° and 4°), and three temporal scales (week, fortnight, and month). The coefficients of variation (CV) of the weekly, biweekly and monthly suitability index (SI) were compared to determine which temporal and spatial scales of SI model are more precise. This study shows that the optimal temporal and spatial scales with the lowest CV are month, and 0.5° latitude and 0.5° longitude for O. bartramii in the northwest Pacific Ocean. This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts. We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.

Model simulations and proxy-based reconstructions for the European region in the past millennium (Invited)

NASA Astrophysics Data System (ADS)

Zorita, E.

2009-12-01

One of the objectives when comparing simulations of past climates to proxy-based climate reconstructions is to asses the skill of climate models to simulate climate change. This comparison may accomplished at large spatial scales, for instance the evolution of simulated and reconstructed Northern Hemisphere annual temperature, or at regional or point scales. In both approaches a 'fair' comparison has to take into account different aspects that affect the inevitable uncertainties and biases in the simulations and in the reconstructions. These efforts face a trade-off: climate models are believed to be more skillful at large hemispheric scales, but climate reconstructions are these scales are burdened by the spatial distribution of available proxies and by methodological issues surrounding the statistical method used to translate the proxy information into large-spatial averages. Furthermore, the internal climatic noise at large hemispheric scales is low, so that the sampling uncertainty tends to be also low. On the other hand, the skill of climate models at regional scales is limited by the coarse spatial resolution, which hinders a faithful representation of aspects important for the regional climate. At small spatial scales, the reconstruction of past climate probably faces less methodological problems if information from different proxies is available. The internal climatic variability at regional scales is, however, high. In this contribution some examples of the different issues faced when comparing simulation and reconstructions at small spatial scales in the past millennium are discussed. These examples comprise reconstructions from dendrochronological data and from historical documentary data in Europe and climate simulations with global and regional models. These examples indicate that the centennial climate variations can offer a reasonable target to assess the skill of global climate models and of proxy-based reconstructions, even at small spatial scales. However, as the focus shifts towards higher frequency variability, decadal or multidecadal, the need for larger simulation ensembles becomes more evident. Nevertheless,the comparison at these time scales may expose some lines of research on the origin of multidecadal regional climate variability.

DOE Office of Scientific and Technical Information (OSTI.GOV)

LaGory, K. E.; Walston, L. J.; Goulet, C

The decline of many snake populations is attributable to habitat loss, and knowledge of habitat use is critical to their conservation. Resource characteristics (e.g., relative availability of different habitat types, soils, and slopes) within a landscape are scale-dependent and may not be equal across multiple spatial scales. Thus, it is important to identify the relevant spatial scales at which resource selection occurs. We conducted a radiotelemetry study of eastern hognose snake (Heterodon platirhinos) home range size and resource use at different hierarchical spatial scales. We present the results for 8 snakes radiotracked during a 2-year study at New Boston Airmore » Force Station (NBAFS) in southern New Hampshire, USA, where the species is listed by the state as endangered. Mean home range size (minimum convex polygon) at NBAFS (51.7 {+-} 14.7 ha) was similar to that reported in other parts of the species range. Radiotracked snakes exhibited different patterns of resource use at different spatial scales. At the landscape scale (selection of locations within the landscape), snakes overutilized old-field and forest edge habitats and underutilized forested habitats and wetlands relative to availability. At this scale, snakes also overutilized areas containing sandy loam soils and areas with lower slope (mean slope = 5.2% at snake locations vs. 6.7% at random locations). We failed to detect some of these patterns of resource use at the home range scale (i.e., within the home range). Our ability to detect resource selection by the snakes only at the landscape scale is likely the result of greater heterogeneity in macrohabitat features at the broader landscape scale. From a management perspective, future studies of habitat selection for rare species should include measurement of available habitat at spatial scales larger than the home range. We suggest that the maintenance of open early successional habitats as a component of forested landscapes will be critical for the persistence of eastern hognose snake populations in the northeastern United States.« less

[Spatial scale effect of urban land use landscape pattern in Shanghai City].

PubMed

Xu, Li-Hua; Yue, Wen Ze; Cao, Yu

2007-12-01

Based on geographic information system (GIS) and remote sensing (RS) techniques, the landscape classes of urban land use in Shanghai City were extracted from SPOT images with 5 m spatial resolution in 2002, and then, the classified data were applied to quantitatively explore the change patterns of several basic landscape metrics at different scales. The results indicated that landscape metrics were sensitive to grain- and extent variance. Urban landscape pattern was spatially dependent. In other words, different landscape metrics showed different responses to scale. The resolution of 40 m was an intrinsic observing scale for urban landscape in Shanghai City since landscape metrics showed random characteristics while the grain was less than 40 m. The extent of 24 km was a symbol scale in a series of extents, which was consistent with the boundary between urban built-up area and suburban area in Shanghai City. As a result, the extent of 12 km away from urban center would be an intrinsic handle scale for urban landscape in Shanghai City. However, due to the complexity of urban structure and asymmetry of urban spatial expansion, the intrinsic handle scale was not regular extent, and the square with size of 24 km was just an approximate intrinsic extent for Shanghai City.

Contrasting patterns of fine-scale herb layer species composition in temperate forests

NASA Astrophysics Data System (ADS)

Chudomelová, Markéta; Zelený, David; Li, Ching-Feng

2017-04-01

Although being well described at the landscape level, patterns in species composition of forest herb layer are rarely studied at smaller scales. Here, we examined fine-scale environmental determinants and spatial structures of herb layer communities in thermophilous oak- and hornbeam dominated forests of the south-eastern part of the Czech Republic. Species composition of herb layer vegetation and environmental variables were recorded within a fixed grid of 2 × 2 m subplots regularly distributed within 1-ha quadrate plots in three forest stands. For each site, environmental models best explaining species composition were constructed using constrained ordination analysis. Spatial eigenvector mapping was used to model and account for spatial structures in community variation. Mean Ellenberg indicator values calculated for each subplot were used for ecological interpretation of spatially structured residual variation. The amount of variation explained by environmental and spatial models as well as the selection of variables with the best explanatory power differed among sites. As an important environmental factor, relative elevation was common to all three sites, while pH and canopy openness were shared by two sites. Both environmental and community variation was mostly coarse-scaled, as was the spatially structured portion of residual variation. When corrected for bias due to spatial autocorrelation, those environmental factors with already weak explanatory power lost their significance. Only a weak evidence of possibly omitted environmental predictor was found for autocorrelated residuals of site models using mean Ellenberg indicator values. Community structure was determined by different factors at different sites. The relative importance of environmental filtering vs. spatial processes was also site specific, implying that results of fine-scale studies tend to be shaped by local conditions. Contrary to expectations based on other studies, overall dominance of spatial processes at fine scale has not been detected. Ecologists should keep this in mind when making generalizations about community dynamics.

Process, pattern and scale: hydrogeomorphology and plant diversity in forested wetlands across multiple spatial scales

NASA Astrophysics Data System (ADS)

Alexander, L.; Hupp, C. R.; Forman, R. T.

2002-12-01

Many geodisturbances occur across large spatial scales, spanning entire landscapes and creating ecological phenomena in their wake. Ecological study at large scales poses special problems: (1) large-scale studies require large-scale resources, and (2) sampling is not always feasible at the appropriate scale, and researchers rely on data collected at smaller scales to interpret patterns across broad regions. A criticism of landscape ecology is that findings at small spatial scales are "scaled up" and applied indiscriminately across larger spatial scales. In this research, landscape scaling is addressed through process-pattern relationships between hydrogeomorphic processes and patterns of plant diversity in forested wetlands. The research addresses: (1) whether patterns and relationships between hydrogeomorphic, vegetation, and spatial variables can transcend scale; and (2) whether data collected at small spatial scales can be used to describe patterns and relationships across larger spatial scales. Field measurements of hydrologic, geomorphic, spatial, and vegetation data were collected or calculated for 15- 1-ha sites on forested floodplains of six (6) Chesapeake Bay Coastal Plain streams over a total area of about 20,000 km2. Hydroperiod (day/yr), floodplain surface elevation range (m), discharge (m3/s), stream power (kg-m/s2), sediment deposition (mm/yr), relative position downstream and other variables were used in multivariate analyses to explain differences in species richness, tree diversity (Shannon-Wiener Diversity Index H'), and plant community composition at four spatial scales. Data collected at the plot (400-m2) and site- (c. 1-ha) scales are applied to and tested at the river watershed and regional spatial scales. Results indicate that plant species richness and tree diversity (Shannon-Wiener diversity index H') can be described by hydrogeomorphic conditions at all scales, but are best described at the site scale. Data collected at plot and site scales are tested for spatial heterogeneity across the Chesapeake Bay Coastal Plain using a geostatistical variogram, and multiple regression analysis is used to relate plant diversity, spatial, and hydrogeomorphic variables across Coastal Plain regions and hydrologic regimes. Results indicate that relationships between hydrogeomorphic processes and patterns of plant diversity at finer scales can proxy relationships at coarser scales in some, not all, cases. Findings also suggest that data collected at small scales can be used to describe trends across broader scales under limited conditions.

Spatial variation in the climatic predictors of species compositional turnover and endemism

PubMed Central

Di Virgilio, Giovanni; Laffan, Shawn W; Ebach, Malte C; Chapple, David G

2014-01-01

Previous research focusing on broad-scale or geographically invariant species-environment dependencies suggest that temperature-related variables explain more of the variation in reptile distributions than precipitation. However, species–environment relationships may exhibit considerable spatial variation contingent upon the geographic nuances that vary between locations. Broad-scale, geographically invariant analyses may mask this local variation and their findings may not generalize to different locations at local scales. We assess how reptile–climatic relationships change with varying spatial scale, location, and direction. Since the spatial distributions of diversity and endemism hotspots differ for other species groups, we also assess whether reptile species turnover and endemism hotspots are influenced differently by climatic predictors. Using New Zealand reptiles as an example, the variation in species turnover, endemism and turnover in climatic variables was measured using directional moving window analyses, rotated through 360°. Correlations between the species turnover, endemism and climatic turnover results generated by each rotation of the moving window were analysed using multivariate generalized linear models applied at national, regional, and local scales. At national-scale, temperature turnover consistently exhibited the greatest influence on species turnover and endemism, but model predictive capacity was low (typically r2 = 0.05, P < 0.001). At regional scales the relative influence of temperature and precipitation turnover varied between regions, although model predictive capacity was also generally low. Climatic turnover was considerably more predictive of species turnover and endemism at local scales (e.g., r2 = 0.65, P < 0.001). While temperature turnover had the greatest effect in one locale (the northern North Island), there was substantial variation in the relative influence of temperature and precipitation predictors in the remaining four locales. Species turnover and endemism hotspots often occurred in different locations. Climatic predictors had a smaller influence on endemism. Our results caution against assuming that variability in temperature will always be most predictive of reptile biodiversity across different spatial scales, locations and directions. The influence of climatic turnover on the species turnover and endemism of other taxa may exhibit similar patterns of spatial variation. Such intricate variation might be discerned more readily if studies at broad scales are complemented by geographically variant, local-scale analyses. PMID:25473479

Going the distance: spatial scale of athletic experience affects the accuracy of path integration.

PubMed

Smith, Alastair D; Howard, Christina J; Alcock, Niall; Cater, Kirsten

2010-09-01

Evidence suggests that athletically trained individuals are more accurate than untrained individuals in updating their spatial position through idiothetic cues. We assessed whether training at different spatial scales affects the accuracy of path integration. Groups of rugby players (large-scale training) and martial artists (small-scale training) participated in a triangle-completion task: they were led (blindfolded) along two sides of a right-angled triangle and were required to complete the hypotenuse by returning to the origin. The groups did not differ in their assessment of the distance to the origin, but rugby players were more accurate than martial artists in assessing the correct angle to turn (heading), and landed significantly closer to the origin. These data support evidence that distance and heading components can be dissociated. Furthermore, they suggest that the spatial scale at which an individual is trained may affect the accuracy of one component of path integration but not the other.

Spatiotemporal Thinking in the Geosciences

NASA Astrophysics Data System (ADS)

Shipley, T. F.; Manduca, C. A.; Ormand, C. J.; Tikoff, B.

2011-12-01

Reasoning about spatial relations is a critical skill for geoscientists. Within the geosciences different disciplines may reason about different sorts of relationships. These relationships may span vastly different spatial and temporal scales (from the spatial alignment in atoms in crystals to the changes in the shape of plates). As part of work in a research center on spatial thinking in STEM education, we have been working to classify the spatial skills required in geology, develop tests for each spatial skill, and develop the cognitive science tools to promote the critical spatial reasoning skills. Research in psychology, neurology and linguistics supports a broad classification of spatial skills along two dimensions: one versus many objects (which roughly translates to object- focused and navigation focused skills) and static versus dynamic spatial relations. The talk will focus on the interaction of space and time in spatial cognition in the geosciences. We are working to develop measures of skill in visualizing spatiotemporal changes. A new test developed to measure visualization of brittle deformations will be presented. This is a skill that has not been clearly recognized in the cognitive science research domain and thus illustrates the value of interdisciplinary work that combines geosciences with cognitive sciences. Teaching spatiotemporal concepts can be challenging. Recent theoretical work suggests analogical reasoning can be a powerful tool to aid student learning to reason about temporal relations using spatial skills. Recent work in our lab has found that progressive alignment of spatial and temporal scales promotes accurate reasoning about temporal relations at geological time scales.

Variability in results from negative binomial models for Lyme disease measured at different spatial scales.

PubMed

Tran, Phoebe; Waller, Lance

2015-01-01

Lyme disease has been the subject of many studies due to increasing incidence rates year after year and the severe complications that can arise in later stages of the disease. Negative binomial models have been used to model Lyme disease in the past with some success. However, there has been little focus on the reliability and consistency of these models when they are used to study Lyme disease at multiple spatial scales. This study seeks to explore how sensitive/consistent negative binomial models are when they are used to study Lyme disease at different spatial scales (at the regional and sub-regional levels). The study area includes the thirteen states in the Northeastern United States with the highest Lyme disease incidence during the 2002-2006 period. Lyme disease incidence at county level for the period of 2002-2006 was linked with several previously identified key landscape and climatic variables in a negative binomial regression model for the Northeastern region and two smaller sub-regions (the New England sub-region and the Mid-Atlantic sub-region). This study found that negative binomial models, indeed, were sensitive/inconsistent when used at different spatial scales. We discuss various plausible explanations for such behavior of negative binomial models. Further investigation of the inconsistency and sensitivity of negative binomial models when used at different spatial scales is important for not only future Lyme disease studies and Lyme disease risk assessment/management but any study that requires use of this model type in a spatial context. Copyright © 2014 Elsevier Inc. All rights reserved.

Raccoon spatial requirements and multi-scale habitat selection within an intensively managed central Appalachian forest

USGS Publications Warehouse

Owen, Sheldon F.; Berl, Jacob L.; Edwards, John W.; Ford, W. Mark; Wood, Petra Bohall

2015-01-01

We studied a raccoon (Procyon lotor) population within a managed central Appalachian hardwood forest in West Virginia to investigate the effects of intensive forest management on raccoon spatial requirements and habitat selection. Raccoon home-range (95% utilization distribution) and core-area (50% utilization distribution) size differed between sexes with males maintaining larger (2×) home ranges and core areas than females. Home-range and core-area size did not differ between seasons for either sex. We used compositional analysis to quantify raccoon selection of six different habitat types at multiple spatial scales. Raccoons selected riparian corridors (riparian management zones [RMZ]) and intact forests (> 70 y old) at the core-area spatial scale. RMZs likely were used by raccoons because they provided abundant denning resources (i.e., large-diameter trees) as well as access to water. Habitat composition associated with raccoon foraging locations indicated selection for intact forests, riparian areas, and regenerating harvest (stands <10 y old). Although raccoons were able to utilize multiple habitat types for foraging resources, a selection of intact forest and RMZs at multiple spatial scales indicates the need of mature forest (with large-diameter trees) for this species in managed forests in the central Appalachians.

Variability in Soil Properties at Different Spatial Scales (1 m to 1 km) in a Deciduous Forest Ecosystem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garten Jr, Charles T; Kang, S.; Brice, Deanne Jane

2007-01-01

The purpose of this research was to test the hypothesis that variability in 11 soil properties, related to soil texture and soil C and N, would increase from small (1 m) to large (1 km) spatial scales in a temperate, mixed-hardwood forest ecosystem in east Tennessee, USA. The results were somewhat surprising and indicated that a fundamental assumption in geospatial analysis, namely that variability increases with increasing spatial scale, did not apply for at least five of the 11 soil properties measured over a 0.5-km2 area. Composite mineral soil samples (15 cm deep) were collected at 1, 5, 10, 50,more » 250, and 500 m distances from a center point along transects in a north, south, east, and westerly direction. A null hypothesis of equal variance at different spatial scales was rejected (P{le}0.05) for mineral soil C concentration, silt content, and the C-to-N ratios in particulate organic matter (POM), mineral-associated organic matter (MOM), and whole surface soil. Results from different tests of spatial variation, based on coefficients of variation or a Mantel test, led to similar conclusions about measurement variability and geographic distance for eight of the 11 variables examined. Measurements of mineral soil C and N concentrations, C concentrations in MOM, extractable soil NH{sub 4}-N, and clay contents were just as variable at smaller scales (1-10 m) as they were at larger scales (50-500 m). On the other hand, measurement variation in mineral soil C-to-N ratios, MOM C-to-N ratios, and the fraction of soil C in POM clearly increased from smaller to larger spatial scales. With the exception of extractable soil NH4-N, measured soil properties in the forest ecosystem could be estimated (with 95% confidence) to within 15% of their true mean with a relatively modest number of sampling points (n{le}25). For some variables, scaling up variation from smaller to larger spatial domains within the ecosystem could be relatively easy because small-scale variation may be indicative of variation at larger scales.« less

Sex differences in virtual navigation influenced by scale and navigation experience.

PubMed

Padilla, Lace M; Creem-Regehr, Sarah H; Stefanucci, Jeanine K; Cashdan, Elizabeth A

2017-04-01

The Morris water maze is a spatial abilities test adapted from the animal spatial cognition literature and has been studied in the context of sex differences in humans. This is because its standard design, which manipulates proximal (close) and distal (far) cues, applies to human navigation. However, virtual Morris water mazes test navigation skills on a scale that is vastly smaller than natural human navigation. Many researchers have argued that navigating in large and small scales is fundamentally different, and small-scale navigation might not simulate natural human navigation. Other work has suggested that navigation experience could influence spatial skills. To address the question of how individual differences influence navigational abilities in differently scaled environments, we employed both a large- (146.4 m in diameter) and a traditional- (36.6 m in diameter) scaled virtual Morris water maze along with a novel measure of navigation experience (lifetime mobility). We found sex differences on the small maze in the distal cue condition only, but in both cue-conditions on the large maze. Also, individual differences in navigation experience modulated navigation performance on the virtual water maze, showing that higher mobility was related to better performance with proximal cues for only females on the small maze, but for both males and females on the large maze.

Network analysis reveals multiscale controls on streamwater chemistry

USGS Publications Warehouse

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Network analysis reveals multiscale controls on streamwater chemistry

PubMed Central

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks. PMID:24753575

Network analysis reveals multiscale controls on streamwater chemistry.

PubMed

McGuire, Kevin J; Torgersen, Christian E; Likens, Gene E; Buso, Donald C; Lowe, Winsor H; Bailey, Scott W

2014-05-13

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Control factors and scale analysis of annual river water, sediments and carbon transport in China.

PubMed

Song, Chunlin; Wang, Genxu; Sun, Xiangyang; Chang, Ruiying; Mao, Tianxu

2016-05-11

Under the context of dramatic human disturbances on river system, the processes that control the transport of water, sediment, and carbon from river basins to coastal seas are not completely understood. Here we performed a quantitative synthesis for 121 sites across China to find control factors of annual river exports (Rc: runoff coefficient; TSSC: total suspended sediment concentration; TSSL: total suspended sediment loads; TOCL: total organic carbon loads) at different spatial scales. The results indicated that human activities such as dam construction and vegetation restoration might have a greater influence than climate on the transport of river sediment and carbon, although climate was a major driver of Rc. Multiple spatial scale analyses indicated that Rc increased from the small to medium scale by 20% and then decreased at the sizable scale by 20%. TSSC decreased from the small to sizeable scale but increase from the sizeable to large scales; however, TSSL significantly decreased from small (768 g·m(-2)·a(-1)) to medium spatial scale basins (258 g·m(-2)·a(-1)), and TOCL decreased from the medium to large scale. Our results will improve the understanding of water, sediment and carbon transport processes and contribute better water and land resources management strategies from different spatial scales.

Seed harvesting by a generalist consumer is context-dependent: Interactive effects across multiple spatial scales

USGS Publications Warehouse

Ostoja, Steven M.; Schupp, Eugene W.; Klinger, Rob

2013-01-01

Granivore foraging decisions affect consumer success and determine the quantity and spatial pattern of seed survival. These decisions are influenced by environmental variation at spatial scales ranging from landscapes to local foraging patches. In a field experiment, the effects of seed patch variation across three spatial scales on seed removal by western harvester ants Pogonomyrmex occidentalis were evaluated. At the largest scale we assessed harvesting in different plant communities, at the intermediate scale we assessed harvesting at different distances from ant mounds, and at the smallest scale we assessed the effects of interactions among seed species in local seed neighborhoods on seed harvesting (i.e. resource–consumer interface). Selected seed species were presented alone (monospecific treatment) and in mixture with Bromus tectorum (cheatgrass; mixture treatment) at four distances from P. occidentalis mounds in adjacent intact sagebrush and non-native cheatgrass-dominated communities in the Great Basin, Utah, USA. Seed species differed in harvest, with B. tectorum being least preferred. Large and intermediate scale variation influenced harvest. More seeds were harvested in sagebrush than in cheatgrass-dominated communities (largest scale), and the quantity of seed harvested varied with distance from mounds (intermediate-scale), although the form of the distance effect differed between plant communities. At the smallest scale, seed neighborhood affected harvest, but the patterns differed among seed species considered. Ants harvested fewer seeds from mixed-seed neighborhoods than from monospecific neighborhoods, suggesting context dependence and potential associational resistance. Further, the effects of plant community and distance from mound on seed harvest in mixtures differed from their effects in monospecific treatments. Beyond the local seed neighborhood, selection of seed resources is better understood by simultaneously evaluating removal at multiple scales. Associational effects provide a useful theoretical basis for better understanding harvester ant foraging decisions. These results demonstrate the importance of ecological context for seed removal, which has implications for seed pools, plant populations and communities.

Spatial Pattern of Attacks of the Invasive Woodwasp Sirex noctilio, at Landscape and Stand Scales.

PubMed

Lantschner, M Victoria; Corley, Juan C

2015-01-01

Invasive insect pests are responsible for important damage to native and plantation forests, when population outbreaks occur. Understanding the spatial pattern of attacks by forest pest populations is essential to improve our understanding of insect population dynamics and for predicting attack risk by invasives or planning pest management strategies. The woodwasp Sirex noctilio is an invasive woodwasp that has become probably the most important pest of pine plantations in the Southern Hemisphere. Our aim was to study the spatial dynamics of S. noctilio populations in Southern Argentina. Specifically we describe: (1) the spatial patterns of S. noctilio outbreaks and their relation with environmental factors at a landscape scale; and (2) characterize the spatial pattern of attacked trees at the stand scale. We surveyed the spatial distribution of S. noctilio outbreaks in three pine plantation landscapes, and we assessed potential associations with topographic variables, habitat characteristics, and distance to other outbreaks. We also looked at the spatial distribution of attacked trees in 20 stands with different levels of infestation, and assessed the relationship of attacks with stand composition and management. We found that the spatial pattern of pine stands with S. noctilio outbreaks at the landscape scale is influenced mainly by the host species present, slope aspect, and distance to other outbreaks. At a stand scale, there is strong aggregation of attacked trees in stands with intermediate infestation levels, and the degree of attacks is influenced by host species and plantation management. We conclude that the pattern of S. noctilio damage at different spatial scales is influenced by a combination of both inherent population dynamics and the underlying patterns of environmental factors. Our results have important implications for the understanding and management of invasive insect outbreaks in forest systems.

Using Electromagnetic Induction Technique to Detect Hydropedological Dynamics: Principles and Applications

NASA Astrophysics Data System (ADS)

Zhu, Qing; Liao, Kaihua; Doolittle, James; Lin, Henry

2014-05-01

Hydropedological dynamics including soil moisture variation, subsurface flow, and spatial distributions of different soil properties are important parameters in ecological, environmental, hydrological, and agricultural modeling and applications. However, technical gap exists in mapping these dynamics at intermediate spatial scale (e.g., farm and catchment scales). At intermediate scales, in-situ monitoring provides detailed data, but is restricted in number and spatial coverage; while remote sensing provides more acceptable spatial coverage, but has comparatively low spatial resolution, limited observation depths, and is greatly influenced by the surface condition and climate. As a non-invasive, fast, and convenient geophysical tool, electromagnetic induction (EMI) measures soil apparent electrical conductivity (ECa) and has great potential to bridge this technical gap. In this presentation, principles of different EMI meters are briefly introduced. Then, case studies of using repeated EMI to detect spatial distributions of subsurface convergent flow, soil moisture dynamics, soil types and their transition zones, and different soil properties are presented. The suitability, effectiveness, and accuracy of EMI are evaluated for mapping different hydropedological dynamics. Lastly, contributions of different hydropedological and terrain properties on soil ECa are quantified under different wetness conditions, seasons, and land use types using Classification and Regression Tree model. Trend removal and residual analysis are then used for further mining of EMI survey data. Based on these analyses, proper EMI survey designs and data processing are proposed.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis.

PubMed

Westerholt, Rene; Steiger, Enrico; Resch, Bernd; Zipf, Alexander

2016-01-01

Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially.

Spatial and Temporal Uncertainty of Crop Yield Aggregations

NASA Technical Reports Server (NTRS)

Porwollik, Vera; Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Iizumi, Toshichika; Ray, Deepak K.; Ruane, Alex C.; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe;

Multiple regression and inverse moments improve the characterization of the spatial scaling behavior of daily streamflows in the Southeast United States

USGS Publications Warehouse

Farmer, William H.; Over, Thomas M.; Vogel, Richard M.

2015-01-01

Understanding the spatial structure of daily streamflow is essential for managing freshwater resources, especially in poorly-gaged regions. Spatial scaling assumptions are common in flood frequency prediction (e.g., index-flood method) and the prediction of continuous streamflow at ungaged sites (e.g. drainage-area ratio), with simple scaling by drainage area being the most common assumption. In this study, scaling analyses of daily streamflow from 173 streamgages in the southeastern US resulted in three important findings. First, the use of only positive integer moment orders, as has been done in most previous studies, captures only the probabilistic and spatial scaling behavior of flows above an exceedance probability near the median; negative moment orders (inverse moments) are needed for lower streamflows. Second, assessing scaling by using drainage area alone is shown to result in a high degree of omitted-variable bias, masking the true spatial scaling behavior. Multiple regression is shown to mitigate this bias, controlling for regional heterogeneity of basin attributes, especially those correlated with drainage area. Previous univariate scaling analyses have neglected the scaling of low-flow events and may have produced biased estimates of the spatial scaling exponent. Third, the multiple regression results show that mean flows scale with an exponent of one, low flows scale with spatial scaling exponents greater than one, and high flows scale with exponents less than one. The relationship between scaling exponents and exceedance probabilities may be a fundamental signature of regional streamflow. This signature may improve our understanding of the physical processes generating streamflow at different exceedance probabilities. 

Environmental filtering structures tree functional traits combination and lineages across space in tropical tree assemblages.

PubMed

Asefa, Mengesha; Cao, Min; Zhang, Guocheng; Ci, Xiuqin; Li, Jie; Yang, Jie

2017-03-09

Environmental filtering consistently shapes the functional and phylogenetic structure of species across space within diverse forests. However, poor descriptions of community functional and lineage distributions across space hamper the accurate understanding of coexistence mechanisms. We combined environmental variables and geographic space to explore how traits and lineages are filtered by environmental factors using extended RLQ and fourth-corner analyses across different spatial scales. The dispersion patterns of traits and lineages were also examined in a 20-ha tropical rainforest dynamics plot in southwest China. We found that environmental filtering was detected across all spatial scales except the largest scale (100 × 100 m). Generally, the associations between functional traits and environmental variables were more or less consistent across spatial scales. Species with high resource acquisition-related traits were associated with the resource-rich part of the plot across the different spatial scales, whereas resource-conserving functional traits were distributed in limited-resource environments. Furthermore, we found phylogenetic and functional clustering at all spatial scales. Similar functional strategies were also detected among distantly related species, suggesting that phylogenetic distance is not necessarily a proxy for functional distance. In summary, environmental filtering considerably structured the trait and lineage assemblages in this species-rich tropical rainforest.

Radar ornithology and the conservation of migratory birds

Treesearch

Sidney A. Gauthreaux; Carroll G. Belser

2005-01-01

It is possible to study with surveillance radar the movements of migrating birds in the atmosphere at different spatial scales. At a spatial scale within a range of 6 kilometers, high-resolution, 3-centimeter wavelength surveillance radar (e.g. BIRDRAD) can detect the departure of migrants from different types of habitat within a few kilometers of the radar. The radar...

Spatial and temporal variability in forest growth in the Olympic Mountains, Washington: sensitivity to climatic variability.

Treesearch

Melisa L. Holman; David L. Peterson

2006-01-01

We compared annual basal area increment (BAI) at different spatial scales among all size classes and species at diverse locations in the wet western and dry northeastern Olympic Mountains. Weak growth correlations at small spatial scales (average R = 0.084-0.406) suggest that trees are responding to local growth conditions. However, significant...

Spatial congruence in language and species richness but not threat in the world's top linguistic hotspot.

PubMed

Turvey, Samuel T; Pettorelli, Nathalie

2014-12-07

Languages share key evolutionary properties with biological species, and global-level spatial congruence in richness and threat is documented between languages and several taxonomic groups. However, there is little understanding of the functional connection between diversification or extinction in languages and species, or the relationship between linguistic and species richness across different spatial scales. New Guinea is the world's most linguistically rich region and contains extremely high biological diversity. We demonstrate significant positive relationships between language and mammal richness in New Guinea across multiple spatial scales, revealing a likely functional relationship over scales at which infra-island diversification may occur. However, correlations are driven by spatial congruence between low levels of language and species richness. Regional biocultural richness may have showed closer congruence before New Guinea's linguistic landscape was altered by Holocene demographic events. In contrast to global studies, we demonstrate a significant negative correlation across New Guinea between areas with high levels of threatened languages and threatened mammals, indicating that landscape-scale threats differ between these groups. Spatial resource prioritization to conserve biodiversity may not benefit threatened languages, and conservation policy must adopt a multi-faceted approach to protect biocultural diversity as a whole.

Regional and sediment depth differences in nematode community structure greater than between habitats on the New Zealand margin: Implications for vulnerability to anthropogenic disturbance

NASA Astrophysics Data System (ADS)

Rosli, Norliana; Leduc, Daniel; Rowden, Ashley A.; Probert, P. Keith; Clark, Malcolm R.

2018-01-01

Deep-sea community attributes vary at a range of spatial scales. However, identifying the scale at which environmental factors affect variability in deep-sea communities remains difficult, as few studies have been designed in such a way as to allow meaningful comparisons across more than two spatial scales. In the present study, we investigated nematode diversity, community structure and trophic structure at different spatial scales (sediment depth (cm), habitat (seamount, canyon, continental slope; 1-100 km), and geographic region (100-10000 km)), while accounting for the effects of water depth, in two regions on New Zealand's continental margin. The greatest variability in community attributes was found between sediment depth layers and between regions, which explained 2-4 times more variability than habitats. The effect of habitat was consistently stronger in the Hikurangi Margin than the Bay of Plenty for all community attributes, whereas the opposite pattern was found in the Bay of Plenty where effect of sediment depth was greater in Bay of Plenty. The different patterns at each scale in each region reflect the differences in the environmental variables between regions that control nematode community attributes. Analyses suggest that nematode communities are mostly influenced by sediment characteristics and food availability, but that disturbance (fishing activity and bioturbation) also accounts for some of the observed patterns. The results provide new insight on the relative importance of processes operating at different spatial scales in regulating nematode communities in the deep-sea, and indicate potential differences in vulnerability to anthropogenic disturbance.

Integrating High-Resolution Datasets to Target Mitigation Efforts for Improving Air Quality and Public Health in Urban Neighborhoods

PubMed Central

Shandas, Vivek; Voelkel, Jackson; Rao, Meenakshi; George, Linda

2016-01-01

Reducing exposure to degraded air quality is essential for building healthy cities. Although air quality and population vary at fine spatial scales, current regulatory and public health frameworks assess human exposures using county- or city-scales. We build on a spatial analysis technique, dasymetric mapping, for allocating urban populations that, together with emerging fine-scale measurements of air pollution, addresses three objectives: (1) evaluate the role of spatial scale in estimating exposure; (2) identify urban communities that are disproportionately burdened by poor air quality; and (3) estimate reduction in mobile sources of pollutants due to local tree-planting efforts using nitrogen dioxide. Our results show a maximum value of 197% difference between cadastrally-informed dasymetric system (CIDS) and standard estimations of population exposure to degraded air quality for small spatial extent analyses, and a lack of substantial difference for large spatial extent analyses. These results provide the foundation for improving policies for managing air quality, and targeting mitigation efforts to address challenges of environmental justice. PMID:27527205

The relationship between observational scale and explained variance in benthic communities

PubMed Central

Flood, Roger D.; Frisk, Michael G.; Garza, Corey D.; Lopez, Glenn R.; Maher, Nicole P.

2018-01-01

This study addresses the impact of spatial scale on explaining variance in benthic communities. In particular, the analysis estimated the fraction of community variation that occurred at a spatial scale smaller than the sampling interval (i.e., the geographic distance between samples). This estimate is important because it sets a limit on the amount of community variation that can be explained based on the spatial configuration of a study area and sampling design. Six benthic data sets were examined that consisted of faunal abundances, common environmental variables (water depth, grain size, and surficial percent cover), and sonar backscatter treated as a habitat proxy (categorical acoustic provinces). Redundancy analysis was coupled with spatial variograms generated by multiscale ordination to quantify the explained and residual variance at different spatial scales and within and between acoustic provinces. The amount of community variation below the sampling interval of the surveys (< 100 m) was estimated to be 36–59% of the total. Once adjusted for this small-scale variation, > 71% of the remaining variance was explained by the environmental and province variables. Furthermore, these variables effectively explained the spatial structure present in the infaunal community. Overall, no scale problems remained to compromise inferences, and unexplained infaunal community variation had no apparent spatial structure within the observational scale of the surveys (> 100 m), although small-scale gradients (< 100 m) below the observational scale may be present. PMID:29324746

Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States

NASA Astrophysics Data System (ADS)

Peng, Dailiang; Zhang, Xiaoyang; Zhang, Bing; Liu, Liangyun; Liu, Xinjie; Huete, Alfredo R.; Huang, Wenjiang; Wang, Siyuan; Luo, Shezhou; Zhang, Xiao; Zhang, Helin

2017-10-01

Land surface phenology (LSP) has been widely retrieved from satellite data at multiple spatial resolutions, but the spatial scaling effects on LSP detection are poorly understood. In this study, we collected enhanced vegetation index (EVI, 250 m) from collection 6 MOD13Q1 product over the contiguous United States (CONUS) in 2007 and 2008, and generated a set of multiple spatial resolution EVI data by resampling 250 m to 2 × 250 m and 3 × 250 m, 4 × 250 m, …, 35 × 250 m. These EVI time series were then used to detect the start of spring season (SOS) at various spatial resolutions. Further the SOS variation across scales was examined at each coarse resolution grid (35 × 250 m ≈ 8 km, refer to as reference grid) and ecoregion. Finally, the SOS scaling effects were associated with landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation within each reference grid. The results revealed the influences of satellite spatial resolutions on SOS retrievals and the related impact factors. Specifically, SOS significantly varied lineally or logarithmically across scales although the relationship could be either positive or negative. The overall SOS values averaged from spatial resolutions between 250 m and 35 × 250 m at large ecosystem regions were generally similar with a difference less than 5 days, while the SOS values within the reference grid could differ greatly in some local areas. Moreover, the standard deviation of SOS across scales in the reference grid was less than 5 days in more than 70% of area over the CONUS, which was smaller in northeastern than in southern and western regions. The SOS scaling effect was significantly associated with heterogeneity of vegetation properties characterized using land landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation, but the latter was the most important impact factor.

EXAMINATION OF MODEL PREDICTIONS AT DIFFERENT HORIZONTAL GRID RESOLUTIONS

EPA Science Inventory

While fluctuations in meteorological and air quality variables occur on a continuum of spatial scales, the horizontal grid spacing of coupled meteorological and photochemical models sets a lower limit on the spatial scales that they can resolve. However, both computational costs ...

Predator-guided sampling reveals biotic structure in the bathypelagic.

PubMed

Benoit-Bird, Kelly J; Southall, Brandon L; Moline, Mark A

2016-02-24

We targeted a habitat used differentially by deep-diving, air-breathing predators to empirically sample their prey's distributions off southern California. Fine-scale measurements of the spatial variability of potential prey animals from the surface to 1,200 m were obtained using conventional fisheries echosounders aboard a surface ship and uniquely integrated into a deep-diving autonomous vehicle. Significant spatial variability in the size, composition, total biomass, and spatial organization of biota was evident over all spatial scales examined and was consistent with the general distribution patterns of foraging Cuvier's beaked whales (Ziphius cavirostris) observed in separate studies. Striking differences found in prey characteristics between regions at depth, however, did not reflect differences observed in surface layers. These differences in deep pelagic structure horizontally and relative to surface structure, absent clear physical differences, change our long-held views of this habitat as uniform. The revelation that animals deep in the water column are so spatially heterogeneous at scales from 10 m to 50 km critically affects our understanding of the processes driving predator-prey interactions, energy transfer, biogeochemical cycling, and other ecological processes in the deep sea, and the connections between the productive surface mixed layer and the deep-water column. © 2016 The Author(s).

Environmental Controls on Multi-Scale Soil Nutrient Variability in the Tropics: the Importance of Land-Cover Change

NASA Astrophysics Data System (ADS)

Holmes, K. W.; Kyriakidis, P. C.; Chadwick, O. A.; Matricardi, E.; Soares, J. V.; Roberts, D. A.

2003-12-01

The natural controls on soil variability and the spatial scales at which correlation exists among soil and environmental variables are critical information for evaluating the effects of deforestation. We detect different spatial scales of variability in soil nutrient levels over a large region (hundreds of thousands of km2) in the Amazon, analyze correlations among soil properties at these different scales, and evaluate scale-specific relationships among soil properties and the factors potentially driving soil development. Statistical relationships among physical drivers of soil formation, namely geology, precipitation, terrain attributes, classified soil types, and land cover derived from remote sensing, were included to determine which factors are related to soil biogeochemistry at each spatial scale. Surface and subsurface soil profile data from a 3000 sample database collected in Rond“nia, Brazil, were used to investigate patterns in pH, phosphorus, nitrogen, organic carbon, effective cation exchange capacity, calcium, magnesium, potassium, aluminum, sand, and clay in this environment grading from closed canopy tropical forest to savanna. We focus on pH in this presentation for simplicity, because pH is the single most important soil characteristic for determining the chemical environment of higher plants and soil microbial activity. We determined four spatial scales which characterize integrated patterns of soil chemistry: less than 3 km; 3 to 10 km; 10 to 68 km; and from 68 to 550 km (extent of study area). Although the finest observable scale was fixed by the field sampling density, the coarser scales were determined from relationships in the data through coregionalization modeling, rather than being imposed by the researcher. Processes which affect soils over short distances, such as land cover and terrain attributes, were good predictors of fine scale spatial components of nutrients; processes which affect soils over very large distances, such as precipitation and geology, were better predictors at coarse spatial scales. However, this result may be affected by the resolution of the available predictor maps. Land-cover change exerted a strong influence on soil chemistry at fine spatial scales, and had progressively less of an effect at coarser scales. It is important to note that land cover, and interactions among land cover and the other predictors, continued to be a significant predictor of soil chemistry at every spatial scale up to hundreds of thousands of kilometers.

Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh.

PubMed

Bi, Qifang; Azman, Andrew S; Satter, Syed Moinuddin; Khan, Azharul Islam; Ahmed, Dilruba; Riaj, Altaf Ahmed; Gurley, Emily S; Lessler, Justin

2016-02-01

Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets) near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs) to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98), type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00), and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00) exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a cholera endemic population suggests a possible role for highly targeted interventions. Studies with cluster designs in areas with strong spatial clustering of exposures should increase sample size to account for the correlation of these exposures.

Individual species affect plant traits structure in their surroundings: evidence of functional mechanisms of assembly.

PubMed

Chacón-Labella, Julia; de la Cruz, Marcelino; Pescador, David S; Escudero, Adrián

2016-04-01

Evaluating community assembly through the use of functional traits is a promising tool for testing predictions arising from Niche and Coexistence theories. Although interactions among neighboring species and their inter-specific differences are known drivers of coexistence with a strong spatial signal, assessing the role of individual species on the functional structure of the community at different spatial scales remains a challenge. Here, we ask whether individual species exert a measurable effect on the spatial organization of different functional traits in local assemblages. We first propose and compute two functions that describe different aspects of functional trait organization around individual species at multiple scales: individual weighted mean area relationship and individual functional diversity area relationship. Secondly, we develop a conceptual model on the relationship and simultaneous variation of these two metrics, providing five alternative scenarios in response to the ability of some target species to modify its neighbor environment and the possible assembly mechanisms involved. Our results show that some species influence the spatial structure of specific functional traits, but their effects were always restricted to the finest spatial scales. In the basis of our conceptual model, the observed patterns point to two main mechanisms driving the functional structure of the community at the fine scale, "biotic" filtering meditated by individual species and resource partitioning driven by indirect facilitation rather than by competitive mechanisms.

Relative Contribution of Matrix Structure, Patch Resources and Management to the Local Densities of Two Large Blue Butterfly Species

PubMed Central

Skórka, Piotr; Nowicki, Piotr; Bonk, Maciej; Król, Wiesław; Szpiłyk, Damian; Woyciechowski, Michal

2016-01-01

The type of matrix, the landscape surrounding habitat patches, may determine the distribution and function of local populations. However, the matrix is often heterogeneous, and its various components may differentially contribute to metapopulation processes at different spatial scales, a phenomenon that has rarely been investigated. The aim of this study was to estimate the relative importance of matrix composition and spatial scale, habitat quality, and management intensity on the occurrence and density of local populations of two endangered large blue butterflies: Phengaris teleius and P. nausithous. Presence and abundance data were assessed over two years, 2011–12, in 100 local patches within two heterogeneous regions (near Kraków and Tarnów, southern Poland). The matrix composition was analyzed at eight spatial scales. We observed high occupancy rates in both species, regions and years. With the exception of area and isolation, almost all of the matrix components contributed to Phengaris sp. densities. The different matrix components acted at different spatial scales (grassland cover within 4 and 3 km, field cover within 0.4 and 0.3 km and water cover within 4 km radii for P. teleius and P. nausithous, respectively) and provided the highest independent contribution to the butterfly densities. Additionally, the effects of a 0.4 km radius of forest cover and a food plant cover on P. teleius, and a 1 km radius of settlement cover and management intensity on P. nausithous densities were observed. Contrary to former studies we conclude that the matrix heterogeneity and spatial scale rather than general matrix type are of relevance for densities of butterflies. Conservation strategies for these umbrella species should concentrate on maintaining habitat quality and managing matrix composition at the most appropriate spatial scales. PMID:28005942

Relative Contribution of Matrix Structure, Patch Resources and Management to the Local Densities of Two Large Blue Butterfly Species.

PubMed

Kajzer-Bonk, Joanna; Skórka, Piotr; Nowicki, Piotr; Bonk, Maciej; Król, Wiesław; Szpiłyk, Damian; Woyciechowski, Michal

2016-01-01

The type of matrix, the landscape surrounding habitat patches, may determine the distribution and function of local populations. However, the matrix is often heterogeneous, and its various components may differentially contribute to metapopulation processes at different spatial scales, a phenomenon that has rarely been investigated. The aim of this study was to estimate the relative importance of matrix composition and spatial scale, habitat quality, and management intensity on the occurrence and density of local populations of two endangered large blue butterflies: Phengaris teleius and P. nausithous. Presence and abundance data were assessed over two years, 2011-12, in 100 local patches within two heterogeneous regions (near Kraków and Tarnów, southern Poland). The matrix composition was analyzed at eight spatial scales. We observed high occupancy rates in both species, regions and years. With the exception of area and isolation, almost all of the matrix components contributed to Phengaris sp. densities. The different matrix components acted at different spatial scales (grassland cover within 4 and 3 km, field cover within 0.4 and 0.3 km and water cover within 4 km radii for P. teleius and P. nausithous, respectively) and provided the highest independent contribution to the butterfly densities. Additionally, the effects of a 0.4 km radius of forest cover and a food plant cover on P. teleius, and a 1 km radius of settlement cover and management intensity on P. nausithous densities were observed. Contrary to former studies we conclude that the matrix heterogeneity and spatial scale rather than general matrix type are of relevance for densities of butterflies. Conservation strategies for these umbrella species should concentrate on maintaining habitat quality and managing matrix composition at the most appropriate spatial scales.

Spatial and temporal variance in fatty acid and stable isotope signatures across trophic levels in large river systems

USGS Publications Warehouse

Fritts, Andrea; Knights, Brent C.; Lafrancois, Toben D.; Bartsch, Lynn; Vallazza, Jon; Bartsch, Michelle; Richardson, William B.; Karns, Byron N.; Bailey, Sean; Kreiling, Rebecca

2018-01-01

Fatty acid and stable isotope signatures allow researchers to better understand food webs, food sources, and trophic relationships. Research in marine and lentic systems has indicated that the variance of these biomarkers can exhibit substantial differences across spatial and temporal scales, but this type of analysis has not been completed for large river systems. Our objectives were to evaluate variance structures for fatty acids and stable isotopes (i.e. δ13C and δ15N) of seston, threeridge mussels, hydropsychid caddisflies, gizzard shad, and bluegill across spatial scales (10s-100s km) in large rivers of the Upper Mississippi River Basin, USA that were sampled annually for two years, and to evaluate the implications of this variance on the design and interpretation of trophic studies. The highest variance for both isotopes was present at the largest spatial scale for all taxa (except seston δ15N) indicating that these isotopic signatures are responding to factors at a larger geographic level rather than being influenced by local-scale alterations. Conversely, the highest variance for fatty acids was present at the smallest spatial scale (i.e. among individuals) for all taxa except caddisflies, indicating that the physiological and metabolic processes that influence fatty acid profiles can differ substantially between individuals at a given site. Our results highlight the need to consider the spatial partitioning of variance during sample design and analysis, as some taxa may not be suitable to assess ecological questions at larger spatial scales.

A variance-decomposition approach to investigating multiscale habitat associations

USGS Publications Warehouse

Lawler, J.J.; Edwards, T.C.

2006-01-01

The recognition of the importance of spatial scale in ecology has led many researchers to take multiscale approaches to studying habitat associations. However, few of the studies that investigate habitat associations at multiple spatial scales have considered the potential effects of cross-scale correlations in measured habitat variables. When cross-scale correlations in such studies are strong, conclusions drawn about the relative strength of habitat associations at different spatial scales may be inaccurate. Here we adapt and demonstrate an analytical technique based on variance decomposition for quantifying the influence of cross-scale correlations on multiscale habitat associations. We used the technique to quantify the variation in nest-site locations of Red-naped Sapsuckers (Sphyrapicus nuchalis) and Northern Flickers (Colaptes auratus) associated with habitat descriptors at three spatial scales. We demonstrate how the method can be used to identify components of variation that are associated only with factors at a single spatial scale as well as shared components of variation that represent cross-scale correlations. Despite the fact that no explanatory variables in our models were highly correlated (r < 0.60), we found that shared components of variation reflecting cross-scale correlations accounted for roughly half of the deviance explained by the models. These results highlight the importance of both conducting habitat analyses at multiple spatial scales and of quantifying the effects of cross-scale correlations in such analyses. Given the limits of conventional analytical techniques, we recommend alternative methods, such as the variance-decomposition technique demonstrated here, for analyzing habitat associations at multiple spatial scales. ?? The Cooper Ornithological Society 2006.

Accuracy of stream habitat interpolations across spatial scales

USGS Publications Warehouse

Sheehan, Kenneth R.; Welsh, Stuart A.

2013-01-01

Stream habitat data are often collected across spatial scales because relationships among habitat, species occurrence, and management plans are linked at multiple spatial scales. Unfortunately, scale is often a factor limiting insight gained from spatial analysis of stream habitat data. Considerable cost is often expended to collect data at several spatial scales to provide accurate evaluation of spatial relationships in streams. To address utility of single scale set of stream habitat data used at varying scales, we examined the influence that data scaling had on accuracy of natural neighbor predictions of depth, flow, and benthic substrate. To achieve this goal, we measured two streams at gridded resolution of 0.33 × 0.33 meter cell size over a combined area of 934 m2 to create a baseline for natural neighbor interpolated maps at 12 incremental scales ranging from a raster cell size of 0.11 m2 to 16 m2 . Analysis of predictive maps showed a logarithmic linear decay pattern in RMSE values in interpolation accuracy for variables as resolution of data used to interpolate study areas became coarser. Proportional accuracy of interpolated models (r2 ) decreased, but it was maintained up to 78% as interpolation scale moved from 0.11 m2 to 16 m2 . Results indicated that accuracy retention was suitable for assessment and management purposes at various scales different from the data collection scale. Our study is relevant to spatial modeling, fish habitat assessment, and stream habitat management because it highlights the potential of using a single dataset to fulfill analysis needs rather than investing considerable cost to develop several scaled datasets.

A multi-scale approach of fluvial biogeomorphic dynamics using photogrammetry.

PubMed

Hortobágyi, Borbála; Corenblit, Dov; Vautier, Franck; Steiger, Johannes; Roussel, Erwan; Burkart, Andreas; Peiry, Jean-Luc

2017-11-01

Over the last twenty years, significant technical advances turned photogrammetry into a relevant tool for the integrated analysis of biogeomorphic cross-scale interactions within vegetated fluvial corridors, which will largely contribute to the development and improvement of self-sustainable river restoration efforts. Here, we propose a cost-effective, easily reproducible approach based on stereophotogrammetry and Structure from Motion (SfM) technique to study feedbacks between fluvial geomorphology and riparian vegetation at different nested spatiotemporal scales. We combined different photogrammetric methods and thus were able to investigate biogeomorphic feedbacks at all three spatial scales (i.e., corridor, alluvial bar and micro-site) and at three different temporal scales, i.e., present, recent past and long term evolution on a diversified riparian landscape mosaic. We evaluate the performance and the limits of photogrammetric methods by targeting a set of fundamental parameters necessary to study biogeomorphic feedbacks at each of the three nested spatial scales and, when possible, propose appropriate solutions. The RMSE varies between 0.01 and 2 m depending on spatial scale and photogrammetric methods. Despite some remaining difficulties to properly apply them with current technologies under all circumstances in fluvial biogeomorphic studies, e.g. the detection of vegetation density or landform topography under a dense vegetation canopy, we suggest that photogrammetry is a promising instrument for the quantification of biogeomorphic feedbacks at nested spatial scales within river systems and for developing appropriate river management tools and strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.

The modifiable areal unit problem (MAUP) in the relationship between exposure to NO2 and respiratory health

PubMed Central

2011-01-01

Background Many Canadian population health studies, including those focusing on the relationship between exposure to air pollution and health, have operationalized neighbourhoods at the census tract scale. At the same time, the conceptualization of place at the local scale is one of the weakest theoretical aspects in health geography. The modifiable areal unit problem (MAUP) raises issues when census tracts are used as neighbourhood proxies, and no other alternate spatial structure is used for sensitivity analysis. In the literature, conclusions on the relationship between NO2 and health outcomes are divided, and this situation may in part be due to the selection of an inappropriate spatial structure for analysis. Here, we undertake an analysis of NO2 and respiratory health in Ottawa, Canada using three different spatial structures in order to elucidate the effects that the spatial unit of analysis can have on analytical results. Results Using three different spatial structures to examine and quantify the relationship between NO2 and respiratory morbidity, we offer three main conclusions: 1) exploratory spatial analytical methods can serve as an indication of the potential effect of the MAUP; 2) OLS regression results differ significantly using different spatial representations, and this could be a contributing factor to the lack of consensus in studies that focus on the relation between NO2 and respiratory health at the area-level; and 3) the use of three spatial representations confirms no measured effect of NO2 exposure on respiratory health in Ottawa. Conclusions Area units used in population health studies should be delineated so as to represent the a priori scale of the expected scale interaction between neighbourhood processes and health. A thorough understanding of the role of the MAUP in the study of the relationship between NO2 and respiratory health is necessary for research into disease pathways based on statistical models, and for decision-makers to assess the scale at which interventions will have maximum benefit. In general, more research on the role of spatial representation in health studies is needed. PMID:22040001

Bridging the gap between small and large scale sediment budgets? - A scaling challenge in the Upper Rhone Basin, Switzerland

NASA Astrophysics Data System (ADS)

Schoch, Anna; Blöthe, Jan; Hoffmann, Thomas; Schrott, Lothar

2016-04-01

A large number of sediment budgets have been compiled on different temporal and spatial scales in alpine regions. Detailed sediment budgets based on the quantification of a number of sediment storages (e.g. talus cones, moraine deposits) exist only for a few small scale drainage basins (up to 10² km²). In contrast, large scale sediment budgets (> 10³ km²) consider only long term sediment sinks such as valley fills and lakes. Until now, these studies often neglect small scale sediment storages in the headwaters. However, the significance of these sediment storages have been reported. A quantitative verification whether headwaters function as sediment source regions is lacking. Despite substantial transport energy in mountain environments due to steep gradients and high relief, sediment flux in large river systems is frequently disconnected from alpine headwaters. This leads to significant storage of coarse-grained sediment along the flow path from rockwall source regions to large sedimentary sinks in major alpine valleys. To improve the knowledge on sediment budgets in large scale alpine catchments and to bridge the gap between small and large scale sediment budgets, we apply a multi-method approach comprising investigations on different spatial scales in the Upper Rhone Basin (URB). The URB is the largest inneralpine basin in the European Alps with a size of > 5400 km². It is a closed system with Lake Geneva acting as an ultimate sediment sink for suspended and clastic sediment. We examine the spatial pattern and volumes of sediment storages as well as the morphometry on the local and catchment-wide scale. We mapped sediment storages and bedrock in five sub-regions of the study area (Goms, Lötschen valley, Val d'Illiez, Vallée de la Liène, Turtmann valley) in the field and from high-resolution remote sensing imagery to investigate the spatial distribution of different sediment storage types (e.g. talus deposits, debris flow cones, alluvial fans). These sub-regions cover all three litho-tectonic units of the URB (Helvetic nappes, Penninic nappes, External massifs) and different catchment sizes to capture the inherent variability. Different parameters characterizing topography, surface characteristics, and vegetation cover are analyzed for each storage type. The data is then used in geostatistical models (PCA, stepwise logistic regression) to predict the spatial distribution of sediment storage for the whole URB. We further conduct morphometric analyses of the URB to gain information on the varying degree of glacial imprint and postglacial landscape evolution and their control on the spatial distribution of sediment storage in a large scale drainage basin. Geophysical methods (ground penetrating radar and electrical resistivity tomography) are applied on different sediment storage types on the local scale to estimate mean thicknesses. Additional data from published studies are used to complement our dataset. We integrate the local data in the statistical model on the spatial distribution of sediment storages for the whole URB. Hence, we can extrapolate the stored sediment volumes to the regional scale in order to bridge the gap between small and large scale studies.

Soil Bacteria and Fungi Respond on Different Spatial Scales to Invasion by the Legume Lespedeza cuneata.

PubMed

Yannarell, Anthony C; Busby, Ryan R; Denight, Michael L; Gebhart, Dick L; Taylor, Steven J

2011-01-01

The spatial scale on which microbial communities respond to plant invasions may provide important clues as to the nature of potential invader-microbe interactions. Lespedeza cuneata (Dum. Cours.) G. Don is an invasive legume that may benefit from associations with mycorrhizal fungi; however, it has also been suggested that the plant is allelopathic and may alter the soil chemistry of invaded sites through secondary metabolites in its root exudates or litter. Thus, L. cuneata invasion may interact with soil microorganisms on a variety of scales. We investigated L. cuneata-related changes to soil bacterial and fungal communities at two spatial scales using multiple sites from across its invaded N. American range. Using whole-community DNA fingerprinting, we characterized microbial community variation at the scale of entire invaded sites and at the scale of individual plants. Based on permutational multivariate analysis of variance, soil bacterial communities in heavily invaded sites were significantly different from those of uninvaded sites, but bacteria did not show any evidence of responding at very local scales around individual plants. In contrast, soil fungi did not change significantly at the scale of entire sites, but there were significant differences between fungal communities of native versus exotic plants within particular sites. The differential scaling of bacterial and fungal responses indicates that L. cuneata interacts differently with soil bacteria and soil fungi, and these microorganisms may play very different roles in the invasion process of this plant.

Multi-scale approach to the environmental factors effects on spatio-temporal variability of Chironomus salinarius (Diptera: Chironomidae) in a French coastal lagoon

NASA Astrophysics Data System (ADS)

Cartier, V.; Claret, C.; Garnier, R.; Fayolle, S.; Franquet, E.

2010-03-01

The complexity of the relationships between environmental factors and organisms can be revealed by sampling designs which consider the contribution to variability of different temporal and spatial scales, compared to total variability. From a management perspective, a multi-scale approach can lead to time-saving. Identifying environmental patterns that help maintain patchy distribution is fundamental in studying coastal lagoons, transition zones between continental and marine waters characterised by great environmental variability on spatial and temporal scales. They often present organic enrichment inducing decreased species richness and increased densities of opportunist species like C hironomus salinarius, a common species that tends to swarm and thus constitutes a nuisance for human populations. This species is dominant in the Bolmon lagoon, a French Mediterranean coastal lagoon under eutrophication. Our objective was to quantify variability due to both spatial and temporal scales and identify the contribution of different environmental factors to this variability. The population of C. salinarius was sampled from June 2007 to June 2008 every two months at 12 sites located in two areas of the Bolmon lagoon, at two different depths, with three sites per area-depth combination. Environmental factors (temperature, dissolved oxygen both in sediment and under water surface, sediment organic matter content and grain size) and microbial activities (i.e. hydrolase activities) were also considered as explanatory factors of chironomid densities and distribution. ANOVA analysis reveals significant spatial differences regarding the distribution of chironomid larvae for the area and the depth scales and their interaction. The spatial effect is also revealed for dissolved oxygen (water), salinity and fine particles (area scale), and for water column depth. All factors but water column depth show a temporal effect. Spearman's correlations highlight the seasonal effect (temperature, dissolved oxygen in sediment and water) as well as the effect of microbial activities on chironomid larvae. Our results show that a multi-scale approach identifies patchy distribution, even when there is relative environmental homogeneity.

Spatially Different Tissue-Scale Diffusivity Shapes ANGUSTIFOLIA3 Gradient in Growing Leaves.

PubMed

Kawade, Kensuke; Tanimoto, Hirokazu; Horiguchi, Gorou; Tsukaya, Hirokazu

2017-09-05

The spatial gradient of signaling molecules is pivotal for establishing developmental patterns of multicellular organisms. It has long been proposed that these gradients could arise from the pure diffusion process of signaling molecules between cells, but whether this simplest mechanism establishes the formation of the tissue-scale gradient remains unclear. Plasmodesmata are unique channel structures in plants that connect neighboring cells for molecular transport. In this study, we measured cellular- and tissue-scale kinetics of molecular transport through plasmodesmata in Arabidopsis thaliana developing leaf primordia by fluorescence recovery assays. These trans-scale measurements revealed biophysical properties of diffusive molecular transport through plasmodesmata and revealed that the tissue-scale diffusivity, but not the cellular-scale diffusivity, is spatially different along the leaf proximal-to-distal axis. We found that the gradient in cell size along the developmental axis underlies this spatially different tissue-scale diffusivity. We then asked how this diffusion-based framework functions in establishing a signaling gradient of endogenous molecules. ANGUSTIFOLIA3 (AN3) is a transcriptional co-activator, and as we have shown here, it forms a long-range signaling gradient along the leaf proximal-to-distal axis to determine a cell-proliferation domain. By genetically engineering AN3 mobility, we assessed each contribution of cell-to-cell movement and tissue growth to the distribution of the AN3 gradient. We constructed a diffusion-based theoretical model using these quantitative data to analyze the AN3 gradient formation and demonstrated that it could be achieved solely by the diffusive molecular transport in a growing tissue. Our results indicate that the spatially different tissue-scale diffusivity is a core mechanism for AN3 gradient formation. This provides evidence that the pure diffusion process establishes the formation of the long-range signaling gradient in leaf development. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Climate and Human Pressure Constraints Co-Explain Regional Plant Invasion at Different Spatial Scales

PubMed Central

García-Baquero, Gonzalo; Caño, Lidia; Biurrun, Idoia; García-Mijangos, Itziar; Loidi, Javier; Herrera, Mercedes

2016-01-01

Alien species invasion represents a global threat to biodiversity and ecosystems. Explaining invasion patterns in terms of environmental constraints will help us to assess invasion risks and plan control strategies. We aim to identify plant invasion patterns in the Basque Country (Spain), and to determine the effects of climate and human pressure on that pattern. We modeled the regional distribution of 89 invasive plant species using two approaches. First, distance-based Moran’s eigenvector maps were used to partition variation in the invasive species richness, S, into spatial components at broad and fine scales; redundancy analysis was then used to explain those components on the basis of climate and human pressure descriptors. Second, we used generalized additive mixed modeling to fit species-specific responses to the same descriptors. Climate and human pressure descriptors have different effects on S at different spatial scales. Broad-scale spatially structured temperature and precipitation, and fine-scale spatially structured human population density and percentage of natural and semi-natural areas, explained altogether 38.7% of the total variance. The distribution of 84% of the individually tested species was related to either temperature, precipitation or both, and 68% was related to either population density or natural and semi-natural areas, displaying similar responses. The spatial pattern of the invasive species richness is strongly environmentally forced, mainly by climate factors. Since individual species responses were proved to be both similarly constrained in shape and explained variance by the same environmental factors, we conclude that the pattern of invasive species richness results from individual species’ environmental preferences. PMID:27741276

Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis

PubMed Central

Zipf, Alexander

2016-01-01

Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially. PMID:27611199

Denitrification potential of riparian soils in relation to multiscale spatial environmental factors: a case study of a typical watershed, China.

PubMed

Wei, Jianbing; Feng, Hao; Cheng, Quanguo; Gao, Shiqian; Liu, Haiyan

2017-02-01

The objective of this study was to test the hypothesis that environmental regulators of riparian zone soil denitrification potential differ according to spatial scale within a watershed; consequently, a second objective was to provide spatial strategies for conserving and restoring the purification function of runoff in riparian ecosystems. The results show that soil denitrification in riparian zones was more heterogeneous at the profile scale than at the cross-section and landscape scales. At the profile scale, biogeochemical factors (including soil total organic carbon, total nitrogen, and nitrate-nitrogen) were the major direct regulators of the spatial distribution of soil denitrification enzyme activity (DEA). At the cross-section scale, factors included distance from river bank and vegetation density, while landscape-scale factors, including topographic index, elevation, and land use types, indirectly regulated the spatial distribution of DEA. At the profile scale, soil DEA was greatest in the upper soil layers. At the cross-section scale, maximum soil DEA occurred in the mid-part of the riparian zone. At the landscape scale, soil DEA showed an increasing trend towards downstream sites, except for those in urbanized areas.

Logistic regression accuracy across different spatial and temporal scales for a wide-ranging species, the marbled murrelet

Treesearch

Carolyn B. Meyer; Sherri L. Miller; C. John Ralph

2004-01-01

The scale at which habitat variables are measured affects the accuracy of resource selection functions in predicting animal use of sites. We used logistic regression models for a wide-ranging species, the marbled murrelet, (Brachyramphus marmoratus) in a large region in California to address how much changing the spatial or temporal scale of...

Spatial Interpretation of Tower, Chamber and Modelled Terrestrial Fluxes in a Tropical Forest Plantation

NASA Astrophysics Data System (ADS)

Whidden, E.; Roulet, N.

2003-04-01

Interpretation of a site average terrestrial flux may be complicated in the presence of inhomogeneities. Inhomogeneity may invalidate the basic assumptions of aerodynamic flux measurement. Chamber measurement may miss or misinterpret important temporal or spatial anomalies. Models may smooth over important nonlinearities depending on the scale of application. Although inhomogeneity is usually seen as a design problem, many sites have spatial variance that may have a large impact on net flux, and in many cases a large homogeneous surface is unrealistic. The sensitivity and validity of a site average flux are investigated in the presence of an inhomogeneous site. Directional differences are used to evaluate the validity of aerodynamic methods and the computation of a site average tower flux. Empirical and modelling methods are used to interpret the spatial controls on flux. An ecosystem model, Ecosys, is used to assess spatial length scales appropriate to the ecophysiologic controls. A diffusion model is used to compare tower, chamber, and model data, by spatially weighting contributions within the tower footprint. Diffusion model weighting is also used to improve tower flux estimates by producing footprint averaged ecological parameters (soil moisture, soil temperature, etc.). Although uncertainty remains in the validity of measurement methods and the accuracy of diffusion models, a detailed spatial interpretation is required at an inhomogeneous site. Flux estimation between methods improves with spatial interpretation, showing the importance to an estimation of a site average flux. Small-scale temporal and spatial anomalies may be relatively unimportant to overall flux, but accounting for medium-scale differences in ecophysiological controls is necessary. A combination of measurements and modelling can be used to define the appropriate time and length scales of significant non-linearity due to inhomogeneity.

A representation of place attachment: A study of spatial cognition in Latvia

NASA Astrophysics Data System (ADS)

Skilters, Jurgis; Zarina, Liga; Raita, Liva

2017-04-01

Perception of geographical space is reflected in place attachment, i.e., a multidimensional cognitive-affective link between humans and their spatial environment. Place attachment balances emotions, conception of proximity. It is both social and spatial cognitive structure. Place attachment has an impact on people's actions, which in turn reversibly affect the environment in which people live. Place attachment provides emotional regulation for humans linking local - neighborhood-scale and country and world-scale environments. In Latvia a large-scale spatial cognition study has been conducted within participatory research project „Telpas pavasaris" ("Spatial Spring") by foundation Viegli. In the study 1523 respondents reported their associations characterizing certain type of places (e.g., safe place, dangerous place, far place, close place, dear place). The answers were analyzed according to several cognitive-affective categories including modes of experience, emotional valence, geographical distance, and perceptual modality. The current results indicate that socio-cognitive and affective information are primary in respect to purely spatial information (referring to spatial objects or regions and their relations). However, different types of geographical places and spatial objects (natural or artefactual) have to be distinguished and are significant to a different degree. Our results are important for environmental and urban planning because they show the ways how socio-cognitive and affective knowledge shapes the spatial cognition of geographic environment.

Representative Sinusoids for Hepatic Four-Scale Pharmacokinetics Simulations

PubMed Central

Schwen, Lars Ole; Schenk, Arne; Kreutz, Clemens; Timmer, Jens; Bartolomé Rodríguez, María Matilde; Kuepfer, Lars; Preusser, Tobias

2015-01-01

The mammalian liver plays a key role for metabolism and detoxification of xenobiotics in the body. The corresponding biochemical processes are typically subject to spatial variations at different length scales. Zonal enzyme expression along sinusoids leads to zonated metabolization already in the healthy state. Pathological states of the liver may involve liver cells affected in a zonated manner or heterogeneously across the whole organ. This spatial heterogeneity, however, cannot be described by most computational models which usually consider the liver as a homogeneous, well-stirred organ. The goal of this article is to present a methodology to extend whole-body pharmacokinetics models by a detailed liver model, combining different modeling approaches from the literature. This approach results in an integrated four-scale model, from single cells via sinusoids and the organ to the whole organism, capable of mechanistically representing metabolization inhomogeneity in livers at different spatial scales. Moreover, the model shows circulatory mixing effects due to a delayed recirculation through the surrounding organism. To show that this approach is generally applicable for different physiological processes, we show three applications as proofs of concept, covering a range of species, compounds, and diseased states: clearance of midazolam in steatotic human livers, clearance of caffeine in mouse livers regenerating from necrosis, and a parameter study on the impact of different cell entities on insulin uptake in mouse livers. The examples illustrate how variations only discernible at the local scale influence substance distribution in the plasma at the whole-body level. In particular, our results show that simultaneously considering variations at all relevant spatial scales may be necessary to understand their impact on observations at the organism scale. PMID:26222615

Cross-scale analysis of cluster correspondence using different operational neighborhoods

NASA Astrophysics Data System (ADS)

Lu, Yongmei; Thill, Jean-Claude

2008-09-01

Cluster correspondence analysis examines the spatial autocorrelation of multi-location events at the local scale. This paper argues that patterns of cluster correspondence are highly sensitive to the definition of operational neighborhoods that form the spatial units of analysis. A subset of multi-location events is examined for cluster correspondence if they are associated with the same operational neighborhood. This paper discusses the construction of operational neighborhoods for cluster correspondence analysis based on the spatial properties of the underlying zoning system and the scales at which the zones are aggregated into neighborhoods. Impacts of this construction on the degree of cluster correspondence are also analyzed. Empirical analyses of cluster correspondence between paired vehicle theft and recovery locations are conducted on different zoning methods and across a series of geographic scales and the dynamics of cluster correspondence patterns are discussed.

Cross-scale interactions drive ecosystem responses to precipitation in the Chihuahuan Desert

USDA-ARS?s Scientific Manuscript database

Regime shifts from grass- to shrub-dominated states are widespread in arid and semiarid regions globally. These patterns of grass production and shifts to shrub dominance are spatially variable and correlate weakly with precipitation, suggesting that processes at different spatial and temporal scale...

Over 150 years of long-term fertilization alters spatial scaling of microbial biodiversity

DOE PAGES

Liang, Yuting; Wu, Liyou; Clark, Ian M.; ...

2015-04-07

Spatial scaling is a critical issue in ecology, but how anthropogenic activities like fertilization affect spatial scaling is poorly understood, especially for microbial communities. Here, we determined the effects of long-term fertilization on the spatial scaling of microbial functional diversity and its relationships to plant diversity in the 150-year-old Park Grass Experiment, the oldest continuous grassland experiment in the world. Nested samples were taken from plots with contrasting inorganic fertilization regimes, and community DNAs were analyzed using the GeoChip-based functional gene array. The slopes of microbial gene-area relationships (GARs) and plant species-area relationships (SARs) were estimated in a plot receivingmore » nitrogen (N), phosphorus (P), and potassium (K) and a control plot without fertilization. Our results indicated that long-term inorganic fertilization significantly increased both microbial GARs and plant SARs. Microbial spatial turnover rates (i.e., z values) were less than 0.1 and were significantly higher in the fertilized plot (0.0583) than in the control plot (0.0449) (P < 0.0001). The z values also varied significantly with different functional genes involved in carbon (C), N, P, and sulfur (S) cycling and with various phylogenetic groups (archaea, bacteria, and fungi). Similarly, the plant SARs increased significantly (P < 0.0001), from 0.225 in the control plot to 0.419 in the fertilized plot. Soil fertilization, plant diversity, and spatial distance had roughly equal contributions in shaping the microbial functional community structure, while soil geochemical variables contributed less. These results indicated that long-term agricultural practice could alter the spatial scaling of microbial biodiversity. Determining the spatial scaling of microbial biodiversity and its response to human activities is important but challenging in microbial ecology. Most studies to date are based on different sites that may not be truly comparable or on short-term perturbations, and hence, the results observed could represent transient responses. This study examined the spatial patterns of microbial communities in response to different fertilization regimes at the Rothamsted Research Experimental Station, which has become an invaluable resource for ecologists, environmentalists, and soil scientists. The current study is the first showing that long-term fertilization has dramatic impacts on the spatial scaling of microbial communities. By identifying the spatial patterns in response to long-term fertilization and their underlying mechanisms, this study makes fundamental contributions to predictive understanding of microbial biogeography.« less

Over 150 years of long-term fertilization alters spatial scaling of microbial biodiversity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liang, Yuting; Wu, Liyou; Clark, Ian M.

Spatial scaling is a critical issue in ecology, but how anthropogenic activities like fertilization affect spatial scaling is poorly understood, especially for microbial communities. Here, we determined the effects of long-term fertilization on the spatial scaling of microbial functional diversity and its relationships to plant diversity in the 150-year-old Park Grass Experiment, the oldest continuous grassland experiment in the world. Nested samples were taken from plots with contrasting inorganic fertilization regimes, and community DNAs were analyzed using the GeoChip-based functional gene array. The slopes of microbial gene-area relationships (GARs) and plant species-area relationships (SARs) were estimated in a plot receivingmore » nitrogen (N), phosphorus (P), and potassium (K) and a control plot without fertilization. Our results indicated that long-term inorganic fertilization significantly increased both microbial GARs and plant SARs. Microbial spatial turnover rates (i.e., z values) were less than 0.1 and were significantly higher in the fertilized plot (0.0583) than in the control plot (0.0449) (P < 0.0001). The z values also varied significantly with different functional genes involved in carbon (C), N, P, and sulfur (S) cycling and with various phylogenetic groups (archaea, bacteria, and fungi). Similarly, the plant SARs increased significantly (P < 0.0001), from 0.225 in the control plot to 0.419 in the fertilized plot. Soil fertilization, plant diversity, and spatial distance had roughly equal contributions in shaping the microbial functional community structure, while soil geochemical variables contributed less. These results indicated that long-term agricultural practice could alter the spatial scaling of microbial biodiversity. Determining the spatial scaling of microbial biodiversity and its response to human activities is important but challenging in microbial ecology. Most studies to date are based on different sites that may not be truly comparable or on short-term perturbations, and hence, the results observed could represent transient responses. This study examined the spatial patterns of microbial communities in response to different fertilization regimes at the Rothamsted Research Experimental Station, which has become an invaluable resource for ecologists, environmentalists, and soil scientists. The current study is the first showing that long-term fertilization has dramatic impacts on the spatial scaling of microbial communities. By identifying the spatial patterns in response to long-term fertilization and their underlying mechanisms, this study makes fundamental contributions to predictive understanding of microbial biogeography.« less

Integrating hydrologic and geophysical data to constrain coastal surficial aquifer processes at multiple spatial and temporal scales

USGS Publications Warehouse

Schultz, Gregory M.; Ruppel, Carolyn; Fulton, Patrick; Hyndman, David W.; Day-Lewis, Frederick D.; Singha, Kamini

2007-01-01

Since 1997, repeated, coincident geophysical surveys and extensive hydrologic studies in shallow monitoring wells have been used to study static and dynamic processes associated with surface water-groundwater interaction at a range of spatial scales at the estuarine and ocean boundaries of an undeveloped, permeable barrier island in the Georgia part of the U.S. South Atlantic Bight. Because geophysical and hydrologic data measure different parameters, at different resolution and precision, and over vastly different spatial scales, reconciling the coincident data or even combining complementary inversion, hydrogeochemcial analyses and well-based groundwater monitoring, and, in some cases, limited vegetation mapping to demonstrate the utility of an integrative, multidisciplinary approach for elucidating groundwater processes at spatial scales (tens to thousands of meters) that are often difficult to capture with traditional hydrologic approaches. The case studies highlight regional aquifer characteristics, varying degrees of lateral saltwater intrusion at estuarine boundaries, complex subsurface salinity gradients at the ocean boundary, and imaging of submarsh groundwater discharge and possible free convection in the pore waters of a clastic marsh. This study also documents the use of geophysical techniques for detecting temporal changes in groundwater salinity regimes under natural (not forced) gradients at intratidal to interannual (1998-200 Southeastern U.S.A. drought) time scales.

Space and time scales of shoreline change at Cape Cod National Seashore, MA, USA

USGS Publications Warehouse

Allen, J.R.; LaBash, C.L.; List, J.H.; Kraus, Nicholas C.; McDougal, William G.

1999-01-01

Different processes cause patterns of shoreline change which are exhibited at different magnitudes and nested into different spatial and time scale hierarchies. The 77-km outer beach at Cape Cod National Seashore offers one of the few U.S. federally owned portions of beach to study shoreline change within the full range of sediment source and sink relationships, and barely affected by human intervention. 'Mean trends' of shoreline changes are best observed at long time scales but contain much spatial variation thus many sites are not equal in response. Long-term, earlier-noted trends are confirmed but the added quantification and resolution improves greatly the understanding of appropriate spatial and time scales of those processes driving bluff retreat and barrier island changes in both north and south depocenters. Shorter timescales allow for comparison of trends and uncertainty in shoreline change at local scales but are dependent upon some measure of storm intensity and seasonal frequency. Single-event shoreline survey results for one storm at daily intervals after the erosional phase suggest a recovery time for the system of six days, identifies three sites with abnormally large change, and that responses at these sites are spatially coherent for now unknown reasons. Areas near inlets are the most variable at all time scales. Hierarchies in both process and form are suggested.

Spatio-temporal variability of soil water content on the local scale in a Mediterranean mountain area (Vallcebre, North Eastern Spain). How different spatio-temporal scales reflect mean soil water content

NASA Astrophysics Data System (ADS)

Molina, Antonio J.; Latron, Jérôme; Rubio, Carles M.; Gallart, Francesc; Llorens, Pilar

2014-08-01

As a result of complex human-land interactions and topographic variability, many Mediterranean mountain catchments are covered by agricultural terraces that have locally modified the soil water content dynamic. Understanding these local-scale dynamics helps us grasp better how hydrology behaves on the catchment scale. Thus, this study examined soil water content variability in the upper 30 cm of the soil on a Mediterranean abandoned terrace in north-east Spain. Using a dataset of high spatial (regular grid of 128 automatic TDR probes at 2.5 m intervals) and temporal (20-min time step) resolution, gathered throughout a 84-day period, the spatio-temporal variability of soil water content at the local scale and the way that different spatio-temporal scales reflect the mean soil water content were investigated. Soil water content spatial variability and its relation to wetness conditions were examined, along with the spatial structuring of the soil water content within the terrace. Then, the ability of single probes and of different combinations of spatial measurements (transects and grids) to provide a good estimate of mean soil water content on the terrace scale was explored by means of temporal stability analyses. Finally, the effect of monitoring frequency on the magnitude of detectable daily soil water content variations was studied. Results showed that soil water content spatial variability followed a bimodal pattern of increasing absolute variability with increasing soil water content. In addition, a linear trend of decreasing soil water content as the distance from the inner part of the terrace increased was identified. Once this trend was subtracted, resulting semi-variograms suggested that the spatial resolution examined was too high to appreciate spatial structuring in the data. Thus, the spatial pattern should be considered as random. Of all the spatial designs tested, the 10 × 10 m mesh grid (9 probes) was considered the most suitable option for a good, time-stable estimate of mean soil water content, as no improvement was obtained with the 5 × 5 m mesh grid (30 probes). Finally, the results of temporal aggregation showed that decreasing the monitoring frequency down to 8 h during wetting-up periods and to 1 day during drying-down ones did not result in a loss of information on daily soil water content variations.

Integration of multi-disciplinary geospatial data for delineating agroecosystem uniform management zones.

PubMed

Liu, Huanjun; Huffman, Ted; Liu, Jiangui; Li, Zhe; Daneshfar, Bahram; Zhang, Xinle

2015-01-01

Understanding agricultural ecosystems and their complex interactions with the environment is important for improving agricultural sustainability and environmental protection. Developing the necessary understanding requires approaches that integrate multi-source geospatial data and interdisciplinary relationships at different spatial scales. In order to identify and delineate landscape units representing relatively homogenous biophysical properties and eco-environmental functions at different spatial scales, a hierarchical system of uniform management zones (UMZ) is proposed. The UMZ hierarchy consists of seven levels of units at different spatial scales, namely site-specific, field, local, regional, country, continent, and globe. Relatively few studies have focused on the identification of the two middle levels of units in the hierarchy, namely the local UMZ (LUMZ) and the regional UMZ (RUMZ), which prevents true eco-environmental studies from being carried out across the full range of scales. This study presents a methodology to delineate LUMZ and RUMZ spatial units using land cover, soil, and remote sensing data. A set of objective criteria were defined and applied to evaluate the within-zone homogeneity and between-zone separation of the delineated zones. The approach was applied in a farming and forestry region in southeastern Ontario, Canada, and the methodology was shown to be objective, flexible, and applicable with commonly available spatial data. The hierarchical delineation of UMZs can be used as a tool to organize the spatial structure of agricultural landscapes, to understand spatial relationships between cropping practices and natural resources, and to target areas for application of specific environmental process models and place-based policy interventions.

SIMULATED IMPACTS OF SMALL-SCALE SPATIAL DISTRIBUTION OF IMPERVIOUS AREA ON RUNOFF RESPONSE OF FIELD-SCALE CATCHMENTS

EPA Science Inventory

Impervious surface is known to negatively affect catchment hydrology through both its extent and spatial distribution. In this study, we empirically quantify via model simulations the impacts of different configurations of impervious surface on watershed response to rainfall. An ...

Distribution patterns of the crab Ucides cordatus (Brachyura, Ucididae) at different spatial scales in subtropical mangroves of Paranaguá Bay (southern Brazil)

NASA Astrophysics Data System (ADS)

Sandrini-Neto, L.; Lana, P. C.

2012-06-01

Heterogeneity in the distribution of organisms occurs at a range of spatial scales, which may vary from few centimeters to hundreds of kilometers. The exclusion of small-scale variability from routine sampling designs may confound comparisons at larger scales and lead to inconsistent interpretation of data. Despite its ecological and social-economic importance, little is known about the spatial structure of the mangrove crab Ucides cordatus in the southwest Atlantic. Previous studies have commonly compared densities at relatively broad scales, relying on alleged distribution patterns (e.g., mangroves of distinct composition and structure). We have assessed variability patterns of U. cordatus in mangroves of Paranaguá Bay at four levels of spatial hierarchy (10 s km, km, 10 s m and m) using a nested ANOVA and variance components measures. The potential role of sediment parameters, pneumatophore density, and organic matter content in regulating observed patterns was assessed by multiple regression models. Densities of total and non-commercial size crabs varied mostly at 10 s m to km scales. Densities of commercial size crabs differed at the scales of 10 s m and 10 s km. Variance components indicated that small-scale variation was the most important, contributing up to 70% of the crab density variability. Multiple regression models could not explain the observed variations. Processes driving differences in crab abundance were not related to the measured variables. Small-scale patchy distribution has direct implications to current management practices of U. cordatus. Future studies should consider processes operating at smaller scales, which are responsible for a complex mosaic of patches within previously described patterns.

Spatial localization in heterogeneous systems

NASA Astrophysics Data System (ADS)

Kao, Hsien-Ching; Beaume, Cédric; Knobloch, Edgar

2014-01-01

We study spatial localization in the generalized Swift-Hohenberg equation with either quadratic-cubic or cubic-quintic nonlinearity subject to spatially heterogeneous forcing. Different types of forcing (sinusoidal or Gaussian) with different spatial scales are considered and the corresponding localized snaking structures are computed. The results indicate that spatial heterogeneity exerts a significant influence on the location of spatially localized structures in both parameter space and physical space, and on their stability properties. The results are expected to assist in the interpretation of experiments on localized structures where departures from spatial homogeneity are generally unavoidable.

Fractal Characterization of Multitemporal Scaled Remote Sensing Data

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Lam, Nina Siu-Ngan; Qiu, Hong-lie

1998-01-01

Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the ingestion, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISS. Scale is fundamental to the characterization of geo-spatial data as represented in GISS, but we have relatively little insight on the effects of, or how to measure the effects of, scale in representing multiscaled data; i.e., data that are acquired in different formats (e.g., map, digital) and exist in varying spatial, temporal, and in the case of remote sensing data, radiometric, configurations. This is particularly true in the emerging era of Integrated GISs (IGIS), wherein spatial data in a variety of formats (e.g., raster, vector) are combined with multiscaled remote sensing data, capable of performing highly sophisticated space-time data analyses and modeling. Moreover, the complexities associated with the integration of multiscaled data sets in a multitude of formats are exacerbated by the confusion of what the term "scale" is from a multidisciplinary perspective; i.e., "scale" takes on significantly different meanings depending upon one's disciplinary background and spatial perspective which can lead to substantive confusion in the input, manipulation, analyses, and output of IGISs (Quattrochi, 1993). Hence, we must begin to look at the universality of scale and begin to develop the theory, methods, and techniques necessary to advance knowledge on the "Science of Scale" across a wide number of spatial disciplines that use GISs.

A Conceptual Framework for the Assessment of Cumulative Exposure to Air Pollution at a Fine Spatial Scale

PubMed Central

Wahida, Kihal-Talantikite; Padilla, Cindy M.; Denis, Zmirou-Navier; Olivier, Blanchard; Géraldine, Le Nir; Philippe, Quenel; Séverine, Deguen

2016-01-01

Many epidemiological studies examining long-term health effects of exposure to air pollutants have characterized exposure by the outdoor air concentrations at sites that may be distant to subjects’ residences at different points in time. The temporal and spatial mobility of subjects and the spatial scale of exposure assessment could thus lead to misclassification in the cumulative exposure estimation. This paper attempts to fill the gap regarding cumulative exposure assessment to air pollution at a fine spatial scale in epidemiological studies investigating long-term health effects. We propose a conceptual framework showing how major difficulties in cumulative long-term exposure assessment could be surmounted. We then illustrate this conceptual model on the case of exposure to NO2 following two steps: (i) retrospective reconstitution of NO2 concentrations at a fine spatial scale; and (ii) a novel approach to assigning the time-relevant exposure estimates at the census block level, using all available data on residential mobility throughout a 10- to 20-year period prior to that for which the health events are to be detected. Our conceptual framework is both flexible and convenient for the needs of different epidemiological study designs. PMID:26999170

A Conceptual Framework for the Assessment of Cumulative Exposure to Air Pollution at a Fine Spatial Scale.

PubMed

Wahida, Kihal-Talantikite; Padilla, Cindy M; Denis, Zmirou-Navier; Olivier, Blanchard; Géraldine, Le Nir; Philippe, Quenel; Séverine, Deguen

2016-03-15

Many epidemiological studies examining long-term health effects of exposure to air pollutants have characterized exposure by the outdoor air concentrations at sites that may be distant to subjects' residences at different points in time. The temporal and spatial mobility of subjects and the spatial scale of exposure assessment could thus lead to misclassification in the cumulative exposure estimation. This paper attempts to fill the gap regarding cumulative exposure assessment to air pollution at a fine spatial scale in epidemiological studies investigating long-term health effects. We propose a conceptual framework showing how major difficulties in cumulative long-term exposure assessment could be surmounted. We then illustrate this conceptual model on the case of exposure to NO₂ following two steps: (i) retrospective reconstitution of NO₂ concentrations at a fine spatial scale; and (ii) a novel approach to assigning the time-relevant exposure estimates at the census block level, using all available data on residential mobility throughout a 10- to 20-year period prior to that for which the health events are to be detected. Our conceptual framework is both flexible and convenient for the needs of different epidemiological study designs.

Multiscale recurrence analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

Riedl, M.; Marwan, N.; Kurths, J.

2015-12-01

The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

Multiscale recurrence analysis of spatio-temporal data.

PubMed

Riedl, M; Marwan, N; Kurths, J

2015-12-01

The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

NASA Astrophysics Data System (ADS)

Hoffmann, Mathias; Jurisch, Nicole; Garcia Alba, Juana; Albiac Borraz, Elisa; Schmidt, Marten; Huth, Vytas; Rogasik, Helmut; Rieckh, Helene; Verch, Gernot; Sommer, Michael; Augustin, Jürgen

2017-03-01

Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon (ΔSOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial (10-30 m) and temporal changes in SOC stocks, particularly pronounced in arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in ΔSOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil-plant-atmosphere system may help to obtain temporal ΔSOC patterns but lack small-scale spatial resolution. To overcome these limitations, this study presents a reliable method to detect both short-term temporal dynamics as well as small-scale spatial differences of ΔSOC using measurements of the net ecosystem carbon balance (NECB) as a proxy. To estimate the NECB, a combination of automatic chamber (AC) measurements of CO2 exchange and empirically modeled aboveground biomass development (NPPshoot) were used. To verify our method, results were compared with ΔSOC observed by soil resampling. Soil resampling and AC measurements were performed from 2010 to 2014 at a colluvial depression located in the hummocky ground moraine landscape of northeastern Germany. The measurement site is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity regarding SOC and nitrogen (Nt) stocks. Tendencies and magnitude of ΔSOC values derived by AC measurements and repeated soil inventories corresponded well. The period of maximum plant growth was identified as being most important for the development of spatial differences in annual ΔSOC. Hence, we were able to confirm that AC-based C budgets are able to reveal small-scale spatial differences and short-term temporal dynamics of ΔSOC.

Phylogenetic congruence of lichenised fungi and algae is affected by spatial scale and taxonomic diversity.

PubMed

Buckley, Hannah L; Rafat, Arash; Ridden, Johnathon D; Cruickshank, Robert H; Ridgway, Hayley J; Paterson, Adrian M

2014-01-01

The role of species' interactions in structuring biological communities remains unclear. Mutualistic symbioses, involving close positive interactions between two distinct organismal lineages, provide an excellent means to explore the roles of both evolutionary and ecological processes in determining how positive interactions affect community structure. In this study, we investigate patterns of co-diversification between fungi and algae for a range of New Zealand lichens at the community, genus, and species levels and explore explanations for possible patterns related to spatial scale and pattern, taxonomic diversity of the lichens considered, and the level sampling replication. We assembled six independent datasets to compare patterns in phylogenetic congruence with varied spatial extent of sampling, taxonomic diversity and level of specimen replication. For each dataset, we used the DNA sequences from the ITS regions of both the fungal and algal genomes from lichen specimens to produce genetic distance matrices. Phylogenetic congruence between fungi and algae was quantified using distance-based redundancy analysis and we used geographic distance matrices in Moran's eigenvector mapping and variance partitioning to evaluate the effects of spatial variation on the quantification of phylogenetic congruence. Phylogenetic congruence was highly significant for all datasets and a large proportion of variance in both algal and fungal genetic distances was explained by partner genetic variation. Spatial variables, primarily at large and intermediate scales, were also important for explaining genetic diversity patterns in all datasets. Interestingly, spatial structuring was stronger for fungal than algal genetic variation. As the spatial extent of the samples increased, so too did the proportion of explained variation that was shared between the spatial variables and the partners' genetic variation. Different lichen taxa showed some variation in their phylogenetic congruence and spatial genetic patterns and where greater sample replication was used, the amount of variation explained by partner genetic variation increased. Our results suggest that the phylogenetic congruence pattern, at least at small spatial scales, is likely due to reciprocal co-adaptation or co-dispersal. However, the detection of these patterns varies among different lichen taxa, across spatial scales and with different levels of sample replication. This work provides insight into the complexities faced in determining how evolutionary and ecological processes may interact to generate diversity in symbiotic association patterns at the population and community levels. Further, it highlights the critical importance of considering sample replication, taxonomic diversity and spatial scale in designing studies of co-diversification.

Statistical analysis of mesoscale rainfall: Dependence of a random cascade generator on large-scale forcing

NASA Technical Reports Server (NTRS)

Over, Thomas, M.; Gupta, Vijay K.

1994-01-01

Under the theory of independent and identically distributed random cascades, the probability distribution of the cascade generator determines the spatial and the ensemble properties of spatial rainfall. Three sets of radar-derived rainfall data in space and time are analyzed to estimate the probability distribution of the generator. A detailed comparison between instantaneous scans of spatial rainfall and simulated cascades using the scaling properties of the marginal moments is carried out. This comparison highlights important similarities and differences between the data and the random cascade theory. Differences are quantified and measured for the three datasets. Evidence is presented to show that the scaling properties of the rainfall can be captured to the first order by a random cascade with a single parameter. The dependence of this parameter on forcing by the large-scale meteorological conditions, as measured by the large-scale spatial average rain rate, is investigated for these three datasets. The data show that this dependence can be captured by a one-to-one function. Since the large-scale average rain rate can be diagnosed from the large-scale dynamics, this relationship demonstrates an important linkage between the large-scale atmospheric dynamics and the statistical cascade theory of mesoscale rainfall. Potential application of this research to parameterization of runoff from the land surface and regional flood frequency analysis is briefly discussed, and open problems for further research are presented.

A scale-invariant change detection method for land use/cover change research

NASA Astrophysics Data System (ADS)

Xing, Jin; Sieber, Renee; Caelli, Terrence

2018-07-01

Land Use/Cover Change (LUCC) detection relies increasingly on comparing remote sensing images with different spatial and spectral scales. Based on scale-invariant image analysis algorithms in computer vision, we propose a scale-invariant LUCC detection method to identify changes from scale heterogeneous images. This method is composed of an entropy-based spatial decomposition, two scale-invariant feature extraction methods, Maximally Stable Extremal Region (MSER) and Scale-Invariant Feature Transformation (SIFT) algorithms, a spatial regression voting method to integrate MSER and SIFT results, a Markov Random Field-based smoothing method, and a support vector machine classification method to assign LUCC labels. We test the scale invariance of our new method with a LUCC case study in Montreal, Canada, 2005-2012. We found that the scale-invariant LUCC detection method provides similar accuracy compared with the resampling-based approach but this method avoids the LUCC distortion incurred by resampling.

Cortical feedback signals generalise across different spatial frequencies of feedforward inputs.

PubMed

Revina, Yulia; Petro, Lucy S; Muckli, Lars

2017-09-22

Visual processing in cortex relies on feedback projections contextualising feedforward information flow. Primary visual cortex (V1) has small receptive fields and processes feedforward information at a fine-grained spatial scale, whereas higher visual areas have larger, spatially invariant receptive fields. Therefore, feedback could provide coarse information about the global scene structure or alternatively recover fine-grained structure by targeting small receptive fields in V1. We tested if feedback signals generalise across different spatial frequencies of feedforward inputs, or if they are tuned to the spatial scale of the visual scene. Using a partial occlusion paradigm, functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis (MVPA) we investigated whether feedback to V1 contains coarse or fine-grained information by manipulating the spatial frequency of the scene surround outside an occluded image portion. We show that feedback transmits both coarse and fine-grained information as it carries information about both low (LSF) and high spatial frequencies (HSF). Further, feedback signals containing LSF information are similar to feedback signals containing HSF information, even without a large overlap in spatial frequency bands of the HSF and LSF scenes. Lastly, we found that feedback carries similar information about the spatial frequency band across different scenes. We conclude that cortical feedback signals contain information which generalises across different spatial frequencies of feedforward inputs. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Disentangling how landscape spatial and temporal heterogeneity affects Savanna birds.

PubMed

Price, Bronwyn; McAlpine, Clive A; Kutt, Alex S; Ward, Doug; Phinn, Stuart R; Ludwig, John A

2013-01-01

In highly seasonal tropical environments, temporal changes in habitat and resources are a significant determinant of the spatial distribution of species. This study disentangles the effects of spatial and mid to long-term temporal heterogeneity in habitat on the diversity and abundance of savanna birds by testing four competing conceptual models of varying complexity. Focussing on sites in northeast Australia over a 20 year time period, we used ground cover and foliage projected cover surfaces derived from a time series of Landsat Thematic Mapper imagery, rainfall data and site-level vegetation surveys to derive measures of habitat structure at local (1-100 ha) and landscape (100-1000s ha) scales. We used generalised linear models and an information theoretic approach to test the independent effects of spatial and temporal influences on savanna bird diversity and the abundance of eight species with different life-history behaviours. Of four competing models defining influences on assemblages of savanna birds, the most parsimonious included temporal and spatial variability in vegetation cover and site-scale vegetation structure, suggesting savanna bird species respond to spatial and temporal habitat heterogeneity at both the broader landscape scale and at the fine-scale. The relative weight, strength and direction of the explanatory variables changed with each of the eight species, reflecting their different ecology and behavioural traits. This study demonstrates that variations in the spatial pattern of savanna vegetation over periods of 10 to 20 years at the local and landscape scale strongly affect bird diversity and abundance. Thus, it is essential to monitor and manage both spatial and temporal variability in avian habitat to achieve long-term biodiversity outcomes.

A space-time multiscale modelling of Earth's gravity field variations

NASA Astrophysics Data System (ADS)

Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric

2017-04-01

The mass distribution within the Earth varies over a wide range of spatial and temporal scales, generating variations in the Earth's gravity field in space and time. These variations are monitored by satellites as the GRACE mission, with a 400 km spatial resolution and 10 days to 1 month temporal resolution. They are expressed in the form of gravity field models, often with a fixed spatial or temporal resolution. The analysis of these models allows us to study the mass transfers within the Earth system. Here, we have developed space-time multi-scale models of the gravity field, in order to optimize the estimation of gravity signals resulting from local processes at different spatial and temporal scales, and to adapt the time resolution of the model to its spatial resolution according to the satellites sampling. For that, we first build a 4D wavelet family combining spatial Poisson wavelets with temporal Haar wavelets. Then, we set-up a regularized inversion of inter-satellites gravity potential differences in a bayesian framework, to estimate the model parameters. To build the prior, we develop a spectral analysis, localized in time and space, of geophysical models of mass transport and associated gravity variations. Finally, we test our approach to the reconstruction of space-time variations of the gravity field due to hydrology. We first consider a global distribution of observations along the orbit, from a simplified synthetic hydrology signal comprising only annual variations at large spatial scales. Then, we consider a regional distribution of observations in Africa, and a larger number of spatial and temporal scales. We test the influence of an imperfect prior and discuss our results.

Disentangling How Landscape Spatial and Temporal Heterogeneity Affects Savanna Birds

PubMed Central

Price, Bronwyn; McAlpine, Clive A.; Kutt, Alex S.; Ward, Doug; Phinn, Stuart R.; Ludwig, John A.

2013-01-01

In highly seasonal tropical environments, temporal changes in habitat and resources are a significant determinant of the spatial distribution of species. This study disentangles the effects of spatial and mid to long-term temporal heterogeneity in habitat on the diversity and abundance of savanna birds by testing four competing conceptual models of varying complexity. Focussing on sites in northeast Australia over a 20 year time period, we used ground cover and foliage projected cover surfaces derived from a time series of Landsat Thematic Mapper imagery, rainfall data and site-level vegetation surveys to derive measures of habitat structure at local (1–100 ha) and landscape (100–1000s ha) scales. We used generalised linear models and an information theoretic approach to test the independent effects of spatial and temporal influences on savanna bird diversity and the abundance of eight species with different life-history behaviours. Of four competing models defining influences on assemblages of savanna birds, the most parsimonious included temporal and spatial variability in vegetation cover and site-scale vegetation structure, suggesting savanna bird species respond to spatial and temporal habitat heterogeneity at both the broader landscape scale and at the fine-scale. The relative weight, strength and direction of the explanatory variables changed with each of the eight species, reflecting their different ecology and behavioural traits. This study demonstrates that variations in the spatial pattern of savanna vegetation over periods of 10 to 20 years at the local and landscape scale strongly affect bird diversity and abundance. Thus, it is essential to monitor and manage both spatial and temporal variability in avian habitat to achieve long-term biodiversity outcomes. PMID:24066138

Multi-scale assimilation of remotely sensed snow observations for hydrologic estimation

NASA Astrophysics Data System (ADS)

Andreadis, K.; Lettenmaier, D.

2008-12-01

Data assimilation provides a framework for optimally merging model predictions and remote sensing observations of snow properties (snow cover extent, water equivalent, grain size, melt state), ideally overcoming limitations of both. A synthetic twin experiment is used to evaluate a data assimilation system that would ingest remotely sensed observations from passive microwave and visible wavelength sensors (brightness temperature and snow cover extent derived products, respectively) with the objective of estimating snow water equivalent. Two data assimilation techniques are used, the Ensemble Kalman filter and the Ensemble Multiscale Kalman filter (EnMKF). One of the challenges inherent in such a data assimilation system is the discrepancy in spatial scales between the different types of snow-related observations. The EnMKF represents the sample model error covariance with a tree that relates the system state variables at different locations and scales through a set of parent-child relationships. This provides an attractive framework to efficiently assimilate observations at different spatial scales. This study provides a first assessment of the feasibility of a system that would assimilate observations from multiple sensors (MODIS snow cover and AMSR-E brightness temperatures) and at different spatial scales for snow water equivalent estimation. The relative value of the different types of observations is examined. Additionally, the error characteristics of both model and observations are discussed.

Effect of spatial averaging on multifractal properties of meteorological time series

NASA Astrophysics Data System (ADS)

Hoffmann, Holger; Baranowski, Piotr; Krzyszczak, Jaromir; Zubik, Monika

2016-04-01

Introduction The process-based models for large-scale simulations require input of agro-meteorological quantities that are often in the form of time series of coarse spatial resolution. Therefore, the knowledge about their scaling properties is fundamental for transferring locally measured fluctuations to larger scales and vice-versa. However, the scaling analysis of these quantities is complicated due to the presence of localized trends and non-stationarities. Here we assess how spatially aggregating meteorological data to coarser resolutions affects the data's temporal scaling properties. While it is known that spatial aggregation may affect spatial data properties (Hoffmann et al., 2015), it is unknown how it affects temporal data properties. Therefore, the objective of this study was to characterize the aggregation effect (AE) with regard to both temporal and spatial input data properties considering scaling properties (i.e. statistical self-similarity) of the chosen agro-meteorological time series through multifractal detrended fluctuation analysis (MFDFA). Materials and Methods Time series coming from years 1982-2011 were spatially averaged from 1 to 10, 25, 50 and 100 km resolution to assess the impact of spatial aggregation. Daily minimum, mean and maximum air temperature (2 m), precipitation, global radiation, wind speed and relative humidity (Zhao et al., 2015) were used. To reveal the multifractal structure of the time series, we used the procedure described in Baranowski et al. (2015). The diversity of the studied multifractals was evaluated by the parameters of time series spectra. In order to analyse differences in multifractal properties to 1 km resolution grids, data of coarser resolutions was disaggregated to 1 km. Results and Conclusions Analysing the spatial averaging on multifractal properties we observed that spatial patterns of the multifractal spectrum (MS) of all meteorological variables differed from 1 km grids and MS-parameters were biased by -29.1 % (precipitation; width of MS) up to >4 % (min. Temperature, Radiation; asymmetry of MS). Also, the spatial variability of MS parameters was strongly affected at the highest aggregation (100 km). Obtained results confirm that spatial data aggregation may strongly affect temporal scaling properties. This should be taken into account when upscaling for large-scale studies. Acknowledgements The study was conducted within FACCE MACSUR. Please see Baranowski et al. (2015) for details on funding. References Baranowski, P., Krzyszczak, J., Sławiński, C. et al. (2015). Climate Research 65, 39-52. Hoffman, H., G. Zhao, L.G.J. Van Bussel et al. (2015). Climate Research 65, 53-69. Zhao, G., Siebert, S., Rezaei E. et al. (2015). Agricultural and Forest Meteorology 200, 156-171.

Studying neighborhood crime across different macro spatial scales: The case of robbery in 4 cities.

PubMed

Hipp, John R; Wo, James C; Kim, Young-An

2017-11-01

Whereas there is a burgeoning literature focusing on the spatial distribution of crime events across neighborhoods or micro-geographic units in a specific city, the present study expands this line of research by selecting four cities that vary across two macro-spatial dimensions: population in the micro-environment, and population in the broader macro-environment. We assess the relationship between measures constructed at different spatial scales and robbery rates in blocks in four cities: 1) San Francisco (high in micro- and macro-environment population); 2) Honolulu (high in micro- but low in macro-environment population); 3) Los Angeles (low in micro- but high in macro-environment population); 4) Sacramento (low in micro- and macro-environment population). Whereas the socio-demographic characteristics of residents further than ½ mile away do not impact robbery rates, the number of people up to 2.5 miles away are related to robbery rates, especially in the two cities with smaller micro-environment population, implying a larger spatial scale than is often considered. The results show that coefficient estimates differ somewhat more between cities differing in micro-environment population compared to those differing based on macro-environment population. It is therefore necessary to consider the broader macro-environment even when focusing on the level of crime across neighborhoods or micro-geographic units within an area. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi scale habitat relationships of Martes americana in northern Idaho, U.S.A.

Treesearch

Tzeidle N. Wasserman; Samuel A. Cushman; David O. Wallin; Jim Hayden

2012-01-01

We used bivariate scaling and logistic regression to investigate multiple-scale habitat selection by American marten (Martes americana). Bivariate scaling reveals dramatic differences in the apparent nature and strength of relationships between marten occupancy and a number of habitat variables across a range of spatial scales. These differences include reversals in...

Flexible hydrological modeling - Disaggregation from lumped catchment scale to higher spatial resolutions

NASA Astrophysics Data System (ADS)

Tran, Quoc Quan; Willems, Patrick; Pannemans, Bart; Blanckaert, Joris; Pereira, Fernando; Nossent, Jiri; Cauwenberghs, Kris; Vansteenkiste, Thomas

2015-04-01

Based on an international literature review on model structures of existing rainfall-runoff and hydrological models, a generalized model structure is proposed. It consists of different types of meteorological components, storage components, splitting components and routing components. They can be spatially organized in a lumped way, or on a grid, spatially interlinked by source-to-sink or grid-to-grid (cell-to-cell) routing. The grid size of the model can be chosen depending on the application. The user can select/change the spatial resolution depending on the needs and/or the evaluation of the accuracy of the model results, or use different spatial resolutions in parallel for different applications. Major research questions addressed during the study are: How can we assure consistent results of the model at any spatial detail? How can we avoid strong or sudden changes in model parameters and corresponding simulation results, when one moves from one level of spatial detail to another? How can we limit the problem of overparameterization/equifinality when we move from the lumped model to the spatially distributed model? The proposed approach is a step-wise one, where first the lumped conceptual model is calibrated using a systematic, data-based approach, followed by a disaggregation step where the lumped parameters are disaggregated based on spatial catchment characteristics (topography, land use, soil characteristics). In this way, disaggregation can be done down to any spatial scale, and consistently among scales. Only few additional calibration parameters are introduced to scale the absolute spatial differences in model parameters, but keeping the relative differences as obtained from the spatial catchment characteristics. After calibration of the spatial model, the accuracies of the lumped and spatial models were compared for peak, low and cumulative runoff total and sub-flows (at downstream and internal gauging stations). For the distributed models, additional validation on spatial results was done for the groundwater head values at observation wells. To ensure that the lumped model can produce results as accurate as the spatially distributed models or close regardless to the number of parameters and implemented physical processes, it was checked whether the structure of the lumped models had to be adjusted. The concept has been implemented in a PCRaster - Python platform and tested for two Belgian case studies (catchments of the rivers Dijle and Grote Nete). So far, use is made of existing model structures (NAM, PDM, VHM and HBV). Acknowledgement: These results were obtained within the scope of research activities for the Flemish Environment Agency (VMM) - division Operational Water Management on "Next Generation hydrological modeling", in cooperation with IMDC consultants, and for Flanders Hydraulics Research (Waterbouwkundig Laboratorium) on "Effect of climate change on the hydrological regime of navigable watercourses in Belgium".

Cross-scale assessment of potential habitat shifts in a rapidly changing climate

USGS Publications Warehouse

Jarnevich, Catherine S.; Holcombe, Tracy R.; Bella, Elizabeth S.; Carlson, Matthew L.; Graziano, Gino; Lamb, Melinda; Seefeldt, Steven S.; Morisette, Jeffrey T.

2014-01-01

We assessed the ability of climatic, environmental, and anthropogenic variables to predict areas of high-risk for plant invasion and consider the relative importance and contribution of these predictor variables by considering two spatial scales in a region of rapidly changing climate. We created predictive distribution models, using Maxent, for three highly invasive plant species (Canada thistle, white sweetclover, and reed canarygrass) in Alaska at both a regional scale and a local scale. Regional scale models encompassed southern coastal Alaska and were developed from topographic and climatic data at a 2 km (1.2 mi) spatial resolution. Models were applied to future climate (2030). Local scale models were spatially nested within the regional area; these models incorporated physiographic and anthropogenic variables at a 30 m (98.4 ft) resolution. Regional and local models performed well (AUC values > 0.7), with the exception of one species at each spatial scale. Regional models predict an increase in area of suitable habitat for all species by 2030 with a general shift to higher elevation areas; however, the distribution of each species was driven by different climate and topographical variables. In contrast local models indicate that distance to right-of-ways and elevation are associated with habitat suitability for all three species at this spatial level. Combining results from regional models, capturing long-term distribution, and local models, capturing near-term establishment and distribution, offers a new and effective tool for highlighting at-risk areas and provides insight on how variables acting at different scales contribute to suitability predictions. The combinations also provides easy comparison, highlighting agreement between the two scales, where long-term distribution factors predict suitability while near-term do not and vice versa.

Scale-dependent variation in forest structures in naturally dynamic boreal forest landscapes

NASA Astrophysics Data System (ADS)

Kulha, Niko; Pasanen, Leena; De Grandpré, Louis; Kuuluvainen, Timo; Aakala, Tuomas

2017-04-01

Natural forest structures vary at multiple spatial scales. This variation reflects the occurrence of driving factors, such as disturbances and variation in soil or topography. To explore and understand the linkages of forest structural characteristics and factors driving their variation, we need to recognize how the structural characteristics vary in relation to spatial scale. This can be achieved by identifying scale-dependent features in forest structure within unmanaged forest landscapes. By identifying these features and examining their relationship with potential driving factors, we can better understand the dynamics of forest structural development. Here, we examine the spatial variation in forest structures at multiple spatial scales, utilizing data from old-growth boreal forests in two regions with contrasting disturbance regimes: northern Finland and north-eastern Québec, Canada ( 67° 45'N, 29° 36'E, 49° 39'N, 67° 55'W, respectively). The three landscapes (4 km2 each) in Finland are dominated by Pinus sylvestris and Picea abies, whereas the two landscapes in Québec are dominated by Abies balsamea and Picea mariana. Québec's forests are a subject to cyclic outbreaks of the eastern spruce budworm, causing extensive mortality especially in A. balsamea-dominated stands. In the Finnish landscapes, gap- to patch-scale disturbances due to tree senescence, fungi and wind, as well as infrequent surface fires in areas dominated by P. sylvestris, prevail. Owing to the differences in the species compositions and the disturbance regimes, we expect differing scales of variation between the landscapes. To quantify patterns of variation, we visually interpret stereopairs of recent aerial photographs. From the photographs, we collect information on forest canopy coverage, species composition and dead wood. For the interpretation, each 4 km2 plot is divided into 0.1ha square cells (4096 per plot). Interpretations are validated against field observations and compiled to raster maps. We analyze the raster maps with Bayesian scale space approach (iBSiZer), which aims in capturing credible variations at different spatial scales. As a result, we can detect structural entities (e.g. patches with higher canopy cover), which deviate credibly from their surroundings. The detected entities can further be linked to specific drivers. Our results show that the role of a particular driving factor varies in relation to spatial scale. For example, in the Finnish landscapes, topoedaphic factors exerted a stronger control on broad-scale forest structural characteristics, whereas recent disturbances (quantified as the amount of dead wood) appeared to play an important role in explaining the smaller scale variation of forest structures. Here, we showcase the methodology used in the detection of scale-dependent forest structural entities and present the results of our analysis of the spatial scales of variation in the natural boreal forest structures.

Implications of construction method and spatial scale on measures of the built environment.

PubMed

Strominger, Julie; Anthopolos, Rebecca; Miranda, Marie Lynn

2016-04-28

Research surrounding the built environment (BE) and health has resulted in inconsistent findings. Experts have identified the need to examine methodological choices, such as development and testing of BE indices at varying spatial scales. We sought to examine the impact of construction method and spatial scale on seven measures of the BE using data collected at two time points. The Children's Environmental Health Initiative conducted parcel-level assessments of 57 BE variables in Durham, NC (parcel N = 30,319). Based on a priori defined variable groupings, we constructed seven mutually exclusive BE domains (housing damage, property disorder, territoriality, vacancy, public nuisances, crime, and tenancy). Domain-based indices were developed according to four different index construction methods that differentially account for number of parcels and parcel area. Indices were constructed at the census block level and two alternative spatial scales that better depict the larger neighborhood context experienced by local residents: the primary adjacency community and secondary adjacency community. Spearman's rank correlation was used to assess if indices and relationships among indices were preserved across methods. Territoriality, public nuisances, and tenancy were weakly to moderately preserved across methods at the block level while all other indices were well preserved. Except for the relationships between public nuisances and crime or tenancy, and crime and housing damage or territoriality, relationships among indices were poorly preserved across methods. The number of indices affected by construction method increased as spatial scale increased, while the impact of construction method on relationships among indices varied according to spatial scale. We found that the impact of construction method on BE measures was index and spatial scale specific. Operationalizing and developing BE measures using alternative methods at varying spatial scales before connecting to health outcomes allows researchers to better understand how methodological decisions may affect associations between health outcomes and BE measures. To ensure that associations between the BE and health outcomes are not artifacts of methodological decisions, researchers would be well-advised to conduct sensitivity analysis using different construction methods. This approach may lead to more robust results regarding the BE and health outcomes.

Spatial and temporal drivers of wildfire occurrence in the context of rural development in northern Wisconsin, USA

Treesearch

Brian R Miranda; Brian R Sturtevant; Susan I Stewart; Roger B. Hammer

2012-01-01

Most drivers underlying wildfire are dynamic, but at different spatial and temporal scales. We quantified temporal and spatial trends in wildfire patterns over two spatial extents in northern Wisconsin to identify drivers and their change through time. We used spatial point pattern analysis to quantify the spatial pattern of wildfire occurrences, and linear regression...

Multiscale Bayesian neural networks for soil water content estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.; Springer, Everett P.

2008-08-01

Artificial neural networks (ANN) have been used for some time now to estimate soil hydraulic parameters from other available or more easily measurable soil properties. However, most such uses of ANNs as pedotransfer functions (PTFs) have been at matching spatial scales (1:1) of inputs and outputs. This approach assumes that the outputs are only required at the same scale as the input data. Unfortunately, this is rarely true. Different hydrologic, hydroclimatic, and contaminant transport models require soil hydraulic parameter data at different spatial scales, depending upon their grid sizes. While conventional (deterministic) ANNs have been traditionally used in these studies, the use of Bayesian training of ANNs is a more recent development. In this paper, we develop a Bayesian framework to derive soil water retention function including its uncertainty at the point or local scale using PTFs trained with coarser-scale Soil Survey Geographic (SSURGO)-based soil data. The approach includes an ANN trained with Bayesian techniques as a PTF tool with training and validation data collected across spatial extents (scales) in two different regions in the United States. The two study areas include the Las Cruces Trench site in the Rio Grande basin of New Mexico, and the Southern Great Plains 1997 (SGP97) hydrology experimental region in Oklahoma. Each region-specific Bayesian ANN is trained using soil texture and bulk density data from the SSURGO database (scale 1:24,000), and predictions of the soil water contents at different pressure heads with point scale data (1:1) inputs are made. The resulting outputs are corrected for bias using both linear and nonlinear correction techniques. The results show good agreement between the soil water content values measured at the point scale and those predicted by the Bayesian ANN-based PTFs for both the study sites. Overall, Bayesian ANNs coupled with nonlinear bias correction are found to be very suitable tools for deriving soil hydraulic parameters at the local/fine scale from soil physical properties at coarser-scale and across different spatial extents. This approach could potentially be used for soil hydraulic properties estimation and downscaling.

Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil

PubMed Central

Luiz, Amom Mendes; Leão-Pires, Thiago Augusto; Sawaya, Ricardo J.

2016-01-01

Beta diversity patterns are the outcome of multiple processes operating at different scales. Amphibian assemblages seem to be affected by contemporary climate and dispersal-based processes. However, historical processes involved in present patterns of beta diversity remain poorly understood. We assess and disentangle geomorphological, climatic and spatial drivers of amphibian beta diversity in coastal lowlands of the Atlantic Forest, southeastern Brazil. We tested the hypothesis that geomorphological factors are more important in structuring anuran beta diversity than climatic and spatial factors. We obtained species composition via field survey (N = 766 individuals), museum specimens (N = 9,730) and literature records (N = 4,763). Sampling area was divided in four spatially explicit geomorphological units, representing historical predictors. Climatic descriptors were represented by the first two axis of a Principal Component Analysis. Spatial predictors in different spatial scales were described by Moran Eigenvector Maps. Redundancy Analysis was implemented to partition the explained variation of species composition by geomorphological, climatic and spatial predictors. Moreover, spatial autocorrelation analyses were used to test neutral theory predictions. Beta diversity was spatially structured in broader scales. Shared fraction between climatic and geomorphological variables was an important predictor of species composition (13%), as well as broad scale spatial predictors (13%). However, geomorphological variables alone were the most important predictor of beta diversity (42%). Historical factors related to geomorphology must have played a crucial role in structuring amphibian beta diversity. The complex relationships between geomorphological history and climatic gradients generated by the Serra do Mar Precambrian basements were also important. We highlight the importance of combining spatially explicit historical and contemporary predictors for understanding and disentangling major drivers of beta diversity patterns. PMID:27171522

Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil.

PubMed

Luiz, Amom Mendes; Leão-Pires, Thiago Augusto; Sawaya, Ricardo J

2016-01-01

Beta diversity patterns are the outcome of multiple processes operating at different scales. Amphibian assemblages seem to be affected by contemporary climate and dispersal-based processes. However, historical processes involved in present patterns of beta diversity remain poorly understood. We assess and disentangle geomorphological, climatic and spatial drivers of amphibian beta diversity in coastal lowlands of the Atlantic Forest, southeastern Brazil. We tested the hypothesis that geomorphological factors are more important in structuring anuran beta diversity than climatic and spatial factors. We obtained species composition via field survey (N = 766 individuals), museum specimens (N = 9,730) and literature records (N = 4,763). Sampling area was divided in four spatially explicit geomorphological units, representing historical predictors. Climatic descriptors were represented by the first two axis of a Principal Component Analysis. Spatial predictors in different spatial scales were described by Moran Eigenvector Maps. Redundancy Analysis was implemented to partition the explained variation of species composition by geomorphological, climatic and spatial predictors. Moreover, spatial autocorrelation analyses were used to test neutral theory predictions. Beta diversity was spatially structured in broader scales. Shared fraction between climatic and geomorphological variables was an important predictor of species composition (13%), as well as broad scale spatial predictors (13%). However, geomorphological variables alone were the most important predictor of beta diversity (42%). Historical factors related to geomorphology must have played a crucial role in structuring amphibian beta diversity. The complex relationships between geomorphological history and climatic gradients generated by the Serra do Mar Precambrian basements were also important. We highlight the importance of combining spatially explicit historical and contemporary predictors for understanding and disentangling major drivers of beta diversity patterns.

The effects of habitat connectivity and regional heterogeneity on artificial pond metacommunities.

PubMed

Pedruski, Michael T; Arnott, Shelley E

2011-05-01

Habitat connectivity and regional heterogeneity represent two factors likely to affect biodiversity across different spatial scales. We performed a 3 × 2 factorial design experiment to investigate the effects of connectivity, heterogeneity, and their interaction on artificial pond communities of freshwater invertebrates at the local (α), among-community (β), and regional (γ) scales. Despite expectations that the effects of connectivity would depend on levels of regional heterogeneity, no significant interactions were found for any diversity index investigated at any spatial scale. While observed responses of biodiversity to connectivity and heterogeneity depended to some extent on the diversity index and spatial partitioning formula used, the general pattern shows that these factors largely act at the β scale, as opposed to the α or γ scales. We conclude that the major role of connectivity in aquatic invertebrate communities is to act as a homogenizing force with relatively little effect on diversity at the α or γ levels. Conversely, heterogeneity acts as a force maintaining differences between communities.

Range-wide wetland associations of the King Rail: A multi-scale approach

USGS Publications Warehouse

Glisson, Wesley J.; Conway, Courtney J.; Nadeau, Christopher P.; Borgmann, Kathi L.; Laxson, Thomas A.

2015-01-01

King Rail populations have declined and identifying wetland features that influence King Rail occupancy can help prevent further population declines. We integrated continent-wide marsh bird survey data with spatial wetland data from the National Wetland Inventory (NWI) to examine wetland features that influenced King Rail occupancy throughout the species’ range. We analyzed wetland data at 7 spatial scales to examine the scale(s) at which 68 wetland features were most strongly related to King Rail occupancy. Occupancy was most strongly associated with estuarine features and brackish and tidal saltwater regimes. King Rail occupancy was positively associated with emergent and scrub-shrub wetlands and negatively associated with forested wetlands. The best spatial scale for assessing King Rail occupancy differed among wetland features; we could not identify one spatial scale (among all wetland features) that best explained variation in occupancy. Future research on King Rail habitat that includes multiple spatial scales is more likely to identify the suite of features that influence occupancy. Our results indicate that NWI data may be useful for predicting occupancy based on broad habitat features across the King Rail’s range, which may help inform management decisions for this and other wetland-dependent birds.

Dissecting the multi-scale spatial relationship of earthworm assemblages with soil environmental variability.

PubMed

Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre

2014-12-05

Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.

Assessment of the water supply:demand ratios in a Mediterranean basin under different global change scenarios and mitigation alternatives.

PubMed

Boithias, Laurie; Acuña, Vicenç; Vergoñós, Laura; Ziv, Guy; Marcé, Rafael; Sabater, Sergi

2014-02-01

Spatial differences in the supply and demand of ecosystem services such as water provisioning often imply that the demand for ecosystem services cannot be fulfilled at the local scale, but it can be fulfilled at larger scales (regional, continental). Differences in the supply:demand (S:D) ratio for a given service result in different values, and these differences might be assessed with monetary or non-monetary metrics. Water scarcity occurs where and when water resources are not enough to meet all the demands, and this affects equally the service of water provisioning and the ecosystem needs. In this study we assess the value of water in a Mediterranean basin under different global change (i.e. both climate and anthropogenic changes) and mitigation scenarios, with a non-monetary metric: the S:D ratio. We computed water balances across the Ebro basin (North-East Spain) with the spatially explicit InVEST model. We highlight the spatial and temporal mismatches existing across a single hydrological basin regarding water provisioning and its consumption, considering or not, the environmental demand (environmental flow). The study shows that water scarcity is commonly a local issue (sub-basin to region), but that all demands are met at the largest considered spatial scale (basin). This was not the case in the worst-case scenario (increasing demands and decreasing supply), as the S:D ratio at the basin scale was near 1, indicating that serious problems of water scarcity might occur in the near future even at the basin scale. The analysis of possible mitigation scenarios reveals that the impact of global change may be counteracted by the decrease of irrigated areas. Furthermore, the comparison between a non-monetary (S:D ratio) and a monetary (water price) valuation metrics reveals that the S:D ratio provides similar values and might be therefore used as a spatially explicit metric to valuate the ecosystem service water provisioning. © 2013.

Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh

PubMed Central

Bi, Qifang; Azman, Andrew S.; Satter, Syed Moinuddin; Khan, Azharul Islam; Ahmed, Dilruba; Riaj, Altaf Ahmed; Gurley, Emily S.; Lessler, Justin

2016-01-01

Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets) near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs) to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98), type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00), and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00) exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a cholera endemic population suggests a possible role for highly targeted interventions. Studies with cluster designs in areas with strong spatial clustering of exposures should increase sample size to account for the correlation of these exposures. PMID:26866926

Spatial/Temporal Variations of Crime: A Routine Activity Theory Perspective.

PubMed

de Melo, Silas Nogueira; Pereira, Débora V S; Andresen, Martin A; Matias, Lindon Fonseca

2018-05-01

Temporal and spatial patterns of crime in Campinas, Brazil, are analyzed considering the relevance of routine activity theory in a Latin American context. We use geo-referenced criminal event data, 2010-2013, analyzing spatial patterns using census tracts and temporal patterns considering seasons, months, days, and hours. Our analyses include difference in means tests, count-based regression models, and Kulldorff's scan test. We find that crime in Campinas, Brazil, exhibits both temporal and spatial-temporal patterns. However, the presence of these patterns at the different temporal scales varies by crime type. Specifically, not all crime types have statistically significant temporal patterns at all scales of analysis. As such, routine activity theory works well to explain temporal and spatial-temporal patterns of crime in Campinas, Brazil. However, local knowledge of Brazilian culture is necessary for understanding a portion of these crime patterns.

Area-based tests for association between spatial patterns

NASA Astrophysics Data System (ADS)

Maruca, Susan L.; Jacquez, Geoffrey M.

Edge effects pervade natural systems, and the processes that determine spatial heterogeneity (e.g. physical, geochemical, biological, ecological factors) occur on diverse spatial scales. Hence, tests for association between spatial patterns should be unbiased by edge effects and be based on null spatial models that incorporate the spatial heterogeneity characteristic of real-world systems. This paper develops probabilistic pattern association tests that are appropriate when edge effects are present, polygon size is heterogeneous, and the number of polygons varies from one classification to another. The tests are based on the amount of overlap between polygons in each of two partitions. Unweighted and area-weighted versions of the statistics are developed and verified using scenarios representing both polygon overlap and avoidance at different spatial scales and for different distributions of polygon sizes. These statistics were applied to Soda Butte Creek, Wyoming, to determine whether stream microhabitats, such as riffles, pools and glides, can be identified remotely using high spatial resolution hyperspectral imagery. These new ``spatially explicit'' techniques provide information and insights that cannot be obtained from the spectral information alone.

A multi-scale comparison of trait linkages to environmental and spatial variables in fish communities across a large freshwater lake.

PubMed

Strecker, Angela L; Casselman, John M; Fortin, Marie-Josée; Jackson, Donald A; Ridgway, Mark S; Abrams, Peter A; Shuter, Brian J

2011-07-01

Species present in communities are affected by the prevailing environmental conditions, and the traits that these species display may be sensitive indicators of community responses to environmental change. However, interpretation of community responses may be confounded by environmental variation at different spatial scales. Using a hierarchical approach, we assessed the spatial and temporal variation of traits in coastal fish communities in Lake Huron over a 5-year time period (2001-2005) in response to biotic and abiotic environmental factors. The association of environmental and spatial variables with trophic, life-history, and thermal traits at two spatial scales (regional basin-scale, local site-scale) was quantified using multivariate statistics and variation partitioning. We defined these two scales (regional, local) on which to measure variation and then applied this measurement framework identically in all 5 study years. With this framework, we found that there was no change in the spatial scales of fish community traits over the course of the study, although there were small inter-annual shifts in the importance of regional basin- and local site-scale variables in determining community trait composition (e.g., life-history, trophic, and thermal). The overriding effects of regional-scale variables may be related to inter-annual variation in average summer temperature. Additionally, drivers of fish community traits were highly variable among study years, with some years dominated by environmental variation and others dominated by spatially structured variation. The influence of spatial factors on trait composition was dynamic, which suggests that spatial patterns in fish communities over large landscapes are transient. Air temperature and vegetation were significant variables in most years, underscoring the importance of future climate change and shoreline development as drivers of fish community structure. Overall, a trait-based hierarchical framework may be a useful conservation tool, as it highlights the multi-scaled interactive effect of variables over a large landscape.

Application of spatial and non-spatial data analysis in determination of the factors that impact municipal solid waste generation rates in Turkey

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keser, Saniye; Duzgun, Sebnem; Department of Geodetic and Geographic Information Technologies, Middle East Technical University, 06800 Ankara

Highlights: Black-Right-Pointing-Pointer Spatial autocorrelation exists in municipal solid waste generation rates for different provinces in Turkey. Black-Right-Pointing-Pointer Traditional non-spatial regression models may not provide sufficient information for better solid waste management. Black-Right-Pointing-Pointer Unemployment rate is a global variable that significantly impacts the waste generation rates in Turkey. Black-Right-Pointing-Pointer Significances of global parameters may diminish at local scale for some provinces. Black-Right-Pointing-Pointer GWR model can be used to create clusters of cities for solid waste management. - Abstract: In studies focusing on the factors that impact solid waste generation habits and rates, the potential spatial dependency in solid waste generation datamore » is not considered in relating the waste generation rates to its determinants. In this study, spatial dependency is taken into account in determination of the significant socio-economic and climatic factors that may be of importance for the municipal solid waste (MSW) generation rates in different provinces of Turkey. Simultaneous spatial autoregression (SAR) and geographically weighted regression (GWR) models are used for the spatial data analyses. Similar to ordinary least squares regression (OLSR), regression coefficients are global in SAR model. In other words, the effect of a given independent variable on a dependent variable is valid for the whole country. Unlike OLSR or SAR, GWR reveals the local impact of a given factor (or independent variable) on the waste generation rates of different provinces. Results show that provinces within closer neighborhoods have similar MSW generation rates. On the other hand, this spatial autocorrelation is not very high for the exploratory variables considered in the study. OLSR and SAR models have similar regression coefficients. GWR is useful to indicate the local determinants of MSW generation rates. GWR model can be utilized to plan waste management activities at local scale including waste minimization, collection, treatment, and disposal. At global scale, the MSW generation rates in Turkey are significantly related to unemployment rate and asphalt-paved roads ratio. Yet, significances of these variables may diminish at local scale for some provinces. At local scale, different factors may be important in affecting MSW generation rates.« less

Consistency of Aquarius version-4 sea surface salinity with Argo products on various spatial and temporal scales

NASA Astrophysics Data System (ADS)

Lee, Tong

2017-04-01

Understanding the accuracies of satellite-derived sea surface salinity (SSS) measurements in depicting temporal changes and the dependence of the accuracies on spatiotemporal scales are important to capability assessment, future mission design, and applications to study oceanic phenomena of different spatiotemporal scales. This study quantifies the consistency between Aquarius Version-4 monthly gridded SSS (released in late 2015) with two widely used Argo monthly gridded near-surface salinity products. The analysis focused on their consistency in depicting temporal changes (including seasonal and non-seasonal) on various spatial scales: 1˚ x1˚ , 3˚ x3˚ , and 10˚ x10˚ . Globally averaged standard deviation (STD) values for Aquarius-Argo salinity differences on these three spatial scales are 0.16, 0.14, 0.09 psu, compared to those between the two Argo products of 0.10, 0.09, and 0.04 psu. Aquarius SSS compare better with Argo data on non-seasonal (e.g., interannual and intraseasonal) than for seasonal time scales. The seasonal Aquarius-Argo SSS differences are mostly concentrated at high latitudes. The Aquarius team is making active efforts to further reduce these high-latitude seasonal biases. The consistency between Aquarius and Argo salinity is similar to that between the two Argo products in the tropics and subtropics for non-seasonal signals, and in the tropics for seasonal signals. Therefore, the representativeness errors of the Argo products for various spatial scales (related to sampling and gridding) need to be taken into account when estimating the uncertainty of Aquarius SSS. The globally averaged uncertainty of large-scale (10˚ x10˚ ) non-seasonal Aquarius SSS is approximately 0.04 psu. These estimates reflect the significant improvements of Aquarius Version-4 SSS over the previous versions. The estimates can be used as baseline requirements for future ocean salinity missions from space. The spatial distribution of the uncertainty estimates is also useful for assimilation of Aquarius SSS.

Effects of hedgerows on bats and bush crickets at different spatial scales

NASA Astrophysics Data System (ADS)

Lacoeuilhe, Aurélie; Machon, Nathalie; Julien, Jean-François; Kerbiriou, Christian

2016-02-01

Biodiversity is threatened by the loss and fragmentation of habitats. The role of hedgerows in maintaining biodiversity is well established, but few studies have addressed the importance for biodiversity of the intrinsic characteristics of hedgerows and the quality of hedgerow networks along a spatial scale. We examined three quality indices providing information at different territorial levels: density in the landscape, structural diversity and wood production. We performed an acoustic survey in a grassland to estimate the species abundance and community composition of bats (9 taxa) and bush crickets (11 species). Using an approach based on species and traits, we assessed how hedgerow quality influenced the activity of these taxa at different spatial scales (from 50 to 1000 m) and focused on three types of traits: bush cricket mobility ability, bat foraging strategy and habitat specialization. In general, our results showed the importance of hedgerow quality for bats and bush crickets, but the strength of the association between taxa and hedgerows varied substantially among the species and the spatial scales. Although it depends on the taxa, the production, density and structural diversity of hedgerows each had an overall positive effect. Our results suggested that these effects were generally more important at large scales. The scale effect of the production index is the best predictor of activity for bat and bush cricket taxa and traits. Our results showed the importance of hedgerow quality for the ecology of bat and bush cricket communities and could be used to improve conservation management.

Scaling range sizes to threats for robust predictions of risks to biodiversity.

PubMed

Keith, David A; Akçakaya, H Resit; Murray, Nicholas J

2018-04-01

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range-size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red-list assessments for decades, appropriate spatial scales of AOO for predicting risks of species' extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale-sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1-1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer-scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid-measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape-scale threats to species and ecosystems. © 2017 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Sources of errors and uncertainties in the assessment of forest soil carbon stocks at different scales-review and recommendations.

PubMed

Vanguelova, E I; Bonifacio, E; De Vos, B; Hoosbeek, M R; Berger, T W; Vesterdal, L; Armolaitis, K; Celi, L; Dinca, L; Kjønaas, O J; Pavlenda, P; Pumpanen, J; Püttsepp, Ü; Reidy, B; Simončič, P; Tobin, B; Zhiyanski, M

2016-11-01

Spatially explicit knowledge of recent and past soil organic carbon (SOC) stocks in forests will improve our understanding of the effect of human- and non-human-induced changes on forest C fluxes. For SOC accounting, a minimum detectable difference must be defined in order to adequately determine temporal changes and spatial differences in SOC. This requires sufficiently detailed data to predict SOC stocks at appropriate scales within the required accuracy so that only significant changes are accounted for. When designing sampling campaigns, taking into account factors influencing SOC spatial and temporal distribution (such as soil type, topography, climate and vegetation) are needed to optimise sampling depths and numbers of samples, thereby ensuring that samples accurately reflect the distribution of SOC at a site. Furthermore, the appropriate scales related to the research question need to be defined: profile, plot, forests, catchment, national or wider. Scaling up SOC stocks from point sample to landscape unit is challenging, and thus requires reliable baseline data. Knowledge of the associated uncertainties related to SOC measures at each particular scale and how to reduce them is crucial for assessing SOC stocks with the highest possible accuracy at each scale. This review identifies where potential sources of errors and uncertainties related to forest SOC stock estimation occur at five different scales-sample, profile, plot, landscape/regional and European. Recommendations are also provided on how to reduce forest SOC uncertainties and increase efficiency of SOC assessment at each scale.

Downscaling near-surface soil moisture from field to plot scale: A comparative analysis under different environmental conditions

NASA Astrophysics Data System (ADS)

Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio

2018-02-01

Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently correlated to a climate indicator such as the aridity index.

Fractals and Spatial Methods for Mining Remote Sensing Imagery

NASA Technical Reports Server (NTRS)

Lam, Nina; Emerson, Charles; Quattrochi, Dale

2003-01-01

The rapid increase in digital remote sensing and GIS data raises a critical problem -- how can such an enormous amount of data be handled and analyzed so that useful information can be derived quickly? Efficient handling and analysis of large spatial data sets is central to environmental research, particularly in global change studies that employ time series. Advances in large-scale environmental monitoring and modeling require not only high-quality data, but also reliable tools to analyze the various types of data. A major difficulty facing geographers and environmental scientists in environmental assessment and monitoring is that spatial analytical tools are not easily accessible. Although many spatial techniques have been described recently in the literature, they are typically presented in an analytical form and are difficult to transform to a numerical algorithm. Moreover, these spatial techniques are not necessarily designed for remote sensing and GIS applications, and research must be conducted to examine their applicability and effectiveness in different types of environmental applications. This poses a chicken-and-egg problem: on one hand we need more research to examine the usability of the newer techniques and tools, yet on the other hand, this type of research is difficult to conduct if the tools to be explored are not accessible. Another problem that is fundamental to environmental research are issues related to spatial scale. The scale issue is especially acute in the context of global change studies because of the need to integrate remote-sensing and other spatial data that are collected at different scales and resolutions. Extrapolation of results across broad spatial scales remains the most difficult problem in global environmental research. There is a need for basic characterization of the effects of scale on image data, and the techniques used to measure these effects must be developed and implemented to allow for a multiple scale assessment of the data before any useful process-oriented modeling involving scale-dependent data can be conducted. Through the support of research grants from NASA, we have developed a software module called ICAMS (Image Characterization And Modeling System) to address the need to develop innovative spatial techniques and make them available to the broader scientific communities. ICAMS provides new spatial techniques, such as fractal analysis, geostatistical functions, and multiscale analysis that are not easily available in commercial GIS/image processing software. By bundling newer spatial methods in a user-friendly software module, researchers can begin to test and experiment with the new spatial analysis methods and they can gauge scale effects using a variety of remote sensing imagery. In the following, we describe briefly the development of ICAMS and present application examples.

Spatial Downscaling of TRMM Precipitation using MODIS product in the Korean Peninsula

NASA Astrophysics Data System (ADS)

Cho, H.; Choi, M.

2013-12-01

Precipitation is a major driving force in the water cycle. But, it is difficult to provide spatially distributed precipitation data from isolated individual in situ. The Tropical Rainfall Monitoring Mission (TRMM) satellite can provide precipitation data with relatively coarse spatial resolution (0.25° scale) at daily basis. In order to overcome the coarse spatial resolution of TRMM precipitation products, we conducted a downscaling technique using a scaling parameter from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor. In this study, statistical relations between precipitation estimates derived from the TRMM satellite and the normalized difference vegetation index (NDVI) which is obtained from the MODIS sensor in TERRA satellite are found for different spatial scales on the Korean peninsula in northeast Asia. We obtain the downscaled precipitation mapping by regression equation between yearly TRMM precipitations values and annual average NDVI aggregating 1km to 25 degree. The downscaled precipitation is validated using time series of the ground measurements precipitation dataset provided by Korea Meteorological Organization (KMO) from 2002 to 2005. To improve the spatial downscaling of precipitation, we will conduct a study about correlation between precipitation and land surface temperature, perceptible water and other hydrological parameters.

Influence of land use on water quality in a tropical landscape: a multi-scale analysis

PubMed Central

Yackulic, Charles B.; Lim, Yili; Arce-Nazario, Javier A.

2015-01-01

There is a pressing need to understand the consequences of human activities, such as land transformations, on watershed ecosystem services. This is a challenging task because different indicators of water quality and yield are expected to vary in their responsiveness to large versus local-scale heterogeneity in land use and land cover (LUC). Here we rely on water quality data collected between 1977 and 2000 from dozens of gauge stations in Puerto Rico together with precipitation data and land cover maps to (1) quantify impacts of spatial heterogeneity in LUC on several water quality indicators; (2) determine the spatial scale at which this heterogeneity influences water quality; and (3) examine how antecedent precipitation modulates these impacts. Our models explained 30–58% of observed variance in water quality metrics. Temporal variation in antecedent precipitation and changes in LUC between measurements periods rather than spatial variation in LUC accounted for the majority of variation in water quality. Urbanization and pasture development generally degraded water quality while agriculture and secondary forest re-growth had mixed impacts. The spatial scale over which LUC influenced water quality differed across indicators. Turbidity and dissolved oxygen (DO) responded to LUC in large-scale watersheds, in-stream nitrogen concentrations to LUC in riparian buffers of large watersheds, and fecal matter content and in-stream phosphorus concentration to LUC at the sub-watershed scale. Stream discharge modulated impacts of LUC on water quality for most of the metrics. Our findings highlight the importance of considering multiple spatial scales for understanding the impacts of human activities on watershed ecosystem services. PMID:26146455

A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint

PubMed Central

Kang, Chaogui; Liu, Yu; Guo, Diansheng; Qin, Kun

2015-01-01

We generalized the recently introduced “radiation model”, as an analog to the generalization of the classic “gravity model”, to consolidate its nature of universality for modeling diverse mobility systems. By imposing the appropriate scaling exponent λ, normalization factor κ and system constraints including searching direction and trip OD constraint, the generalized radiation model accurately captures real human movements in various scenarios and spatial scales, including two different countries and four different cities. Our analytical results also indicated that the generalized radiation model outperformed alternative mobility models in various empirical analyses. PMID:26600153

A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint.

PubMed

Kang, Chaogui; Liu, Yu; Guo, Diansheng; Qin, Kun

2015-01-01

We generalized the recently introduced "radiation model", as an analog to the generalization of the classic "gravity model", to consolidate its nature of universality for modeling diverse mobility systems. By imposing the appropriate scaling exponent λ, normalization factor κ and system constraints including searching direction and trip OD constraint, the generalized radiation model accurately captures real human movements in various scenarios and spatial scales, including two different countries and four different cities. Our analytical results also indicated that the generalized radiation model outperformed alternative mobility models in various empirical analyses.

Spatial and temporal variation in evapotranspiration

USDA-ARS?s Scientific Manuscript database

Spatial and temporal variation in evapotranspiration occurs at multiple scales as the result of several different spatial and temporal patterns in precipitation, soil water holding capacity, cloudiness (available energy), types of crops, and residue and tillage management practices. We have often as...

How large is large enough for insects? Forest fragmentation effects at three spatial scales

NASA Astrophysics Data System (ADS)

Ribas, C. R.; Sobrinho, T. G.; Schoereder, J. H.; Sperber, C. F.; Lopes-Andrade, C.; Soares, S. M.

2005-02-01

Several mechanisms may lead to species loss in fragmented habitats, such as edge and shape effects, loss of habitat and heterogeneity. Ants and crickets were sampled in 18 forest remnants in south-eastern Brazil, to test whether a group of small remnants maintains the same insect species richness as similar sized large remnants, at three spatial scales. We tested hypotheses about alpha and gamma diversity to explain the results. Groups of remnants conserve as many species of ants as a single one. Crickets, however, showed a scale-dependent pattern: at small scales there was no significant or important difference between groups of remnants and a single one, while at the larger scale the group of remnants maintained more species. Alpha diversity (local species richness) was similar in a group of remnants and in a single one, at the three spatial scales, both for ants and crickets. Gamma diversity, however, varied both with taxa (ants and crickets) and spatial scale, which may be linked to insect mobility, remnant isolation, and habitat heterogeneity. Biological characteristics of the organisms involved have to be considered when studying fragmentation effects, as well as spatial scale at which it operates. Mobility of the organisms influences fragmentation effects, and consequently conservation strategies.

Estimating Soil Organic Carbon Stocks and Spatial Patterns with Statistical and GIS-Based Methods

PubMed Central

Zhi, Junjun; Jing, Changwei; Lin, Shengpan; Zhang, Cao; Liu, Qiankun; DeGloria, Stephen D.; Wu, Jiaping

2014-01-01

Accurately quantifying soil organic carbon (SOC) is considered fundamental to studying soil quality, modeling the global carbon cycle, and assessing global climate change. This study evaluated the uncertainties caused by up-scaling of soil properties from the county scale to the provincial scale and from lower-level classification of Soil Species to Soil Group, using four methods: the mean, median, Soil Profile Statistics (SPS), and pedological professional knowledge based (PKB) methods. For the SPS method, SOC stock is calculated at the county scale by multiplying the mean SOC density value of each soil type in a county by its corresponding area. For the mean or median method, SOC density value of each soil type is calculated using provincial arithmetic mean or median. For the PKB method, SOC density value of each soil type is calculated at the county scale considering soil parent materials and spatial locations of all soil profiles. A newly constructed 1∶50,000 soil survey geographic database of Zhejiang Province, China, was used for evaluation. Results indicated that with soil classification levels up-scaling from Soil Species to Soil Group, the variation of estimated SOC stocks among different soil classification levels was obviously lower than that among different methods. The difference in the estimated SOC stocks among the four methods was lowest at the Soil Species level. The differences in SOC stocks among the mean, median, and PKB methods for different Soil Groups resulted from the differences in the procedure of aggregating soil profile properties to represent the attributes of one soil type. Compared with the other three estimation methods (i.e., the SPS, mean and median methods), the PKB method holds significant promise for characterizing spatial differences in SOC distribution because spatial locations of all soil profiles are considered during the aggregation procedure. PMID:24840890

Factors Driving Potential Ammonia Oxidation in Canadian Arctic Ecosystems: Does Spatial Scale Matter?

PubMed Central

Banerjee, Samiran

2012-01-01

Ammonia oxidation is a major process in nitrogen cycling, and it plays a key role in nitrogen limited soil ecosystems such as those in the arctic. Although mm-scale spatial dependency of ammonia oxidizers has been investigated, little is known about the field-scale spatial dependency of aerobic ammonia oxidation processes and ammonia-oxidizing archaeal and bacterial communities, particularly in arctic soils. The purpose of this study was to explore the drivers of ammonia oxidation at the field scale in cryosols (soils with permafrost within 1 m of the surface). We measured aerobic ammonia oxidation potential (both autotrophic and heterotrophic) and functional gene abundance (bacterial amoA and archaeal amoA) in 279 soil samples collected from three arctic ecosystems. The variability associated with quantifying genes was substantially less than the spatial variability observed in these soils, suggesting that molecular methods can be used reliably evaluate spatial dependency in arctic ecosystems. Ammonia-oxidizing archaeal and bacterial communities and aerobic ammonia oxidation were spatially autocorrelated. Gene abundances were spatially structured within 4 m, whereas biochemical processes were structured within 40 m. Ammonia oxidation was driven at small scales (<1m) by moisture and total organic carbon, whereas gene abundance and other edaphic factors drove ammonia oxidation at medium (1 to 10 m) and large (10 to 100 m) scales. In these arctic soils heterotrophs contributed between 29 and 47% of total ammonia oxidation potential. The spatial scale for aerobic ammonia oxidation genes differed from potential ammonia oxidation, suggesting that in arctic ecosystems edaphic, rather than genetic, factors are an important control on ammonia oxidation. PMID:22081570

Depth and Medium-Scale Spatial Processes Influence Fish Assemblage Structure of Unconsolidated Habitats in a Subtropical Marine Park

PubMed Central

Schultz, Arthur L.; Malcolm, Hamish A.; Bucher, Daniel J.; Linklater, Michelle; Smith, Stephen D. A.

2014-01-01

Where biological datasets are spatially limited, abiotic surrogates have been advocated to inform objective planning for Marine Protected Areas. However, this approach assumes close correlation between abiotic and biotic patterns. The Solitary Islands Marine Park, northern NSW, Australia, currently uses a habitat classification system (HCS) to assist with planning, but this is based only on data for reefs. We used Baited Remote Underwater Videos (BRUVs) to survey fish assemblages of unconsolidated substrata at different depths, distances from shore, and across an along-shore spatial scale of 10 s of km (2 transects) to examine how well the HCS works for this dominant habitat. We used multivariate regression modelling to examine the importance of these, and other environmental factors (backscatter intensity, fine-scale bathymetric variation and rugosity), in structuring fish assemblages. There were significant differences in fish assemblages across depths, distance from shore, and over the medium spatial scale of the study: together, these factors generated the optimum model in multivariate regression. However, marginal tests suggested that backscatter intensity, which itself is a surrogate for sediment type and hardness, might also influence fish assemblages and needs further investigation. Species richness was significantly different across all factors: however, total MaxN only differed significantly between locations. This study demonstrates that the pre-existing abiotic HCS only partially represents the range of fish assemblages of unconsolidated habitats in the region. PMID:24824998

Temporal and spatial scaling impacts on extreme precipitation

NASA Astrophysics Data System (ADS)

Eggert, B.; Berg, P.; Haerter, J. O.; Jacob, D.; Moseley, C.

2015-01-01

Both in the current climate and in the light of climate change, understanding of the causes and risk of precipitation extremes is essential for protection of human life and adequate design of infrastructure. Precipitation extreme events depend qualitatively on the temporal and spatial scales at which they are measured, in part due to the distinct types of rain formation processes that dominate extremes at different scales. To capture these differences, we first filter large datasets of high-resolution radar measurements over Germany (5 min temporally and 1 km spatially) using synoptic cloud observations, to distinguish convective and stratiform rain events. In a second step, for each precipitation type, the observed data are aggregated over a sequence of time intervals and spatial areas. The resulting matrix allows a detailed investigation of the resolutions at which convective or stratiform events are expected to contribute most to the extremes. We analyze where the statistics of the two types differ and discuss at which resolutions transitions occur between dominance of either of the two precipitation types. We characterize the scales at which the convective or stratiform events will dominate the statistics. For both types, we further develop a mapping between pairs of spatially and temporally aggregated statistics. The resulting curve is relevant when deciding on data resolutions where statistical information in space and time is balanced. Our study may hence also serve as a practical guide for modelers, and for planning the space-time layout of measurement campaigns. We also describe a mapping between different pairs of resolutions, possibly relevant when working with mismatched model and observational resolutions, such as in statistical bias correction.

Spatial clustering of mental disorders and associated characteristics of the neighbourhood context in Malmö, Sweden, in 2001

PubMed Central

Chaix, Basile; Leyland, Alastair H; Sabel, Clive E; Chauvin, Pierre; Råstam, Lennart; Kristersson, Håkan; Merlo, Juan

2006-01-01

Study objective Previous research provides preliminary evidence of spatial variations of mental disorders and associations between neighbourhood social context and mental health. This study expands past literature by (1) using spatial techniques, rather than multilevel models, to compare the spatial distributions of two groups of mental disorders (that is, disorders due to psychoactive substance use, and neurotic, stress related, and somatoform disorders); and (2) investigating the independent impact of contextual deprivation and neighbourhood social disorganisation on mental health, while assessing both the magnitude and the spatial scale of these effects. Design Using different spatial techniques, the study investigated mental disorders due to psychoactive substance use, and neurotic disorders. Participants All 89 285 persons aged 40–69 years residing in Malmö, Sweden, in 2001, geolocated to their place of residence. Main results The spatial scan statistic identified a large cluster of increased prevalence in a similar location for the two mental disorders in the northern part of Malmö. However, hierarchical geostatistical models showed that the two groups of disorders exhibited a different spatial distribution, in terms of both magnitude and spatial scale. Mental disorders due to substance consumption showed larger neighbourhood variations, and varied in space on a larger scale, than neurotic disorders. After adjustment for individual factors, the risk of substance related disorders increased with neighbourhood deprivation and neighbourhood social disorganisation. The risk of neurotic disorders only increased with contextual deprivation. Measuring contextual factors across continuous space, it was found that these associations operated on a local scale. Conclusions Taking space into account in the analyses permitted deeper insight into the contextual determinants of mental disorders. PMID:16614334

Defining ecologically relevant scales for spatial protection with long-term data on an endangered seabird and local prey availability.

PubMed

Sherley, Richard B; Botha, Philna; Underhill, Les G; Ryan, Peter G; van Zyl, Danie; Cockcroft, Andrew C; Crawford, Robert J M; Dyer, Bruce M; Cook, Timothée R

2017-12-01

Human activities are important drivers of marine ecosystem functioning. However, separating the synergistic effects of fishing and environmental variability on the prey base of nontarget predators is difficult, often because prey availability estimates on appropriate scales are lacking. Understanding how prey abundance at different spatial scales links to population change can help integrate the needs of nontarget predators into fisheries management by defining ecologically relevant areas for spatial protection. We investigated the local population response (number of breeders) of the Bank Cormorant (Phalacrocorax neglectus), a range-restricted endangered seabird, to the availability of its prey, the heavily fished west coast rock lobster (Jasus lalandii). Using Bayesian state-space modeled cormorant counts at 3 colonies, 22 years of fisheries-independent data on local lobster abundance, and generalized additive modeling, we determined the spatial scale pertinent to these relationships in areas with different lobster availability. Cormorant numbers responded positively to lobster availability in the regions with intermediate and high abundance but not where regime shifts and fishing pressure had depleted lobster stocks. The relationships were strongest when lobsters 20-30 km offshore of the colony were considered, a distance greater than the Bank Cormorant's foraging range when breeding, and may have been influenced by prey availability for nonbreeding birds, prey switching, or prey ecology. Our results highlight the importance of considering the scale of ecological relationships in marine spatial planning and suggest that designing spatial protection around focal species can benefit marine predators across their full life cycle. We propose the precautionary implementation of small-scale marine protected areas, followed by robust assessment and adaptive-management, to confirm population-level benefits for the cormorants, their prey, and the wider ecosystem, without negative impacts on local fisheries. © 2017 Society for Conservation Biology.

Spatial scaling of core and dominant forest cover in the Upper Mississippi and Illinois River floodplains, USA

USGS Publications Warehouse

De Jager, Nathan R.; Rohweder, Jason J.

2011-01-01

Different organisms respond to spatial structure in different terms and across different spatial scales. As a consequence, efforts to reverse habitat loss and fragmentation through strategic habitat restoration ought to account for the different habitat density and scale requirements of various taxonomic groups. Here, we estimated the local density of floodplain forest surrounding each of ~20 million 10-m forested pixels of the Upper Mississippi and Illinois River floodplains by using moving windows of multiple sizes (1–100 ha). We further identified forest pixels that met two local density thresholds: 'core' forest pixels were nested in a 100% (unfragmented) forested window and 'dominant' forest pixels were those nested in a >60% forested window. Finally, we fit two scaling functions to declines in the proportion of forest cover meeting these criteria with increasing window length for 107 management-relevant focal areas: a power function (i.e. self-similar, fractal-like scaling) and an exponential decay function (fractal dimension depends on scale). The exponential decay function consistently explained more variation in changes to the proportion of forest meeting both the 'core' and 'dominant' criteria with increasing window length than did the power function, suggesting that elevation, soil type, hydrology, and human land use constrain these forest types to a limited range of scales. To examine these scales, we transformed the decay constants to measures of the distance at which the probability of forest meeting the 'core' and 'dominant' criteria was cut in half (S 1/2, m). S 1/2 for core forest was typically between ~55 and ~95 m depending on location along the river, indicating that core forest cover is restricted to extremely fine scales. In contrast, half of all dominant forest cover was lost at scales that were typically between ~525 and 750 m, but S 1/2 was as long as 1,800 m. S 1/2 is a simple measure that (1) condenses information derived from multi-scale analyses, (2) allows for comparisons of the amount of forest habitat available to species with different habitat density and scale requirements, and (3) can be used as an index of the spatial continuity of habitat types that do not scale fractally.

Still searching for the Holy Grail: on the use of effective soil parameters for Parflow-CLM.

NASA Astrophysics Data System (ADS)

Baroni, Gabriele; Schalge, Bernd; Rihani, Jehan; Attinger, Sabine

2015-04-01

In the last decades the advances in computer science have led to a growing number of coupled and distributed hydrological models based on Richards' equation. Several studies were conducted for understanding hydrological processes at different spatial and temporal scales and they showed promising uses of these types of models also in practical applications. However, these models are generally applied to scales different from that at which the equation is deduced and validated. For this reason, the models are implemented with effective soil parameters that, in principle, should preserve the water fluxes that would have been estimated assuming the finer resolution scale. In this context, the reduction in spatial discretization becomes a trade-off between complexity and performance of the model. The aim of the present contribution is to assess the performance of Parflow-CLM implemented at different spatial scales. A virtual experiment based on data available for the Neckar catchment (Germany) is used as reference at 100x100m resolution. Different upscaling rules for the soil hydraulic parameters are used for coarsening the model up to 1x1km. The analysis is carried out based on different model output e.g., river discharge, evapotranspiration, soil moisture and groundwater recharge. The effects of soil variability, correlation length and spatial distribution over the water flow direction on the simulation results are discussed. Further researches aim to quantify the related uncertainty in model output and the possibility to fill in the model structure inadequacy with data assimilation techniques.

Comparing riparian and catchment influences on stream habitat in a forested, montane landscape.

Treesearch

K.M. Burnett; G.H. Reeves

2006-01-01

The goal of this study was to understand relationships between salmon habitat and landscape characteristics, summarized at multiple spatial scales, in a montane basin where forestry is the dominant land use. Specific study objectives were to (1) examine differences among spatial scales for landscape characteristics described with relatively coarse-resolution data, (2)...

A Spectral Method for Spatial Downscaling

PubMed Central

Reich, Brian J.; Chang, Howard H.; Foley, Kristen M.

2014-01-01

Summary Complex computer models play a crucial role in air quality research. These models are used to evaluate potential regulatory impacts of emission control strategies and to estimate air quality in areas without monitoring data. For both of these purposes, it is important to calibrate model output with monitoring data to adjust for model biases and improve spatial prediction. In this article, we propose a new spectral method to study and exploit complex relationships between model output and monitoring data. Spectral methods allow us to estimate the relationship between model output and monitoring data separately at different spatial scales, and to use model output for prediction only at the appropriate scales. The proposed method is computationally efficient and can be implemented using standard software. We apply the method to compare Community Multiscale Air Quality (CMAQ) model output with ozone measurements in the United States in July 2005. We find that CMAQ captures large-scale spatial trends, but has low correlation with the monitoring data at small spatial scales. PMID:24965037

Characterizing Spatial Organization of Cell Surface Receptors in Human Breast Cancer with STORM

NASA Astrophysics Data System (ADS)

Lyall, Evan; Chapman, Matthew R.; Sohn, Lydia L.

2012-02-01

Regulation and control of complex biological functions are dependent upon spatial organization of biological structures at many different length scales. For instance Eph receptors and their ephrin ligands bind when opposing cells come into contact during development, resulting in spatial organizational changes on the nanometer scale that lead to changes on the macro scale, in a process known as organ morphogenesis. One technique able to probe this important spatial organization at both the nanometer and micrometer length scales, including at cell-cell junctions, is stochastic optical reconstruction microscopy (STORM). STORM is a technique that localizes individual fluorophores based on the centroids of their point spread functions and then reconstructs a composite image to produce super resolved structure. We have applied STORM to study spatial organization of the cell surface of human breast cancer cells, specifically the organization of tyrosine kinase receptors and chemokine receptors. A better characterization of spatial organization of breast cancer cell surface proteins is necessary to fully understand the tumorigenisis pathways in the most common malignancy in United States women.

Asynchrony among local communities stabilises ecosystem function of metacommunities.

PubMed

Wilcox, Kevin R; Tredennick, Andrew T; Koerner, Sally E; Grman, Emily; Hallett, Lauren M; Avolio, Meghan L; La Pierre, Kimberly J; Houseman, Gregory R; Isbell, Forest; Johnson, David Samuel; Alatalo, Juha M; Baldwin, Andrew H; Bork, Edward W; Boughton, Elizabeth H; Bowman, William D; Britton, Andrea J; Cahill, James F; Collins, Scott L; Du, Guozhen; Eskelinen, Anu; Gough, Laura; Jentsch, Anke; Kern, Christel; Klanderud, Kari; Knapp, Alan K; Kreyling, Juergen; Luo, Yiqi; McLaren, Jennie R; Megonigal, Patrick; Onipchenko, Vladimir; Prevéy, Janet; Price, Jodi N; Robinson, Clare H; Sala, Osvaldo E; Smith, Melinda D; Soudzilovskaia, Nadejda A; Souza, Lara; Tilman, David; White, Shannon R; Xu, Zhuwen; Yahdjian, Laura; Yu, Qiang; Zhang, Pengfei; Zhang, Yunhai

2017-12-01

Temporal stability of ecosystem functioning increases the predictability and reliability of ecosystem services, and understanding the drivers of stability across spatial scales is important for land management and policy decisions. We used species-level abundance data from 62 plant communities across five continents to assess mechanisms of temporal stability across spatial scales. We assessed how asynchrony (i.e. different units responding dissimilarly through time) of species and local communities stabilised metacommunity ecosystem function. Asynchrony of species increased stability of local communities, and asynchrony among local communities enhanced metacommunity stability by a wide range of magnitudes (1-315%); this range was positively correlated with the size of the metacommunity. Additionally, asynchronous responses among local communities were linked with species' populations fluctuating asynchronously across space, perhaps stemming from physical and/or competitive differences among local communities. Accordingly, we suggest spatial heterogeneity should be a major focus for maintaining the stability of ecosystem services at larger spatial scales. © 2017 The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

Alternative spatial configurations to reflect landscape structure in a hydrological model: SUMMA applications to the Reynolds Creek Watershed and the Columbia River Basin

NASA Astrophysics Data System (ADS)

Nijssen, Bart; Clark, Martyn; Mizukami, Naoki; Chegwidden, Oriana

2016-04-01

Most existing hydrological models use a fixed representation of landscape structure. For example, high-resolution, spatially-distributed models may use grid cells that exchange moisture through the saturated subsurface or may divide the landscape into hydrologic response units that only exchange moisture through surface channels. Alternatively, many regional models represent the landscape through coarse elements that do not model any moisture exchange between these model elements. These spatial organizations are often represented at a low-level in the model code and its data structures, which makes it difficult to evaluate different landscape representations using the same hydrological model. Instead, such experimentation requires the use of multiple, different hydrological models, which in turn complicates the analysis, because differences in model outcomes are no longer constrained by differing spatial representations. This inflexibility in the representation of landscape structure also limits a model's capability for scaling local processes to regional outcomes. In this study, we used the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to evaluate different model spatial configurations to represent landscape structure and to evaluate scaling behavior. SUMMA can represent the moisture exchange between arbitrarily shaped landscape elements in a number of different ways, while using the same model parameterizations for vertical fluxes. This allows us to isolate the effects of changes in landscape representations on modeled hydrological fluxes and states. We examine the effects of spatial configuration in Reynolds Creek, Idaho, USA, which is a research watershed with gaged areas from 1-20 km2. We then use the same modeling system to evaluate scaling behavior in simulated hydrological fluxes in the Columbia River Basin, Pacific Northwest, USA. This basin drains more than 500,000 km2 and includes the Reynolds Creek Watershed.

Application Perspective of 2D+SCALE Dimension

NASA Astrophysics Data System (ADS)

Karim, H.; Rahman, A. Abdul

2016-09-01

Different applications or users need different abstraction of spatial models, dimensionalities and specification of their datasets due to variations of required analysis and output. Various approaches, data models and data structures are now available to support most current application models in Geographic Information System (GIS). One of the focuses trend in GIS multi-dimensional research community is the implementation of scale dimension with spatial datasets to suit various scale application needs. In this paper, 2D spatial datasets that been scaled up as the third dimension are addressed as 2D+scale (or 3D-scale) dimension. Nowadays, various data structures, data models, approaches, schemas, and formats have been proposed as the best approaches to support variety of applications and dimensionality in 3D topology. However, only a few of them considers the element of scale as their targeted dimension. As the scale dimension is concerned, the implementation approach can be either multi-scale or vario-scale (with any available data structures and formats) depending on application requirements (topology, semantic and function). This paper attempts to discuss on the current and new potential applications which positively could be integrated upon 3D-scale dimension approach. The previous and current works on scale dimension as well as the requirements to be preserved for any given applications, implementation issues and future potential applications forms the major discussion of this paper.

Drivers of protogynous sex change differ across spatial scales.

PubMed

Taylor, Brett M

2014-01-22

The influence of social demography on sex change schedules in protogynous reef fishes is well established, yet effects across spatial scales (in particular, the magnitude of natural variation relative to size-selective fishing effects) are poorly understood. Here, I examine variation in timing of sex change for exploited parrotfishes across a range of environmental, anthropogenic and geographical factors. Results were highly dependent on spatial scale. Fishing pressure was the most influential factor determining length at sex change at the within-island scale where a wide range of anthropogenic pressure existed. Sex transition occurred at smaller sizes where fishing pressure was high. Among islands, however, differences were overwhelmingly predicted by reefal-scale structural features, a pattern evident for all species examined. For the most abundant species, Chlorurus spilurus, length at sex change increased at higher overall densities and greater female-to-male sex ratios at all islands except where targeted by fishermen; here the trend was reversed. This implies differing selective pressures on adult individuals can significantly alter sex change dynamics, highlighting the importance of social structure, demography and the selective forces structuring populations. Considerable life-history responses to exploitation were observed, but results suggest potential fishing effects on demography may be obscured by natural variation at biogeographic scales.

Understanding relationships among ecosystem services across spatial scales and over time

NASA Astrophysics Data System (ADS)

Qiu, Jiangxiao; Carpenter, Stephen R.; Booth, Eric G.; Motew, Melissa; Zipper, Samuel C.; Kucharik, Christopher J.; Loheide, Steven P., II; Turner, Monica G.

2018-05-01

Sustaining ecosystem services (ES), mitigating their tradeoffs and avoiding unfavorable future trajectories are pressing social-environmental challenges that require enhanced understanding of their relationships across scales. Current knowledge of ES relationships is often constrained to one spatial scale or one snapshot in time. In this research, we integrated biophysical modeling with future scenarios to examine changes in relationships among eight ES indicators from 2001–2070 across three spatial scales—grid cell, subwatershed, and watershed. We focused on the Yahara Watershed (Wisconsin) in the Midwestern United States—an exemplar for many urbanizing agricultural landscapes. Relationships among ES indicators changed over time; some relationships exhibited high interannual variations (e.g. drainage vs. food production, nitrate leaching vs. net ecosystem exchange) and even reversed signs over time (e.g. perennial grass production vs. phosphorus yield). Robust patterns were detected for relationships among some regulating services (e.g. soil retention vs. water quality) across three spatial scales, but other relationships lacked simple scaling rules. This was especially true for relationships of food production vs. water quality, and drainage vs. number of days with runoff >10 mm, which differed substantially across spatial scales. Our results also showed that local tradeoffs between food production and water quality do not necessarily scale up, so reducing local tradeoffs may be insufficient to mitigate such tradeoffs at the watershed scale. We further synthesized these cross-scale patterns into a typology of factors that could drive changes in ES relationships across scales: (1) effects of biophysical connections, (2) effects of dominant drivers, (3) combined effects of biophysical linkages and dominant drivers, and (4) artificial scale effects, and concluded with management implications. Our study highlights the importance of taking a dynamic perspective and accounting for spatial scales in monitoring and management to sustain future ES.

Similar Processes but Different Environmental Filters for Soil Bacterial and Fungal Community Composition Turnover on a Broad Spatial Scale

PubMed Central

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P. A.; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

PubMed

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Effects of land use pattern on soil water in revegetation watersheds in semi-arid Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Yang, Lei; Chen, Liding; Wei, Wei

2017-04-01

Soil water stored below rainfall infiltration depth is a reliable water resource for plant growth in arid and semi-arid regions. For decreasing serious soil erosion, large-scale human-introduced vegetation restoration was initiated in Chinese Loess Plateau in late 1990s. However, these activities may result in excessive water consumption and soil water deficit if no appropriate scientific guidance were offered. This in turn impacts the regional ecological restoration and sustainable management of water resources. In this study, soil water content data in depth of 0-5 m was obtained by long-term field observation and geostatistical method in 6 small watersheds covered with different land use pattern. Profile characteristics and spatial-temporal patterns of soil water were compared between different land use types, hillslopes, and watersheds. The results showed that: (1) Introduced vegetation consumed excessive amount of water when compared with native grassland and farmland, and induced temporally stable soil desiccation in depth of 0-5 m. The introduced vegetation decreased soil water content to levels lower than the reference value representing no human impact in all soil layers. (2) The analysis of differences in soil water at hillslope and watershed scales indicated that land use determined the spatial and temporal variability of soil water. Soil water at watershed scale increased with the increasing area of farmland, and decreased with increasing percentage of introduced vegetation. Land use structure determined the soil water condition and land use pattern determined the spatial-temporal variability of soil water at watershed scale. (3) Large-scale revegetation with introduced vegetation diminished the spatial heterogeneity of soil water at different scales. Land use pattern adjustment could be used to improve the water resources management and maintain the sustainability of vegetation restoration.

Phylogenetic turnover during subtropical forest succession across environmental and phylogenetic scales.

PubMed

Purschke, Oliver; Michalski, Stefan G; Bruelheide, Helge; Durka, Walter

2017-12-01

Although spatial and temporal patterns of phylogenetic community structure during succession are inherently interlinked and assembly processes vary with environmental and phylogenetic scales, successional studies of community assembly have yet to integrate spatial and temporal components of community structure, while accounting for scaling issues. To gain insight into the processes that generate biodiversity after disturbance, we combine analyses of spatial and temporal phylogenetic turnover across phylogenetic scales, accounting for covariation with environmental differences. We compared phylogenetic turnover, at the species- and individual-level, within and between five successional stages, representing woody plant communities in a subtropical forest chronosequence. We decomposed turnover at different phylogenetic depths and assessed its covariation with between-plot abiotic differences. Phylogenetic turnover between stages was low relative to species turnover and was not explained by abiotic differences. However, within the late-successional stages, there was high presence-/absence-based turnover (clustering) that occurred deep in the phylogeny and covaried with environmental differentiation. Our results support a deterministic model of community assembly where (i) phylogenetic composition is constrained through successional time, but (ii) toward late succession, species sorting into preferred habitats according to niche traits that are conserved deep in phylogeny, becomes increasingly important.

Complex Spatial Structure in a Population of Didymopanax pittieri, A Tree of Wind-Exposed Lower Montane Rain Forest

NASA Technical Reports Server (NTRS)

Lawton, Robert M.; Lawton, Robert O.

2010-01-01

Didymopanax pittieri is a common shade-intolerant tree colonizing treefall gaps in the elfin forests on windswept ridgecrests in the lower montane rain forests of the Cordillera de Tilarain, Costa Rica. All D. pittieri taller than > 0.5 m in a 5.2-ha elfin forested portion of a gridded study watershed in the Monteverde Cloud Forest Preserve were located, mapped, and measured. This local population of D. pittieri is spatially inhomogeneous, in that density increases with increasing wind exposure; D. pittieri are more abundant near ridge crests than lower on windward slopes. The important and ubiquitous phenomenon of spatial inhomogeneity in population density is addressed and corrected for in spatial analyses by the application of the inhomogeneous version of Ripley's K. The spatial patterns of four size classes of D. pittieri (<5 cm dbh, 5-10 cm dbh, 10-20 cm dbh, and> 20 cm dbh) were investigated. Within the large-scale trend in density driven by wind exposure, D. pittieri saplings are clumped at the scale of treefall gaps and at the scale of patches of aggregated gaps. D. pittieri 5-10 cm dbh are randomly distributed, apparently due to competitive thinning of sapling clumps during the early stages of gap-phase regeneration. D. pittieri larger than 10 cm dbh are overdispersed at a scale larger than that of patches of gaps. Natural disturbance can influence the distribution of shade intolerant tree populations at several different spatial scales, and can have discordant effects at different life history stages.

Spatial patterns of giant sequoia (Sequoiadendron giganteum) in two sequoia groves in Sequoia National Park, California

USGS Publications Warehouse

Stohlgren, Thomas J.

1993-01-01

Although Muir Grove and Castle Creek Grove are similar in area, elevation, and number of giant sequoias, various spatial pattern analysis techniques showed that they had dissimilar spatial patterns for similar-sized trees. Two-dimensional and transect two-term local quadrat variance techniques detected general trends in the spatial patterns of different-sized trees, detected multiple-scale patterns within individual size classes, and provided information on the scale and intensity of patches of individual size classes of trees in Muir and Castle Creek groves. In Muir Grove, midsized sequoias (1.5 to 2.4 m DBH classes) had major pattern scales 350–450 m in diameter, whereas the same-sized trees in Castle Creek Grove had pattern scales >1000 m in diameter. Many size classes of trees had minor patches superimposed on larger scale patterns in both groves. There may be different recruitment patterns in core (i.e., central) areas compared with peripheral areas of sequoia groves; core areas of both groves had more small live sequoias and dead sequoias than peripheral areas of the groves. Higher densities of sequoias and, perhaps, more rapid turnover of individuals in core areas may indicate (i) differences in disturbance histories and favorability of microsites in the core and peripheral areas of groves; (ii) different responses to disturbance due to shifts in the species composition of the stand and thus, the relative influences of intra- to inter-specific competition; or (iii) slower growth or lower survivorship rates in marginal habitat (i.e., peripheral areas).

The spatial sensitivity of the spectral diversity-biodiversity relationship: an experimental test in a prairie grassland.

PubMed

Wang, Ran; Gamon, John A; Cavender-Bares, Jeannine; Townsend, Philip A; Zygielbaum, Arthur I

2018-03-01

Remote sensing has been used to detect plant biodiversity in a range of ecosystems based on the varying spectral properties of different species or functional groups. However, the most appropriate spatial resolution necessary to detect diversity remains unclear. At coarse resolution, differences among spectral patterns may be too weak to detect. In contrast, at fine resolution, redundant information may be introduced. To explore the effect of spatial resolution, we studied the scale dependence of spectral diversity in a prairie ecosystem experiment at Cedar Creek Ecosystem Science Reserve, Minnesota, USA. Our study involved a scaling exercise comparing synthetic pixels resampled from high-resolution images within manipulated diversity treatments. Hyperspectral data were collected using several instruments on both ground and airborne platforms. We used the coefficient of variation (CV) of spectral reflectance in space as the indicator of spectral diversity and then compared CV at different scales ranging from 1 mm 2 to 1 m 2 to conventional biodiversity metrics, including species richness, Shannon's index, Simpson's index, phylogenetic species variation, and phylogenetic species evenness. In this study, higher species richness plots generally had higher CV. CV showed higher correlations with Shannon's index and Simpson's index than did species richness alone, indicating evenness contributed to the spectral diversity. Correlations with species richness and Simpson's index were generally higher than with phylogenetic species variation and evenness measured at comparable spatial scales, indicating weaker relationships between spectral diversity and phylogenetic diversity metrics than with species diversity metrics. High resolution imaging spectrometer data (1 mm 2 pixels) showed the highest sensitivity to diversity level. With decreasing spatial resolution, the difference in CV between diversity levels decreased and greatly reduced the optical detectability of biodiversity. The optimal pixel size for distinguishing α diversity in these prairie plots appeared to be around 1 mm to 10 cm, a spatial scale similar to the size of an individual herbaceous plant. These results indicate a strong scale-dependence of the spectral diversity-biodiversity relationships, with spectral diversity best able to detect a combination of species richness and evenness, and more weakly detecting phylogenetic diversity. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods. ©2018 The Authors Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.

Elevational Gradients in β-Diversity Reflect Variation in the Strength of Local Community Assembly Mechanisms across Spatial Scales

PubMed Central

Tello, J. Sebastián; Myers, Jonathan A.; Macía, Manuel J.; Fuentes, Alfredo F.; Cayola, Leslie; Arellano, Gabriel; Loza, M. Isabel; Torrez, Vania; Cornejo, Maritza; Miranda, Tatiana B.; Jørgensen, Peter M.

2015-01-01

Despite long-standing interest in elevational-diversity gradients, little is known about the processes that cause changes in the compositional variation of communities (β-diversity) across elevations. Recent studies have suggested that β-diversity gradients are driven by variation in species pools, rather than by variation in the strength of local community assembly mechanisms such as dispersal limitation, environmental filtering, or local biotic interactions. However, tests of this hypothesis have been limited to very small spatial scales that limit inferences about how the relative importance of assembly mechanisms may change across spatial scales. Here, we test the hypothesis that scale-dependent community assembly mechanisms shape biogeographic β-diversity gradients using one of the most well-characterized elevational gradients of tropical plant diversity. Using an extensive dataset on woody plant distributions along a 4,000-m elevational gradient in the Bolivian Andes, we compared observed patterns of β-diversity to null-model expectations. β-deviations (standardized differences from null values) were used to measure the relative effects of local community assembly mechanisms after removing sampling effects caused by variation in species pools. To test for scale-dependency, we compared elevational gradients at two contrasting spatial scales that differed in the size of local assemblages and regions by at least an order of magnitude. Elevational gradients in β-diversity persisted after accounting for regional variation in species pools. Moreover, the elevational gradient in β-deviations changed with spatial scale. At small scales, local assembly mechanisms were detectable, but variation in species pools accounted for most of the elevational gradient in β-diversity. At large spatial scales, in contrast, local assembly mechanisms were a dominant force driving changes in β-diversity. In contrast to the hypothesis that variation in species pools alone drives β-diversity gradients, we show that local community assembly mechanisms contribute strongly to systematic changes in β-diversity across elevations. We conclude that scale-dependent variation in community assembly mechanisms underlies these iconic gradients in global biodiversity. PMID:25803846

Spatial and Temporal Scaling of Thermal Infrared Remote Sensing Data

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Goel, Narendra S.

1995-01-01

Although remote sensing has a central role to play in the acquisition of synoptic data obtained at multiple spatial and temporal scales to facilitate our understanding of local and regional processes as they influence the global climate, the use of thermal infrared (TIR) remote sensing data in this capacity has received only minimal attention. This results from some fundamental challenges that are associated with employing TIR data collected at different space and time scales, either with the same or different sensing systems, and also from other problems that arise in applying a multiple scaled approach to the measurement of surface temperatures. In this paper, we describe some of the more important problems associated with using TIR remote sensing data obtained at different spatial and temporal scales, examine why these problems appear as impediments to using multiple scaled TIR data, and provide some suggestions for future research activities that may address these problems. We elucidate the fundamental concept of scale as it relates to remote sensing and explore how space and time relationships affect TIR data from a problem-dependency perspective. We also describe how linearity and non-linearity observation versus parameter relationships affect the quantitative analysis of TIR data. Some insight is given on how the atmosphere between target and sensor influences the accurate measurement of surface temperatures and how these effects will be compounded in analyzing multiple scaled TIR data. Last, we describe some of the challenges in modeling TIR data obtained at different space and time scales and discuss how multiple scaled TIR data can be used to provide new and important information for measuring and modeling land-atmosphere energy balance processes.

Spatial variability of macrobenthic zonation on exposed sandy beaches

NASA Astrophysics Data System (ADS)

Veiga, Puri; Rubal, Marcos; Cacabelos, Eva; Maldonado, Cristina; Sousa-Pinto, Isabel

2014-07-01

We analysed the consistence of vertical patterns of distribution (i.e. zonation) for macrofauna at different spatial scales on four intermediate exposed beaches in the North of Portugal. We tested the hypothesis that biological zonation on exposed sandy beaches would vary at the studied spatial scales. For this aim, abundance, diversity and structure of macrobenthic assemblages were examined at the scales of transect and beach. Moreover, the main environmental factors that could potentially drive zonation patterns were investigated. Univariate and multivariate analyses revealed that the number of biological zones ranged from two to three depending on the beach and from indistinct zonation to three zones at the scale of transect. Therefore, results support our working hypothesis because zonation patterns were not consistent at the studied spatial scales. The median particle size, sorting coefficient and water content were significantly correlated with zonation patterns of macrobenthic assemblages. However, a high degree of correlation was not reached when the total structure of the assemblage was considered.

On the sub-model errors of a generalized one-way coupling scheme for linking models at different scales

NASA Astrophysics Data System (ADS)

Zeng, Jicai; Zha, Yuanyuan; Zhang, Yonggen; Shi, Liangsheng; Zhu, Yan; Yang, Jinzhong

2017-11-01

Multi-scale modeling of the localized groundwater flow problems in a large-scale aquifer has been extensively investigated under the context of cost-benefit controversy. An alternative is to couple the parent and child models with different spatial and temporal scales, which may result in non-trivial sub-model errors in the local areas of interest. Basically, such errors in the child models originate from the deficiency in the coupling methods, as well as from the inadequacy in the spatial and temporal discretizations of the parent and child models. In this study, we investigate the sub-model errors within a generalized one-way coupling scheme given its numerical stability and efficiency, which enables more flexibility in choosing sub-models. To couple the models at different scales, the head solution at parent scale is delivered downward onto the child boundary nodes by means of the spatial and temporal head interpolation approaches. The efficiency of the coupling model is improved either by refining the grid or time step size in the parent and child models, or by carefully locating the sub-model boundary nodes. The temporal truncation errors in the sub-models can be significantly reduced by the adaptive local time-stepping scheme. The generalized one-way coupling scheme is promising to handle the multi-scale groundwater flow problems with complex stresses and heterogeneity.

Forecasting Influenza Outbreaks in Boroughs and Neighborhoods of New York City.

PubMed

Yang, Wan; Olson, Donald R; Shaman, Jeffrey

2016-11-01

The ideal spatial scale, or granularity, at which infectious disease incidence should be monitored and forecast has been little explored. By identifying the optimal granularity for a given disease and host population, and matching surveillance and prediction efforts to this scale, response to emergent and recurrent outbreaks can be improved. Here we explore how granularity and representation of spatial structure affect influenza forecast accuracy within New York City. We develop network models at the borough and neighborhood levels, and use them in conjunction with surveillance data and a data assimilation method to forecast influenza activity. These forecasts are compared to an alternate system that predicts influenza for each borough or neighborhood in isolation. At the borough scale, influenza epidemics are highly synchronous despite substantial differences in intensity, and inclusion of network connectivity among boroughs generally improves forecast accuracy. At the neighborhood scale, we observe much greater spatial heterogeneity among influenza outbreaks including substantial differences in local outbreak timing and structure; however, inclusion of the network model structure generally degrades forecast accuracy. One notable exception is that local outbreak onset, particularly when signal is modest, is better predicted with the network model. These findings suggest that observation and forecast at sub-municipal scales within New York City provides richer, more discriminant information on influenza incidence, particularly at the neighborhood scale where greater heterogeneity exists, and that the spatial spread of influenza among localities can be forecast.

Spatial pattern of Baccharis platypoda shrub as determined by sex and life stages

NASA Astrophysics Data System (ADS)

Fonseca, Darliana da Costa; de Oliveira, Marcio Leles Romarco; Pereira, Israel Marinho; Gonzaga, Anne Priscila Dias; de Moura, Cristiane Coelho; Machado, Evandro Luiz Mendonça

2017-11-01

Spatial patterns of dioecious species can be determined by their nutritional requirements and intraspecific competition, apart from being a response to environmental heterogeneity. The aim of the study was to evaluate the spatial pattern of populations of a dioecious shrub reporting to sex and reproductive stage patterns of individuals. Sampling was carried out in three areas located in the meridional portion of Serra do Espinhaço, where in individuals of the studied species were mapped. The spatial pattern was determined through O-ring analysis and Ripley's K-function and the distribution of individuals' frequencies was verified through x2 test. Populations in two areas showed an aggregate spatial pattern tending towards random or uniform according to the observed scale. Male and female adults presented an aggregate pattern at smaller scales, while random and uniform patterns were verified above 20 m for individuals of both sexes of the areas A2 and A3. Young individuals presented an aggregate pattern in all areas and spatial independence in relation to adult individuals, especially female plants. The interactions between individuals of both genders presented spatial independence with respect to spatial distribution. Baccharis platypoda showed characteristics in accordance with the spatial distribution of savannic and dioecious species, whereas the population was aggregated tending towards random at greater spatial scales. Young individuals showed an aggregated pattern at different scales compared to adults, without positive association between them. Female and male adult individuals presented similar characteristics, confirming that adult individuals at greater scales are randomly distributed despite their distinct preferences for environments with moisture variation.

Spatiotemporal variability in biogenic gas dynamics in a subtropical peat soil at the laboratory scale is revealed using high-resolution ground-penetrating radar

NASA Astrophysics Data System (ADS)

Mustasaar, Mario; Comas, Xavier

2017-09-01

The importance of peatlands as sources of greenhouse gas emissions has been demonstrated in many studies during the last two decades. While most studies have shown the heterogeneous distribution of biogenic gas in peat soils at the field scale (sampling volumes in the order of meters), little information exists for submeter scales, particularly relevant to properly capture the dynamics of hot spots for gas accumulation and release when designing sampling routines with methods that use smaller (i.e., submeter) sampling volumes like flux chambers. In this study, ground-penetrating radar is used at the laboratory scale to evaluate biogenic gas dynamics at high spatial resolution (i.e., cm) in a peat monolith from the Everglades. The results indicate sharp changes (both spatially and temporally) in the dynamics of gas accumulation and release, representing hot spots for production and release of biogenic gases with surface areas ranging between 5 to 10 cm diameter and are associated with increases in porosity. Furthermore, changes in gas composition and inferred methane (CH4) and carbon dioxide (CO2) fluxes also displayed a high spatiotemporal variability associated with hot spots, resulting in CH4 and CO2 flux estimates showing differences up to 1 order of magnitude during the same day for different parts of the sample. This work follows on recent studies in the Everglades and questions the appropriateness of spatial and temporal scales of measurement when defining gas dynamics by showing how flux values may change both spatially and temporarily even when considering submeter spatial scales.

Simulation of nitrate reduction in groundwater - An upscaling approach from small catchments to the Baltic Sea basin

NASA Astrophysics Data System (ADS)

Hansen, A. L.; Donnelly, C.; Refsgaard, J. C.; Karlsson, I. B.

2018-01-01

This paper describes a modeling approach proposed to simulate the impact of local-scale, spatially targeted N-mitigation measures for the Baltic Sea Basin. Spatially targeted N-regulations aim at exploiting the considerable spatial differences in the natural N-reduction taking place in groundwater and surface water. While such measures can be simulated using local-scale physically-based catchment models, use of such detailed models for the 1.8 million km2 Baltic Sea basin is not feasible due to constraints on input data and computing power. Large-scale models that are able to simulate the Baltic Sea basin, on the other hand, do not have adequate spatial resolution to simulate some of the field-scale measures. Our methodology combines knowledge and results from two local-scale physically-based MIKE SHE catchment models, the large-scale and more conceptual E-HYPE model, and auxiliary data in order to enable E-HYPE to simulate how spatially targeted regulation of agricultural practices may affect N-loads to the Baltic Sea. We conclude that the use of E-HYPE with this upscaling methodology enables the simulation of the impact on N-loads of applying a spatially targeted regulation at the Baltic Sea basin scale to the correct order-of-magnitude. The E-HYPE model together with the upscaling methodology therefore provides a sound basis for large-scale policy analysis; however, we do not expect it to be sufficiently accurate to be useful for the detailed design of local-scale measures.

Interactive effects of nitrogen addition, warming and invasion across organizational levels in an old-field plant community.

PubMed

Gornish, Elise S

2014-10-08

Response to global change is dependent on the level of biological organization (e.g. the ecologically relevant spatial scale) in which species are embedded. For example, individual responses can affect population-level responses, which, in turn, can affect community-level responses. Although relationships are known to exist among responses to global change across levels of biological organization, formal investigations of these relationships are still uncommon. I conducted an exploratory analysis to identify how nitrogen addition and warming by open top chambers might affect plants across spatial scales by estimating treatment effect size at the leaf level, the plant level and the community level. Moreover, I investigated if the presence of Pityopsis aspera, an experimentally introduced plant species, modified the relationship between spatial scale and effect size across treatments. I found that, overall, the spatial scale significantly contributes to differences in effect size, supporting previous work which suggests that mechanisms driving biotic response to global change are scale dependent. Interestingly, the relationship between spatial scale and effect size in both the absence and presence of experimental invasion is very similar for nitrogen addition and warming treatments. The presence of invasion, however, did not affect the relationship between spatial scale and effect size, suggesting that in this system, invasion may not exacerbate or attenuate climate change effects. This exercise highlights the value of moving beyond integration and scaling to the practice of directly testing for scale effects within single experiments. Published by Oxford University Press on behalf of the Annals of Botany Company.

Effects of scale and logging on landscape structure in a forest mosaic.

PubMed

Leimgruber, P; McShea, W J; Schnell, G D

2002-03-01

Landscape structure in a forest mosaic changes with spatial scale (i.e. spatial extent) and thresholds may occur where structure changes markedly. Forest management alters landscape structure and may affect the intensity and location of thresholds. Our purpose was to examine landscape structure at different scales to determine thresholds where landscape structure changes markedly in managed forest mosaics of the Appalachian Mountains in the eastern United States. We also investigated how logging influences landscape structure and whether these management activities change threshold values. Using threshold and autocorrelation analyses, we found that thresholds in landscape indices exist at 400, 500, and 800 m intervals from the outer edge of management units in our study region. For landscape indices that consider all landcover categories, such as dominance and contagion, landscape structure and thresholds did not change after logging occurred. Measurements for these overall landscape indices were strongly influenced by midsuccessional deciduous forest, the most common landcover category in the landscape. When restricting analyses for mean patch size and percent cover to individual forest types, thresholds for early-successional forests changed after logging. However, logging changed the landscape structure at small spatial scale, but did not alter the structure of the entire forest mosaic. Previous forest management may already have increased the heterogeneity of the landscape beyond the point where additional small cuts alter the overall structure of the forest. Because measurements for landscape indices yield very different results at different spatial scales, it is important first to identify thresholds in order to determine the appropriate scales for landscape ecological studies. We found that threshold and autocorrelation analyses were simple but powerful tools for the detection of appropriate scales in the managed forest mosaic under study.

SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iliopoulos, AS; Sun, X; Floros, D

Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well asmore » histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.« less

Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study

PubMed Central

2013-01-01

Background There is a rising public and political demand for prospective cancer cluster monitoring. But there is little empirical evidence on the performance of established cluster detection tests under conditions of small and heterogeneous sample sizes and varying spatial scales, such as are the case for most existing population-based cancer registries. Therefore this simulation study aims to evaluate different cluster detection methods, implemented in the open soure environment R, in their ability to identify clusters of lung cancer using real-life data from an epidemiological cancer registry in Germany. Methods Risk surfaces were constructed with two different spatial cluster types, representing a relative risk of RR = 2.0 or of RR = 4.0, in relation to the overall background incidence of lung cancer, separately for men and women. Lung cancer cases were sampled from this risk surface as geocodes using an inhomogeneous Poisson process. The realisations of the cancer cases were analysed within small spatial (census tracts, N = 1983) and within aggregated large spatial scales (communities, N = 78). Subsequently, they were submitted to the cluster detection methods. The test accuracy for cluster location was determined in terms of detection rates (DR), false-positive (FP) rates and positive predictive values. The Bayesian smoothing models were evaluated using ROC curves. Results With moderate risk increase (RR = 2.0), local cluster tests showed better DR (for both spatial aggregation scales > 0.90) and lower FP rates (both < 0.05) than the Bayesian smoothing methods. When the cluster RR was raised four-fold, the local cluster tests showed better DR with lower FPs only for the small spatial scale. At a large spatial scale, the Bayesian smoothing methods, especially those implementing a spatial neighbourhood, showed a substantially lower FP rate than the cluster tests. However, the risk increases at this scale were mostly diluted by data aggregation. Conclusion High resolution spatial scales seem more appropriate as data base for cancer cluster testing and monitoring than the commonly used aggregated scales. We suggest the development of a two-stage approach that combines methods with high detection rates as a first-line screening with methods of higher predictive ability at the second stage. PMID:24314148

A comparison of MIKE SHE and DRAINMOD for modeling forested wetland hydrology in coastal South Carolina, USA

Treesearch

Zhaohua Dai; Devendra M. Amatya; Ge Sun; Carl C. Trettin; Changsheng Li; Harbin Li

2010-01-01

Models are widely used to assess hydrologic impacts of land-management, land-use change and climate change. Two hydrologic models with different spatial scales, MIKE SHE (spatially distributed, watershed-scale) and DRAINMOD (lumped, fieldscale), were compared in terms of their performance in predicting stream flow and water table depth in a first-order forested...

Need for multiscale planning for conservation of urban bats.

PubMed

Gallo, Travis; Lehrer, Elizabeth W; Fidino, Mason; Kilgour, R Julia; Wolff, Patrick J; Magle, Seth B

2017-11-10

For over a century there have been continual efforts to incorporate nature into urban planning. These efforts (i.e., urban reconciliation) aim to manage and create habitats that support biodiversity within cities. Given that species select habitat at different spatial scales, understanding the scale at which urban species respond to their environment is critical to the success of urban reconciliation efforts. We assessed species-habitat relationships for common bat species at 50-m, 500-m, and 1 km spatial scales in the Chicago (U.S.A.) metropolitan area and predicted bat activity across the greater Chicago region. Habitat characteristics across all measured scales were important predictors of silver-haired bat (Lasionycteris noctivagans) and eastern red bat (Lasiurus borealis) activity, and big brown bat (Eptesicus fuscus) activity was significantly lower at urban sites relative to rural sites. Open vegetation had a negative effect on silver-haired bat activity at the 50-m scale but a positive effect at the 500-m scale, indicating potential shifts in the relative importance of some habitat characteristics at different scales. These results demonstrate that localized effects may be constrained by broader spatial patterns. Our findings highlight the importance of considering scale in urban reconciliation efforts and our landscape predictions provide information that can help prioritize urban conservation work. © 2017 Society for Conservation Biology.

Variance in composition of inquiline communities in leaves of Sarracenia purpurea L. on multiple spatial scales.

PubMed

Harvey, E; Miller, T E

1996-11-01

A survey of the abundances of species that inhabit the water-bearing leaves of the pitcher plant Sarracenia purpurea was conducted at several different spatial scales in northern Florida. Individual leaves are hosts to communities of inquiline species, including mosquitoes, midges, mites, copepods, cladocerans, and a diverse bacterial assemblage. Inquiline communities were quantified from four pitchers per plant, three plants per subpopulation, two subpopulations per population, and three populations. Species varied in abundance at different spatial scales. Variation in the abundances of mosquitoes and copepods was not significantly associated with any spatial scale. Midges varied in abundance at the level of populations; one population contained significantly more midges than the other two. Cladocerans varied at the level of the subpopulation, whereas mites varied at the level of the individual plants. Bacterial communities were described by means of Biolog plates, which quantify the types of carbon media used by the bacteria in each pitcher. Bacterial communities were found to vary significantly in composition among individual plants but not among populations or subpopulations. These results suggest that independent factors determining the abundances of individual species are important in determining community patterns in pitcher-plant inquilines.

The relationship between the spatial scaling of biodiversity and ecosystem stability

PubMed Central

Delsol, Robin; Loreau, Michel; Haegeman, Bart

2018-01-01

Aim Ecosystem stability and its link with biodiversity have mainly been studied at the local scale. Here we present a simple theoretical model to address the joint dependence of diversity and stability on spatial scale, from local to continental. Methods The notion of stability we use is based on the temporal variability of an ecosystem-level property, such as primary productivity. In this way, our model integrates the well-known species–area relationship (SAR) with a recent proposal to quantify the spatial scaling of stability, called the invariability–area relationship (IAR). Results We show that the link between the two relationships strongly depends on whether the temporal fluctuations of the ecosystem property of interest are more correlated within than between species. If fluctuations are correlated within species but not between them, then the IAR is strongly constrained by the SAR. If instead individual fluctuations are only correlated by spatial proximity, then the IAR is unrelated to the SAR. We apply these two correlation assumptions to explore the effects of species loss and habitat destruction on stability, and find a rich variety of multi-scale spatial dependencies, with marked differences between the two assumptions. Main conclusions The dependence of ecosystem stability on biodiversity across spatial scales is governed by the spatial decay of correlations within and between species. Our work provides a point of reference for mechanistic models and data analyses. More generally, it illustrates the relevance of macroecology for ecosystem functioning and stability. PMID:29651225

Spatial scale of land-use impacts on riverine drinking source water quality

NASA Astrophysics Data System (ADS)

Hurley, Tim; Mazumder, Asit

2013-03-01

Drinking water purveyors are increasingly relying on land conservation and management to ensure the safety of the water that they provide to consumers. To cost-effectively implement any such landscape initiatives, resources must be targeted to the appropriate spatial scale to address quality impairments of concern in a cost-effective manner. Using data gathered from 40 Canadian rivers across four ecozones, we examined the spatial scales at which land use was most closely associated with drinking source water quality metrics. Exploratory linear mixed-effects models accounting for climatic, hydrological, and physiographic variation among sites suggested that different spatial areas of land-use influence drinking source water quality depending on the parameter and season investigated. Escherichia coli spatial variability was only associated with land use at a local (5-10 km) spatial scale. Turbidity measures exhibited a complex association with land use, suggesting that the land-use areas of greatest influence can range from a 1 km subcatchment to the entire watershed depending on the season. Total organic carbon concentrations were only associated with land use characterized at the entire watershed scale. The Canadian Council of Ministers of the Environment Water Quality Index was used to calculate a composite measure of seasonal drinking source water quality but did not provide additional information beyond the analyses of individual parameters. These results suggest that entire watershed management is required to safeguard drinking water sources with more focused efforts at targeted spatial scales to reduce specific risk parameters.

X-ray Tomography and Chemical Imaging within Butterfly Wing Scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen Jianhua; Lee Yaochang; Tang, M.-T.

2007-01-19

The rainbow like color of butterfly wings is associated with the internal and surface structures of the wing scales. While the photonic structure of the scales is believed to diffract specific lights at different angle, there is no adequate probe directly answering the 3-D structures with sufficient spatial resolution. The NSRRC nano-transmission x-ray microscope (nTXM) with tens nanometers spatial resolution is able to image biological specimens without artifacts usually introduced in sophisticated sample staining processes. With the intrinsic deep penetration of x-rays, the nTXM is capable of nondestructively investigating the internal structures of fragile and soft samples. In this study,more » we imaged the structure of butterfly wing scales in 3-D view with 60 nm spatial resolution. In addition, synchrotron-radiation-based Fourier transform Infrared (FT-IR) microspectroscopy was employed to analyze the chemical components with spatial information of the butterfly wing scales. Based on the infrared spectral images, we suggest that the major components of scale structure were rich in protein and polysaccharide.« less

Multi-scale habitat selection modeling: A review and outlook

Treesearch

Kevin McGarigal; Ho Yi Wan; Kathy A. Zeller; Brad C. Timm; Samuel A. Cushman

2016-01-01

Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.

Uncovering Spatial Variation in Acoustic Environments Using Sound Mapping.

PubMed

Job, Jacob R; Myers, Kyle; Naghshineh, Koorosh; Gill, Sharon A

2016-01-01

Animals select and use habitats based on environmental features relevant to their ecology and behavior. For animals that use acoustic communication, the sound environment itself may be a critical feature, yet acoustic characteristics are not commonly measured when describing habitats and as a result, how habitats vary acoustically over space and time is poorly known. Such considerations are timely, given worldwide increases in anthropogenic noise combined with rapidly accumulating evidence that noise hampers the ability of animals to detect and interpret natural sounds. Here, we used microphone arrays to record the sound environment in three terrestrial habitats (forest, prairie, and urban) under ambient conditions and during experimental noise introductions. We mapped sound pressure levels (SPLs) over spatial scales relevant to diverse taxa to explore spatial variation in acoustic habitats and to evaluate the number of microphones needed within arrays to capture this variation under both ambient and noisy conditions. Even at small spatial scales and over relatively short time spans, SPLs varied considerably, especially in forest and urban habitats, suggesting that quantifying and mapping acoustic features could improve habitat descriptions. Subset maps based on input from 4, 8, 12 and 16 microphones differed slightly (< 2 dBA/pixel) from those based on full arrays of 24 microphones under ambient conditions across habitats. Map differences were more pronounced with noise introductions, particularly in forests; maps made from only 4-microphones differed more (> 4 dBA/pixel) from full maps than the remaining subset maps, but maps with input from eight microphones resulted in smaller differences. Thus, acoustic environments varied over small spatial scales and variation could be mapped with input from 4-8 microphones. Mapping sound in different environments will improve understanding of acoustic environments and allow us to explore the influence of spatial variation in sound on animal ecology and behavior.

The relative influence of habitat amount and configuration on genetic structure across multiple spatial scales

PubMed Central

Millette, Katie L; Keyghobadi, Nusha

2015-01-01

Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (FST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent. PMID:25628865

The relative influence of habitat amount and configuration on genetic structure across multiple spatial scales.

PubMed

Millette, Katie L; Keyghobadi, Nusha

2015-01-01

Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (F ST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent.

A worldwide analysis of the impact of forest cover change on annual runoff across multiple spatial scales

NASA Astrophysics Data System (ADS)

Zhang, M.; Liu, S.

2017-12-01

Despite extensive studies on hydrological responses to forest cover change in small watersheds, the hydrological responses to forest change and associated mechanisms across multiple spatial scales have not been fully understood. This review thus examined about 312 watersheds worldwide to provide a generalized framework to evaluate hydrological responses to forest cover change and to identify the contribution of spatial scale, climate, forest type and hydrological regime in determining the intensity of forest change related hydrological responses in small (<1000 km2) and large watersheds (≥1000 km2). Key findings include: 1) the increase in annual runoff associated with forest cover loss is statistically significant at multiple spatial scales whereas the effect of forest cover gain is statistically inconsistent; 2) the sensitivity of annual runoff to forest cover change tends to attenuate as watershed size increases only in large watersheds; 3) annual runoff is more sensitive to forest cover change in water-limited watersheds than in energy-limited watersheds across all spatial scales; and 4) small mixed forest-dominated watersheds or large snow-dominated watersheds are more hydrologically resilient to forest cover change. These findings improve the understanding of hydrological response to forest cover change at different spatial scales and provide a scientific underpinning to future watershed management in the context of climate change and increasing anthropogenic disturbances.

Multiscale spatial and temporal estimation of the b-value

NASA Astrophysics Data System (ADS)

García-Hernández, R.; D'Auria, L.; Barrancos, J.; Padilla, G.

2017-12-01

The estimation of the spatial and temporal variations of the Gutenberg-Richter b-value is of great importance in different seismological applications. One of the problems affecting its estimation is the heterogeneous distribution of the seismicity which makes its estimate strongly dependent upon the selected spatial and/or temporal scale. This is especially important in volcanoes where dense clusters of earthquakes often overlap the background seismicity. Proposed solutions for estimating temporal variations of the b-value include considering equally spaced time intervals or variable intervals having an equal number of earthquakes. Similar approaches have been proposed to image the spatial variations of this parameter as well.We propose a novel multiscale approach, based on the method of Ogata and Katsura (1993), allowing a consistent estimation of the b-value regardless of the considered spatial and/or temporal scales. Our method, named MUST-B (MUltiscale Spatial and Temporal characterization of the B-value), basically consists in computing estimates of the b-value at multiple temporal and spatial scales, extracting for a give spatio-temporal point a statistical estimator of the value, as well as and indication of the characteristic spatio-temporal scale. This approach includes also a consistent estimation of the completeness magnitude (Mc) and of the uncertainties over both b and Mc.We applied this method to example datasets for volcanic (Tenerife, El Hierro) and tectonic areas (Central Italy) as well as an example application at global scale.

Herbivore-induced plant volatiles and tritrophic interactions across spatial scales.

PubMed

Aartsma, Yavanna; Bianchi, Felix J J A; van der Werf, Wopke; Poelman, Erik H; Dicke, Marcel

2017-12-01

Herbivore-induced plant volatiles (HIPVs) are an important cue used in herbivore location by carnivorous arthropods such as parasitoids. The effects of plant volatiles on parasitoids have been well characterised at small spatial scales, but little research has been done on their effects at larger spatial scales. The spatial matrix of volatiles ('volatile mosaic') within which parasitoids locate their hosts is dynamic and heterogeneous. It is shaped by the spatial pattern of HIPV-emitting plants, the concentration, chemical composition and breakdown of the emitted HIPV blends, and by environmental factors such as wind, turbulence and vegetation that affect transport and mixing of odour plumes. The volatile mosaic may be exploited differentially by different parasitoid species, in relation to species traits such as sensory ability to perceive volatiles and the physical ability to move towards the source. Understanding how HIPVs influence parasitoids at larger spatial scales is crucial for our understanding of tritrophic interactions and sustainable pest management in agriculture. However, there is a large gap in our knowledge on how volatiles influence the process of host location by parasitoids at the landscape scale. Future studies should bridge the gap between the chemical and behavioural ecology of tritrophic interactions and landscape ecology. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Spatial scales of bacterial community diversity at cold seeps (Eastern Mediterranean Sea)

PubMed Central

Pop Ristova, Petra; Wenzhöfer, Frank; Ramette, Alban; Felden, Janine; Boetius, Antje

2015-01-01

Cold seeps are highly productive, fragmented marine ecosystems that form at the seafloor around hydrocarbon emission pathways. The products of microbial utilization of methane and other hydrocarbons fuel rich chemosynthetic communities at these sites, with much higher respiration rates compared with the surrounding deep-sea floor. Yet little is known as to the richness, composition and spatial scaling of bacterial communities of cold seeps compared with non-seep communities. Here we assessed the bacterial diversity across nine different cold seeps in the Eastern Mediterranean deep-sea and surrounding seafloor areas. Community similarity analyses were carried out based on automated ribosomal intergenic spacer analysis (ARISA) fingerprinting and high-throughput 454 tag sequencing and were combined with in situ and ex situ geochemical analyses across spatial scales of a few tens of meters to hundreds of kilometers. Seep communities were dominated by Deltaproteobacteria, Epsilonproteobacteria and Gammaproteobacteria and shared, on average, 36% of bacterial types (ARISA OTUs (operational taxonomic units)) with communities from nearby non-seep deep-sea sediments. Bacterial communities of seeps were significantly different from those of non-seep sediments. Within cold seep regions on spatial scales of only tens to hundreds of meters, the bacterial communities differed considerably, sharing <50% of types at the ARISA OTU level. Their variations reflected differences in porewater sulfide concentrations from anaerobic degradation of hydrocarbons. This study shows that cold seep ecosystems contribute substantially to the microbial diversity of the deep-sea. PMID:25500510

Trap configuration and spacing influences parameter estimates in spatial capture-recapture models

USGS Publications Warehouse

Sun, Catherine C.; Fuller, Angela K.; Royle, J. Andrew

2014-01-01

An increasing number of studies employ spatial capture-recapture models to estimate population size, but there has been limited research on how different spatial sampling designs and trap configurations influence parameter estimators. Spatial capture-recapture models provide an advantage over non-spatial models by explicitly accounting for heterogeneous detection probabilities among individuals that arise due to the spatial organization of individuals relative to sampling devices. We simulated black bear (Ursus americanus) populations and spatial capture-recapture data to evaluate the influence of trap configuration and trap spacing on estimates of population size and a spatial scale parameter, sigma, that relates to home range size. We varied detection probability and home range size, and considered three trap configurations common to large-mammal mark-recapture studies: regular spacing, clustered, and a temporal sequence of different cluster configurations (i.e., trap relocation). We explored trap spacing and number of traps per cluster by varying the number of traps. The clustered arrangement performed well when detection rates were low, and provides for easier field implementation than the sequential trap arrangement. However, performance differences between trap configurations diminished as home range size increased. Our simulations suggest it is important to consider trap spacing relative to home range sizes, with traps ideally spaced no more than twice the spatial scale parameter. While spatial capture-recapture models can accommodate different sampling designs and still estimate parameters with accuracy and precision, our simulations demonstrate that aspects of sampling design, namely trap configuration and spacing, must consider study area size, ranges of individual movement, and home range sizes in the study population.

Searching for the right scale in catchment hydrology: the effect of soil spatial variability in simulated states and fluxes

NASA Astrophysics Data System (ADS)

Baroni, Gabriele; Zink, Matthias; Kumar, Rohini; Samaniego, Luis; Attinger, Sabine

2017-04-01

The advances in computer science and the availability of new detailed data-sets have led to a growing number of distributed hydrological models applied to finer and finer grid resolutions for larger and larger catchment areas. It was argued, however, that this trend does not necessarily guarantee better understanding of the hydrological processes or it is even not necessary for specific modelling applications. In the present study, this topic is further discussed in relation to the soil spatial heterogeneity and its effect on simulated hydrological state and fluxes. To this end, three methods are developed and used for the characterization of the soil heterogeneity at different spatial scales. The methods are applied at the soil map of the upper Neckar catchment (Germany), as example. The different soil realizations are assessed regarding their impact on simulated state and fluxes using the distributed hydrological model mHM. The results are analysed by aggregating the model outputs at different spatial scales based on the Representative Elementary Scale concept (RES) proposed by Refsgaard et al. (2016). The analysis is further extended in the present study by aggregating the model output also at different temporal scales. The results show that small scale soil variabilities are not relevant when the integrated hydrological responses are considered e.g., simulated streamflow or average soil moisture over sub-catchments. On the contrary, these small scale soil variabilities strongly affect locally simulated states and fluxes i.e., soil moisture and evapotranspiration simulated at the grid resolution. A clear trade-off is also detected by aggregating the model output by spatial and temporal scales. Despite the scale at which the soil variabilities are (or are not) relevant is not universal, the RES concept provides a simple and effective framework to quantify the predictive capability of distributed models and to identify the need for further model improvements e.g., finer resolution input. For this reason, the integration in this analysis of all the relevant input factors (e.g., precipitation, vegetation, geology) could provide a strong support for the definition of the right scale for each specific model application. In this context, however, the main challenge for a proper model assessment will be the correct characterization of the spatio- temporal variability of each input factor. Refsgaard, J.C., Højberg, A.L., He, X., Hansen, A.L., Rasmussen, S.H., Stisen, S., 2016. Where are the limits of model predictive capabilities?: Representative Elementary Scale - RES. Hydrol. Process. doi:10.1002/hyp.11029

Performance of some biotic indices in the real variable world: a case study at different spatial scales in North-Western Mediterranean Sea.

PubMed

Tataranni, Mariella; Lardicci, Claudio

2010-01-01

The aim of this study was to analyse the variability of four different benthic biotic indices (AMBI, BENTIX, H', M-AMBI) in two marine coastal areas of the North-Western Mediterranean Sea. In each coastal area, 36 replicates were randomly selected according to a hierarchical sampling design, which allowed estimating the variance components of the indices associated with four different spatial scales (ranging from metres to kilometres). All the analyses were performed at two different sampling periods in order to evaluate if the observed trends were consistent over the time. The variance components of the four indices revealed complex trends and different patterns in the two sampling periods. These results highlighted that independently from the employed index, a rigorous and appropriate sampling design taking into account different scales should always be used in order to avoid erroneous classifications and to develop effective monitoring programs.

Spatial aspects of building and population exposure data and their implications for global earthquake exposure modeling

USGS Publications Warehouse

Dell’Acqua, F.; Gamba, P.; Jaiswal, K.

2012-01-01

This paper discusses spatial aspects of the global exposure dataset and mapping needs for earthquake risk assessment. We discuss this in the context of development of a Global Exposure Database for the Global Earthquake Model (GED4GEM), which requires compilation of a multi-scale inventory of assets at risk, for example, buildings, populations, and economic exposure. After defining the relevant spatial and geographic scales of interest, different procedures are proposed to disaggregate coarse-resolution data, to map them, and if necessary to infer missing data by using proxies. We discuss the advantages and limitations of these methodologies and detail the potentials of utilizing remote-sensing data. The latter is used especially to homogenize an existing coarser dataset and, where possible, replace it with detailed information extracted from remote sensing using the built-up indicators for different environments. Present research shows that the spatial aspects of earthquake risk computation are tightly connected with the availability of datasets of the resolution necessary for producing sufficiently detailed exposure. The global exposure database designed by the GED4GEM project is able to manage datasets and queries of multiple spatial scales.

Downscaling remotely sensed imagery using area-to-point cokriging and multiple-point geostatistical simulation

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Atkinson, Peter M.; Zhang, Jingxiong

2015-03-01

A cross-scale data integration method was developed and tested based on the theory of geostatistics and multiple-point geostatistics (MPG). The goal was to downscale remotely sensed images while retaining spatial structure by integrating images at different spatial resolutions. During the process of downscaling, a rich spatial correlation model in the form of a training image was incorporated to facilitate reproduction of similar local patterns in the simulated images. Area-to-point cokriging (ATPCK) was used as locally varying mean (LVM) (i.e., soft data) to deal with the change of support problem (COSP) for cross-scale integration, which MPG cannot achieve alone. Several pairs of spectral bands of remotely sensed images were tested for integration within different cross-scale case studies. The experiment shows that MPG can restore the spatial structure of the image at a fine spatial resolution given the training image and conditioning data. The super-resolution image can be predicted using the proposed method, which cannot be realised using most data integration methods. The results show that ATPCK-MPG approach can achieve greater accuracy than methods which do not account for the change of support issue.

Factorial Kriging analysis and sources of heavy metals in soils of different land-use types in the Yangtze River Delta of Eastern China.

PubMed

Zhou, Jie; Feng, Ke; Li, Yinju; Zhou, Yang

2016-08-01

The objectives of this study are to analyse the pollution status and spatial correlation of soil heavy metals and identify natural and anthropogenic sources of these heavy metals at different spatial scales. Two hundred and twenty-four soil samples (0-20 cm) were collected and analysed for eight heavy metals (Cd, Hg, As, Cu, Pb, Cr, Zn and Ni) in soils of different land-use types in the Yangtze River Delta of Eastern China. The multivariate methods and factorial Kriging analysis were used to achieve the research objectives. The results indicated that the human and natural effects of different land-use types on the contents of soil heavy metals were different. The Cd, Hg, Cu, Pb and Zn in soils of industrial area were affected by human activities, and the pollution level of these heavy metals in this area was moderate. The Pb in soils of traffic area was affected by human activities, and eight heavy metals in soils of residential area and farmland area were affected by natural factor. The ecological risk status of eight heavy metals in soils of the whole study area was light. The heavy metals in soils showed three spatial scales (nugget effect, short range and long range). At the nugget effect and short range scales, the Cd, Hg, Cu, Pb and Zn in soils were affected by human and natural factors. At three spatial scales, the As, Cr and Ni in soils were affected by soil parent materials.

Functional strategies drive community assembly of stream fishes along environmental gradients and across spatial scales

DOE Office of Scientific and Technical Information (OSTI.GOV)

Troia, Matthew J.; Gido, Keith B.

Trade-offs among functional traits produce multi-trait strategies that shape species interactions with the environment and drive the assembly of local communities from regional species pools. Stream fish communities vary along stream size gradients and among hierarchically structured habitat patches, but little is known about how the dispersion of strategies varies along environmental gradients and across spatial scales. We used null models to quantify the dispersion of reproductive life history, feeding, and locomotion strategies in communities sampled at three spatial scales in a prairie stream network in Kansas, USA. Strategies were generally underdispersed at all spatial scales, corroborating the longstanding notionmore » of abiotic filtering in stream fish communities. We tested for variation in strategy dispersion along a gradient of stream size and between headwater streams draining different ecoregions. Reproductive life history strategies became increasingly underdispersed moving from downstream to upstream, suggesting that abiotic filtering is stronger in headwaters. This pattern was stronger among reaches compared to mesohabitats, supporting the premise that differences in hydrologic regime among reaches filter reproductive life history strategies. Feeding strategies became increasingly underdispersed moving from upstream to downstream, indicating that environmental filters associated with stream size affect the dispersion of feeding and reproductive life history in opposing ways. Weak differences in strategy dispersion were detected between ecoregions, suggesting that different abiotic filters or strategies drive community differences between ecoregions. Lastly, given the pervasiveness of multi-trait strategies in plant and animal communities, we conclude that the assessment of strategy dispersion offers a comprehensive approach for elucidating mechanisms of community assembly.« less

Spatial variability of the Black Sea surface temperature from high resolution modeling and satellite measurements

NASA Astrophysics Data System (ADS)

Mizyuk, Artem; Senderov, Maxim; Korotaev, Gennady

2016-04-01

Large number of numerical ocean models were implemented for the Black Sea basin during last two decades. They reproduce rather similar structure of synoptical variability of the circulation. Since 00-s numerical studies of the mesoscale structure are carried out using high performance computing (HPC). With the growing capacity of computing resources it is now possible to reconstruct the Black Sea currents with spatial resolution of several hundreds meters. However, how realistic these results can be? In the proposed study an attempt is made to understand which spatial scales are reproduced by ocean model in the Black Sea. Simulations are made using parallel version of NEMO (Nucleus for European Modelling of the Ocean). A two regional configurations with spatial resolutions 5 km and 2.5 km are described. Comparison of the SST from simulations with two spatial resolutions shows rather qualitative difference of the spatial structures. Results of high resolution simulation are compared also with satellite observations and observation-based products from Copernicus using spatial correlation and spectral analysis. Spatial scales of correlations functions for simulated and observed SST are rather close and differs much from satellite SST reanalysis. Evolution of spectral density for modelled SST and reanalysis showed agreed time periods of small scales intensification. Using of the spectral analysis for satellite measurements is complicated due to gaps. The research leading to this results has received funding from Russian Science Foundation (project № 15-17-20020)

Spatial heterogeneity of leaf area index across scales from simulation and remote sensing

NASA Astrophysics Data System (ADS)

Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl

2016-04-01

Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.

Analysis of the historical precipitation in the South East Iberian Peninsula at different spatio-temporal scale. Study of the meteorological drought

NASA Astrophysics Data System (ADS)

Fernández-Chacón, Francisca; Pulido-Velazquez, David; Jiménez-Sánchez, Jorge; Luque-Espinar, Juan Antonio

2017-04-01

Precipitation is a fundamental climate variable that has a pronounced spatial and temporal variability on a global scale, as well as at regional and sub-regional scales. Due to its orographic complexity and its latitude the Iberian Peninsula (IP), located to the west of the Mediterranean Basin between the Atlantic Ocean and the Mediterranean Sea, has a complex climate. Over the peninsula there are strong north-south and east-west gradients, as a consequence of the different low-frequency atmospheric patterns, and he overlap of these over the year will be determinants in the variability of climatic variables. In the southeast of the Iberian Peninsula dominates a dry Mediterranean climate, the precipitation is characterized as being an intermittent and discontinuous variable. In this research information coming from the Spain02 v4 database was used to study the South East (SE) IP for the 1971-2010 period with a spatial resolution of 0.11 x 0.11. We analysed precipitation at different time scale (daily, monthly, seasonal, annual,…) to study the spatial distribution and temporal tendencies. The high spatial, intra-annual and inter-annual climatic variability observed makes it necessary to propose a climatic regionalization. In addition, for the identified areas and subareas of homogeneous climate we have analysed the evolution of the meteorological drought for the same period at different time scales. The standardized precipitation index has been used at 12, 24 and 48 month temporal scale. The climatic complexity of the area determines a high variability in the drought characteristics, duration, intensity and frequency in the different climatic areas. This research has been supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank Spain02 project for the data provided for this study.

Estimating spatial variations in water content of clay soils from time-lapse electrical conductivity surveys

USDA-ARS?s Scientific Manuscript database

Soil water content (theta) is one of the most important drivers for many biogeochemical fluxes at different temporal and spatial scales. Hydrogeophysical non-invasive sensors that measure the soil apparent electrical conductivity (ECa) have been widely used to infer spatial and temporal patterns of...

An evaluation of the ecological and environmental security on China's terrestrial ecosystems.

PubMed

Zhang, Hongqi; Xu, Erqi

2017-04-11

With rapid economic growth, industrialization, and urbanization, various ecological and environmental problems occur, which threaten and undermine the sustainable development and domestic survival of China. On the national scale, our progress remains in a state of qualitative or semi-quantitative evaluation, lacking a quantitative evaluation and a spatial visualization of ecological and environmental security. This study collected 14 indictors of water, land, air, and biodiversity securities to compile a spatial evaluation of ecological and environmental security in terrestrial ecosystems of China. With area-weighted normalization and scaling transformations, the veto aggregation (focusing on the limit indicator) and balanced aggregation (measuring balanced performance among different indicators) methods were used to aggregate security evaluation indicators. Results showed that water, land, air, and biodiversity securities presented different spatial distributions. A relatively serious ecological and environmental security crisis was found in China, but presented an obviously spatial variation of security evaluation scores. Hotspot areas at the danger level, which are scattered throughout the entirety of the country, were identified. The spatial diversities and causes of ecological and environmental problems in different regions were analyzed. Spatial integration of regional development and proposals for improving the ecological and environmental security were put forward.

Multilevel landscape utilization of the Siberian flying squirrel: Scale effects on species habitat use.

PubMed

Remm, Jaanus; Hanski, Ilpo K; Tuominen, Sakari; Selonen, Vesa

2017-10-01

Animals use and select habitat at multiple hierarchical levels and at different spatial scales within each level. Still, there is little knowledge on the scale effects at different spatial levels of species occupancy patterns. The objective of this study was to examine nonlinear effects and optimal-scale landscape characteristics that affect occupancy of the Siberian flying squirrel, Pteromys volans , in South- and Mid-Finland. We used presence-absence data ( n  = 10,032 plots of 9 ha) and novel approach to separate the effects on site-, landscape-, and regional-level occupancy patterns. Our main results were: landscape variables predicted the placement of population patches at least twice as well as they predicted the occupancy of particular sites; the clear optimal value of preferred habitat cover for species landscape-level abundance is a surprisingly low value (10% within a 4 km buffer); landscape metrics exert different effects on species occupancy and abundance in high versus low population density regions of our study area. We conclude that knowledge of regional variation in landscape utilization will be essential for successful conservation of the species. The results also support the view that large-scale landscape variables have high predictive power in explaining species abundance. Our study demonstrates the complex response of species occurrence at different levels of population configuration on landscape structure. The study also highlights the need for data in large spatial scale to increase the precision of biodiversity mapping and prediction of future trends.

Theories of Simplification and Scaling of Spatially Distributed Processes. Chapter 12

NASA Technical Reports Server (NTRS)

Levin, Simon A.; Pacala, Stephen W.

1997-01-01

The problem of scaling is at the heart of ecological theory, the essence of understanding and of the development of a predictive capability. The description of any system depends on the spatial, temporal, and organizational perspective chosen; hence it is essential to understand not only how patterns and dynamics vary with scale, but also how patterns at one scale are manifestations of processes operating at other scales. Evolution has shaped the characteristics of species in ways that result in scale displacement: Each species experiences the environment at its own unique set of spatial and temporal scales and interfaces the biota through unique assemblages of phenotypes. In this way, coexistence becomes possible, and biodiversity is enhanced. By averaging over space, time, and biological interactions, a genotype filters variation at fine scales and selects the arena in which it will face the vicissitudes of nature. Variation at finer scales is then noise, of minor importance to the survival and dynamics of the species, and consequently of minor importance in any attempt at description. In attempting to model ecological interactions in space, contributors throughout this book have struggled with a trade-off between simplification and "realistic" complexity and detail. Although the challenge of simplification is widely recognized in ecology, less appreciated is the intertwining of scaling questions and scaling laws with the process of simplification. In the context of this chapter simplification will in general mean the use of spatial or ensemble means and low-order moments to capture more detailed interactions by integrating over given areas. In this way, one can derive descriptions of the system at different spatial scales, which provides the essentials for the extraction of scaling laws by examination of how system properties vary with scale.

Spatial Metrics of Tumour Vascular Organisation Predict Radiation Efficacy in a Computational Model

PubMed Central

Scott, Jacob G.

2016-01-01

Intratumoural heterogeneity is known to contribute to poor therapeutic response. Variations in oxygen tension in particular have been correlated with changes in radiation response in vitro and at the clinical scale with overall survival. Heterogeneity at the microscopic scale in tumour blood vessel architecture has been described, and is one source of the underlying variations in oxygen tension. We seek to determine whether histologic scale measures of the erratic distribution of blood vessels within a tumour can be used to predict differing radiation response. Using a two-dimensional hybrid cellular automaton model of tumour growth, we evaluate the effect of vessel distribution on cell survival outcomes of simulated radiation therapy. Using the standard equations for the oxygen enhancement ratio for cell survival probability under differing oxygen tensions, we calculate average radiation effect over a range of different vessel densities and organisations. We go on to quantify the vessel distribution heterogeneity and measure spatial organization using Ripley’s L function, a measure designed to detect deviations from complete spatial randomness. We find that under differing regimes of vessel density the correlation coefficient between the measure of spatial organization and radiation effect changes sign. This provides not only a useful way to understand the differences seen in radiation effect for tissues based on vessel architecture, but also an alternate explanation for the vessel normalization hypothesis. PMID:26800503

An innovative expression model of human health risk based on the quantitative analysis of soil metals sources contribution in different spatial scales.

PubMed

Zhang, Yimei; Li, Shuai; Wang, Fei; Chen, Zhuang; Chen, Jie; Wang, Liqun

2018-09-01

Toxicity of heavy metals from industrialization poses critical concern, and analysis of sources associated with potential human health risks is of unique significance. Assessing human health risk of pollution sources (factored health risk) concurrently in the whole and the sub region can provide more instructive information to protect specific potential victims. In this research, we establish a new expression model of human health risk based on quantitative analysis of sources contribution in different spatial scales. The larger scale grids and their spatial codes are used to initially identify the level of pollution risk, the type of pollution source and the sensitive population at high risk. The smaller scale grids and their spatial codes are used to identify the contribution of various sources of pollution to each sub region (larger grid) and to assess the health risks posed by each source for each sub region. The results of case study show that, for children (sensitive populations, taking school and residential area as major region of activity), the major pollution source is from the abandoned lead-acid battery plant (ALP), traffic emission and agricultural activity. The new models and results of this research present effective spatial information and useful model for quantifying the hazards of source categories and human health a t complex industrial system in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial-pattern-induced evolution of a self-replicating loop network.

PubMed

Suzuki, Keisuke; Ikegami, Takashi

2006-01-01

We study a system of self-replicating loops in which interaction rules between individuals allow competition that leads to the formation of a hypercycle-like network. The main feature of the model is the multiple layers of interaction between loops, which lead to both global spatial patterns and local replication. The network of loops manifests itself as a spiral structure from which new kinds of self-replicating loops emerge at the boundaries between different species. In these regions, larger and more complex self-replicating loops live for longer periods of time, managing to self-replicate in spite of their slower replication. Of particular interest is how micro-scale interactions between replicators lead to macro-scale spatial pattern formation, and how these macro-scale patterns in turn perturb the micro-scale replication dynamics.

Spatial Competition: Roughening of an Experimental Interface.

PubMed

Allstadt, Andrew J; Newman, Jonathan A; Walter, Jonathan A; Korniss, G; Caraco, Thomas

2016-07-28

Limited dispersal distance generates spatial aggregation. Intraspecific interactions are then concentrated within clusters, and between-species interactions occur near cluster boundaries. Spread of a locally dispersing invader can become motion of an interface between the invading and resident species, and spatial competition will produce variation in the extent of invasive advance along the interface. Kinetic roughening theory offers a framework for quantifying the development of these fluctuations, which may structure the interface as a self-affine fractal, and so induce a series of temporal and spatial scaling relationships. For most clonal plants, advance should become spatially correlated along the interface, and width of the interface (where invader and resident compete directly) should increase as a power function of time. Once roughening equilibrates, interface width and the relative location of the most advanced invader should each scale with interface length. We tested these predictions by letting white clover (Trifolium repens) invade ryegrass (Lolium perenne). The spatial correlation of clover growth developed as anticipated by kinetic roughening theory, and both interface width and the most advanced invader's lead scaled with front length. However, the scaling exponents differed from those predicted by recent simulation studies, likely due to clover's growth morphology.

Spatial Competition: Roughening of an Experimental Interface

PubMed Central

Allstadt, Andrew J.; Newman, Jonathan A.; Walter, Jonathan A.; Korniss, G.; Caraco, Thomas

2016-01-01

Limited dispersal distance generates spatial aggregation. Intraspecific interactions are then concentrated within clusters, and between-species interactions occur near cluster boundaries. Spread of a locally dispersing invader can become motion of an interface between the invading and resident species, and spatial competition will produce variation in the extent of invasive advance along the interface. Kinetic roughening theory offers a framework for quantifying the development of these fluctuations, which may structure the interface as a self-affine fractal, and so induce a series of temporal and spatial scaling relationships. For most clonal plants, advance should become spatially correlated along the interface, and width of the interface (where invader and resident compete directly) should increase as a power function of time. Once roughening equilibrates, interface width and the relative location of the most advanced invader should each scale with interface length. We tested these predictions by letting white clover (Trifolium repens) invade ryegrass (Lolium perenne). The spatial correlation of clover growth developed as anticipated by kinetic roughening theory, and both interface width and the most advanced invader’s lead scaled with front length. However, the scaling exponents differed from those predicted by recent simulation studies, likely due to clover’s growth morphology. PMID:27465518

Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models.

PubMed

Rogers, Lauren A; Storvik, Geir O; Knutsen, Halvor; Olsen, Esben M; Stenseth, Nils C

2017-07-01

Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93-year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod. Cross-validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density-dependent survival. Recent biomass was estimated to be at a near-record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may have played a role in driving local dynamics. More generally, we demonstrated how state-space models can be used to test evidence for population spatial structure based on survey time-series data. Our study shows the importance of considering spatially structured dynamics, as the inferences from such an approach can lead to a different ecological understanding of the drivers of population declines, and fundamentally different management actions to restore populations. © 2017 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Use of Fouler Transforms to define landscape scales of analysis for disturbances: A case study of thinned and unthinned forest stands

Treesearch

J. E. Lundquist; R. A. Sommerfeld

2002-01-01

Various disturbances such as disease and management practices cause canopy gaps that change patterns of forest stand structure. This study examined the usefulness of digital image analysis using aerial photos, Fourier Tranforms, and cluster analysis to investigate how different spatial statistics are affected by spatial scale. The specific aims were to: 1) evaluate how...

Spatial, temporal and geographic considerations of the problem of rock varnish diagenesis

NASA Astrophysics Data System (ADS)

Dorn, Ronald I.; Krinsley, David

2011-07-01

The rock varnish literature hosts an abundance of prima facie contradictory empirical data. Past and perhaps future empirical contradictions, however, can be resolved by theoretical considerations of different spatial and temporal scales of varnish diagenesis, as well as the geomorphic position of different types of varnishes. For example, twentieth-century contamination by lead and other heavy metals has led to claims of accumulation rates in the last century far more rapid than prior published empirical studies. A consideration of spatial scales resolves this contradiction; nanoscale processes allow migration of lead into varnish deposited well before the twentieth century time of heavy metal pollution. Evidence of nanometer-scale disequilibrium in three samples led to claims that varnish cannot be used in paleoclimatic research; these data rest in contrast to replicable patterns in varnish deposition observed by Dr. Tanzhuo Liu and others in over ten thousand micro-sedimentary basins. This contraction can be resolved by understanding that the types of varnishes studied differ and that processes differ substantially between the nanoscale and the micron scale. A lack of evidence of Mn-oxidizers in genetic analyses contrasts with culturing studies and in situ evidence of Mn-enhancement by bacteria. This contradiction has a likely resolution in vastly different temporal scales; DNA material analyzed may be no older than 200 years, but in situ fossilized remains of bacteria may be preserved for thousands of years recording palaeoecological conditions favoring growth of Mn-enhancing bacteria.

Redefining yield gaps at various spatial scales

NASA Astrophysics Data System (ADS)

Meng, K.; Fishman, R.; Norstrom, A. V.; Diekert, F. K.; Engstrom, G.; Gars, J.; McCarney, G. R.; Sjostedt, M.

2013-12-01

Recent research has highlighted the prevalence of 'yield gaps' around the world and the importance of closing them for global food security. However, the traditional concept of yield gap -defined as the difference between observed and optimal yield under biophysical conditions - omit relevant socio-economic and ecological constraints and thus offer limited guidance on potential policy interventions. This paper proposes alternative definitions of yield gaps by incorporating rich, high resolution, national and sub-national agricultural datasets. We examine feasible efforts to 'close yield gaps' at various spatial scales and across different socio-economic and ecological domains.

Assessment of the spatial scaling behaviour of floods in the United Kingdom

NASA Astrophysics Data System (ADS)

Formetta, Giuseppe; Stewart, Elizabeth; Bell, Victoria

2017-04-01

Floods are among the most dangerous natural hazards, causing loss of life and significant damage to private and public property. Regional flood-frequency analysis (FFA) methods are essential tools to assess the flood hazard and plan interventions for its mitigation. FFA methods are often based on the well-known index flood method that assumes the invariance of the coefficient of variation of floods with drainage area. This assumption is equivalent to the simple scaling or self-similarity assumption for peak floods, i.e. their spatial structure remains similar in a particular, relatively simple, way to itself over a range of scales. Spatial scaling of floods has been evaluated at national scale for different countries such as Canada, USA, and Australia. According our knowledge. Such a study has not been conducted for the United Kingdom even though the standard FFA method there is based on the index flood assumption. In this work we present an integrated approach to assess of the spatial scaling behaviour of floods in the United Kingdom using three different methods: product moments (PM), probability weighted moments (PWM), and quantile analysis (QA). We analyse both instantaneous and daily annual observed maximum floods and performed our analysis both across the entire country and in its sub-climatic regions as defined in the Flood Studies Report (NERC, 1975). To evaluate the relationship between the k-th moments or quantiles and the drainage area we used both regression with area alone and multiple regression considering other explanatory variables to account for the geomorphology, amount of rainfall, and soil type of the catchments. The latter multiple regression approach was only recently demonstrated being more robust than the traditional regression with area alone that can lead to biased estimates of scaling exponents and misinterpretation of spatial scaling behaviour. We tested our framework on almost 600 rural catchments in UK considered as entire region and split in 11 sub-regions with 50 catchments per region on average. Preliminary results from the three different spatial scaling methods are generally in agreement and indicate that: i) only some of the peak flow variability is explained by area alone (approximately 50% for the entire country and ranging between the 40% and 70% for the sub-regions); ii) this percentage increases to 90% for the entire country and ranges between 80% and 95% for the sub-regions when the multiple regression is used; iii) the simple scaling hypothesis holds in all sub-regions with the exception of weak multi-scaling found in the regions 2 (North), and 5 and 6 (South East). We hypothesize that these deviations can be explained by heterogeneity in large scale precipitation and by the influence of the soil type (predominantly chalk) on the flood formation process in regions 5 and 6.

Exploring the effects of spatial autocorrelation when identifying key drivers of wildlife crop-raiding.

PubMed

Songhurst, Anna; Coulson, Tim

2014-03-01

Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human-wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative survey of raided and nonraided fields to determine key drivers of crop-raiding. Data were subsampled at different spatial scales to select independent raiding data points. The model derived from all data was fitted to subsample data sets. Model parameters from these models were compared to determine the effect of SA. Most methods used to account for SA in data attempt to correct for the change in P-values; yet, by subsampling data at broader spatial scales, we identified changes in regression estimates. We consequently advocate reporting both model parameters across a range of spatial scales to help biological interpretation. Patterns of SA vary spatially in our crop-raiding data. Spatial distribution of fields should therefore be considered when choosing the spatial scale for analyses of HWC studies. Robust key drivers of elephant crop-raiding included raiding history of a field and distance of field to a main elephant pathway. Understanding spatial patterns and determining reliable socio-ecological drivers of wildlife crop-raiding is paramount for designing mitigation and land-use planning strategies to reduce HWC. Spatial patterns of HWC are complex, determined by multiple factors acting at more than one scale; therefore, studies need to be designed with an understanding of the effects of SA. Our methods are accessible to a variety of practitioners to assess the effects of SA, thereby improving the reliability of conservation management actions.

How beta diversity and the underlying causes vary with sampling scales in the Changbai mountain forests.

PubMed

Tan, Lingzhao; Fan, Chunyu; Zhang, Chunyu; von Gadow, Klaus; Fan, Xiuhua

2017-12-01

This study aims to establish a relationship between the sampling scale and tree species beta diversity temperate forests and to identify the underlying causes of beta diversity at different sampling scales. The data were obtained from three large observational study areas in the Changbai mountain region in northeastern China. All trees with a dbh ≥1 cm were stem-mapped and measured. The beta diversity was calculated for four different grain sizes, and the associated variances were partitioned into components explained by environmental and spatial variables to determine the contributions of environmental filtering and dispersal limitation to beta diversity. The results showed that both beta diversity and the causes of beta diversity were dependent on the sampling scale. Beta diversity decreased with increasing scales. The best-explained beta diversity variation was up to about 60% which was discovered in the secondary conifer and broad-leaved mixed forest (CBF) study area at the 40 × 40 m scale. The variation partitioning result indicated that environmental filtering showed greater effects at bigger grain sizes, while dispersal limitation was found to be more important at smaller grain sizes. What is more, the result showed an increasing explanatory ability of environmental effects with increasing sampling grains but no clearly trend of spatial effects. The study emphasized that the underlying causes of beta diversity variation may be quite different within the same region depending on varying sampling scales. Therefore, scale effects should be taken into account in future studies on beta diversity, which is critical in identifying different relative importance of spatial and environmental drivers on species composition variation.

Understanding the Complexity of Temperature Dynamics in Xinjiang, China, from Multitemporal Scale and Spatial Perspectives

PubMed Central

Chen, Yaning; Li, Weihong; Liu, Zuhan; Wei, Chunmeng; Tang, Jie

2013-01-01

Based on the observed data from 51 meteorological stations during the period from 1958 to 2012 in Xinjiang, China, we investigated the complexity of temperature dynamics from the temporal and spatial perspectives by using a comprehensive approach including the correlation dimension (CD), classical statistics, and geostatistics. The main conclusions are as follows (1) The integer CD values indicate that the temperature dynamics are a complex and chaotic system, which is sensitive to the initial conditions. (2) The complexity of temperature dynamics decreases along with the increase of temporal scale. To describe the temperature dynamics, at least 3 independent variables are needed at daily scale, whereas at least 2 independent variables are needed at monthly, seasonal, and annual scales. (3) The spatial patterns of CD values at different temporal scales indicate that the complex temperature dynamics are derived from the complex landform. PMID:23843732

Forecasting Influenza Outbreaks in Boroughs and Neighborhoods of New York City

PubMed Central

2016-01-01

The ideal spatial scale, or granularity, at which infectious disease incidence should be monitored and forecast has been little explored. By identifying the optimal granularity for a given disease and host population, and matching surveillance and prediction efforts to this scale, response to emergent and recurrent outbreaks can be improved. Here we explore how granularity and representation of spatial structure affect influenza forecast accuracy within New York City. We develop network models at the borough and neighborhood levels, and use them in conjunction with surveillance data and a data assimilation method to forecast influenza activity. These forecasts are compared to an alternate system that predicts influenza for each borough or neighborhood in isolation. At the borough scale, influenza epidemics are highly synchronous despite substantial differences in intensity, and inclusion of network connectivity among boroughs generally improves forecast accuracy. At the neighborhood scale, we observe much greater spatial heterogeneity among influenza outbreaks including substantial differences in local outbreak timing and structure; however, inclusion of the network model structure generally degrades forecast accuracy. One notable exception is that local outbreak onset, particularly when signal is modest, is better predicted with the network model. These findings suggest that observation and forecast at sub-municipal scales within New York City provides richer, more discriminant information on influenza incidence, particularly at the neighborhood scale where greater heterogeneity exists, and that the spatial spread of influenza among localities can be forecast. PMID:27855155

Risk assessment of salinity and turbidity in Victoria (Australia) to stream insects' community structure does not always protect functional traits.

PubMed

Kefford, Ben J; Schäfer, Ralf B; Metzeling, Leon

2012-01-15

Ecological risk assessments mostly consider measures of community composition (structure) across large spatial scales. These assessments, using species sensitivity distributions (SSDs) or the relative species retention (RSR), may not be protective of ecosystem functions and services at smaller spatial scales. Here we examine how changes in biological traits, as proxy for ecosystem functions/services, at a fine spatial scale relate to larger scale assessment of structure. We use functional traits of stream insect species in south-east Australia in two habitats (riffle and edge/pool). We find that the protection of community structure in terms of 95% of species over multiple sites against adverse effects of salinity (as electrical conductivity) and turbidity will mostly, but not always, protect traits at smaller scales. Considering different combinations of trait modalities, contaminants and habitat, a mean of 17.5% (range 0%-36.8) of cases would result in under-protection of trait modalities despite protecting species composition (in terms of Jaccard's Index). This under-protection of trait modalities is only because of the different spatial scales that community structure and the traits were considered. We recommend that where the protection of biological traits, ecosystem functions or ecosystem services from stressors is a management goal, protective targets should not be solely set using measures of community structure such as SSDs or RSR. To protect both structural and functional attributes separate risk assessments should be done. Copyright © 2011 Elsevier B.V. All rights reserved.

Spatial Covariability of Temperature and Hydroclimate as a Function of Timescale During the Common Era

NASA Astrophysics Data System (ADS)

McKay, N.

2017-12-01

As timescale increases from years to centuries, the spatial scale of covariability in the climate system is hypothesized to increase as well. Covarying spatial scales are larger for temperature than for hydroclimate, however, both aspects of the climate system show systematic changes on large-spatial scales on orbital to tectonic timescales. The extent to which this phenomenon is evident in temperature and hydroclimate at centennial timescales is largely unknown. Recent syntheses of multidecadal to century-scale variability in hydroclimate during the past 2k in the Arctic, North America, and Australasia show little spatial covariability in hydroclimate during the Common Era. To determine 1) the evidence for systematic relationships between the spatial scale of climate covariability as a function of timescale, and 2) whether century-scale hydroclimate variability deviates from the relationship between spatial covariability and timescale, we quantify this phenomenon during the Common Era by calculating the e-folding distance in large instrumental and paleoclimate datasets. We calculate this metric of spatial covariability, at different timescales (1, 10 and 100-yr), for a large network of temperature and precipitation observations from the Global Historical Climatology Network (n=2447), from v2.0.0 of the PAGES2k temperature database (n=692), and from moisture-sensitive paleoclimate records North America, the Arctic, and the Iso2k project (n = 328). Initial results support the hypothesis that the spatial scale of covariability is larger for temperature, than for precipitation or paleoclimate hydroclimate indicators. Spatially, e-folding distances for temperature are largest at low latitudes and over the ocean. Both instrumental and proxy temperature data show clear evidence for increasing spatial extent as a function of timescale, but this phenomenon is very weak in the hydroclimate data analyzed here. In the proxy hydroclimate data, which are predominantly indicators of effective moisture, e-folding distance increases from annual to decadal timescales, but does not continue to increase to centennial timescales. Future work includes examining additional instrumental and proxy datasets of moisture variability, and extending the analysis to millennial timescales of variability.

Spatial and Functional Organization of Pig Trade in Different European Production Systems: Implications for Disease Prevention and Control.

PubMed

Relun, Anne; Grosbois, Vladimir; Sánchez-Vizcaíno, José Manuel; Alexandrov, Tsviatko; Feliziani, Francesco; Waret-Szkuta, Agnès; Molia, Sophie; Etter, Eric Marcel Charles; Martínez-López, Beatriz

2016-01-01

Understanding the complexity of live pig trade organization is a key factor to predict and control major infectious diseases, such as classical swine fever (CSF) or African swine fever (ASF). Whereas the organization of pig trade has been described in several European countries with indoor commercial production systems, little information is available on this organization in other systems, such as outdoor or small-scale systems. The objective of this study was to describe and compare the spatial and functional organization of live pig trade in different European countries and different production systems. Data on premise characteristics and pig movements between premises were collected during 2011 from Bulgaria, France, Italy, and Spain, which swine industry is representative of most of the production systems in Europe (i.e., commercial vs. small-scale and outdoor vs. indoor). Trade communities were identified in each country using the Walktrap algorithm. Several descriptive and network metrics were generated at country and community levels. Pig trade organization showed heterogeneous spatial and functional organization. Trade communities mostly composed of indoor commercial premises were identified in western France, northern Italy, northern Spain, and north-western Bulgaria. They covered large distances, overlapped in space, demonstrated both scale-free and small-world properties, with a role of trade operators and multipliers as key premises. Trade communities involving outdoor commercial premises were identified in western Spain, south-western and central France. They were more spatially clustered, demonstrated scale-free properties, with multipliers as key premises. Small-scale communities involved the majority of premises in Bulgaria and in central and Southern Italy. They were spatially clustered and had scale-free properties, with key premises usually being commercial production premises. These results indicate that a disease might spread very differently according to the production system and that key premises could be targeted to more cost-effectively control diseases. This study provides useful epidemiological information and parameters that could be used to design risk-based surveillance strategies or to more accurately model the risk of introduction or spread of devastating swine diseases, such as ASF, CSF, or foot-and-mouth disease.

Spatial and Functional Organization of Pig Trade in Different European Production Systems: Implications for Disease Prevention and Control

PubMed Central

Relun, Anne; Grosbois, Vladimir; Sánchez-Vizcaíno, José Manuel; Alexandrov, Tsviatko; Feliziani, Francesco; Waret-Szkuta, Agnès; Molia, Sophie; Etter, Eric Marcel Charles; Martínez-López, Beatriz

2016-01-01

Understanding the complexity of live pig trade organization is a key factor to predict and control major infectious diseases, such as classical swine fever (CSF) or African swine fever (ASF). Whereas the organization of pig trade has been described in several European countries with indoor commercial production systems, little information is available on this organization in other systems, such as outdoor or small-scale systems. The objective of this study was to describe and compare the spatial and functional organization of live pig trade in different European countries and different production systems. Data on premise characteristics and pig movements between premises were collected during 2011 from Bulgaria, France, Italy, and Spain, which swine industry is representative of most of the production systems in Europe (i.e., commercial vs. small-scale and outdoor vs. indoor). Trade communities were identified in each country using the Walktrap algorithm. Several descriptive and network metrics were generated at country and community levels. Pig trade organization showed heterogeneous spatial and functional organization. Trade communities mostly composed of indoor commercial premises were identified in western France, northern Italy, northern Spain, and north-western Bulgaria. They covered large distances, overlapped in space, demonstrated both scale-free and small-world properties, with a role of trade operators and multipliers as key premises. Trade communities involving outdoor commercial premises were identified in western Spain, south-western and central France. They were more spatially clustered, demonstrated scale-free properties, with multipliers as key premises. Small-scale communities involved the majority of premises in Bulgaria and in central and Southern Italy. They were spatially clustered and had scale-free properties, with key premises usually being commercial production premises. These results indicate that a disease might spread very differently according to the production system and that key premises could be targeted to more cost-effectively control diseases. This study provides useful epidemiological information and parameters that could be used to design risk-based surveillance strategies or to more accurately model the risk of introduction or spread of devastating swine diseases, such as ASF, CSF, or foot-and-mouth disease. PMID:26870738

Long-term Spatial Distribution Patterns of Protozoa in Connected Microhabitats

NASA Astrophysics Data System (ADS)

Taghon, G. L.; Tuorto, S. J.

2016-02-01

Studies of microbial ecosystems usually assume habitat homogeneity. Recent research, however, indicates that habitat structure varies at millimeter scales and that this patchiness affects abundance and behavior of microbes. In this study, two species of ciliated protozoa were maintained, together, for multiple generations in microfluidic devices consisting of arrays of interconnected microhabitats with differing resource availability. The species differed in their population dynamics and tendency to disperse among microhabitats. Both species coexisted for over 45 days, and their coexistence likely resulted from habitat selection at millimeter scales. We demonstrate that it is not only possible, but imperative, that detailed ecological phenomena of microbial systems be studied at the relevant spatial and temporal scales.

Models of chromatin spatial organisation in the cell nucleus

NASA Astrophysics Data System (ADS)

Nicodemi, Mario

2014-03-01

In the cell nucleus chromosomes have a complex architecture serving vital functional purposes. Recent experiments have started unveiling the interaction map of DNA sites genome-wide, revealing different levels of organisation at different scales. The principles, though, which orchestrate such a complex 3D structure remain still mysterious. I will overview the scenario emerging from some classical polymer physics models of the general aspect of chromatin spatial organisation. The available experimental data, which can be rationalised in a single framework, support a picture where chromatin is a complex mixture of differently folded regions, self-organised across spatial scales according to basic physical mechanisms. I will also discuss applications to specific DNA loci, e.g. the HoxB locus, where models informed with biological details, and tested against targeted experiments, can help identifying the determinants of folding.

3D deblending of simultaneous source data based on 3D multi-scale shaping operator

NASA Astrophysics Data System (ADS)

Zu, Shaohuan; Zhou, Hui; Mao, Weijian; Gong, Fei; Huang, Weilin

2018-04-01

We propose an iterative three-dimensional (3D) deblending scheme using 3D multi-scale shaping operator to separate 3D simultaneous source data. The proposed scheme is based on the property that signal is coherent, whereas interference is incoherent in some domains, e.g., common receiver domain and common midpoint domain. In two-dimensional (2D) blended record, the coherency difference of signal and interference is in only one spatial direction. Compared with 2D deblending, the 3D deblending can take more sparse constraints into consideration to obtain better performance, e.g., in 3D common receiver gather, the coherency difference is in two spatial directions. Furthermore, with different levels of coherency, signal and interference distribute in different scale curvelet domains. In both 2D and 3D blended records, most coherent signal locates in coarse scale curvelet domain, while most incoherent interference distributes in fine scale curvelet domain. The scale difference is larger in 3D deblending, thus, we apply the multi-scale shaping scheme to further improve the 3D deblending performance. We evaluate the performance of 3D and 2D deblending with the multi-scale and global shaping operators, respectively. One synthetic and one field data examples demonstrate the advantage of the 3D deblending with 3D multi-scale shaping operator.

Ecotoxicology and spatial modeling in population dynamics: an illustration with brown trout.

PubMed

Chaumot, Arnaud; Charles, Sandrine; Flammarion, Patrick; Auger, Pierre

2003-05-01

We developed a multiregion matrix population model to explore how the demography of a hypothetical brown trout population living in a river network varies in response to different spatial scenarios of cadmium contamination. Age structure, spatial distribution, and demographic and migration processes are taken into account in the model. Chronic or acute cadmium concentrations affect the demographic parameters at the scale of the river range. The outputs of the model constitute population-level end points (the asymptotic population growth rate, the stable age structure, and the asymptotic spatial distribution) that allow comparing the different spatial scenarios of contamination regarding the demographic response at the scale of the whole river network. An analysis of the sensitivity of these end points to lower order parameters enables us to link the local effects of cadmium to the global demographic behavior of the brown trout population. Such a link is of broad interest in the point of view of ecotoxicological management.

Comparison of two spatially-resolved fossil fuel CO2 emissions inventories at the urban scale in four US cities

NASA Astrophysics Data System (ADS)

Liang, J.; Gurney, K. R.; O'Keeffe, D.; Patarasuk, R.; Hutchins, M.; Rao, P.

2017-12-01

Spatially-resolved fossil fuel CO2 (FFCO2) emissions are used not only in complex atmospheric modeling systems as prior scenarios to simulate concentrations of CO2 in the atmosphere, but to improve understanding of relationships with socioeconomic factors in support of sustainability policymaking. We present a comparison of ODIAC, a top-down global gridded FFCO2 emissions dataset, and Hesita, a bottom-up FFCO2 emissions dataset, in four US cities, including Los Angles, Indianapolis, Salt Lake City and Baltimore City. ODIAC was developed by downscaling national total emissions to 1km-by-1km grid cells using satellite nightlight imagery as proxy. Hesita was built from the ground up by allocating sector-specific county-level emissions to urban-level spatial surrogates including facility locations, road maps, building footprints/parcels, railroad maps and shipping lanes. The differences in methodology and data sources could lead to large discrepancies in FFCO2 estimates at the urban scale, and these discrepancies need to be taken into account in conducting atmospheric modeling or socioeconomic analysis. This comparison work is aimed at quantifying the statistical and spatial difference between the two FFCO2 inventories. An analysis of the difference in total emissions, spatial distribution and statistical distribution resulted in the following findings: (1) ODIAC agrees well with Hestia in total FFCO2 emissions estimates across the four cities with a difference from 3%-20%; (2) Small-scale areal and linear spatial features such as roads and buildings are either entirely missing or not very well represented in ODIAC, since nightlight imagery might not be able to capture these information. This might further lead to underestimated on-road FFCO2 emissions in ODIAC; (3) The statistical distribution of ODIAC is more concentrated around the mean with much less samples in the lower range. These phenomena could result from the nightlight halo and saturation effects; (4) The grid-cell cumulative emissions of ODIAC appear in good agreement with that of Hestia, implying the two inventories have similar overall spatial structures at the city scale.

A Comparative Study of Spatial Aggregation Methodologies under the BioEarth Framework

NASA Astrophysics Data System (ADS)

Chandrasekharan, B.; Rajagopalan, K.; Malek, K.; Stockle, C. O.; Adam, J. C.; Brady, M.

2014-12-01

The increasing probability of water resource scarcity due to climate change has highlighted the need for adopting an economic focus in modelling water resource uses. Hydro-economic models, developed by integrating economic optimization with biophysical crop models, are driven by the economic value of water, revealing it's most efficient uses and helping policymakers evaluate different water management strategies. One of the challenges in integrating biophysical models with economic models is the difference in the spatial scales in which they operate. Biophysical models that provide crop production functions typically run at smaller scale than economic models, and substantial spatial aggregation is required. However, any aggregation introduces a bias, i.e., a discrepancy between the functional value at the higher spatial scale and the value at the spatial scale of the aggregated units. The objective of this work is to study the sensitivity of net economic benefits in the Yakima River basin (YRB) to different spatial aggregation methods for crop production functions. The spatial aggregation methodologies that we compare involve agro-ecological zones (AEZs) and aggregation levels that reflect water management regimes (e.g. irrigation districts). Aggregation bias can distort the underlying data and result in extreme solutions. In order to avoid this we use an economic optimization model that incorporates the synthetic and historical crop mixes approach (Onal & Chen, 2012). This restricts the solutions between the weighted averages of historical and simulated feasible planting decisions, with the weights associated with crop mixes being treated as endogenous variables. This study is focused on 5 major irrigation districts of the YRB in the Pacific Northwest US. The biophysical modeling framework we use, BioEarth, includes the coupled hydrology and crop growth model, VIC-Cropsyst and an economic optimization model. Preliminary findings indicate that the standard approach of developing AEZs does not perform well when overlaid with irrigation districts. Moreover, net economic benefits were significantly different between the two aggregation methodologies. Therefore, while developing hydro-economic models, significant consideration should be placed on the aggregation methodology.

Organic carbon stock modelling for the quantification of the carbon sinks in terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Durante, Pilar; Algeet, Nur; Oyonarte, Cecilio

2017-04-01

Given the recent environmental policies derived from the serious threats caused by global change, practical measures to decrease net CO2 emissions have to be put in place. Regarding this, carbon sequestration is a major measure to reduce atmospheric CO2 concentrations within a short and medium term, where terrestrial ecosystems play a basic role as carbon sinks. Development of tools for quantification, assessment and management of organic carbon in ecosystems at different scales and management scenarios, it is essential to achieve these commitments. The aim of this study is to establish a methodological framework for the modeling of this tool, applied to a sustainable land use planning and management at spatial and temporal scale. The methodology for carbon stock estimation in ecosystems is based on merger techniques between carbon stored in soils and aerial biomass. For this purpose, both spatial variability map of soil organic carbon (SOC) and algorithms for calculation of forest species biomass will be created. For the modelling of the SOC spatial distribution at different map scales, it is necessary to fit in and screen the available information of soil database legacy. Subsequently, SOC modelling will be based on the SCORPAN model, a quantitative model use to assess the correlation among soil-forming factors measured at the same site location. These factors will be selected from both static (terrain morphometric variables) and dynamic variables (climatic variables and vegetation indexes -NDVI-), providing to the model the spatio-temporal characteristic. After the predictive model, spatial inference techniques will be used to achieve the final map and to extrapolate the data to unavailable information areas (automated random forest regression kriging). The estimated uncertainty will be calculated to assess the model performance at different scale approaches. Organic carbon modelling of aerial biomass will be estimate using LiDAR (Light Detection And Ranging) algorithms. The available LiDAR databases will be used. LiDAR statistics (which describe the LiDAR cloud point data to calculate forest stand parameters) will be correlated with different canopy cover variables. The regression models applied to the total area will produce a continuous geo-information map to each canopy variable. The CO2 estimation will be calculated by dry-mass conversion factors for each forest species (C kg-CO2 kg equivalent). The result is the organic carbon modelling at spatio-temporal scale with different levels of uncertainty associated to the predictive models and diverse detailed scales. However, one of the main expected problems is due to the heterogeneous spatial distribution of the soil information, which influences on the prediction of the models at different spatial scales and, consequently, at SOC map scale. Besides this, the variability and mixture of the forest species of the aerial biomass decrease the accuracy assessment of the organic carbon.

The spatial scaling of species interaction networks.

PubMed

Galiana, Nuria; Lurgi, Miguel; Claramunt-López, Bernat; Fortin, Marie-Josée; Leroux, Shawn; Cazelles, Kevin; Gravel, Dominique; Montoya, José M

2018-05-01

Species-area relationships (SARs) are pivotal to understand the distribution of biodiversity across spatial scales. We know little, however, about how the network of biotic interactions in which biodiversity is embedded changes with spatial extent. Here we develop a new theoretical framework that enables us to explore how different assembly mechanisms and theoretical models affect multiple properties of ecological networks across space. We present a number of testable predictions on network-area relationships (NARs) for multi-trophic communities. Network structure changes as area increases because of the existence of different SARs across trophic levels, the preferential selection of generalist species at small spatial extents and the effect of dispersal limitation promoting beta-diversity. Developing an understanding of NARs will complement the growing body of knowledge on SARs with potential applications in conservation ecology. Specifically, combined with further empirical evidence, NARs can generate predictions of potential effects on ecological communities of habitat loss and fragmentation in a changing world.

Pattern-based, multi-scale segmentation and regionalization of EOSD land cover

NASA Astrophysics Data System (ADS)

Niesterowicz, Jacek; Stepinski, Tomasz F.

2017-10-01

The Earth Observation for Sustainable Development of Forests (EOSD) map is a 25 m resolution thematic map of Canadian forests. Because of its large spatial extent and relatively high resolution the EOSD is difficult to analyze using standard GIS methods. In this paper we propose multi-scale segmentation and regionalization of EOSD as new methods for analyzing EOSD on large spatial scales. Segments, which we refer to as forest land units (FLUs), are delineated as tracts of forest characterized by cohesive patterns of EOSD categories; we delineated from 727 to 91,885 FLUs within the spatial extent of EOSD depending on the selected scale of a pattern. Pattern of EOSD's categories within each FLU is described by 1037 landscape metrics. A shapefile containing boundaries of all FLUs together with an attribute table listing landscape metrics make up an SQL-searchable spatial database providing detailed information on composition and pattern of land cover types in Canadian forest. Shapefile format and extensive attribute table pertaining to the entire legend of EOSD are designed to facilitate broad range of investigations in which assessment of composition and pattern of forest over large areas is needed. We calculated four such databases using different spatial scales of pattern. We illustrate the use of FLU database for producing forest regionalization maps of two Canadian provinces, Quebec and Ontario. Such maps capture the broad scale variability of forest at the spatial scale of the entire province. We also demonstrate how FLU database can be used to map variability of landscape metrics, and thus the character of landscape, over the entire Canada.

Stochastic Spatial Models in Ecology: A Statistical Physics Approach

NASA Astrophysics Data System (ADS)

Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.

2018-07-01

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.

Stochastic Spatial Models in Ecology: A Statistical Physics Approach

NASA Astrophysics Data System (ADS)

Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.

2017-11-01

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.

GIS-based regionalized life cycle assessment: how big is small enough? Methodology and case study of electricity generation.

PubMed

Mutel, Christopher L; Pfister, Stephan; Hellweg, Stefanie

2012-01-17

We describe a new methodology for performing regionalized life cycle assessment and systematically choosing the spatial scale of regionalized impact assessment methods. We extend standard matrix-based calculations to include matrices that describe the mapping from inventory to impact assessment spatial supports. Uncertainty in inventory spatial data is modeled using a discrete spatial distribution function, which in a case study is derived from empirical data. The minimization of global spatial autocorrelation is used to choose the optimal spatial scale of impact assessment methods. We demonstrate these techniques on electricity production in the United States, using regionalized impact assessment methods for air emissions and freshwater consumption. Case study results show important differences between site-generic and regionalized calculations, and provide specific guidance for future improvements of inventory data sets and impact assessment methods.

The importance of lake-specific characteristics for water quality across the continental United States.

PubMed

Read, Emily K; Patil, Vijay P; Oliver, Samantha K; Hetherington, Amy L; Brentrup, Jennifer A; Zwart, Jacob A; Winters, Kirsten M; Corman, Jessica R; Nodine, Emily R; Woolway, R Iestyn; Dugan, Hilary A; Jaimes, Aline; Santoso, Arianto B; Hong, Grace S; Winslow, Luke A; Hanson, Paul C; Weathers, Kathleen C

2015-06-01

Lake water quality is affected by local and regional drivers, including lake physical characteristics, hydrology, landscape position, land cover, land use, geology, and climate. Here, we demonstrate the utility of hypothesis testing within the landscape limnology framework using a random forest algorithm on a national-scale, spatially explicit data set, the United States Environmental Protection Agency's 2007 National Lakes Assessment. For 1026 lakes, we tested the relative importance of water quality drivers across spatial scales, the importance of hydrologic connectivity in mediating water quality drivers, and how the importance of both spatial scale and connectivity differ across response variables for five important in-lake water quality metrics (total phosphorus, total nitrogen, dissolved organic carbon, turbidity, and conductivity). By modeling the effect of water quality predictors at different spatial scales, we found that lake-specific characteristics (e.g., depth, sediment area-to-volume ratio) were important for explaining water quality (54-60% variance explained), and that regionalization schemes were much less effective than lake specific metrics (28-39% variance explained). Basin-scale land use and land cover explained between 45-62% of variance, and forest cover and agricultural land uses were among the most important basin-scale predictors. Water quality drivers did not operate independently; in some cases, hydrologic connectivity (the presence of upstream surface water features) mediated the effect of regional-scale drivers. For example, for water quality in lakes with upstream lakes, regional classification schemes were much less effective predictors than lake-specific variables, in contrast to lakes with no upstream lakes or with no surface inflows. At the scale of the continental United States, conductivity was explained by drivers operating at larger spatial scales than for other water quality responses. The current regulatory practice of using regionalization schemes to guide water quality criteria could be improved by consideration of lake-specific characteristics, which were the most important predictors of water quality at the scale of the continental United States. The spatial extent and high quality of contextual data available for this analysis makes this work an unprecedented application of landscape limnology theory to water quality data. Further, the demonstrated importance of lake morphology over other controls on water quality is relevant to both aquatic scientists and managers.

Decoding the spatial signatures of multi-scale climate variability - a climate network perspective

NASA Astrophysics Data System (ADS)

Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

2017-12-01

During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results demonstrate the potential usefulness of systematically exploiting scale-specific climate networks, whose general patterns are in line with existing climatological knowledge, but provide vast opportunities for further quantifications at local, regional and global scales that are yet to be explored.

A spectral method for spatial downscaling | Science Inventory ...

EPA Pesticide Factsheets

Complex computer models play a crucial role in air quality research. These models are used to evaluate potential regulatory impacts of emission control strategies and to estimate air quality in areas without monitoring data. For both of these purposes, it is important to calibrate model output with monitoring data to adjust for model biases and improve spatial prediction. In this paper, we propose a new spectral method to study and exploit complex relationships between model output and monitoring data. Spectral methods allow us to estimate the relationship between model output and monitoring data separately at different spatial scales, and to use model output for prediction only at the appropriate scales. The proposed method is computationally efficient and can be implemented using standard software. We apply the method to compare Community Multiscale Air Quality (CMAQ) model output with ozone measurements in the United States in July, 2005. We find that CMAQ captures large-scale spatial trends, but has low correlation with the monitoring data at small spatial scales. The National Exposure Research Laboratory′s (NERL′s)Atmospheric Modeling Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing ch

Fine-scale spatial distribution of the common lugworm Arenicola marina, and effects of intertidal clam fishing

NASA Astrophysics Data System (ADS)

Boldina, Inna; Beninger, Peter G.

2014-04-01

Despite its ubiquity and its role as an ecosystem engineer on temperate intertidal mudflats, little is known of the spatial ecology of the lugworm Arenicola marina. We estimated lugworm densities and analyzed the spatial distribution of A. marina on a French Atlantic mudflat subjected to long-term clam digging activities, and compared these to a nearby pristine reference mudflat, using a combination of geostatistical techniques: point-pattern analysis, autocorrelation, and wavelet analysis. Lugworm densities were an order of magnitude greater at the reference site. Although A. marina showed an aggregative spatial distribution at both sites, the characteristics and intensity of aggregation differed markedly between sites. The reference site showed an inhibition process (regular distribution) at distances <7.5 cm, whereas the impacted site showed a random distribution at this scale. At distances from 15 cm to several tens of meters, the spatial distribution of A. marina was clearly aggregated at both sites; however, the autocorrelation strength was much weaker at the impacted site. In addition, the non-impacted site presented multi-scale spatial distribution, which was not evident at the impacted site. The differences observed between the spatial distributions of the fishing-impacted vs. the non-impacted site reflect similar findings for other components of these two mudflat ecosystems, suggesting common community-level responses to prolonged mechanical perturbation: a decrease in naturally-occurring aggregation. This change may have consequences for basic biological characteristics such as reproduction, recruitment, growth, and feeding.

Spatial, temporal and frequency based climate change assessment in Columbia River Basin using multi downscaled-scenarios

NASA Astrophysics Data System (ADS)

Rana, Arun; Moradkhani, Hamid

2016-07-01

Uncertainties in climate modelling are well documented in literature. Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional scale. In the present work, we have analyzed the changes in precipitation and temperature for future scenario period of 2070-2099 with respect to historical period of 1970-2000 from statistically downscaled GCM projections in Columbia River Basin (CRB). Analysis is performed using two different statistically downscaled climate projections (with ten GCMs downscaled products each, for RCP 4.5 and RCP 8.5, from CMIP5 dataset) namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, totaling to 40 different scenarios. The two datasets for BCSD and MACA are downscaled from observed data for both scenarios projections i.e. RCP4.5 and RCP8.5. Analysis is performed using spatial change (yearly scale), temporal change (monthly scale), percentile change (seasonal scale), quantile change (yearly scale), and wavelet analysis (yearly scale) in the future period from the historical period, respectively, at a scale of 1/16th of degree for entire CRB region. Results have indicated in varied degree of spatial change pattern for the entire Columbia River Basin, especially western part of the basin. At temporal scales, winter precipitation has higher variability than summer and vice versa for temperature. Most of the models have indicated considerate positive change in quantiles and percentiles for both precipitation and temperature. Wavelet analysis provided insights into possible explanation to changes in precipitation.

Effect of land use on the spatial variability of organic matter and nutrient status in an Oxisol

NASA Astrophysics Data System (ADS)

Paz-Ferreiro, Jorge; Alves, Marlene Cristina; Vidal Vázquez, Eva

2013-04-01

Heterogeneity is now considered as an inherent soil property. Spatial variability of soil attributes in natural landscapes results mainly from soil formation factors. In cultivated soils much heterogeneity can additionally occur as a result of land use, agricultural systems and management practices. Organic matter content (OMC) and nutrients associated to soil exchange complex are key attribute in the maintenance of a high quality soil. Neglecting spatial heterogeneity in soil OMC and nutrient status at the field scale might result in reduced yield and in environmental damage. We analyzed the impact of land use on the pattern of spatial variability of OMC and soil macronutrients at the stand scale. The study was conducted in São Paulo state, Brazil. Land uses were pasture, mango orchard and corn field. Soil samples were taken at 0-10 cm and 10-20 cm depth in 84 points, within 100 m x 100 m plots. Texture, pH, OMC, cation exchange capacity (CEC), exchangeable cations (Ca, Mg, K, H, Al) and resin extractable phosphorus were analyzed.. Statistical variability was found to be higher in parameters defining the soil nutrient status (resin extractable P, K, Ca and Mg) than in general soil properties (OMC, CEC, base saturation and pH). Geostatistical analysis showed contrasting patterns of spatial dependence for the different soil uses, sampling depths and studied properties. Most of the studied data sets collected at two different depths exhibited spatial dependence at the sampled scale and their semivariograms were modeled by a nugget effect plus a structure. The pattern of soil spatial variability was found to be different between the three study soil uses and at the two sampling depths, as far as model type, nugget effect or ranges of spatial dependence were concerned. Both statistical and geostatistical results pointed out the importance of OMC as a driver responsible for the spatial variability of soil nutrient status.

Dispersal and population structure at different spatial scales in the subterranean rodent Ctenomys australis

PubMed Central

2010-01-01

Background The population genetic structure of subterranean rodent species is strongly affected by demographic (e.g. rates of dispersal and social structure) and stochastic factors (e.g. random genetic drift among subpopulations and habitat fragmentation). In particular, gene flow estimates at different spatial scales are essential to understand genetic differentiation among populations of a species living in a highly fragmented landscape. Ctenomys australis (the sand dune tuco-tuco) is a territorial subterranean rodent that inhabits a relatively secure, permanently sealed burrow system, occurring in sand dune habitats on the coastal landscape in the south-east of Buenos Aires province, Argentina. Currently, this habitat is threatened by urban development and forestry and, therefore, the survival of this endemic species is at risk. Here, we assess population genetic structure and patterns of dispersal among individuals of this species at different spatial scales using 8 polymorphic microsatellite loci. Furthermore, we evaluate the relative importance of sex and habitat configuration in modulating the dispersal patterns at these geographical scales. Results Our results show that dispersal in C. australis is not restricted at regional spatial scales (~ 4 km). Assignment tests revealed significant population substructure within the study area, providing support for the presence of two subpopulations from three original sampling sites. Finally, male-biased dispersal was found in the Western side of our study area, but in the Eastern side no apparent philopatric pattern was found, suggesting that in a more continuous habitat males might move longer distances than females. Conclusions Overall, the assignment-based approaches were able to detect population substructure at fine geographical scales. Additionally, the maintenance of a significant genetic structure at regional (~ 4 km) and small (less than 1 km) spatial scales despite apparently moderate to high levels of gene flow between local sampling sites could not be explained simply by the linear distance among them. On the whole, our results support the hypothesis that males disperse more frequently than females; however they do not provide support for strict philopatry within females. PMID:20109219

A Study on the Effects of Spatial Scale on Snow Process in Hyper-Resolution Hydrological Modelling over Mountainous Areas

NASA Astrophysics Data System (ADS)

Garousi Nejad, I.; He, S.; Tang, Q.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Tarboton, D. G.; Ohara, N.; Lin, H.

2017-12-01

Spatial scale is one of the main considerations in hydrological modeling of snowmelt in mountainous areas. The size of model elements controls the degree to which variability can be explicitly represented versus what needs to be parameterized using effective properties such as averages or other subgrid variability parameterizations that may degrade the quality of model simulations. For snowmelt modeling terrain parameters such as slope, aspect, vegetation and elevation play an important role in the timing and quantity of snowmelt that serves as an input to hydrologic runoff generation processes. In general, higher resolution enhances the accuracy of the simulation since fine meshes represent and preserve the spatial variability of atmospheric and surface characteristics better than coarse resolution. However, this increases computational cost and there may be a scale beyond which the model response does not improve due to diminishing sensitivity to variability and irreducible uncertainty associated with the spatial interpolation of inputs. This paper examines the influence of spatial resolution on the snowmelt process using simulations of and data from the Animas River watershed, an alpine mountainous area in Colorado, USA, using an unstructured distributed physically based hydrological model developed for a parallel computing environment, ADHydro. Five spatial resolutions (30 m, 100 m, 250 m, 500 m, and 1 km) were used to investigate the variations in hydrologic response. This study demonstrated the importance of choosing the appropriate spatial scale in the implementation of ADHydro to obtain a balance between representing spatial variability and the computational cost. According to the results, variation in the input variables and parameters due to using different spatial resolution resulted in changes in the obtained hydrological variables, especially snowmelt, both at the basin-scale and distributed across the model mesh.

Scale-dependent effects of land cover on water physico-chemistry and diatom-based metrics in a major river system, the Adour-Garonne basin (South Western France).

PubMed

Tudesque, Loïc; Tisseuil, Clément; Lek, Sovan

2014-01-01

The scale dependence of ecological phenomena remains a central issue in ecology. Particularly in aquatic ecology, the consideration of the accurate spatial scale in assessing the effects of landscape factors on stream condition is critical. In this context, our study aimed at assessing the relationships between multi-spatial scale land cover patterns and a variety of water quality and diatom metrics measured at the stream reach level. This investigation was conducted in a major European river system, the Adour-Garonne river basin, characterized by a wide range of ecological conditions. Redundancy analysis (RDA) and variance partitioning techniques were used to disentangle the different relationships between land cover, water-chemistry and diatom metrics. Our results revealed a top-down "cascade effect" indirectly linking diatom metrics to land cover patterns through water physico-chemistry, which occurred at the largest spatial scales. In general, the strength of the relationships between land cover, physico-chemistry, and diatoms was shown to increase with the spatial scale, from the local to the basin scale, emphasizing the importance of continuous processes of accumulation throughout the river gradient. Unexpectedly, we established that the influence of land cover on the diatom metric was of primary importance both at the basin and local scale, as a result of discontinuous but not necessarily antagonist processes. The most detailed spatial grain of the Corine land cover classification appeared as the most relevant spatial grain to relate land cover to water chemistry and diatoms. Our findings provide suitable information to improve the implementation of effective diatom-based monitoring programs, especially within the scope of the European Water Framework Directive. © 2013 Elsevier B.V. All rights reserved.

Scaling field data to calibrate and validate moderate spatial resolution remote sensing models

USGS Publications Warehouse

Baccini, A.; Friedl, M.A.; Woodcock, C.E.; Zhu, Z.

2007-01-01

Validation and calibration are essential components of nearly all remote sensing-based studies. In both cases, ground measurements are collected and then related to the remote sensing observations or model results. In many situations, and particularly in studies that use moderate resolution remote sensing, a mismatch exists between the sensor's field of view and the scale at which in situ measurements are collected. The use of in situ measurements for model calibration and validation, therefore, requires a robust and defensible method to spatially aggregate ground measurements to the scale at which the remotely sensed data are acquired. This paper examines this challenge and specifically considers two different approaches for aggregating field measurements to match the spatial resolution of moderate spatial resolution remote sensing data: (a) landscape stratification; and (b) averaging of fine spatial resolution maps. The results show that an empirically estimated stratification based on a regression tree method provides a statistically defensible and operational basis for performing this type of procedure. 

Dryland soil microbial communities display spatial biogeographic patterns associated with soil depth and soil parent material

USGS Publications Warehouse

Steven, Blaire; Gallegos-Graves, La Verne; Belnap, Jayne; Kuske, Cheryl R.

2013-01-01

Biological soil crusts (biocrusts) are common to drylands worldwide. We employed replicated, spatially nested sampling and 16S rRNA gene sequencing to describe the soil microbial communities in three soils derived from different parent material (sandstone, shale, and gypsum). For each soil type, two depths (biocrusts, 0–1 cm; below-crust soils, 2–5 cm) and two horizontal spatial scales (15 cm and 5 m) were sampled. In all three soils, Cyanobacteria and Proteobacteria demonstrated significantly higher relative abundance in the biocrusts, while Chloroflexi and Archaea were significantly enriched in the below-crust soils. Biomass and diversity of the communities in biocrusts or below-crust soils did not differ with soil type. However, biocrusts on gypsum soil harbored significantly larger populations of Actinobacteria and Proteobacteria and lower populations of Cyanobacteria. Numerically dominant operational taxonomic units (OTU; 97% sequence identity) in the biocrusts were conserved across the soil types, whereas two dominant OTUs in the below-crust sand and shale soils were not identified in the gypsum soil. The uniformity with which small-scale vertical community differences are maintained across larger horizontal spatial scales and soil types is a feature of dryland ecosystems that should be considered when designing management plans and determining the response of biocrusts to environmental disturbances.

Changeable camouflage: how well can flounder resemble the colour and spatial scale of substrates in their natural habitats?

PubMed Central

Akkaynak, Derya; Siemann, Liese A.; Barbosa, Alexandra

2017-01-01

Flounder change colour and pattern for camouflage. We used a spectrometer to measure reflectance spectra and a digital camera to capture body patterns of two flounder species camouflaged on four natural backgrounds of different spatial scale (sand, small gravel, large gravel and rocks). We quantified the degree of spectral match between flounder and background relative to the situation of perfect camouflage in which flounder and background were assumed to have identical spectral distribution. Computations were carried out for three biologically relevant observers: monochromatic squid, dichromatic crab and trichromatic guitarfish. Our computations present a new approach to analysing datasets with multiple spectra that have large variance. Furthermore, to investigate the spatial match between flounder and background, images of flounder patterns were analysed using a custom program originally developed to study cuttlefish camouflage. Our results show that all flounder and background spectra fall within the same colour gamut and that, in terms of different observer visual systems, flounder matched most substrates in luminance and colour contrast. Flounder matched the spatial scales of all substrates except for rocks. We discuss findings in terms of flounder biology; furthermore, we discuss our methodology in light of hyperspectral technologies that combine high-resolution spectral and spatial imaging. PMID:28405370

Changeable camouflage: how well can flounder resemble the colour and spatial scale of substrates in their natural habitats?

PubMed

Akkaynak, Derya; Siemann, Liese A; Barbosa, Alexandra; Mäthger, Lydia M

2017-03-01

Flounder change colour and pattern for camouflage. We used a spectrometer to measure reflectance spectra and a digital camera to capture body patterns of two flounder species camouflaged on four natural backgrounds of different spatial scale (sand, small gravel, large gravel and rocks). We quantified the degree of spectral match between flounder and background relative to the situation of perfect camouflage in which flounder and background were assumed to have identical spectral distribution. Computations were carried out for three biologically relevant observers: monochromatic squid, dichromatic crab and trichromatic guitarfish. Our computations present a new approach to analysing datasets with multiple spectra that have large variance. Furthermore, to investigate the spatial match between flounder and background, images of flounder patterns were analysed using a custom program originally developed to study cuttlefish camouflage. Our results show that all flounder and background spectra fall within the same colour gamut and that, in terms of different observer visual systems, flounder matched most substrates in luminance and colour contrast. Flounder matched the spatial scales of all substrates except for rocks. We discuss findings in terms of flounder biology; furthermore, we discuss our methodology in light of hyperspectral technologies that combine high-resolution spectral and spatial imaging.

Spatial and temporal variability of hyperspectral signatures of terrain

NASA Astrophysics Data System (ADS)

Jones, K. F.; Perovich, D. K.; Koenig, G. G.

2008-04-01

Electromagnetic signatures of terrain exhibit significant spatial heterogeneity on a range of scales as well as considerable temporal variability. A statistical characterization of the spatial heterogeneity and spatial scaling algorithms of terrain electromagnetic signatures are required to extrapolate measurements to larger scales. Basic terrain elements including bare soil, grass, deciduous, and coniferous trees were studied in a quasi-laboratory setting using instrumented test sites in Hanover, NH and Yuma, AZ. Observations were made using a visible and near infrared spectroradiometer (350 - 2500 nm) and hyperspectral camera (400 - 1100 nm). Results are reported illustrating: i) several difference scenes; ii) a terrain scene time series sampled over an annual cycle; and iii) the detection of artifacts in scenes. A principal component analysis indicated that the first three principal components typically explained between 90 and 99% of the variance of the 30 to 40-channel hyperspectral images. Higher order principal components of hyperspectral images are useful for detecting artifacts in scenes.

Scaling biodiversity responses to hydrological regimes.

PubMed

Rolls, Robert J; Heino, Jani; Ryder, Darren S; Chessman, Bruce C; Growns, Ivor O; Thompson, Ross M; Gido, Keith B

2018-05-01

Of all ecosystems, freshwaters support the most dynamic and highly concentrated biodiversity on Earth. These attributes of freshwater biodiversity along with increasing demand for water mean that these systems serve as significant models to understand drivers of global biodiversity change. Freshwater biodiversity changes are often attributed to hydrological alteration by water-resource development and climate change owing to the role of the hydrological regime of rivers, wetlands and floodplains affecting patterns of biodiversity. However, a major gap remains in conceptualising how the hydrological regime determines patterns in biodiversity's multiple spatial components and facets (taxonomic, functional and phylogenetic). We synthesised primary evidence of freshwater biodiversity responses to natural hydrological regimes to determine how distinct ecohydrological mechanisms affect freshwater biodiversity at local, landscape and regional spatial scales. Hydrological connectivity influences local and landscape biodiversity, yet responses vary depending on spatial scale. Biodiversity at local scales is generally positively associated with increasing connectivity whereas landscape-scale biodiversity is greater with increasing fragmentation among locations. The effects of hydrological disturbance on freshwater biodiversity are variable at separate spatial scales and depend on disturbance frequency and history and organism characteristics. The role of hydrology in determining habitat for freshwater biodiversity also depends on spatial scaling. At local scales, persistence, stability and size of habitat each contribute to patterns of freshwater biodiversity yet the responses are variable across the organism groups that constitute overall freshwater biodiversity. We present a conceptual model to unite the effects of different ecohydrological mechanisms on freshwater biodiversity across spatial scales, and develop four principles for applying a multi-scaled understanding of freshwater biodiversity responses to hydrological regimes. The protection and restoration of freshwater biodiversity is both a fundamental justification and a central goal of environmental water allocation worldwide. Clearer integration of concepts of spatial scaling in the context of understanding impacts of hydrological regimes on biodiversity will increase uptake of evidence into environmental flow implementation, identify suitable biodiversity targets responsive to hydrological change or restoration, and identify and manage risks of environmental flows contributing to biodiversity decline. © 2017 Cambridge Philosophical Society.

Asynchrony in the inter-annual recruitment of lake whitefish Coregonus clupeaformis in the Great Lakes region

USGS Publications Warehouse

Zischke, Mitchell T.; Bunnell, David B.; Troy, Cary D.; Berglund, Eric K.; Caroffino, David C.; Ebener, Mark P.; He, Ji X.; Sitar, Shawn P.; Hook, Tomas O.

2017-01-01

Spatially separated fish populations may display synchrony in annual recruitment if the factors that drive recruitment success, particularly abiotic factors such as temperature, are synchronised across broad spatial scales. We examined inter-annual variation in recruitment among lake whitefish (Coregonus clupeaformis) populations in lakes Huron, Michigan and Superior using fishery-dependent and -independent data from 1971 to 2014. Relative year-class strength (RYCS) was calculated from catch-curve residuals for each year class across multiple sampling years. Pairwise comparison of RYCS among datasets revealed no significant associations either within or between lakes, suggesting that recruitment of lake whitefish is spatially asynchronous. There was no consistent correlation between pairwise agreement and the distance between datasets, and models to estimate the spatial scale of recruitment synchrony did not fit well to these data. This suggests that inter-annual recruitment variation of lake whitefish is asynchronous across broad spatial scales in the Great Lakes. While our method primarily evaluated year-to-year recruitment variation, it is plausible that recruitment of lake whitefish varies at coarser temporal scales (e.g. decadal). Nonetheless, our findings differ from research on some other Coregonus species and suggest that local biotic or density-dependent factors may contribute strongly to lake whitefish recruitment rather than inter-annual variability in broad-scale abiotic factors.

The functional organization of human epileptic hippocampus

PubMed Central

Klimes, Petr; Duque, Juliano J.; Brinkmann, Ben; Van Gompel, Jamie; Stead, Matt; St. Louis, Erik K.; Halamek, Josef; Jurak, Pavel

2016-01-01

The function and connectivity of human brain is disrupted in epilepsy. We previously reported that the region of epileptic brain generating focal seizures, i.e., the seizure onset zone (SOZ), is functionally isolated from surrounding brain regions in focal neocortical epilepsy. The modulatory effect of behavioral state on the spatial and spectral scales over which the reduced functional connectivity occurs, however, is unclear. Here we use simultaneous sleep staging from scalp EEG with intracranial EEG recordings from medial temporal lobe to investigate how behavioral state modulates the spatial and spectral scales of local field potential synchrony in focal epileptic hippocampus. The local field spectral power and linear correlation between adjacent electrodes provide measures of neuronal population synchrony at different spatial scales, ∼1 and 10 mm, respectively. Our results show increased connectivity inside the SOZ and low connectivity between electrodes in SOZ and outside the SOZ. During slow-wave sleep, we observed decreased connectivity for ripple and fast ripple frequency bands within the SOZ at the 10 mm spatial scale, while the local synchrony remained high at the 1 mm spatial scale. Further study of these phenomena may prove useful for SOZ localization and help understand seizure generation, and the functional deficits seen in epileptic eloquent cortex. PMID:27030735

Toward seamless hydrologic predictions across spatial scales

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin H.; Warrach-Sagi, Kirsten; Attinger, Sabine

2017-09-01

Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

Effects of biotic and abiotic factors on resistance versus resilience of Douglas fir to drought.

PubMed

Carnwath, Gunnar; Nelson, Cara

2017-01-01

Significant increases in tree mortality due to drought-induced physiological stress have been documented worldwide. This trend is likely to continue with increased frequency and severity of extreme drought events in the future. Therefore, understanding the factors that influence variability in drought responses among trees will be critical to predicting ecosystem responses to climate change and developing effective management actions. In this study, we used hierarchical mixed-effects models to analyze drought responses of Pseudotsuga menziesii in 20 unmanaged forests stands across a broad range of environmental conditions in northeastern Washington, USA. We aimed to 1) identify the biotic and abiotic attributes most closely associated with the responses of individual trees to drought and 2) quantify the variability in drought responses at different spatial scales. We found that growth rates and competition for resources significantly affected resistance to a severe drought event in 2001: slow-growing trees and trees growing in subordinate canopy positions and/or with more neighbors suffered greater declines in radial growth during the drought event. In contrast, the ability of a tree to return to normal growth when climatic conditions improved (resilience) was unaffected by competition or relative growth rates. Drought responses were significantly influenced by tree age: older trees were more resistant but less resilient than younger trees. Finally, we found differences between resistance and resilience in spatial scale: a significant proportion (approximately 50%) of the variability in drought resistance across the study area was at broad spatial scales (i.e. among different forest types), most likely due to differences in the total amount of precipitation received at different elevations; in contrast, variation in resilience was overwhelmingly (82%) at the level of individual trees within stands and there was no difference in drought resilience among forest types. Our results suggest that for Pseudotsuga menziesii resistance and resilience to drought are driven by different factors and vary at different spatial scales.

Effects of biotic and abiotic factors on resistance versus resilience of Douglas fir to drought

PubMed Central

Nelson, Cara

2017-01-01

Significant increases in tree mortality due to drought-induced physiological stress have been documented worldwide. This trend is likely to continue with increased frequency and severity of extreme drought events in the future. Therefore, understanding the factors that influence variability in drought responses among trees will be critical to predicting ecosystem responses to climate change and developing effective management actions. In this study, we used hierarchical mixed-effects models to analyze drought responses of Pseudotsuga menziesii in 20 unmanaged forests stands across a broad range of environmental conditions in northeastern Washington, USA. We aimed to 1) identify the biotic and abiotic attributes most closely associated with the responses of individual trees to drought and 2) quantify the variability in drought responses at different spatial scales. We found that growth rates and competition for resources significantly affected resistance to a severe drought event in 2001: slow-growing trees and trees growing in subordinate canopy positions and/or with more neighbors suffered greater declines in radial growth during the drought event. In contrast, the ability of a tree to return to normal growth when climatic conditions improved (resilience) was unaffected by competition or relative growth rates. Drought responses were significantly influenced by tree age: older trees were more resistant but less resilient than younger trees. Finally, we found differences between resistance and resilience in spatial scale: a significant proportion (approximately 50%) of the variability in drought resistance across the study area was at broad spatial scales (i.e. among different forest types), most likely due to differences in the total amount of precipitation received at different elevations; in contrast, variation in resilience was overwhelmingly (82%) at the level of individual trees within stands and there was no difference in drought resilience among forest types. Our results suggest that for Pseudotsuga menziesii resistance and resilience to drought are driven by different factors and vary at different spatial scales. PMID:28973008

On the Reliability of Individual Brain Activity Networks.

PubMed

Cassidy, Ben; Bowman, F DuBois; Rae, Caroline; Solo, Victor

2018-02-01

There is intense interest in fMRI research on whole-brain functional connectivity, and however, two fundamental issues are still unresolved: the impact of spatiotemporal data resolution (spatial parcellation and temporal sampling) and the impact of the network construction method on the reliability of functional brain networks. In particular, the impact of spatiotemporal data resolution on the resulting connectivity findings has not been sufficiently investigated. In fact, a number of studies have already observed that functional networks often give different conclusions across different parcellation scales. If the interpretations from functional networks are inconsistent across spatiotemporal scales, then the whole validity of the functional network paradigm is called into question. This paper investigates the consistency of resting state network structure when using different temporal sampling or spatial parcellation, or different methods for constructing the networks. To pursue this, we develop a novel network comparison framework based on persistent homology from a topological data analysis. We use the new network comparison tools to characterize the spatial and temporal scales under which consistent functional networks can be constructed. The methods are illustrated on Human Connectome Project data, showing that the DISCOH 2 network construction method outperforms other approaches at most data spatiotemporal resolutions.

General Relationships between Abiotic Soil Properties and Soil Biota across Spatial Scales and Different Land-Use Types

PubMed Central

Birkhofer, Klaus; Schöning, Ingo; Alt, Fabian; Herold, Nadine; Klarner, Bernhard; Maraun, Mark; Marhan, Sven; Oelmann, Yvonne; Wubet, Tesfaye; Yurkov, Andrey; Begerow, Dominik; Berner, Doreen; Buscot, François; Daniel, Rolf; Diekötter, Tim; Ehnes, Roswitha B.; Erdmann, Georgia; Fischer, Christiane; Foesel, Bärbel; Groh, Janine; Gutknecht, Jessica; Kandeler, Ellen; Lang, Christa; Lohaus, Gertrud; Meyer, Annabel; Nacke, Heiko; Näther, Astrid; Overmann, Jörg; Polle, Andrea; Pollierer, Melanie M.; Scheu, Stefan; Schloter, Michael; Schulze, Ernst-Detlef; Schulze, Waltraud; Weinert, Jan; Weisser, Wolfgang W.; Wolters, Volkmar; Schrumpf, Marion

2012-01-01

Very few principles have been unraveled that explain the relationship between soil properties and soil biota across large spatial scales and different land-use types. Here, we seek these general relationships using data from 52 differently managed grassland and forest soils in three study regions spanning a latitudinal gradient in Germany. We hypothesize that, after extraction of variation that is explained by location and land-use type, soil properties still explain significant proportions of variation in the abundance and diversity of soil biota. If the relationships between predictors and soil organisms were analyzed individually for each predictor group, soil properties explained the highest amount of variation in soil biota abundance and diversity, followed by land-use type and sampling location. After extraction of variation that originated from location or land-use, abiotic soil properties explained significant amounts of variation in fungal, meso- and macrofauna, but not in yeast or bacterial biomass or diversity. Nitrate or nitrogen concentration and fungal biomass were positively related, but nitrate concentration was negatively related to the abundances of Collembola and mites and to the myriapod species richness across a range of forest and grassland soils. The species richness of earthworms was positively correlated with clay content of soils independent of sample location and land-use type. Our study indicates that after accounting for heterogeneity resulting from large scale differences among sampling locations and land-use types, soil properties still explain significant proportions of variation in fungal and soil fauna abundance or diversity. However, soil biota was also related to processes that act at larger spatial scales and bacteria or soil yeasts only showed weak relationships to soil properties. We therefore argue that more general relationships between soil properties and soil biota can only be derived from future studies that consider larger spatial scales and different land-use types. PMID:22937029

Income Inequality across Micro and Meso Geographic Scales in the Midwestern United States, 1979-2009

ERIC Educational Resources Information Center

Peters, David J.

2012-01-01

This article examines the spatial distribution of income inequality and the socioeconomic factors affecting it using spatial analysis techniques across 16,285 block groups, 5,050 tracts, and 618 counties in the western part of the North Central Region of the United States. Different geographic aggregations result in different inequality outcomes,…

The significance of spatial variability of rainfall on streamflow: A synthetic analysis at the Upper Lee catchment, UK

NASA Astrophysics Data System (ADS)

Pechlivanidis, Ilias; McIntyre, Neil; Wheater, Howard

2017-04-01

Rainfall, one of the main inputs in hydrological modeling, is a highly heterogeneous process over a wide range of scales in space, and hence the ignorance of the spatial rainfall information could affect the simulated streamflow. Calibration of hydrological model parameters is rarely a straightforward task due to parameter equifinality and parameters' 'nature' to compensate for other uncertainties, i.e. structural and forcing input. In here, we analyse the significance of spatial variability of rainfall on streamflow as a function of catchment scale and type, and antecedent conditions using the continuous time, semi-distributed PDM hydrological model at the Upper Lee catchment, UK. The impact of catchment scale and type is assessed using 11 nested catchments ranging in scale from 25 to 1040 km2, and further assessed by artificially changing the catchment characteristics and translating these to model parameters with uncertainty using model regionalisation. Synthetic rainfall events are introduced to directly relate the change in simulated streamflow to the spatial variability of rainfall. Overall, we conclude that the antecedent catchment wetness and catchment type play an important role in controlling the significance of the spatial distribution of rainfall on streamflow. Results show a relationship between hydrograph characteristics (streamflow peak and volume) and the degree of spatial variability of rainfall for the impermeable catchments under dry antecedent conditions, although this decreases at larger scales; however this sensitivity is significantly undermined under wet antecedent conditions. Although there is indication that the impact of spatial rainfall on streamflow varies as a function of catchment scale, the variability of antecedent conditions between the synthetic catchments seems to mask this significance. Finally, hydrograph responses to different spatial patterns in rainfall depend on assumptions used for model parameter estimation and also the spatial variation in parameters indicating the need of an uncertainty framework in such investigation.

Measurement of nanoscale three-dimensional diffusion in the interior of living cells by STED-FCS.

PubMed

Lanzanò, Luca; Scipioni, Lorenzo; Di Bona, Melody; Bianchini, Paolo; Bizzarri, Ranieri; Cardarelli, Francesco; Diaspro, Alberto; Vicidomini, Giuseppe

2017-07-06

The observation of molecular diffusion at different spatial scales, and in particular below the optical diffraction limit (<200 nm), can reveal details of the subcellular topology and its functional organization. Stimulated-emission depletion microscopy (STED) has been previously combined with fluorescence correlation spectroscopy (FCS) to investigate nanoscale diffusion (STED-FCS). However, stimulated-emission depletion fluorescence correlation spectroscopy has only been used successfully to reveal functional organization in two-dimensional space, such as the plasma membrane, while, an efficient implementation for measurements in three-dimensional space, such as the cellular interior, is still lacking. Here we integrate the STED-FCS method with two analytical approaches, the recent separation of photons by lifetime tuning and the fluorescence lifetime correlation spectroscopy, to simultaneously probe diffusion in three dimensions at different sub-diffraction scales. We demonstrate that this method efficiently provides measurement of the diffusion of EGFP at spatial scales tunable from the diffraction size down to ∼80 nm in the cytoplasm of living cells.The measurement of molecular diffusion at sub-diffraction scales has been achieved in 2D space using STED-FCS, but an implementation for 3D diffusion is lacking. Here the authors present an analytical approach to probe diffusion in 3D space using STED-FCS and measure the diffusion of EGFP at different spatial scales.

Spatial variability of soil salinity in coastal saline soil at different scales in the Yellow River Delta, China.

PubMed

Wang, Zhuoran; Zhao, Gengxing; Gao, Mingxiu; Chang, Chunyan

2017-02-01

The objectives of this study were to explore the spatial variability of soil salinity in coastal saline soil at macro, meso and micro scales in the Yellow River delta, China. Soil electrical conductivities (ECs) were measured at 0-15, 15-30, 30-45 and 45-60 cm soil depths at 49 sampling sites during November 9 to 11, 2013. Soil salinity was converted from soil ECs based on laboratory analyses. Our results indicated that at the macro scale, soil salinity was high with strong variability in each soil layer, and the content increased and the variability weakened with increasing soil depth. From east to west in the region, the farther away from the sea, the lower the soil salinity was. The degrees of soil salinization in three deeper soil layers are 1.14, 1.24 and 1.40 times higher than that in the surface soil. At the meso scale, the sequence of soil salinity in different topographies, soil texture and vegetation decreased, respectively, as follows: depression >flatland >hillock >batture; sandy loam >light loam >medium loam >heavy loam >clay; bare land >suaeda salsa >reed >cogongrass >cotton >paddy >winter wheat. At the micro scale, soil salinity changed with elevation in natural micro-topography and with anthropogenic activities in cultivated land. As the study area narrowed down to different scales, the spatial variability of soil salinity weakened gradually in cultivated land and salt wasteland except the bare land.

Scale-free networks of the earth’s surface

NASA Astrophysics Data System (ADS)

Liu, Gang; He, Jing; Luo, Kaitian; Gao, Peichao; Ma, Lei

2016-06-01

Studying the structure of real complex systems is of paramount importance in science and engineering. Despite our understanding of lots of real systems, we hardly cognize our unique living environment — the earth. The structural complexity of the earth’s surface is, however, still unknown in detail. Here, we define the modeling of graph topology for the earth’s surface, using the satellite images of the earth’s surface under different spatial resolutions derived from Google Earth. We find that the graph topologies of the earth’s surface are scale-free networks regardless of the spatial resolutions. For different spatial resolutions, the exponents of power-law distributions and the modularity are both quite different; however, the average clustering coefficient is approximately equal to a constant. We explore the morphology study of the earth’s surface, which enables a comprehensive understanding of the morphological feature of the earth’s surface.

[Spatial distribution pattern and fractal analysis of Larix chinensis populations in Qinling Mountain].

PubMed

Guo, Hua; Wang, Xiaoan; Xiao, Yaping

2005-02-01

In this paper, the fractal characters of Larix chinensis populations in Qinling Mountain were studied by contiguous grid quadrate sampling method and by boxing-counting dimension and information dimension. The results showed that the high boxing-counting dimension (1.8087) and information dimension (1.7931) reflected a higher spatial occupational degree of L. chinensis populations. Judged by the dispersal index and Morisita's pattern index, L. chinensis populations clumped at three different age stages (0-25, 25-50 and over 50 years). From Greig-Smiths' mean variance analysis, the figure of pattern scale showed that L. chinensis populations clumped in 128 m2 and 512 m2, and the different age groups clumped in different scales. The pattern intensities decreased with increasing age, and tended to reduce with increasing area when detected by Kershaw's PI index. The spatial pattern characters of L. chinensis populations may be their responses to environmental factors.

Geographic distance and ecosystem size determine the distribution of smallest protists in lacustrine ecosystems.

PubMed

Lepère, Cécile; Domaizon, Isabelle; Taïb, Najwa; Mangot, Jean-François; Bronner, Gisèle; Boucher, Delphine; Debroas, Didier

2013-07-01

Understanding the spatial distribution of aquatic microbial diversity and the underlying mechanisms causing differences in community composition is a challenging and central goal for ecologists. Recent insights into protistan diversity and ecology are increasing the debate over their spatial distribution. In this study, we investigate the importance of spatial and environmental factors in shaping the small protists community structure in lakes. We analyzed small protists community composition (beta-diversity) and richness (alpha-diversity) at regional scale by different molecular methods targeting the gene coding for 18S rRNA gene (T-RFLP and 454 pyrosequencing). Our results show a distance-decay pattern for rare and dominant taxa and the spatial distribution of the latter followed the prediction of the island biogeography theory. Furthermore, geographic distances between lakes seem to be the main force shaping the protists community composition in the lakes studied here. Finally, the spatial distribution of protists was discussed at the global scale (11 worldwide distributed lakes) by comparing these results with those present in the public database. UniFrac analysis showed 18S rRNA gene OTUs compositions significantly different among most of lakes, and this difference does not seem to be related to the trophic status. © 2013 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

Modern Climate Analogues of Late-Quaternary Paleoclimates for the Western United States.

NASA Astrophysics Data System (ADS)

Mock, Cary Jeffrey

This study examined spatial variations of modern and late-Quaternary climates for the western United States. Synoptic climatological analyses of the modern record identified the predominate climatic controls that normally produce the principal modes of spatial climatic variability. They also provided a modern standard to assess past climates. Maps of the month-to-month changes in 500 mb heights, sea-level pressure, temperature, and precipitation illustrated how different climatic controls govern the annual cycle of climatic response. The patterns of precipitation ratios, precipitation bar graphs, and the seasonal precipitation maximum provided additional insight into how different climatic controls influence spatial climatic variations. Synoptic-scale patterns from general circulation model (GCM) simulations or from analyses of climatic indices were used as the basis for finding modern climate analogues for 18 ka and 9 ka. Composite anomaly maps of atmospheric circulation, precipitation, and temperature were compared with effective moisture maps compiled from proxy data to infer how the patterns, which were evident from the proxy data, were generated. The analyses of the modern synoptic climatology indicate that smaller-scale climatic controls must be considered along with larger-scale ones in order to explain patterns of spatial climate heterogeneity. Climatic extremes indicate that changes in the spatial patterns of precipitation seasonality are the exception rather than the rule, reflecting the strong influence of smaller-scale controls. Modern climate analogues for both 18 ka and 9 ka clearly depict the dry Northwest/wet Southwest contrast that is suggested by GCM simulations and paleoclimatic evidence. 18 ka analogues also show the importance of smaller-scale climatic controls in explaining spatial climatic variation in the Northwest and northern Great Plains. 9 ka analogues provide climatological explanations for patterns of spatial heterogeneity over several mountainous areas as suggested by paleoclimatic evidence. Modern analogues of past climates supplement modeling approaches by providing information below the resolution of model simulations. Analogues can be used to examine the controls of spatial paleoclimatic variation if sufficient instrumental data and paleoclimatic evidence are available, and if one carefully exercises uniformitarianism when extrapolating modern relationships to the past.

HIS Design: Big Data that Supports Hydrologic Modeling from Continental to Hillslope Scales

NASA Astrophysics Data System (ADS)

Rasmussen, T. C.; Deemy, J. B.; Younger, S. E.; Kirk, S. E.; Brockman, L. E.

2016-12-01

Analogous to Google Maps, hydrologic data, information, and knowledge resolve differently depending upon the spatial and temporal scales of interest. We show how a multi-scale hydrologic information system (HIS) can be designed and populated for a broad range of spatial (e.g., hillslope, local, regional, continental) and temporal (e.g., current, recent, historic, geologic) scales. Surface and subsurface hydrologic and transport processes are assumed to be scale-dependent, requiring unique governing equations and parameters at each scale. This robust and flexible framework is designed to meet the inventory, monitoring, and management needs of multiple federal agencies (i.e., Forest Service, National Park Service, Fish and Wildlife Service, National Wildlife Reserves). Multi-scale HIS examples are provided using Geographic Information Systems (GIS) for the Southeastern US.

The mosaic structure of plasma bulk flows in the Earth's magnetotail

NASA Technical Reports Server (NTRS)

Ashour-Abdalla, M.; Richard, R. L.; Zelenyi, L. M.; Peroomian, V.; Bosqued, J. M.

1995-01-01

Moments of plasma distributions observed in the magnetotail vary with different time scales. In this paper we attempt to explain the observed variability on intermediate timescales of approximately 10-20 min that result from the simultaneous energization and spatial structuring of solar wind plasma in the distant magnetotail. These processes stimulate the formation of a system of spatially disjointed. highly accelerated filaments (beamlets) in the tail. We use the results from large-scale kinetic modeling of magnetotail formation from a plasma mantle source to calculate moments of ion distribution functions throughout the tail. Statistical restrictions related to the limited number of particles in our system naturally reduce the spatial resolution of our results, but we show that our model is valid on intermediate spatial scales Delta(x) x Delta(z) equal to approximately 1 R(sub E) x 1000 km. For these spatial scales the resulting pattern, which resembles a mosaic, appears to be quite variable. The complexity of the pattern is related to the spatial interference between beamlets accelerated at various locations within the distant tail which mirror in the strong near-Earth magnetic field. Global motion of the magnetotail results in the displacement of spacecraft with respect to this mosaic pattern and can produce variations in all of the moments (especially the x-component of the bulk velocity) on intermediate timescales. The results obtained enable us to view the magnetotail plasma as consisting of two different populations: a tailward-Earthward system of highly accelerated beamlets interfering with each other, and an energized quasithermal population which gradually builds as the Earth is approached. In the near-Earth tail, these populations merge into a hot quasi-isotropic ion population typical of the near-Earth plasma sheet. The transformation of plasma sheet boundary layer (PSBL) beam energy into central plasma sheet (CPS) quasi-thermal energy occurs in the absence of collisions or noise. This paper also clarifies the relationship between the global scale where an MHD description might be appropriate and the lower intermediate scales where MHD fails and large-scale kinetic theory should be used.

Estimating prevalence of coronary heart disease for small areas using collateral indicators of morbidity.

PubMed

Congdon, Peter

2010-01-01

Different indicators of morbidity for chronic disease may not necessarily be available at a disaggregated spatial scale (e.g., for small areas with populations under 10 thousand). Instead certain indicators may only be available at a more highly aggregated spatial scale; for example, deaths may be recorded for small areas, but disease prevalence only at a considerably higher spatial scale. Nevertheless prevalence estimates at small area level are important for assessing health need. An instance is provided by England where deaths and hospital admissions for coronary heart disease are available for small areas known as wards, but prevalence is only available for relatively large health authority areas. To estimate CHD prevalence at small area level in such a situation, a shared random effect method is proposed that pools information regarding spatial morbidity contrasts over different indicators (deaths, hospitalizations, prevalence). The shared random effect approach also incorporates differences between small areas in known risk factors (e.g., income, ethnic structure). A Poisson-multinomial equivalence may be used to ensure small area prevalence estimates sum to the known higher area total. An illustration is provided by data for London using hospital admissions and CHD deaths at ward level, together with CHD prevalence totals for considerably larger local health authority areas. The shared random effect involved a spatially correlated common factor, that accounts for clustering in latent risk factors, and also provides a summary measure of small area CHD morbidity.

Estimating Prevalence of Coronary Heart Disease for Small Areas Using Collateral Indicators of Morbidity

PubMed Central

Congdon, Peter

2010-01-01

Different indicators of morbidity for chronic disease may not necessarily be available at a disaggregated spatial scale (e.g., for small areas with populations under 10 thousand). Instead certain indicators may only be available at a more highly aggregated spatial scale; for example, deaths may be recorded for small areas, but disease prevalence only at a considerably higher spatial scale. Nevertheless prevalence estimates at small area level are important for assessing health need. An instance is provided by England where deaths and hospital admissions for coronary heart disease are available for small areas known as wards, but prevalence is only available for relatively large health authority areas. To estimate CHD prevalence at small area level in such a situation, a shared random effect method is proposed that pools information regarding spatial morbidity contrasts over different indicators (deaths, hospitalizations, prevalence). The shared random effect approach also incorporates differences between small areas in known risk factors (e.g., income, ethnic structure). A Poisson-multinomial equivalence may be used to ensure small area prevalence estimates sum to the known higher area total. An illustration is provided by data for London using hospital admissions and CHD deaths at ward level, together with CHD prevalence totals for considerably larger local health authority areas. The shared random effect involved a spatially correlated common factor, that accounts for clustering in latent risk factors, and also provides a summary measure of small area CHD morbidity. PMID:20195439

Fine-Scale Analysis Reveals Cryptic Landscape Genetic Structure in Desert Tortoises

PubMed Central

Latch, Emily K.; Boarman, William I.; Walde, Andrew; Fleischer, Robert C.

2011-01-01

Characterizing the effects of landscape features on genetic variation is essential for understanding how landscapes shape patterns of gene flow and spatial genetic structure of populations. Most landscape genetics studies have focused on patterns of gene flow at a regional scale. However, the genetic structure of populations at a local scale may be influenced by a unique suite of landscape variables that have little bearing on connectivity patterns observed at broader spatial scales. We investigated fine-scale spatial patterns of genetic variation and gene flow in relation to features of the landscape in desert tortoise (Gopherus agassizii), using 859 tortoises genotyped at 16 microsatellite loci with associated data on geographic location, sex, elevation, slope, and soil type, and spatial relationship to putative barriers (power lines, roads). We used spatially explicit and non-explicit Bayesian clustering algorithms to partition the sample into discrete clusters, and characterize the relationships between genetic distance and ecological variables to identify factors with the greatest influence on gene flow at a local scale. Desert tortoises exhibit weak genetic structure at a local scale, and we identified two subpopulations across the study area. Although genetic differentiation between the subpopulations was low, our landscape genetic analysis identified both natural (slope) and anthropogenic (roads) landscape variables that have significantly influenced gene flow within this local population. We show that desert tortoise movements at a local scale are influenced by features of the landscape, and that these features are different than those that influence gene flow at larger scales. Our findings are important for desert tortoise conservation and management, particularly in light of recent translocation efforts in the region. More generally, our results indicate that recent landscape changes can affect gene flow at a local scale and that their effects can be detected almost immediately. PMID:22132143

Fine-scale analysis reveals cryptic landscape genetic structure in desert tortoises.

PubMed

Latch, Emily K; Boarman, William I; Walde, Andrew; Fleischer, Robert C

2011-01-01

Characterizing the effects of landscape features on genetic variation is essential for understanding how landscapes shape patterns of gene flow and spatial genetic structure of populations. Most landscape genetics studies have focused on patterns of gene flow at a regional scale. However, the genetic structure of populations at a local scale may be influenced by a unique suite of landscape variables that have little bearing on connectivity patterns observed at broader spatial scales. We investigated fine-scale spatial patterns of genetic variation and gene flow in relation to features of the landscape in desert tortoise (Gopherus agassizii), using 859 tortoises genotyped at 16 microsatellite loci with associated data on geographic location, sex, elevation, slope, and soil type, and spatial relationship to putative barriers (power lines, roads). We used spatially explicit and non-explicit Bayesian clustering algorithms to partition the sample into discrete clusters, and characterize the relationships between genetic distance and ecological variables to identify factors with the greatest influence on gene flow at a local scale. Desert tortoises exhibit weak genetic structure at a local scale, and we identified two subpopulations across the study area. Although genetic differentiation between the subpopulations was low, our landscape genetic analysis identified both natural (slope) and anthropogenic (roads) landscape variables that have significantly influenced gene flow within this local population. We show that desert tortoise movements at a local scale are influenced by features of the landscape, and that these features are different than those that influence gene flow at larger scales. Our findings are important for desert tortoise conservation and management, particularly in light of recent translocation efforts in the region. More generally, our results indicate that recent landscape changes can affect gene flow at a local scale and that their effects can be detected almost immediately.

Future of applied watershed science at regional scales

Treesearch

Lee Benda; Daniel Miller; Steve Lanigan; Gordon Reeves

2009-01-01

Resource managers must deal increasingly with land use and conservation plans applied at large spatial scales (watersheds, landscapes, states, regions) involving multiple interacting federal agencies and stakeholders. Access to a geographically focused and application-oriented database would allow users in different locations and with different concerns to quickly...

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds

PubMed Central

Vaughn, Nicholas R.; Asner, Gregory P.; Smit, Izak P. J.; Riddel, Edward S.

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50–450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques. PMID:26660502

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds.

PubMed

Vaughn, Nicholas R; Asner, Gregory P; Smit, Izak P J; Riddel, Edward S

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50-450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques.

Western white pine development in relation to biophysical characteristics across different spatial scales in the Coeur d'Alene River basin in northern Idaho, U.S.A

Treesearch

Theresa B. Jain; Russell T. Graham; Penelope Morgan

2002-01-01

Many studies have assessed tree development beneath canopies in forest ecosystems, but results are seldom placed within the context of broad-scale biophysical factors. Mapped landscape characteristics for three watersheds, located within the Coeur d’Alene River basin in northern Idaho, were integrated to create a spatial hierarchy reflecting biophysical factors that...

Detecting changes in the spatial distribution of nitrate contamination in ground water

USGS Publications Warehouse

Liu, Z.-J.; Hallberg, G.R.; Zimmerman, D.L.; Libra, R.D.

1997-01-01

Many studies of ground water pollution in general and nitrate contamination in particular have often relied on a one-time investigation, tracking of individual wells, or aggregate summaries. Studies of changes in spatial distribution of contaminants over time are lacking. This paper presents a method to compare spatial distributions for possible changes over time. The large-scale spatial distribution at a given time can be considered as a surface over the area (a trend surface). The changes in spatial distribution from period to period can be revealed by the differences in the shape and/or height of surfaces. If such a surface is described by a polynomial function, changes in surfaces can be detected by testing statistically for differences in their corresponding polynomial functions. This method was applied to nitrate concentration in a population of wells in an agricultural drainage basin in Iowa, sampled in three different years. For the period of 1981-1992, the large-scale spatial distribution of nitrate concentration did not show significant change in the shape of spatial surfaces; while the magnitude of nitrate concentration in the basin, or height of the computed surfaces showed significant fluctuations. The change in magnitude of nitrate concentration is closely related to climatic variations, especially in precipitation. The lack of change in the shape of spatial surfaces means that either the influence of land use/nitrogen management was overshadowed by climatic influence, or the changes in land use/management occurred in a random fashion.

Accurate population genetic measurements require cryptic species identification in corals

NASA Astrophysics Data System (ADS)

Sheets, Elizabeth A.; Warner, Patricia A.; Palumbi, Stephen R.

2018-06-01

Correct identification of closely related species is important for reliable measures of gene flow. Incorrectly lumping individuals of different species together has been shown to over- or underestimate population differentiation, but examples highlighting when these different results are observed in empirical datasets are rare. Using 199 single nucleotide polymorphisms, we assigned 768 individuals in the Acropora hyacinthus and A. cytherea morphospecies complexes to each of eight previously identified cryptic genetic species and measured intraspecific genetic differentiation across three geographic scales (within reefs, among reefs within an archipelago, and among Pacific archipelagos). We then compared these calculations to estimated genetic differentiation at each scale with all cryptic genetic species mixed as if we could not tell them apart. At the reef scale, correct genetic species identification yielded lower F ST estimates and fewer significant comparisons than when species were mixed, raising estimates of short-scale gene flow. In contrast, correct genetic species identification at large spatial scales yielded higher F ST measurements than mixed-species comparisons, lowering estimates of long-term gene flow among archipelagos. A meta-analysis of published population genetic studies in corals found similar results: F ST estimates at small spatial scales were lower and significance was found less often in studies that controlled for cryptic species. Our results and these prior datasets controlling for cryptic species suggest that genetic differentiation among local reefs may be lower than what has generally been reported in the literature. Not properly controlling for cryptic species structure can bias population genetic analyses in different directions across spatial scales, and this has important implications for conservation strategies that rely on these estimates.

Circulation controls of the spatial structure of maximum daily precipitation over Poland

NASA Astrophysics Data System (ADS)

Stach, Alfred

2015-04-01

Among forecasts made on the basis of global and regional climatic models is one of a high probability of an increase in the frequency and intensity of extreme precipitation events. Learning the regularities underlying the recurrence and spatial extent of extreme precipitation is obviously of great importance, both economic and social. The main goal of the study was to analyse regularities underlying spatial and temporal variations in monthly Maximum Daily Precipitation Totals (MDPTs) observed in Poland over the years 1956-1980. These data are specific because apart from being spatially discontinuous, which is typical of precipitation, they are also non-synchronic. The main aim of the study was accomplished via several detailed goals: • identification and typology of the spatial structure of monthly MDPTs, • determination of the character and probable origin of events generating MDPTs, and • quantitative assessment of the contribution of the particular events to the overall MDPT figures. The analysis of the spatial structure of MDPTs was based on 300 models of spatial structure, one for each of the analysed sets of monthly MDPTs. The models were built on the basis of empirical anisotropic semivariograms of normalised data. In spite of their spatial discontinuity and asynchronicity, the MDPT data from Poland display marked regularities in their spatial pattern that yield readily to mathematical modelling. The MDPT field in Poland is usually the sum of the outcomes of three types of processes operating at various spatial scales: local (<10-20 km), regional (50-150 km), and supra-regional (>200 km). The spatial scales are probably connected with a convective/ orographic, a frontal and a 'planetary waves' genesis of high precipitation. Their contributions are highly variable. Generally predominant, however, are high daily precipitation totals with a spatial extent of 50 to 150 km connected with mesoscale phenomena and the migration of atmospheric fronts (35-38%). The spatial extent of areas of high local-scale precipitation usually varies at random, especially in the warm season. At supra-local scales, structures of repetitive size predominate. Eight types of anisotropic structures of monthly MDPTs were distinguished. To identify them, an analysis was made of semivariance surface similarities. The types differ not only in the level and direction of anisotropy, but also in the number and type of elementary components, which is evidence of genetic differences in precipitation. Their appearance shows a significant seasonal variability, so the most probable supposition was that temporal variations in the MDPT pattern were connected with circulation conditions: the type and direction of inflow of air masses. This hypothesis was validated by testing differences in the frequency of occurrence of Grosswetterlagen circulation situations in the months belonging to the distinguished types of the spatial MDPT pattern.

Fusion of infrared polarization and intensity images based on improved toggle operator

NASA Astrophysics Data System (ADS)

Zhu, Pan; Ding, Lei; Ma, Xiaoqing; Huang, Zhanhua

2018-01-01

Integration of infrared polarization and intensity images has been a new topic in infrared image understanding and interpretation. The abundant infrared details and target from infrared image and the salient edge and shape information from polarization image should be preserved or even enhanced in the fused result. In this paper, a new fusion method is proposed for infrared polarization and intensity images based on the improved multi-scale toggle operator with spatial scale, which can effectively extract the feature information of source images and heavily reduce redundancy among different scale. Firstly, the multi-scale image features of infrared polarization and intensity images are respectively extracted at different scale levels by the improved multi-scale toggle operator. Secondly, the redundancy of the features among different scales is reduced by using spatial scale. Thirdly, the final image features are combined by simply adding all scales of feature images together, and a base image is calculated by performing mean value weighted method on smoothed source images. Finally, the fusion image is obtained by importing the combined image features into the base image with a suitable strategy. Both objective assessment and subjective vision of the experimental results indicate that the proposed method obtains better performance in preserving the details and edge information as well as improving the image contrast.

Spatial Distribution of Stony Desertification and Key Influencing Factors on Different Sampling Scales in Small Karst Watersheds

PubMed Central

Zhang, Zhenming; Zhou, Yunchao; Wang, Shijie

2018-01-01

Karst areas are typical ecologically fragile areas, and stony desertification has become the most serious ecological and economic problems in these areas worldwide as well as a source of disasters and poverty. A reasonable sampling scale is of great importance for research on soil science in karst areas. In this paper, the spatial distribution of stony desertification characteristics and its influencing factors in karst areas are studied at different sampling scales using a grid sampling method based on geographic information system (GIS) technology and geo-statistics. The rock exposure obtained through sampling over a 150 m × 150 m grid in the Houzhai River Basin was utilized as the original data, and five grid scales (300 m × 300 m, 450 m × 450 m, 600 m × 600 m, 750 m × 750 m, and 900 m × 900 m) were used as the subsample sets. The results show that the rock exposure does not vary substantially from one sampling scale to another, while the average values of the five subsamples all fluctuate around the average value of the entire set. As the sampling scale increases, the maximum value and the average value of the rock exposure gradually decrease, and there is a gradual increase in the coefficient of variability. At the scale of 150 m × 150 m, the areas of minor stony desertification, medium stony desertification, and major stony desertification in the Houzhai River Basin are 7.81 km2, 4.50 km2, and 1.87 km2, respectively. The spatial variability of stony desertification at small scales is influenced by many factors, and the variability at medium scales is jointly influenced by gradient, rock content, and rock exposure. At large scales, the spatial variability of stony desertification is mainly influenced by soil thickness and rock content. PMID:29652811

Spatial Distribution of Stony Desertification and Key Influencing Factors on Different Sampling Scales in Small Karst Watersheds.

PubMed

Zhang, Zhenming; Zhou, Yunchao; Wang, Shijie; Huang, Xianfei

2018-04-13

Karst areas are typical ecologically fragile areas, and stony desertification has become the most serious ecological and economic problems in these areas worldwide as well as a source of disasters and poverty. A reasonable sampling scale is of great importance for research on soil science in karst areas. In this paper, the spatial distribution of stony desertification characteristics and its influencing factors in karst areas are studied at different sampling scales using a grid sampling method based on geographic information system (GIS) technology and geo-statistics. The rock exposure obtained through sampling over a 150 m × 150 m grid in the Houzhai River Basin was utilized as the original data, and five grid scales (300 m × 300 m, 450 m × 450 m, 600 m × 600 m, 750 m × 750 m, and 900 m × 900 m) were used as the subsample sets. The results show that the rock exposure does not vary substantially from one sampling scale to another, while the average values of the five subsamples all fluctuate around the average value of the entire set. As the sampling scale increases, the maximum value and the average value of the rock exposure gradually decrease, and there is a gradual increase in the coefficient of variability. At the scale of 150 m × 150 m, the areas of minor stony desertification, medium stony desertification, and major stony desertification in the Houzhai River Basin are 7.81 km², 4.50 km², and 1.87 km², respectively. The spatial variability of stony desertification at small scales is influenced by many factors, and the variability at medium scales is jointly influenced by gradient, rock content, and rock exposure. At large scales, the spatial variability of stony desertification is mainly influenced by soil thickness and rock content.

On the Scaling Behavior of Reliability-Resilience-Vulnerability ...

EPA Pesticide Factsheets

Risk indices such as reliability-resilience-vulnerability (R-R-V) have been proposed to assess watershed health. In this study, the spatial scaling behavior of R-R-V indices has been explored for five agricultural watersheds in the midwestern United States. The study was conducted using two different measures of spatial scale: (i) the ratio of contributing upland area to area required for channel initiation (FA), and (ii) Strahler stream order. It was found that R-R-V indices do change with spatial scale, but a representative watershed-specific threshold FA value exists for these indices to achieve stable values. Scaling with Strahler stream order is feasible if the watershed possesses a tree-like stream network. As an example of anthropogenic influences, this study also examined the role of BMPs placed within an agricultural watershed via a cost-effective optimization scheme on the evolution of R-R-V values with scale. While the placement of BMPs acheived reductions in concentrations and/or loads of constituents, they may not significantly change watershed risk measures, but are likely to cause significant reduction in vulnerability. If primarily upland BMPs are placed in a diffuse manner throughout the watershed, there might not be a significant change in the scaling behavior of R-R-V values. The primary objective of this study is to investigate the effect of spatial scale on risk-based watershed health assessment. A related objective is to examine wh

Techniques for spatio-temporal analysis of vegetation fires in the topical belt of Africa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brivio, P.A.; Ober, G.; Koffi, B.

1995-12-31

Biomass burning of forests and savannas is a phenomenon of continental or even global proportions, capable of causing large scale environmental changes. Satellite space observations, in particular from NOAA-AVHRR GAC data, are the only source of information allowing one to document burning patterns at regional and continental scale and over long periods of time. This paper presents some techniques, such as clustering and rose-diagram, useful in the spatial-temporal analysis of satellite derived fires maps to characterize the evolution of spatial patterns of vegetation fires at regional scale. An automatic clustering approach is presented which enables one to describe and parameterizemore » spatial distribution of fire patterns at different scales. The problem of geographical distribution of vegetation fires with respect to some location of interest, point or line, is also considered and presented. In particular rose-diagrams are used to relate fires patterns to some reference point, as experimental sites of tropospheric chemistry measurements. Different temporal data-sets in the tropical belt of Africa, covering both Northern and Southern Hemisphere dry seasons, using these techniques were analyzed and showed very promising results when compared with data from rain chemistry studies at different sampling sites in the equatorial forest.« less

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Quattrochi, Dale A.

2000-01-01

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Behavioral self-organization underlies the resilience of a coastal ecosystem.

PubMed

de Paoli, Hélène; van der Heide, Tjisse; van den Berg, Aniek; Silliman, Brian R; Herman, Peter M J; van de Koppel, Johan

2017-07-25

Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds ( Mytilus edulis ) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance.

Behavioral self-organization underlies the resilience of a coastal ecosystem

PubMed Central

de Paoli, Hélène; van der Heide, Tjisse; van den Berg, Aniek; Silliman, Brian R.; Herman, Peter M. J.

2017-01-01

Self-organized spatial patterns occur in many terrestrial, aquatic, and marine ecosystems. Theoretical models and observational studies suggest self-organization, the formation of patterns due to ecological interactions, is critical for enhanced ecosystem resilience. However, experimental tests of this cross-ecosystem theory are lacking. In this study, we experimentally test the hypothesis that self-organized pattern formation improves the persistence of mussel beds (Mytilus edulis) on intertidal flats. In natural beds, mussels generate self-organized patterns at two different spatial scales: regularly spaced clusters of mussels at centimeter scale driven by behavioral aggregation and large-scale, regularly spaced bands at meter scale driven by ecological feedback mechanisms. To test for the relative importance of these two spatial scales of self-organization on mussel bed persistence, we conducted field manipulations in which we factorially constructed small-scale and/or large-scale patterns. Our results revealed that both forms of self-organization enhanced the persistence of the constructed mussel beds in comparison to nonorganized beds. Small-scale, behaviorally driven cluster patterns were found to be crucial for persistence, and thus resistance to wave disturbance, whereas large-scale, self-organized patterns facilitated reformation of small-scale patterns if mussels were dislodged. This study provides experimental evidence that self-organization can be paramount to enhancing ecosystem persistence. We conclude that ecosystems with self-organized spatial patterns are likely to benefit greatly from conservation and restoration actions that use the emergent effects of self-organization to increase ecosystem resistance to disturbance. PMID:28696313

[Prediction and spatial distribution of recruitment trees of natural secondary forest based on geographically weighted Poisson model].

PubMed

Zhang, Ling Yu; Liu, Zhao Gang

2017-12-01

Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.

Spatial scale and distribution of neurovascular signals underlying decoding of orientation and eye of origin from fMRI data

PubMed Central

Harrison, Charlotte; Jackson, Jade; Oh, Seung-Mock; Zeringyte, Vaida

2016-01-01

Multivariate pattern analysis of functional magnetic resonance imaging (fMRI) data is widely used, yet the spatial scales and origin of neurovascular signals underlying such analyses remain unclear. We compared decoding performance for stimulus orientation and eye of origin from fMRI measurements in human visual cortex with predictions based on the columnar organization of each feature and estimated the spatial scales of patterns driving decoding. Both orientation and eye of origin could be decoded significantly above chance in early visual areas (V1–V3). Contrary to predictions based on a columnar origin of response biases, decoding performance for eye of origin in V2 and V3 was not significantly lower than that in V1, nor did decoding performance for orientation and eye of origin differ significantly. Instead, response biases for both features showed large-scale organization, evident as a radial bias for orientation, and a nasotemporal bias for eye preference. To determine whether these patterns could drive classification, we quantified the effect on classification performance of binning voxels according to visual field position. Consistent with large-scale biases driving classification, binning by polar angle yielded significantly better decoding performance for orientation than random binning in V1–V3. Similarly, binning by hemifield significantly improved decoding performance for eye of origin. Patterns of orientation and eye preference bias in V2 and V3 showed a substantial degree of spatial correlation with the corresponding patterns in V1, suggesting that response biases in these areas originate in V1. Together, these findings indicate that multivariate classification results need not reflect the underlying columnar organization of neuronal response selectivities in early visual areas. NEW & NOTEWORTHY Large-scale response biases can account for decoding of orientation and eye of origin in human early visual areas V1–V3. For eye of origin this pattern is a nasotemporal bias; for orientation it is a radial bias. Differences in decoding performance across areas and stimulus features are not well predicted by differences in columnar-scale organization of each feature. Large-scale biases in extrastriate areas are spatially correlated with those in V1, suggesting biases originate in primary visual cortex. PMID:27903637

Concepts: Integrating population survey data from different spatial scales, sampling methods, and species

USGS Publications Warehouse

Dorazio, Robert; Delampady, Mohan; Dey, Soumen; Gopalaswamy, Arjun M.; Karanth, K. Ullas; Nichols, James D.

2017-01-01

Conservationists and managers are continually under pressure from the public, the media, and political policy makers to provide “tiger numbers,” not just for protected reserves, but also for large spatial scales, including landscapes, regions, states, nations, and even globally. Estimating the abundance of tigers within relatively small areas (e.g., protected reserves) is becoming increasingly tractable (see Chaps. 9 and 10), but doing so for larger spatial scales still presents a formidable challenge. Those who seek “tiger numbers” are often not satisfied by estimates of tiger occupancy alone, regardless of the reliability of the estimates (see Chaps. 4 and 5). As a result, wherever tiger conservation efforts are underway, either substantially or nominally, scientists and managers are frequently asked to provide putative large-scale tiger numbers based either on a total count or on an extrapolation of some sort (see Chaps. 1 and 2).

Spatial and temporal analysis of drought variability at several time scales in Syria during 1961-2012

NASA Astrophysics Data System (ADS)

Mathbout, Shifa; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Bech, Joan; Rodrigo, Fernando S.

2018-02-01

This paper analyses the observed spatiotemporal characteristics of drought phenomenon in Syria using the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI). Temporal variability of drought is calculated for various time scales (3, 6, 9, 12, and 24 months) for 20 weather stations over the 1961-2012 period. The spatial patterns of drought were identified by applying a Principal Component Analysis (PCA) to the SPI and SPEI values at different time scales. The results revealed three heterogeneous and spatially well-defined regions with different temporal evolution of droughts: 1) Northeastern (inland desert); 2) Southern (mountainous landscape); 3) Northwestern (Mediterranean coast). The evolutionary characteristics of drought during 1961-2012 were analysed including spatial and temporal variability of SPI and SPEI, the frequency distribution, and the drought duration. The results of the non-parametric Mann-Kendall test applied to the SPI and SPEI series indicate prevailing significant negative trends (drought) at all stations. Both drought indices have been correlated both on spatial and temporal scales and they are highly comparable, especially, over a 12 and 24 month accumulation period. We concluded that the temporal and spatial characteristics of the SPI and SPEI can be used for developing a drought intensity - areal extent - and frequency curve that assesses the variability of regional droughts in Syria. The analysis of both indices suggests that all three regions had a severe drought in the 1990s, which had never been observed before in the country. Furthermore, the 2007-2010 drought was the driest period in the instrumental record, happening just before the onset of the recent conflict in Syria.

Quantifying drivers of wild pig movement across multiple spatial and temporal scales.

PubMed

Kay, Shannon L; Fischer, Justin W; Monaghan, Andrew J; Beasley, James C; Boughton, Raoul; Campbell, Tyler A; Cooper, Susan M; Ditchkoff, Stephen S; Hartley, Steve B; Kilgo, John C; Wisely, Samantha M; Wyckoff, A Christy; VerCauteren, Kurt C; Pepin, Kim M

2017-01-01

The movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management. We obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season. We found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales. The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc ) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

The Effects of Fine-scale Soil Moisture and Canopy Heterogeneities on Energy and Soil Water Fluxes in a Temperate Mixed Deciduous Forest

NASA Astrophysics Data System (ADS)

He, L.; Ivanov, V. Y.; Bohrer, G.; Maurer, K.; Vogel, C. S.; Moghaddam, M.

2011-12-01

Vegetation is heterogeneous at different scales, influencing spatially variable energy and water exchanges between land-surface and atmosphere. Current land surface parameterizations of large-scale models consider spatial variability at a scale of a few kilometers and treat vegetation cover as aggregated patches with uniform properties. However, the coupling mechanisms between fine-scale soil moisture, vegetation, and energy fluxes such as evapotranspiration are strongly nonlinear; the aggregation of surface variations may produce biased energy fluxes. This study aims to improve the understanding of the scale impact in atmosphere-biosphere-hydrosphere interactions, which affects predictive capabilities of land surface models. The study uses a high-resolution, physically-based ecohydrological model tRIBS + VEGGIE as a data integration tool to upscale the heterogeneity of canopy distribution resolved at a few meters to the watershed scale. The study was carried out for a spatially heterogeneous, temperate mixed forest environment of Northern Michigan located near the University of Michigan Biological Station (UMBS). Energy and soil water dynamics were simulated at the tree-canopy resolution in the horizontal plane for a small domain (~2 sq. km) located within a footprint of the AmeriFlux tower. A variety of observational data were used to constrain and confirm the model, including a 3-m profile continuous soil moisture dataset and energy flux data (measured at the AmeriFlux tower footprint). A scenario with a spatially uniform canopy, corresponding to the commonly used 'big-leaf' scheme in land surface parameterizations was used to infer the effects of coarse-scale averaging. To gain insights on how heterogeneous canopy and soil moisture interact and contribute to the domain-averaged transpiration, several scenarios of tree-scale leaf area and soil moisture spatial variability were designed. Specifically, for the same mean states, the scenarios of variability of canopy biomass account for the spatial distribution of photosynthesis (and thus the stomatal resistance), the aerodynamic and leaf boundary layer resistances as well as the differential radiation forcing due to tall tree exposure and lateral shading of short trees. The numerical experiments show that by transpiring spatially varying amounts of water, heterogeneous canopies adjust the spatial soil water state to the scaled inverse of the canopy biomass regardless of the initial moisture state. Such a spatial distribution can be further wiped out because of the differential water stress. The aggregation of canopy-scale atmosphere-biosphere-hydrosphere interactions demonstrates non-linear relationship between soil moisture and evapotranspiration, influencing domain-averaged energy fluxes.

Valley s'Asymmetric Characteristics of the Loess Plateau in Northwestern Shanxi Based on DEM

NASA Astrophysics Data System (ADS)

Duan, J.

2016-12-01

The valleys of the Loess Plateau in northwestern Shanxi show great asymmetry. This study using multi-scale DEMs, high-resolution satellite images and digital terrain analysis method, put forward a quantitative index to describe the asymmetric morphology. Several typical areas are selected to test and verify the spatial variability. Results show: (1) Considering the difference of spatial distribution, Pianguanhe basin, Xianchuanhe basin and Yangjiachuan basin are the areas where show most significant asymmetric characteristics . (2) Considering the difference of scale, the shape of large-scale valleys represents three characteristics: randomness, equilibrium and relative symmetry, while small-scale valleys show directionality and asymmetry. (3) Asymmetric morphology performs orientation, and the east-west valleys extremely obvious. Combined with field survey, its formation mechanism can be interpreted as follows :(1)Loess uneven distribution in the valleys. (2) The distribution diversities of vegetation, water , heat conditions and other factors, make a difference in water erosion capability which leads to asymmetric characteristics.

Scale linkage and contingency effects of field-scale and hillslope-scale controls of long-term soil erosion: Anthropogeomorphic sediment flux in agricultural loess watersheds of Southern Germany

NASA Astrophysics Data System (ADS)

Houben, Peter

2008-10-01

Agricultural landscapes with a millennial-scale history of cultivation are common in many loess areas of central Europe. Over time, patterns of erosion and sedimentation have been continually modified via the variable imposition of anthropogenic discontinuities and linkages on fragmented hillslope sediment cascades, which eventually caused the complicated soilscape pattern. These field records challenge topographically oriented models of hillslope erosion and simple predictions of longer-term change of spatial soilscape by cultivation activities. A thorough understanding how soilscape patterns form in the long-term, however, is essential to develop spatial concepts of the sediment budget, particularly for the spatial modeling of anthropogenic hillslope sediment flux using GIS. In this study I used extensive datasets of anthropogenic soil truncation and burial in a typical undulating loess watershed in southern Germany (10 km 2, Wetterau Basin, N of Frankfurt a.M.). Spatial soilscape properties and historic sediment flux, as caused by cultivation over seven millennia, were evaluated by these data. The soilscape pattern on the low-gradient hillslopes of the study area was found to be marked by a statistical near-random pattern of varying depth (thickness) of truncation and overthickened burial. Moreover, it was shown that truncation and burial had developed independently from each other and did not correlate with either hillslope gradient or downslope curvature. Hence, in the field any combination of (few) nearly preserved, severely truncated or completely removed soil profiles with either no, some or a thick sediment cover is present, thereby lacking an obvious spatial pattern. Here, I suggest putting long-term change of the soilscape into a contextual anthropogeomorphic systems perspective, that accommodates components of human-induced soil erosion operating at different spatial scales to interpret the longer-term spatial consequences at the hillslope-system level. In the study area, system scale linkages are marked by the spatial intersection of a finer-scaled managed field system with a broader hillslope-scale framework of 'natural' erosion controls. In the low-gradient study area, field borders exert control over the spatial reference of soil erosion and sedimentation sites. Over time, this brought about a growing historical and spatial contingency change to the soilscape, because of arbitrary spatial changes of the field system which are inherent in its socio-agricultural maintenance. Thus, the very low-gradient and low-erosivity setting of the study area have singled out the agency of human-induced spatial and connectivity controls and contingency for long-term spatial hillslope sediment flux. Although these findings may be less true for different settings, they allow for deriving a generic conceptual model of the linkages between 'natural' and anthropogenic subsystems to interpret the effects of long-term human-induced sediment flux. Accordingly, the resulting balance between on-hillslope net storage and net delivery to streams is scaling with basic physiographic properties of erosivity and sedimentation as well as the degree of anthropogenic hillslope fragmentation. For loess areas in Europe variable fields are fundamental anthropogeomorphic units that determine appropriate system scaling for historic sediment flux analysis and constrain retrodiction and prediction of changing fluxes at a point and a time at watershed scales. Methodical implications address adequate sampling strategies to record soilscape change, as a result of which a critical review of the applicability of the catena concept to long-cultivated hillslopes in central Europe was included. Finally, the suggested refined generic model of long-term, human-controlled sediment flux involves a number of research opportunities, particularly for linking modeling approaches to long-term field records of cultivation-related change in the soilscape.

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT: A GIS-BASED HYDROLOGIC MODELING TOOL

EPA Science Inventory

Planning and assessment in land and water resource management are evolving toward complex, spatially explicit regional assessments. These problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and temporal scales. The extens...

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

The landscape context of cereal aphid–parasitoid interactions

PubMed Central

Thies, Carsten; Roschewitz, Indra; Tscharntke, Teja

2005-01-01

Analyses at multiple spatial scales may show how important ecosystem services such as biological control are determined by processes acting on the landscape scale. We examined cereal aphid–parasitoid interactions in wheat fields in agricultural landscapes differing in structural complexity (32–100% arable land). Complex landscapes were associated with increased aphid mortality resulting from parasitism, but also with higher aphid colonization, thereby counterbalancing possible biological control by parasitoids and lastly resulting in similar aphid densities across landscapes. Thus, undisturbed perennial habitats appeared to enhance both pests and natural enemies. Analyses at multiple spatial scales (landscape sectors of 0.5–6 km diameter) showed that correlations between parasitism and percentage of arable land were significant at scales of 0.5–2 km, whereas aphid densities responded to percentage of arable land at scales of 1–6 km diameter. Hence, the higher trophic level populations appeared to be determined by smaller landscape sectors owing to dispersal limitation, showing the ‘functional spatial scale’ for species-specific landscape management. PMID:15695212

Optimizing the scale of markets for water quality trading

NASA Astrophysics Data System (ADS)

Doyle, Martin W.; Patterson, Lauren A.; Chen, Yanyou; Schnier, Kurt E.; Yates, Andrew J.

2014-09-01

Applying market approaches to environmental regulations requires establishing a spatial scale for trading. Spatially large markets usually increase opportunities for abatement cost savings but increase the potential for pollution damages (hot spots), vice versa for spatially small markets. We develop a coupled hydrologic-economic modeling approach for application to point source emissions trading by a large number of sources and apply this approach to the wastewater treatment plants (WWTPs) within the watershed of the second largest estuary in the U.S. We consider two different administrative structures that govern the trade of emission permits: one-for-one trading (the number of permits required for each unit of emission is the same for every WWTP) and trading ratios (the number of permits required for each unit of emissions varies across WWTP). Results show that water quality regulators should allow trading to occur at the river basin scale as an appropriate first-step policy, as is being done in a limited number of cases via compliance associations. Larger spatial scales may be needed under conditions of increased abatement costs. The optimal scale of the market is generally the same regardless of whether one-for-one trading or trading ratios are employed.

Influence of snowpack and melt energy heterogeneity on snow cover depletion and snowmelt runoff simulation in a cold mountain environment

NASA Astrophysics Data System (ADS)

DeBeer, Chris M.; Pomeroy, John W.

2017-10-01

The spatial heterogeneity of mountain snow cover and ablation is important in controlling patterns of snow cover depletion (SCD), meltwater production, and runoff, yet is not well-represented in most large-scale hydrological models and land surface schemes. Analyses were conducted in this study to examine the influence of various representations of snow cover and melt energy heterogeneity on both simulated SCD and stream discharge from a small alpine basin in the Canadian Rocky Mountains. Simulations were performed using the Cold Regions Hydrological Model (CRHM), where point-scale snowmelt computations were made using a snowpack energy balance formulation and applied to spatial frequency distributions of snow water equivalent (SWE) on individual slope-, aspect-, and landcover-based hydrological response units (HRUs) in the basin. Hydrological routines were added to represent the vertical and lateral transfers of water through the basin and channel system. From previous studies it is understood that the heterogeneity of late winter SWE is a primary control on patterns of SCD. The analyses here showed that spatial variation in applied melt energy, mainly due to differences in net radiation, has an important influence on SCD at multiple scales and basin discharge, and cannot be neglected without serious error in the prediction of these variables. A single basin SWE distribution using the basin-wide mean SWE (SWE ‾) and coefficient of variation (CV; standard deviation/mean) was found to represent the fine-scale spatial heterogeneity of SWE sufficiently well. Simulations that accounted for differences in (SWE ‾) among HRUs but neglected the sub-HRU heterogeneity of SWE were found to yield similar discharge results as simulations that included this heterogeneity, while SCD was poorly represented, even at the basin level. Finally, applying point-scale snowmelt computations based on a single SWE depth for each HRU (thereby neglecting spatial differences in internal snowpack energetics over the distributions) was found to yield similar SCD and discharge results as simulations that resolved internal energy differences. Spatial/internal snowpack melt energy effects are more pronounced at times earlier in spring before the main period of snowmelt and SCD, as shown in previously published work. The paper discusses the importance of these findings as they apply to the warranted complexity of snowmelt process simulation in cold mountain environments, and shows how the end-of-winter SWE distribution represents an effective means of resolving snow cover heterogeneity at multiple scales for modelling, even in steep and complex terrain.

Identifying spatial priorities for protecting ecosystem services

PubMed Central

Luck, Gary W

2012-01-01

Priorities for protecting ecosystem services must be identified to ensure future human well-being. Approaches to broad-scale spatial prioritization of ecosystem services are becoming increasingly popular and are a vital precursor to identifying locations where further detailed analyses of the management of ecosystem services is required (e.g., examining trade-offs among management actions). Prioritization approaches often examine the spatial congruence between priorities for protecting ecosystem services and priorities for protecting biodiversity; therefore, the spatial prioritization method used is crucial because it will influence the alignment of service protection and conservation goals. While spatial prioritization of ecosystem services and prioritization for conservation share similarities, such as the need to document threats and costs, the former differs substantially from the latter owing to the requirement to measure the following components: supply of services; availability of human-derived alternatives to service provision; capacity to meet beneficiary demand; and site dependency in and scale of service delivery. We review studies that identify broad-scale spatial priorities for managing ecosystem services and demonstrate that researchers have used different approaches and included various measures for identifying priorities, and most studies do not consider all of the components listed above. We describe a conceptual framework for integrating each of these components into spatial prioritization of ecosystem services and illustrate our approach using a worked example for water provision. A fuller characterization of the biophysical and social context for ecosystem services that we call for should improve future prioritization and the identification of locations where ecosystem-service management is especially important or cost effective. PMID:24555017

Spatial distribution and succession of epiphytes on Tsuga heterophylla (western hemlock) in an old-growth Douglas-fir forest

Treesearch

Betsy Lyons; Nalini M. Nadkarni; Malcolm P. North

2000-01-01

We examined the distribution and abundance of nonvascular epiphytes on western hemlock trees in an oldgrowth coniferous forest focusing on patterns of epiphyte distribution at different spatial scales, epiphyte abundance amongst trees differing in size, and crown structures associated with epiphyte abundance. Total epiphyte cover was greatest in four canopy...

Impact of temporal, spatial and cascaded effects on the pulse formation in ultra-broadband parametric amplifiers.

PubMed

Lang, T; Harth, A; Matyschok, J; Binhammer, T; Schultze, M; Morgner, U

2013-01-14

A 2 + 1 dimensional nonlinear pulse propagation model is presented, illustrating the weighting of different effects for the parametric amplification of ultra-broadband spectra in different regimes of energy scaling. Typical features in the distribution of intensity and phase of state-of-the-art OPA-systems can be understood by cascaded spatial and temporal effects.

Fish communities associated with cold-water corals vary with depth and substratum type

NASA Astrophysics Data System (ADS)

Milligan, Rosanna J.; Spence, Gemma; Roberts, J. Murray; Bailey, David M.

2016-08-01

Understanding the processes that drive the distribution patterns of organisms and the scales over which these processes operate are vital when considering the effective management of species with high commercial or conservation value. In the deep sea, the importance of scleractinian cold-water corals (CWCs) to fish has been the focus of several studies but their role remains unclear. We propose this may be due to the confounding effects of multiple drivers operating over multiple spatial scales. The aims of this study were to investigate the role of CWCs in shaping fish community structure and individual species-habitat associations across four spatial scales in the NE Atlantic ranging from "regions" (separated by >500 km) to "substratum types" (contiguous). Demersal fish and substratum types were quantified from three regions: Logachev Mounds, Rockall Bank and Hebrides Terrace Seamount (HTS). PERMANOVA analyses showed significant differences in community composition between all regions which were most likely caused by differences in depths. Within regions, significant variation in community composition was recorded at scales of c. 20-3500 m. CWCs supported significantly different fish communities to non-CWC substrata at Rockall Bank, Logachev and the HTS. Single-species analyses using generalised linear mixed models showed that Sebastes sp. was strongly associated with CWCs at Rockall Bank and that Neocyttus helgae was more likely to occur in CWCs at the HTS. Depth had a significant effect on several other fish species. The results of this study suggest that the importance of CWCs to fish is species-specific and depends on the broader spatial context in which the substratum is found. The precautionary approach would be to assume that CWCs are important for associated fish, but must acknowledge that CWCs in different depths will not provide redundancy or replication within spatially-managed conservation networks.

Spatial structure of soil properties at different scales of Mt. Kilimanjaro, Tanzania

NASA Astrophysics Data System (ADS)

Kühnel, Anna; Huwe, Bernd

2013-04-01

Soils of tropical mountain ecosystems provide important ecosystem services like water and carbon storage, water filtration and erosion control. As these ecosystems are threatened by global warming and the conversion of natural to human-modified landscapes, it is important to understand the implications of these changes. Within the DFG Research Unit "Kilimanjaro ecosystems under global change: Linking biodiversity, biotic interactions and biogeochemical ecosystem processes", we study the spatial heterogeneity of soils and the available water capacity for different land use systems. In the savannah zone of Mt. Kilimanjaro, maize fields are compared to natural savannah ecosystems. In the lower montane forest zone, coffee plantations, traditional home gardens, grasslands and natural forests are studied. We characterize the soils with respect to soil hydrology, emphasizing on the spatial variability of soil texture and bulk density at different scales. Furthermore soil organic carbon and nitrogen, cation exchange capacity and the pH-value are measured. Vis/Nir-Spectroscopy is used to detect small scale physical and chemical heterogeneity within soil profiles, as well as to get information of soil properties on a larger scale. We aim to build a spectral database for these soil properties for the Kilimanjaro region in order to get rapid information for geostatistical analysis. Partial least square regression with leave one out cross validation is used for model calibration. Results for silt and clay content, as well as carbon and nitrogen content are promising, with adjusted R² ranging from 0.70 for silt to 0.86 for nitrogen. Furthermore models for other nutrients, cation exchange capacity and available water capacity will be calibrated. We compare heterogeneity within and across the different ecosystems and state that spatial structure characteristics and complexity patterns in soil parameters can be quantitatively related to biodiversity and functional diversity parameters.

The feasibility of using a universal Random Forest model to map tree height across different locations and vegetation types

NASA Astrophysics Data System (ADS)

Su, Y.; Guo, Q.; Jin, S.; Gao, S.; Hu, T.; Liu, J.; Xue, B. L.

2017-12-01

Tree height is an important forest structure parameter for understanding forest ecosystem and improving the accuracy of global carbon stock quantification. Light detection and ranging (LiDAR) can provide accurate tree height measurements, but its use in large-scale tree height mapping is limited by the spatial availability. Random Forest (RF) has been one of the most commonly used algorithms for mapping large-scale tree height through the fusion of LiDAR and other remotely sensed datasets. However, how the variances in vegetation types, geolocations and spatial scales of different study sites influence the RF results is still a question that needs to be addressed. In this study, we selected 16 study sites across four vegetation types in United States (U.S.) fully covered by airborne LiDAR data, and the area of each site was 100 km2. The LiDAR-derived canopy height models (CHMs) were used as the ground truth to train the RF algorithm to predict canopy height from other remotely sensed variables, such as Landsat TM imagery, terrain information and climate surfaces. To address the abovementioned question, 22 models were run under different combinations of vegetation types, geolocations and spatial scales. The results show that the RF model trained at one specific location or vegetation type cannot be used to predict tree height in other locations or vegetation types. However, by training the RF model using samples from all locations and vegetation types, a universal model can be achieved for predicting canopy height across different locations and vegetation types. Moreover, the number of training samples and the targeted spatial resolution of the canopy height product have noticeable influence on the RF prediction accuracy.

On species persistence-time distributions.

PubMed

Suweis, S; Bertuzzo, E; Mari, L; Rodriguez-Iturbe, I; Maritan, A; Rinaldo, A

2012-06-21

We present new theoretical and empirical results on the probability distributions of species persistence times in natural ecosystems. Persistence times, defined as the timespans occurring between species' colonization and local extinction in a given geographic region, are empirically estimated from local observations of species' presence/absence. A connected sampling problem is presented, generalized and solved analytically. Species persistence is shown to provide a direct connection with key spatial macroecological patterns like species-area and endemics-area relationships. Our empirical analysis pertains to two different ecosystems and taxa: a herbaceous plant community and a estuarine fish database. Despite the substantial differences in ecological interactions and spatial scales, we confirm earlier evidence on the general properties of the scaling of persistence times, including the predicted effects of the structure of the spatial interaction network. The framework tested here allows to investigate directly nature and extent of spatial effects in the context of ecosystem dynamics. The notable coherence between spatial and temporal macroecological patterns, theoretically derived and empirically verified, is suggested to underlie general features of the dynamic evolution of ecosystems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Variation in coastal Antarctic microbial community composition at sub-mesoscale: spatial distance or environmental filtering?

PubMed

Moreno-Pino, Mario; De la Iglesia, Rodrigo; Valdivia, Nelson; Henríquez-Castilo, Carlos; Galán, Alexander; Díez, Beatriz; Trefault, Nicole

2016-07-01

Spatial environmental heterogeneity influences diversity of organisms at different scales. Environmental filtering suggests that local environmental conditions provide habitat-specific scenarios for niche requirements, ultimately determining the composition of local communities. In this work, we analyze the spatial variation of microbial communities across environmental gradients of sea surface temperature, salinity and photosynthetically active radiation and spatial distance in Fildes Bay, King George Island, Antarctica. We hypothesize that environmental filters are the main control of the spatial variation of these communities. Thus, strong relationships between community composition and environmental variation and weak relationships between community composition and spatial distance are expected. Combining physical characterization of the water column, cell counts by flow cytometry, small ribosomal subunit genes fingerprinting and next generation sequencing, we contrast the abundance and composition of photosynthetic eukaryotes and heterotrophic bacterial local communities at a submesoscale. Our results indicate that the strength of the environmental controls differed markedly between eukaryotes and bacterial communities. Whereas eukaryotic photosynthetic assemblages responded weakly to environmental variability, bacteria respond promptly to fine-scale environmental changes in this polar marine system. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Explaining variation in tropical plant community composition: influence of environmental and spatial data quality.

PubMed

Jones, Mirkka M; Tuomisto, Hanna; Borcard, Daniel; Legendre, Pierre; Clark, David B; Olivas, Paulo C

2008-03-01

The degree to which variation in plant community composition (beta-diversity) is predictable from environmental variation, relative to other spatial processes, is of considerable current interest. We addressed this question in Costa Rican rain forest pteridophytes (1,045 plots, 127 species). We also tested the effect of data quality on the results, which has largely been overlooked in earlier studies. To do so, we compared two alternative spatial models [polynomial vs. principal coordinates of neighbour matrices (PCNM)] and ten alternative environmental models (all available environmental variables vs. four subsets, and including their polynomials vs. not). Of the environmental data types, soil chemistry contributed most to explaining pteridophyte community variation, followed in decreasing order of contribution by topography, soil type and forest structure. Environmentally explained variation increased moderately when polynomials of the environmental variables were included. Spatially explained variation increased substantially when the multi-scale PCNM spatial model was used instead of the traditional, broad-scale polynomial spatial model. The best model combination (PCNM spatial model and full environmental model including polynomials) explained 32% of pteridophyte community variation, after correcting for the number of sampling sites and explanatory variables. Overall evidence for environmental control of beta-diversity was strong, and the main floristic gradients detected were correlated with environmental variation at all scales encompassed by the study (c. 100-2,000 m). Depending on model choice, however, total explained variation differed more than fourfold, and the apparent relative importance of space and environment could be reversed. Therefore, we advocate a broader recognition of the impacts that data quality has on analysis results. A general understanding of the relative contributions of spatial and environmental processes to species distributions and beta-diversity requires that methodological artefacts are separated from real ecological differences.

Significant demographic and fine-scale genetic structure in expanding and senescing populations of the terrestrial orchid Cymbidium goeringii (Orchidaceae).

PubMed

Chung, Mi Yoon; Nason, John D; Chung, Myong Gi

2011-12-01

Fine-scale genetic structure (FSGS) in plants is influenced by variation in spatial and temporal demographic processes. To determine how demographic structure and FSGS change with stages of population succession, we studied replicate expanding and senescing populations of the Asian terrestrial orchid Cymbidium goeringii. We used spatial autocorrelation methods (O-ring and kinship statistics) to quantify spatial demographic structure and FSGS in two expanding and two senescing populations, also measuring genetic diversity and inbreeding in each. All populations exhibited significant aggregation of individuals and FSGS at short spatial scales. In expanding populations, this finding was associated with high recruitment rates, suggesting restricted seed dispersal. In senescing populations, recruitment was minimal, suggesting alternative mechanisms of aggregation, perhaps including spatial associations with mycorrhizal fungi. All populations had significant evidence of genetic bottlenecks, and inbreeding levels were consistently high. Our results indicate that different successional stages can generate similar patterns of spatial demographic and genetic structure, but as a consequence of different processes. These results contrast with the only other study of senescence effects on population genetic structure in an herbaceous perennial, which found little to no FSGS in senescing populations. With the exception of populations subject to mass collection by orchid sellers, significant FSGS is characteristic of the 16 terrestrial orchid species examined to date. From a conservation perspective, this result suggests that inference of orchid population history will benefit from analyses of both FSGS and demographic structure in combination with other ecological field data.

Monitoring survival rates of landbirds at varying spatial scales: An application of the MAPS Program

USGS Publications Warehouse

Rosenberg, D.K.; DeSante, D.F.; Hines, J.E.; Bonney, Rick; Pashley, David N.; Cooper, Robert; Niles, Larry

2000-01-01

Survivorship is a primary demographic parameter affecting population dynamics, and thus trends in species abundance. The Monitoring Avian Productivity and Survivorship (MAPS) program is a cooperative effort designed to monitor landbird demographic parameters. A principle goal of MAPS is to estimate annual survivorship and identify spatial patterns and temporal trends in these rates. We evaluated hypotheses of spatial patterns in survival rates among a collection of neighboring sampling sites, such as within national forests, among biogeographic provinces, and between breeding populations that winter in either Central or South America, and compared these geographic-specific models to a model of a common survival rate among all sampling sites. We used data collected during 1992-1995 from Swainson's Thrush (Cathorus ustulatus) populations in the western region of the United States. We evaluated the ability to detect spatial and temporal patterns of survivorship with simulated data. We found weak evidence of spatial differences in survival rates at the local scale of 'location,' which typically contained 3 mist-netting stations. There was little evidence of differences in survival rates among biogeographic provinces or between populations that winter in either Central or South America. When data were pooled for a regional estimate of survivorship, the percent relative bias due to pooling 'locations' was 12 years of monitoring. Detection of spatial patterns and temporal trends in survival rates from local to regional scales will provide important information for management and future research directed toward conservation of landbirds.

An examination of scale of assessment, logging and ENSO-induced fires on butterfly diversity in Borneo.

PubMed

Cleary, Daniel F R

2003-04-01

The impact of disturbance on species diversity may be related to the spatial scales over which it occurs. Here I assess the impact of logging and ENSO (El Niño Southern Oscillation) -induced burning and forest isolation on the species richness (477 species out of more than 28,000 individuals) and community composition of butterflies and butterfly guilds using small (0.9 ha) plots nested within large (450 ha) landscapes. The landscapes were located in three habitat classes: (1) continuous, unburned forest; (2) unburned isolates surrounded by burned forest; and (3) burned forest. Plots with different logging histories were sampled within the two unburned habitat classes, allowing for independent assessment of the two disturbance factors (logging and burning). Disturbance within habitat classes (logging) had a very different impact on butterfly diversity than disturbance among habitat classes (due to ENSO-induced burning and isolation). Logging increased species richness, increased evenness, and lowered dominance. Among guilds based on larval food plants, the species richness of tree and herb specialists was higher in logged areas but their abundance was lower. Both generalist species richness and abundance was higher in logged areas. Among habitat classes, species richness was lower in burned forest and isolates than continuous forest but there was no overall difference in evenness or dominance. Among guilds, generalist species richness was significantly lower in burned forest and isolates than continuous forest. Generalist abundance was also very low in the isolates. There was no difference among disturbance classes in herb specialist species richness but abundance was significantly higher in the isolates and burned forest than in continuous forest. Tree specialist species richness was lower in burned forest than continuous forest but did not differ between continuous forest and isolates. The scale of assessment proved important in estimating the impact of disturbance on species richness. Within disturbance classes, the difference in species richness between primary and logged forest was more pronounced at the smaller spatial scale. Among disturbance classes, the difference in species richness between continuous forest and isolates or burned forest was more pronounced at the larger spatial scale. The lower levels of species richness in ENSO-affected areas and at the larger (landscape) spatial scale indicate that future severe ENSO events may prove one of the most serious threats to extant biodiversity.

Research on the key technology of update of land survey spatial data based on embedded GIS and GPS

NASA Astrophysics Data System (ADS)

Chen, Dan; Liu, Yanfang; Yu, Hai; Xia, Yin

2009-10-01

According to the actual needs of the second land-use survey and the PDA's characteristics of small volume and small memory, it can be analyzed that the key technology of the data collection system of field survey based on GPS-PDA is the read speed of the data. In order to enhance the speed and efficiency of the analysis of the spatial data on mobile devices, we classify the layers of spatial data; get the Layer-Grid Index by getting the different levels and blocks of the layer of spatial data; then get the R-TREE index of the spatial data objects. Different scale levels of space are used in different levels management. The grid method is used to do the block management.

Wavelet analysis applied to the IRAS cirrus

NASA Technical Reports Server (NTRS)

Langer, William D.; Wilson, Robert W.; Anderson, Charles H.

1994-01-01

The structure of infrared cirrus clouds is analyzed with Laplacian pyramid transforms, a form of non-orthogonal wavelets. Pyramid and wavelet transforms provide a means to decompose images into their spatial frequency components such that all spatial scales are treated in an equivalent manner. The multiscale transform analysis is applied to IRAS 100 micrometer maps of cirrus emission in the north Galactic pole region to extract features on different scales. In the maps we identify filaments, fragments and clumps by separating all connected regions. These structures are analyzed with respect to their Hausdorff dimension for evidence of the scaling relationships in the cirrus clouds.

Defensive effects of extrafloral nectaries in quaking aspen differ with scale

Treesearch

Brent Mortensen; Diane Wagner; Patricia Doak

2010-01-01

The effects of plant defenses on herbivory can differ among spatial scales. This may be particularly common with indirect defenses, such as extrafloral nectarines (EFNs), that attract predatory arthropods and are dependent on predator distribution, abundance, and behavior. We tested the defensive effects of EFNs in quaking aspen (Populus tremuloides...

Multi-Scale Clustering of Lyme Disease Risk at the Expanding Leading Edge of the Range of Ixodes scapularis in Canada.

PubMed

Ripoche, Marion; Lindsay, Leslie Robbin; Ludwig, Antoinette; Ogden, Nicholas H; Thivierge, Karine; Leighton, Patrick A

2018-03-27

Since its detection in Canada in the early 1990s, Ixodes scapularis , the primary tick vector of Lyme disease in eastern North America, has continued to expand northward. Estimates of the tick's broad-scale distribution are useful for tracking the extent of the Lyme disease risk zone; however, tick distribution may vary widely within this zone. Here, we investigated I. scapularis nymph distribution at three spatial scales across the Lyme disease emergence zone in southern Quebec, Canada. We collected ticks and compared the nymph densities among different woodlands and different plots and transects within the same woodland. Hot spot analysis highlighted significant nymph clustering at each spatial scale. In regression models, nymph abundance was associated with litter depth, humidity, and elevation, which contribute to a suitable habitat for ticks, but also with the distance from the trail and the type of trail, which could be linked to host distribution and human disturbance. Accounting for this heterogeneous nymph distribution at a fine spatial scale could help improve Lyme disease management strategies but also help people to understand the risk variation around them and to adopt appropriate behaviors, such as staying on the trail in infested parks to limit their exposure to the vector and associated pathogens.

Multi-Scale Clustering of Lyme Disease Risk at the Expanding Leading Edge of the Range of Ixodes scapularis in Canada

PubMed Central

Lindsay, Leslie Robbin; Ludwig, Antoinette; Ogden, Nicholas H.; Thivierge, Karine; Leighton, Patrick A.

2018-01-01

Since its detection in Canada in the early 1990s, Ixodes scapularis, the primary tick vector of Lyme disease in eastern North America, has continued to expand northward. Estimates of the tick’s broad-scale distribution are useful for tracking the extent of the Lyme disease risk zone; however, tick distribution may vary widely within this zone. Here, we investigated I. scapularis nymph distribution at three spatial scales across the Lyme disease emergence zone in southern Quebec, Canada. We collected ticks and compared the nymph densities among different woodlands and different plots and transects within the same woodland. Hot spot analysis highlighted significant nymph clustering at each spatial scale. In regression models, nymph abundance was associated with litter depth, humidity, and elevation, which contribute to a suitable habitat for ticks, but also with the distance from the trail and the type of trail, which could be linked to host distribution and human disturbance. Accounting for this heterogeneous nymph distribution at a fine spatial scale could help improve Lyme disease management strategies but also help people to understand the risk variation around them and to adopt appropriate behaviors, such as staying on the trail in infested parks to limit their exposure to the vector and associated pathogens. PMID:29584627

MULTI-SCALED VULNERABILITY ANALYSES: IMPROVING DECISION-MAKING AT REGIONAL TO LOCAL LEVELS THROUGH PARTNERSHIP

EPA Science Inventory

Decision-makers at all scales are faced with setting priorities for both use of limited resources and for risk management. While there are all kinds of monitoring data and models to project conditions at different spatial and temporal scales, synthesized information to establish ...

Teachers' Concepts of Spatial Scale: An International Comparison

ERIC Educational Resources Information Center

Jones, M. Gail; Paechter, Manuela; Yen, Chiung-Fen; Gardner, Grant; Taylor, Amy; Tretter, Thomas

2013-01-01

Metric scale is an important concept taught as part of science curricula across different countries. This study explored metric and relative (body-length) scale concepts of inservice ("N"?=?92) and preservice ("N"?=?134) teachers from Austria, and Taiwan, and their concepts were compared with those of teachers from the USA.…

Multimodal integration of fMRI and EEG data for high spatial and temporal resolution analysis of brain networks

PubMed Central

Mantini, D.; Marzetti, L.; Corbetta, M.; Romani, G.L.; Del Gratta, C.

2017-01-01

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes. PMID:20052528

Impact of Spatial Scales on the Intercomparison of Climate Scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Wei; Steptoe, Michael; Chang, Zheng

2017-01-01

Scenario analysis has been widely applied in climate science to understand the impact of climate change on the future human environment, but intercomparison and similarity analysis of different climate scenarios based on multiple simulation runs remain challenging. Although spatial heterogeneity plays a key role in modeling climate and human systems, little research has been performed to understand the impact of spatial variations and scales on similarity analysis of climate scenarios. To address this issue, the authors developed a geovisual analytics framework that lets users perform similarity analysis of climate scenarios from the Global Change Assessment Model (GCAM) using a hierarchicalmore » clustering approach.« less

GIS-BASED HYDROLOGIC MODELING: THE AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT TOOL

EPA Science Inventory

Planning and assessment in land and water resource management are evolving from simple, local scale problems toward complex, spatially explicit regional ones. Such problems have to be
addressed with distributed models that can compute runoff and erosion at different spatial a...

Spatial and Temporal Patterns of Suspended Sediment Yields in Nested Urban Catchments

NASA Astrophysics Data System (ADS)

Kemper, J. T.; Miller, A. J.; Welty, C.

2017-12-01

In a highly regulated area such as the Chesapeake Bay watershed, suspended sediment is a matter of primary concern. Near real-time turbidity and discharge data have been collected continuously for more than four years at five stream gages representing three nested watershed scales (1-2 sq km, 5-6 sq km, 14 sq km) in the highly impervious Dead Run watershed, located in Baltimore County, MD. Using turbidity-concentration relationships based on sample analyses at the gage site, sediment yields for each station can be quantified for a variety of temporal scales. Sediment yields have been calculated for 60+ different storms across four years. Yields show significant spatial variation, both at equivalent sub-watershed scales and from headwaters to mouth. Yields are higher at the headwater station with older development and virtually no stormwater management (DR5) than at the station with more recent development and more extensive stormwater management (DR2). However, this pattern is reversed for the stations at the next larger scale: yields are lower at DR4, downstream of DR5, than at DR3, downstream of DR2. This suggests spatial variation in the dominant sediment sources within each subwatershed. Additionally, C-Q hysteresis curves display consistent counterclockwise behavior at the DR4 station, in contrast to the consistent clockwise behavior displayed at the DR3 station. This further suggests variation in dominant sediment sources (perhaps distal vs local, respectively). We observe consistent seasonal trends in the relative magnitudes of sediment yield for different subwatersheds (e.g. DR3>DR4 in summer, DR5>DR2 in spring). We also observe significant year-to-year variation in sediment yield at the headwater and intermediate scales, whereas yields at the 14 sq km scale are largely similar across the monitored years. This observation would be consistent with the possibility that internal storage and remobilization tend to modulate downstream yields even with spatial and temporal variation in upstream sources. The fine-scale design of this study represents a unique opportunity to compare and contrast sediment yields across a variety of spatial and temporal scales, and provide insight into sediment transport dynamics within an urbanized watershed.

The scale dependence of optical diversity in a prairie ecosystem

NASA Astrophysics Data System (ADS)

Gamon, J. A.; Wang, R.; Stilwell, A.; Zygielbaum, A. I.; Cavender-Bares, J.; Townsend, P. A.

2015-12-01

Biodiversity loss, one of the most crucial challenges of our time, endangers ecosystem services that maintain human wellbeing. Traditional methods of measuring biodiversity require extensive and costly field sampling by biologists with extensive experience in species identification. Remote sensing can be used for such assessment based upon patterns of optical variation. This provides efficient and cost-effective means to determine ecosystem diversity at different scales and over large areas. Sampling scale has been described as a "fundamental conceptual problem" in ecology, and is an important practical consideration in both remote sensing and traditional biodiversity studies. On the one hand, with decreasing spatial and spectral resolution, the differences among different optical types may become weak or even disappear. Alternately, high spatial and/or spectral resolution may introduce redundant or contradictory information. For example, at high resolution, the variation within optical types (e.g., between leaves on a single plant canopy) may add complexity unrelated to specie richness. We studied the scale-dependence of optical diversity in a prairie ecosystem at Cedar Creek Ecosystem Science Reserve, Minnesota, USA using a variety of spectrometers from several platforms on the ground and in the air. Using the coefficient of variation (CV) of spectra as an indicator of optical diversity, we found that high richness plots generally have a higher coefficient of variation. High resolution imaging spectrometer data (1 mm pixels) showed the highest sensitivity to richness level. With decreasing spatial resolution, the difference in CV between richness levels decreased, but remained significant. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods.

A Physically Based Runoff Routing Model for Land Surface and Earth System Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Hongyi; Wigmosta, Mark S.; Wu, Huan

2013-06-13

A new physically based runoff routing model, called the Model for Scale Adaptive River Transport (MOSART), has been developed to be applicable across local, regional, and global scales. Within each spatial unit, surface runoff is first routed across hillslopes and then discharged along with subsurface runoff into a ‘‘tributary subnetwork’’ before entering the main channel. The spatial units are thus linked via routing through the main channel network, which is constructed in a scale-consistent way across different spatial resolutions. All model parameters are physically based, and only a small subset requires calibration.MOSART has been applied to the Columbia River basinmore » at 1/ 168, 1/ 88, 1/ 48, and 1/ 28 spatial resolutions and was evaluated using naturalized or observed streamflow at a number of gauge stations. MOSART is compared to two other routing models widely used with land surface models, the River Transport Model (RTM) in the Community Land Model (CLM) and the Lohmann routing model, included as a postprocessor in the Variable Infiltration Capacity (VIC) model package, yielding consistent performance at multiple resolutions. MOSART is further evaluated using the channel velocities derived from field measurements or a hydraulic model at various locations and is shown to be capable of producing the seasonal variation and magnitude of channel velocities reasonably well at different resolutions. Moreover, the impacts of spatial resolution on model simulations are systematically examined at local and regional scales. Finally, the limitations ofMOSART and future directions for improvements are discussed.« less

Fine-Scale Habitat Segregation between Two Ecologically Similar Top Predators.

PubMed

Palomares, Francisco; Fernández, Néstor; Roques, Severine; Chávez, Cuauhtemoc; Silveira, Leandro; Keller, Claudia; Adrados, Begoña

2016-01-01

Similar, coexisting species often segregate along the spatial ecological axis. Here, we examine if two top predators (jaguars and pumas) present different fine-scale habitat use in areas of coexistence, and discuss if the observed pattern can be explained by the risk of interference competition between them. Interference competition theory predicts that pumas should avoid habitats or areas used by jaguars (the dominant species), and as a consequence should present more variability of niche parameters across study areas. We used non-invasive genetic sampling of faeces in 12 different areas and sensor satellite fine-scale habitat indices to answer these questions. Meta-analysis confirmed differences in fine-scale habitat use between jaguars and pumas. Furthermore, average marginality of the realized niches of pumas was more variable than those of jaguars, and tolerance (a measure of niche breadth) was on average 2.2 times higher in pumas than in jaguars, as expected under the interference competition risk hypothesis. The use of sensor satellite fine-scale habitat indices allowed the detection of subtle differences in the environmental characteristics of the habitats used by these two similar top predators, which, as a rule, until now were recorded using the same general habitat types. The detection of fine spatial segregation between these two top predators was scale-dependent.

Multiple Scale Analysis of the Dynamic State Index (DSI)

NASA Astrophysics Data System (ADS)

Müller, A.; Névir, P.

2016-12-01

The Dynamic State Index (DSI) is a novel parameter that indicates local deviations of the atmospheric flow field from a stationary, inviscid and adiabatic solution of the primitive equations of fluid mechanics. This is in contrast to classical methods, which often diagnose deviations from temporal or spatial mean states. We show some applications of the DSI to atmospheric flow phenomena on different scales. The DSI is derived from the Energy-Vorticity-Theory (EVT) which is based on two global conserved quantities, the total energy and Ertel's potential enstrophy. Locally, these global quantities lead to the Bernoulli function and the PV building together with the potential temperature the DSI.If the Bernoulli function and the PV are balanced, the DSI vanishes and the basic state is obtained. Deviations from the basic state provide an indication of diabatic and non-stationary weather events. Therefore, the DSI offers a tool to diagnose and even prognose different atmospheric events on different scales.On synoptic scale, the DSI can help to diagnose storms and hurricanes, where also the dipole structure of the DSI plays an important role. In the scope of the collaborative research center "Scaling Cascades in Complex Systems" we show high correlations between the DSI and precipitation on convective scale. Moreover, we compare the results with reduced models and different spatial resolutions.

Evaluating Water Budget Closure Across Spatial Scales: An Observational Approach through Texas Water Observatory

NASA Astrophysics Data System (ADS)

Gaur, N.; Jaimes, A.; Vaughan, S.; Morgan, C.; Moore, G. W.; Miller, G. R.; Everett, M. E.; Lawing, M.; Mohanty, B.

2017-12-01

Applications varying from improving water conservation practices at the field scale to predicting global hydrology under a changing climate depend upon our ability to achieve water budget closure. 1) Prevalent heterogeneity in soils, geology and land-cover, 2) uncertainties in observations and 3) space-time scales of our control volume and available data are the main factors affecting the percentage of water budget closure that we can achieve. The Texas Water Observatory presents a unique opportunity to observe the major components of the water cycle (namely precipitation, evapotranspiration, root zone soil moisture, streamflow and groundwater) in varying eco-hydrological regions representative of the lower Brazos River basin at multiple scales. The soils in these regions comprise of heavy clays that swell and shrink to create complex preferential pathways in the sub-surface, thus, making the hydrology in this region difficult to quantify. This work evaluates the water budget of the region by varying the control volume in terms of 3 temporal (weekly, monthly and seasonal) and 3 different spatial scales. The spatial scales are 1) Point scale - that is typical for process understanding of water dynamics, 2) Eddy Covariance footprint scale - that is typical of most eco-hydrological applications at the field scale and, 3) Satellite footprint scale- that is typically used in regional and global hydrological analysis. We employed a simple water balance model to evaluate the water budget at all scales. The point scale water budget was assessed using direct observations from hydro-geo-thematically located observation locations within different eddy covariance footprints. At the eddy covariance footprint scale, the sub-surface of each eddy covariance footprint was intensively characterized using electromagnetic induction (EM 38) and the resultant data was used to calculate the inter-point variability to upscale the sub-surface storage while the satellite scale water budget was evaluated using SMAP satellite observations supplemented with reanalysis products. At the point scale, we found differences in sub-surface storage in the same land-cover depending on the landscape position of the observation point while land-cover significantly affected water budget at the larger scales.

Modelling field scale spatial variation in water run-off, soil moisture, N2O emissions and herbage biomass of a grazed pasture using the SPACSYS model.

PubMed

Liu, Yi; Li, Yuefen; Harris, Paul; Cardenas, Laura M; Dunn, Robert M; Sint, Hadewij; Murray, Phil J; Lee, Michael R F; Wu, Lianhai

2018-04-01

In this study, we evaluated the ability of the SPACSYS model to simulate water run-off, soil moisture, N 2 O fluxes and grass growth using data generated from a field of the North Wyke Farm Platform. The field-scale model is adapted via a linked and grid-based approach (grid-to-grid) to account for not only temporal dynamics but also the within-field spatial variation in these key ecosystem indicators. Spatial variability in nutrient and water presence at the field-scale is a key source of uncertainty when quantifying nutrient cycling and water movement in an agricultural system. Results demonstrated that the new spatially distributed version of SPACSYS provided a worthy improvement in accuracy over the standard (single-point) version for biomass productivity. No difference in model prediction performance was observed for water run-off, reflecting the closed-system nature of this variable. Similarly, no difference in model prediction performance was found for N 2 O fluxes, but here the N 2 O predictions were noticeably poor in both cases. Further developmental work, informed by this study's findings, is proposed to improve model predictions for N 2 O. Soil moisture results with the spatially distributed version appeared promising but this promise could not be objectively verified.

A three-dimensional spatial mapping approach to quantify fine-scale heterogeneity among leaves within canopies1

PubMed Central

Wingfield, Jenna L.; Ruane, Lauren G.; Patterson, Joshua D.

2017-01-01

Premise of the study: The three-dimensional structure of tree canopies creates environmental heterogeneity, which can differentially influence the chemistry, morphology, physiology, and/or phenology of leaves. Previous studies that subdivide canopy leaves into broad categories (i.e., “upper/lower”) fail to capture the differences in microenvironments experienced by leaves throughout the three-dimensional space of a canopy. Methods: We use a three-dimensional spatial mapping approach based on spherical polar coordinates to examine the fine-scale spatial distributions of photosynthetically active radiation (PAR) and the concentration of ultraviolet (UV)-absorbing compounds (A300) among leaves within the canopies of black mangroves (Avicennia germinans). Results: Linear regressions revealed that interior leaves received less PAR and produced fewer UV-absorbing compounds than leaves on the exterior of the canopy. By allocating more UV-absorbing compounds to the leaves on the exterior of the canopy, black mangroves may be maximizing UV-protection while minimizing biosynthesis of UV-absorbing compounds. Discussion: Three-dimensional spatial mapping provides an inexpensive and portable method to detect fine-scale differences in environmental and biological traits within canopies. We used it to understand the relationship between PAR and A300, but the same approach can also be used to identify traits associated with the spatial distribution of herbivores, pollinators, and pathogens. PMID:29188145

Temporal and spatial scaling of the genetic structure of a vector-borne plant pathogen.

PubMed

Coletta-Filho, Helvécio D; Francisco, Carolina S; Almeida, Rodrigo P P

2014-02-01

The ecology of plant pathogens of perennial crops is affected by the long-lived nature of their immobile hosts. In addition, changes to the genetic structure of pathogen populations may affect disease epidemiology and management practices; examples include local adaptation of more fit genotypes or introduction of novel genotypes from geographically distant areas via human movement of infected plant material or insect vectors. We studied the genetic structure of Xylella fastidiosa populations causing disease in sweet orange plants in Brazil at multiple scales using fast-evolving molecular markers (simple-sequence DNA repeats). Results show that populations of X. fastidiosa were regionally isolated, and that isolation was maintained for populations analyzed a decade apart from each other. However, despite such geographic isolation, local populations present in year 2000 were largely replaced by novel genotypes in 2009 but not as a result of migration. At a smaller spatial scale (individual trees), results suggest that isolates within plants originated from a shared common ancestor. In summary, new insights on the ecology of this economically important plant pathogen were obtained by sampling populations at different spatial scales and two different time points.

Effect of spatial organisation behaviour on upscaling the overland flow formation in an arable land

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Blöschl, Günter

2014-05-01

Overland flow during rainfall events on arable land is important to investigate as it affects the land erosion process and water quality in the river. The formation of overland flow may happen through different ways (i.e. Hortonian overland flow, saturation excess overland flow) which is influenced by the surface and subsurface soil characteristics (i.e. land cover, soil infiltration rate). As the soil characteristics vary throughout the entire catchment, it will form distinct spatial patterns with organised or random behaviour. During the upscaling of hydrological processes from plot to catchment scale, this behaviour will become substantial since organised patterns will result in higher spatial connectivity and thus higher conductivity. However, very few of the existing studies explicitly address this effect of spatial organisations of the patterns in upscaling the hydrological processes to the catchment scale. This study will assess the upscaling of overland flow formation with concerns of spatial organisation behaviour of the patterns by application of direct field observations under natural conditions using video camera and soil moisture sensors and investigation of the underlying processes using a physical-based hydrology model. The study area is a Hydrological Open Air Laboratory (HOAL) located at Petzenkirchen, Lower Austria. It is a 64 ha catchment with land use consisting of arable land (87%), forest (6%), pasture (5%) and paved surfaces (2%). A video camera is installed 7m above the ground on a weather station mast in the middle of the arable land to monitor the overland flow patterns during rainfall events in a 2m x 6m plot scale. Soil moisture sensors with continuous measurement at different depth (5, 10, 20 and 50cm) are installed at points where the field is monitored by the camera. The patterns of overland flow formation and subsurface flow state at the plot scale will be generated using a coupled surface-subsurface flow physical-based hydrology model. The observation data will be assimilated into the model to verify the corresponding processes between surface and subsurface flow during the rainfall events. The patterns of conductivity then will be analyzed at catchment scale using the spatial stochastic analysis based on the classification of soil characteristics of the entire catchment. These patterns of conductivity then will be applied in the model at catchment scale to see how the organisational behaviour can affect the spatial connectivity of the hydrological processes and the results of the catchment response. A detailed modelling of the underlying processes in the physical-based model will allow us to see the direct effect of the spatial connectivity to the occurring surface and subsurface flow. This will improve the analysis of the effect of spatial organisations of the patterns in upscaling the hydrological processes from plot to catchment scale.

Scale-Dependence of Processes Structuring Dung Beetle Metacommunities Using Functional Diversity and Community Deconstruction Approaches

PubMed Central

da Silva, Pedro Giovâni; Hernández, Malva Isabel Medina

2015-01-01

Community structure is driven by mechanisms linked to environmental, spatial and temporal processes, which have been successfully addressed using metacommunity framework. The relative importance of processes shaping community structure can be identified using several different approaches. Two approaches that are increasingly being used are functional diversity and community deconstruction. Functional diversity is measured using various indices that incorporate distinct community attributes. Community deconstruction is a way to disentangle species responses to ecological processes by grouping species with similar traits. We used these two approaches to determine whether they are improvements over traditional measures (e.g., species composition, abundance, biomass) for identification of the main processes driving dung beetle (Scarabaeinae) community structure in a fragmented mainland-island landscape in southern Brazilian Atlantic Forest. We sampled five sites in each of four large forest areas, two on the mainland and two on the island. Sampling was performed in 2012 and 2013. We collected abundance and biomass data from 100 sampling points distributed over 20 sampling sites. We studied environmental, spatial and temporal effects on dung beetle community across three spatial scales, i.e., between sites, between areas and mainland-island. The γ-diversity based on species abundance was mainly attributed to β-diversity as a consequence of the increase in mean α- and β-diversity between areas. Variation partitioning on abundance, biomass and functional diversity showed scale-dependence of processes structuring dung beetle metacommunities. We identified two major groups of responses among 17 functional groups. In general, environmental filters were important at both local and regional scales. Spatial factors were important at the intermediate scale. Our study supports the notion of scale-dependence of environmental, spatial and temporal processes in the distribution and functional organization of Scarabaeinae beetles. We conclude that functional diversity may be used as a complementary approach to traditional measures, and that community deconstruction allows sufficient disentangling of responses of different trait-based groups. PMID:25822150

Spatial variation in disease resistance: from molecules to metapopulations

PubMed Central

Laine, Anna-Liisa; Burdon, Jeremy J.; Dodds, Peter N.; Thrall, Peter H.

2010-01-01

Summary Variation in disease resistance is a widespread phenomenon in wild plant-pathogen associations. Here, we review current literature on natural plant-pathogen associations to determine how diversity in disease resistance is distributed at different hierarchical levels – within host individuals, within host populations, among host populations at the metapopulation scale and at larger regional scales. We find diversity in resistance across all spatial scales examined. Furthermore, variability seems to be the best counter-defence of plants against their rapidly evolving pathogens. We find that higher diversity of resistance phenotypes also results in higher levels of resistance at the population level. Overall, we find that wild plant populations are more likely to be susceptible than resistant to their pathogens. However, the degree of resistance differs strikingly depending on the origin of the pathogen strains used in experimental inoculation studies. Plant populations are on average 16% more resistant to allopatric pathogen strains than they are to strains that occur within the same population (48 % vs. 32 % respectively). Pathogen dispersal mode affects levels of resistance in natural plant populations with lowest levels detected for hosts of airborne pathogens and highest for waterborne pathogens. Detailed analysis of two model systems, Linum marginale infected by Melampsora lini, and Plantago lanceolata infected by Podosphaera plantaginis, show that the amount of variation in disease resistance declines towards higher spatial scales as we move from individual hosts to metapopulations, but evaluation of multiple spatial scales is needed to fully capture the structure of disease resistance. Synthesis: Variation in disease resistance is ubiquitous in wild plant-pathogen associations. While the debate over whether the resistance structure of plant populations is determined by pathogen-imposed selection versus non-adaptive processes remains unresolved, we do report examples of pathogen-imposed selection on host resistance. Here we highlight the importance of measuring resistance across multiple spatial scales, and of using sympatric strains when looking for signs of coevolution in wild plant-pathogen interactions. PMID:21243068

Does Encope emarginata (Echinodermata: Echinoidea) affect spatial variation patterns of estuarine subtidal meiofauna and microphytobenthos?

NASA Astrophysics Data System (ADS)

Brustolin, Marco C.; Thomas, Micheli C.; Mafra, Luiz L.; Lana, Paulo da Cunha

2014-08-01

Foraging macrofauna, such as the sand dollar Encope emarginata, can modify sediment properties and affect spatial distribution patterns of microphytobenthos and meiobenthos at different spatial scales. We adopted a spatial hierarchical approach composed of five spatial levels (km, 100 s m, 10 s m, 1 s m and cm) to describe variation patterns of microphytobenthos, meiobenthos and sediment variables in shallow subtidal regions in the subtropical Paranaguá Bay (Southern Brazil) with live E. emarginata (LE), dead E. emarginata (only skeletons - (DE), and no E. emarginata (WE). The overall structure of microphytobenthos and meiofauna was always less variable at WE and much of variation at the scale of 100 s m was related to variability within LE and DE, due to foraging activities or to the presence of shell hashes. Likewise, increased variability in chlorophyll-a and phaeopigment contents was observed among locations within LE, although textural parameters of sediment varied mainly at smaller scales. Variations within LE were related to changes on the amount and quality of food as a function of sediment heterogeneity induced by the foraging behavior of sand dollars. We provide strong evidence that top-down effects related to the occurrence of E. emarginata act in synergy with bottom-up structuring related to hydrodynamic processes in determining overall benthic spatial variability. Conversely, species richness is mainly influenced by environmental heterogeneity at small spatial scales (centimeters to meters), which creates a mosaic of microhabitats.

Habitat and Scale Shape the Demographic Fate of the Keystone Sea Urchin Paracentrotus lividus in Mediterranean Macrophyte Communities

PubMed Central

Prado, Patricia; Tomas, Fiona; Pinna, Stefania; Farina, Simone; Roca, Guillem; Ceccherelli, Giulia; Romero, Javier; Alcoverro, Teresa

2012-01-01

Demographic processes exert different degrees of control as individuals grow, and in species that span several habitats and spatial scales, this can influence our ability to predict their population at a particular life-history stage given the previous life stage. In particular, when keystone species are involved, this relative coupling between demographic stages can have significant implications for the functioning of ecosystems. We examined benthic and pelagic abundances of the sea urchin Paracentrotus lividus in order to: 1) understand the main life-history bottlenecks by observing the degree of coupling between demographic stages; and 2) explore the processes driving these linkages. P. lividus is the dominant invertebrate herbivore in the Mediterranean Sea, and has been repeatedly observed to overgraze shallow beds of the seagrass Posidonia oceanica and rocky macroalgal communities. We used a hierarchical sampling design at different spatial scales (100 s, 10 s and <1 km) and habitats (seagrass and rocky macroalgae) to describe the spatial patterns in the abundance of different demographic stages (larvae, settlers, recruits and adults). Our results indicate that large-scale factors (potentially currents, nutrients, temperature, etc.) determine larval availability and settlement in the pelagic stages of urchin life history. In rocky macroalgal habitats, benthic processes (like predation) acting at large or medium scales drive adult abundances. In contrast, adult numbers in seagrass meadows are most likely influenced by factors like local migration (from adjoining rocky habitats) functioning at much smaller scales. The complexity of spatial and habitat-dependent processes shaping urchin populations demands a multiplicity of approaches when addressing habitat conservation actions, yet such actions are currently mostly aimed at managing predation processes and fish numbers. We argue that a more holistic ecosystem management also needs to incorporate the landscape and habitat-quality level processes (eutrophication, fragmentation, etc.) that together regulate the populations of this keystone herbivore. PMID:22536355

Multiscale comparison of GPM radar and passive microwave precipitation fields over oceans and land: effective resolution and global/regional/local diagnostics for improving retrieval algorithms

NASA Astrophysics Data System (ADS)

Guilloteau, C.; Foufoula-Georgiou, E.; Kummerow, C.; Kirstetter, P. E.

2017-12-01

A multiscale approach is used to compare precipitation fields retrieved from GMI using the last version of the GPROF algorithm (GPROF-2017) to the DPR fields all over the globe. Using a wavelet-based spectral analysis, which renders the multi-scale decompositions of the original fields independent of each other spatially and across scales, we quantitatively assess the various scales of variability of the retrieved fields, and thus define the spatially-variable "effective resolution" (ER) of the retrievals. Globally, a strong agreement is found between passive microwave and radar patterns at scales coarser than 80km. Over oceans the patterns match down to the 20km scale. Over land, comparison statistics are spatially heterogeneous. In most areas a strong discrepancy is observed between passive microwave and radar patterns at scales finer than 40-80km. The comparison is also supported by ground-based observations over the continental US derived from the NOAA/NSSL MRMS suite of products. While larger discrepancies over land than over oceans are classically explained by land complex surface emissivity perturbing the passive microwave retrieval, other factors are investigated here, such as intricate differences in the storm structure over oceans and land. Differences in term of statistical properties (PDF of intensities and spatial organization) of precipitation fields over land and oceans are assessed from radar data, as well as differences in the relation between the 89GHz brightness temperature and precipitation. Moreover, the multiscale approach allows quantifying the part of discrepancies caused by miss-match of the location of intense cells and instrument-related geometric effects. The objective is to diagnose shortcomings of current retrieval algorithms such that targeted improvements can be made to achieve over land the same retrieval performance as over oceans.

Damage spreading in spatial and small-world random Boolean networks

NASA Astrophysics Data System (ADS)

Lu, Qiming; Teuscher, Christof

2014-02-01

The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean networks (RBNs) are commonly used as a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other nonrandom connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the Hamming distance at very low connectivities (K¯≪1) and that the critical connectivity of stability Ks changes compared to random networks. At higher K¯, this scaling remains unchanged. We also show that the Hamming distance of spatially local networks scales with a power law as the system size N increases, but with a different exponent for local and small-world networks. The scaling arguments for small-world networks are obtained with respect to the system sizes and strength of spatially local connections. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.

Cross-scale feedbacks and scale mismatches as influences on cultural services and the resilience of protected areas.

PubMed

Maciejewski, Kristine; De Vos, Alta; Cumming, Graeme S; Moore, Christine; Biggs, Duan

2015-01-01

Protected areas are a central strategy for achieving global conservation goals, but their continued existence depends heavily on maintaining sufficient social and political support to outweigh economic interests or other motives for land conversion. Thus, the resilience of protected areas can be considered a function of their perceived benefits to society. Nature-based tourism (NBT), a cultural ecosystem service, provides a key source of income to protected areas, facilitating a sustainable solution to conservation. The ability of tourism to generate income depends, however, on both the scales at which this cultural service is provided and the scales at which tourists respond to services on offer. This observation raises a set of location-, context-, and scale-related questions that need to be confronted before we can understand and value cultural service provision appropriately. We combine elements of resilience analysis with a systems ecology framework and apply this to NBT in protected areas to investigate cross-scale interactions and scale mismatches. We postulate that cross-scale effects can either have a positive effect on protected area resilience or lead to scale mismatches, depending on their interactions with cross-scale feedbacks. To demonstrate this, we compare spatial scales and nested levels of institutions to develop a typology of scale mismatches for common scenarios in NBT. In our new typology, the severity of a scale mismatch is expressed as the ratio of spatial scale to institutional level, producing 25 possible outcomes with differing consequences for system resilience. We predict that greater differences between interacting scales and levels, and greater magnitudes of cross-scale interactions, will lead to greater magnitudes of scale mismatch. Achieving a better understanding of feedbacks and mismatches, and finding ways of aligning spatial and institutional scales, will be critical for strengthening the resilience of protected areas that depend on NBT.

SEX DIFFERENCES ON THE WECHSLER INTELLIGENCE SCALE FOR CHILDREN-III IN BAHRAIN AND THE UNITED STATES.

PubMed

Bakhiet, Salaheldin Farah Attallah; Lynn, Richard

2015-12-01

Sex differences on the Wechsler Intelligence Scale for Children-III (WISC-III) are reported for children in Bahrain and the United States. The results for the two samples were consistent in showing no significant differences in Verbal, Performance, and Full Scale IQs, higher average scores by boys on the Block design and Mazes subtests of spatial ability, and higher average scores by girls on Coding. There was also greater variability in boys than in girls.

The Speech, Spatial and Qualities of Hearing Scale (SSQ)

PubMed Central

Gatehouse, Stuart; Noble, William

2017-01-01

The Speech, Spatial and Qualities of Hearing Scale (SSQ) is designed to measure a range of hearing disabilities across several domains. Particular attention is given to hearing speech in a variety of competing contexts, and to the directional, distance and movement components of spatial hearing. In addition, the abilities both to segregate sounds and to attend to simultaneous speech streams are assessed, reflecting the reality of hearing in the everyday world. Qualities of hearing experience include ease of listening, and the naturalness, clarity and identifiability of different speakers, different musical pieces and instruments, and different everyday sounds. Application of the SSQ to 153 new clinic clients prior to hearing aid fitting showed that the greatest difficulty was experienced with simultaneous speech streams, ease of listening, listening in groups and in noise, and judging distance and movement. SSQ ratings were compared with an independent measure of handicap. After differences in hearing level were controlled for, it was found that identification, attention and effort problems, as well as spatial hearing problems, feature prominently in the disability–handicap relationship, along with certain features of speech hearing. The results implicate aspects of temporal and spatial dynamics of hearing disability in the experience of handicap. The SSQ shows promise as an instrument for evaluating interventions of various kinds, particularly (but not exclusively) those that implicate binaural function. PMID:15035561

[Scale effect of Nanjing urban green infrastructure network pattern and connectivity analysis.

PubMed

Yu, Ya Ping; Yin, Hai Wei; Kong, Fan Hua; Wang, Jing Jing; Xu, Wen Bin

2016-07-01

Based on ArcGIS, Erdas, GuidosToolbox, Conefor and other software platforms, using morphological spatial pattern analysis (MSPA) and landscape connectivity analysis methods, this paper quantitatively analysed the scale effect, edge effect and distance effect of the Nanjing urban green infrastructure network pattern in 2013 by setting different pixel sizes (P) and edge widths in MSPA analysis, and setting different dispersal distance thresholds in landscape connectivity analysis. The results showed that the type of landscape acquired based on the MSPA had a clear scale effect and edge effect, and scale effects only slightly affected landscape types, whereas edge effects were more obvious. Different dispersal distances had a great impact on the landscape connectivity, 2 km or 2.5 km dispersal distance was a critical threshold for Nanjing. When selecting the pixel size 30 m of the input data and the edge wide 30 m used in the morphological model, we could get more detailed landscape information of Nanjing UGI network. Based on MSPA and landscape connectivity, analysis of the scale effect, edge effect, and distance effect on the landscape types of the urban green infrastructure (UGI) network was helpful for selecting the appropriate size, edge width, and dispersal distance when developing these networks, and for better understanding the spatial pattern of UGI networks and the effects of scale and distance on the ecology of a UGI network. This would facilitate a more scientifically valid set of design parameters for UGI network spatiotemporal pattern analysis. The results of this study provided an important reference for Nanjing UGI networks and a basis for the analysis of the spatial and temporal patterns of medium-scale UGI landscape networks in other regions.

Probing Mantle Heterogeneity Across Spatial Scales

NASA Astrophysics Data System (ADS)

Hariharan, A.; Moulik, P.; Lekic, V.

2017-12-01

Inferences of mantle heterogeneity in terms of temperature, composition, grain size, melt and crystal structure may vary across local, regional and global scales. Probing these scale-dependent effects require quantitative comparisons and reconciliation of tomographic models that vary in their regional scope, parameterization, regularization and observational constraints. While a range of techniques like radial correlation functions and spherical harmonic analyses have revealed global features like the dominance of long-wavelength variations in mantle heterogeneity, they have limited applicability for specific regions of interest like subduction zones and continental cratons. Moreover, issues like discrepant 1-D reference Earth models and related baseline corrections have impeded the reconciliation of heterogeneity between various regional and global models. We implement a new wavelet-based approach that allows for structure to be filtered simultaneously in both the spectral and spatial domain, allowing us to characterize heterogeneity on a range of scales and in different geographical regions. Our algorithm extends a recent method that expanded lateral variations into the wavelet domain constructed on a cubed sphere. The isolation of reference velocities in the wavelet scaling function facilitates comparisons between models constructed with arbitrary 1-D reference Earth models. The wavelet transformation allows us to quantify the scale-dependent consistency between tomographic models in a region of interest and investigate the fits to data afforded by heterogeneity at various dominant wavelengths. We find substantial and spatially varying differences in the spectrum of heterogeneity between two representative global Vp models constructed using different data and methodologies. Applying the orthonormality of the wavelet expansion, we isolate detailed variations in velocity from models and evaluate additional fits to data afforded by adding such complexities to long-wavelength variations. Our method provides a way to probe and evaluate localized features in a multi-scale description of mantle heterogeneity.

The sense and non-sense of plot-scale, catchment-scale, continental-scale and global-scale hydrological modelling

NASA Astrophysics Data System (ADS)

Bronstert, Axel; Heistermann, Maik; Francke, Till

2017-04-01

Hydrological models aim at quantifying the hydrological cycle and its constituent processes for particular conditions, sites or periods in time. Such models have been developed for a large range of spatial and temporal scales. One must be aware that the question which is the appropriate scale to be applied depends on the overall question under study. Therefore, it is not advisable to give a general applicable guideline on what is "the best" scale for a model. This statement is even more relevant for coupled hydrological, ecological and atmospheric models. Although a general statement about the most appropriate modelling scale is not recommendable, it is worth to have a look on what are the advantages and the shortcomings of micro-, meso- and macro-scale approaches. Such an appraisal is of increasing importance, since increasingly (very) large / global scale approaches and models are under operation and therefore the question arises how far and for what purposes such methods may yield scientifically sound results. It is important to understand that in most hydrological (and ecological, atmospheric and other) studies process scale, measurement scale, and modelling scale differ from each other. In some cases, the differences between theses scales can be of different orders of magnitude (example: runoff formation, measurement and modelling). These differences are a major source of uncertainty in description and modelling of hydrological, ecological and atmospheric processes. Let us now summarize our viewpoint of the strengths (+) and weaknesses (-) of hydrological models of different scales: Micro scale (e.g. extent of a plot, field or hillslope): (+) enables process research, based on controlled experiments (e.g. infiltration; root water uptake; chemical matter transport); (+) data of state conditions (e.g. soil parameter, vegetation properties) and boundary fluxes (e.g. rainfall or evapotranspiration) are directly measurable and reproducible; (+) equations based on first principals, partly pde-type, are available for several processes (but not for all), because measurement and modelling scale are compatible (-) the spatial model domain are hardly representative for larger spatial entities, including regions for which water resources management decisions are to be taken; straightforward upsizing is also limited by data availability and computational requirements. Meso scale (e.g. extent of a small to large catchment or region): (+) the spatial extent of the model domain has approximately the same extent as the regions for which water resources management decisions are to be taken. I.e., such models enable water resources quantification at the scale of most water management decisions; (+) data of some state conditions (e.g. vegetation cover, topography, river network and cross sections) are available; (+) data of some boundary fluxes (in particular surface runoff / channel flow) are directly measurable with mostly sufficient certainty; (+) equations, partly based on simple water budgeting, partly variants of pde-type equations, are available for most hydrological processes. This enables the construction of meso-scale distributed models reflecting the spatial heterogeneity of regions/landscapes; (-) process scale, measurement scale, and modelling scale differ from each other for a number of processes, e.g., such as runoff generation; (-) the process formulation (usually derived from micro-scale studies) cannot directly be transferred to the modelling domain. Upscaling procedures for this purpose are not readily and generally available. Macro scale (e.g. extent of a continent up to global): (+) the spatial extent of the model may cover the whole Earth. This enables an attractive global display of model results; (+) model results might be technically interchangeable or at least comparable with results from other global models, such as global climate models; (-) process scale, measurement scale, and modelling scale differ heavily from each other for all hydrological and associated processes; (-) the model domain and its results are not representative regions for which water resources management decisions are to be taken. (-) both state condition and boundary flux data are hardly available for the whole model domain. Water management data and discharge data from remote regions are particular incomplete / unavailable for this scale. This undermines the model's verifiability; (-) since process formulation and resulting modelling reliability at this scale is very limited, such models can hardly show any explanatory skills or prognostic power; (-) since both the entire model domain and the spatial sub-units cover large areas, model results represent values averaged over at least the spatial sub-unit's extent. In many cases, the applied time scale implies a long-term averaging in time, too. We emphasize the importance to be aware of the above mentioned strengths and weaknesses of those scale-specific models. (Many of the) results of the current global model studies do not reflect such limitations. In particular, we consider the averaging over large model entities in space and/or time inadequate. Many hydrological processes are of a non-linear nature, including threshold-type behaviour. Such features cannot be reflected by such large scale entities. The model results therefore can be of little or no use for water resources decisions and/or even misleading for public debates or decision making. Some rather newly developed sustainability concepts, e.g. "Planetary Boundaries" in which humanity may "continue to develop and thrive for generations to come" are based on such global-scale approaches and models. However, many of the major problems regarding sustainability on Earth, e.g. water scarcity, do not exhibit on a global but on a regional scale. While on a global scale water might look like being available in sufficient quantity and quality, there are many regions where water problems already have very harmful or even devastating effects. Therefore, it is the challenge to derive models and observation programmes for regional scales. In case a global display is desired future efforts should be directed towards the development of a global picture based on a mosaic of regional sound assessments, rather than "zooming into" the results of large-scale simulations. Still, a key question remains to be discussed, i.e. for which purpose models at this (global) scale can be used.

Interpreting Carbon Fluxes from a Spatially Heterogeneous Peatland with Thawing Permafrost: Scaling from Plant Community Scale to Ecosystem Scale

NASA Astrophysics Data System (ADS)

Harder, S. R.; Roulet, N. T.; Strachan, I. B.; Crill, P. M.; Persson, A.; Pelletier, L.; Watt, C.

2014-12-01

Various microforms, created by spatial differential thawing of permafrost, make up the subarctic heterogeneous Stordalen peatland complex (68°22'N, 19°03'E), near Abisko, Sweden. This results in significantly different peatland vegetation communities across short distances, as well as differences in wetness, temperature and peat substrates. We have been measuring the spatially integrated CO2, heat and water vapour fluxes from this peatland complex using eddy covariance and the CO2 exchange from specific plant communities within the EC tower footprint since spring 2008. With this data we are examining if it is possible to derive the spatially integrated ecosystem-wide fluxes from community-level simple light use efficiency (LUE) and ecosystem respiration (ER) models. These models have been developed using several years of continuous autochamber flux measurements for the three major plant functional types (PFTs) as well as knowledge of the spatial variability of the vegetation, water table and active layer depths. LIDAR was used to produce a 1 m resolution digital evaluation model of the complex and the spatial distribution of PFTs was obtained from concurrent high-resolution digital colour air photography trained from vegetation surveys. Continuous water table depths have been measured for four years at over 40 locations in the complex, and peat temperatures and active layer depths are surveyed every 10 days at more than 100 locations. The EC footprint is calculated for every half-hour and the PFT based models are run with the corresponding environmental variables weighted for the PFTs within the EC footprint. Our results show that the Sphagnum, palsa, and sedge PFTs have distinctly different LUE models, and that the tower fluxes are dominated by a blend of the Sphagnum and palsa PFTs. We also see a distinctly different energy partitioning between the fetches containing intact palsa and those with thawed palsa: the evaporative efficiency is higher and the Bowen ration lower for the thawed palsa fetches.

EVALUATING HYDROLOGICAL RESPONSE TO ...

EPA Pesticide Factsheets

Studies of future management and policy options based on different assumptions provide a mechanism to examine possible outcomes and especially their likely benefits or consequences. Planning and assessment in land and water resource management are evolving toward complex, spatially explicit regional assessments. These problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and temporal scales. The extensive data requirements and the difficult task of building input parameter files, however, have long been an obstacle to the timely and cost-effective use of such complex models by resource managers. The U.S. EPA Landscape Ecology Branch in collaboration with the USDA-ARS Southwest Watershed Research Center has developed a geographic information system (GIS) tool to facilitate this process. A GIS provides the framework within which spatially distributed data are collected and used to prepare model input files, and model results are evaluated. The Automated Geospatial Watershed Assessment (AGWA) tool uses widely available standardized spatial datasets that can be obtained via the internet at no cost to the user. The data are used to develop input parameter files for KINEROS2 and SWAT, two watershed runoff and erosion simulation models that operate at different spatial and temporal scales. AGWA automates the process of transforming digital data into simulation model results and provides a visualization tool

Spatial analysis and characteristics of pig farming in Thailand.

PubMed

Thanapongtharm, Weerapong; Linard, Catherine; Chinson, Pornpiroon; Kasemsuwan, Suwicha; Visser, Marjolein; Gaughan, Andrea E; Epprech, Michael; Robinson, Timothy P; Gilbert, Marius

2016-10-06

In Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Strategies toward more sustainable future developments are currently investigated, and these could be informed by a detailed assessment of the main trends in the pig sector, and on how different production systems are geographically distributed. This study had two main objectives. First, we aimed to describe the main trends and geographic patterns of pig production systems in Thailand in terms of pig type (native, breeding, and fattening pigs), farm scales (smallholder and large-scale farming systems) and type of farming systems (farrow-to-finish, nursery, and finishing systems) based on a very detailed 2010 census. Second, we aimed to study the statistical spatial association between these different types of pig farming distribution and a set of spatial variables describing access to feed and markets. Over the last decades, pig population gradually increased, with a continuously increasing number of pigs per holder, suggesting a continuing intensification of the sector. The different pig-production systems showed very contrasted geographical distributions. The spatial distribution of large-scale pig farms corresponds with that of commercial pig breeds, and spatial analysis conducted using Random Forest distribution models indicated that these were concentrated in lowland urban or peri-urban areas, close to means of transportation, facilitating supply to major markets such as provincial capitals and the Bangkok Metropolitan region. Conversely the smallholders were distributed throughout the country, with higher densities located in highland, remote, and rural areas, where they supply local rural markets. A limitation of the study was that pig farming systems were defined from the number of animals per farm, resulting in their possible misclassification, but this should have a limited impact on the main patterns revealed by the analysis. The very contrasted distribution of different pig production systems present opportunities for future regionalization of pig production. More specifically, the detailed geographical analysis of the different production systems will be used to spatially-inform planning decisions for pig farming accounting for the specific health, environment and economical implications of the different pig production systems.

Determination of the Time-Space Magnetic Correlation Functions in the Solar Wind

NASA Astrophysics Data System (ADS)

Weygand, J. M.; Matthaeus, W. H.; Kivelson, M.; Dasso, S.

2013-12-01

Magnetic field data from many different intervals and 7 different solar wind spacecraft are employed to estimate the scale-dependent time decorrelation function in the interplanetary magnetic field in both the slow and fast solar wind. This estimation requires correlations varying with both space and time lags. The two point correlation function with no time lag is determined by correlating time series data from multiple spacecraft separated in space and for complete coverage of length scales relies on many intervals with different spacecraft spatial separations. In addition we employ single spacecraft time-lagged correlations, and two spacecraft time lagged correlations to access different spatial and temporal correlation data. Combining these data sets gives estimates of the scale-dependent time decorrelation function, which in principle tells us how rapidly time decorrelation occurs at a given wavelength. For static fields the scale-dependent time decorrelation function is trivially unity, but in turbulence the nonlinear cascade process induces time-decorrelation at a given length scale that occurs more rapidly with decreasing scale. The scale-dependent time decorrelation function is valuable input to theories as well as various applications such as scattering, transport, and study of predictability. It is also a fundamental element of formal turbulence theory. Our results are extension of the Eulerian correlation functions estimated in Matthaeus et al. [2010], Weygand et al [2012; 2013].

Abundance and fragmentation patterns of the ecosystem engineer Lithophyllum byssoides (Lamarck) Foslie along the Iberian Peninsula Atlantic coast. Conservation and management implications

NASA Astrophysics Data System (ADS)

Veiga, Puri; Rubal, Marcos; Cacabelos, Eva; Moreira, Juan; Sousa-Pinto, Isabel

2013-10-01

The crustose calcareous red macroalgae Lithophyllum byssoides (Lamarck) Foslie is a common ecosystem engineer along the Atlantic and Mediterranean coast of the Iberian Peninsula. This species is threatened by several anthropogenic impacts acting at different spatial scales, such as pollution or global warming. The aim of this study is to identify scales of spatial variation in the abundance and fragmentation patterns of L. byssoides along the Atlantic coast of the Iberian Peninsula. For this aim we used a hierarchical sampling design considering four spatial scales (from metres to 100s of kilometres). Results of the present study indicated no significant variability among regions investigated whereas significant variability was found at the scales of shore and site in spatial patterns of abundance and fragmentation of L. byssoides. Variance components were higher at the spatial scale of shore for abundance and fragmentation of L. byssoides with the only exception of percentage cover and thus, processes acting at the scale of 10s of kilometres seem to be more relevant in shaping the spatial variability both in abundance and fragmentation of L. byssoides. These results provided quantitative estimates of abundance and fragmentation of L. byssoides at the Atlantic coast of the Iberian Peninsula establishing the observational basis for future assessment, monitoring and experimental investigations to identify the processes and anthropogenic impacts affecting L. byssoides populations. Finally we have also identified percentage cover and patch density as the best variables for long-term monitoring programs aimed to detect future anthropogenic impacts on L. byssoides. Therefore, our results have important implications for conservation and management of this valuable ecosystem engineer along the Atlantic coast of the Iberian Peninsula.

Assessments of habitat preferences and quality depend on spatial scale and metrics of fitness

USGS Publications Warehouse

Chalfoun, A.D.; Martin, T.E.

2007-01-01

1. Identifying the habitat features that influence habitat selection and enhance fitness is critical for effective management. Ecological theory predicts that habitat choices should be adaptive, such that fitness is enhanced in preferred habitats. However, studies often report mismatches between habitat preferences and fitness consequences across a wide variety of taxa based on a single spatial scale and/or a single fitness component. 2. We examined whether habitat preferences of a declining shrub steppe songbird, the Brewer's sparrow Spizella breweri, were adaptive when multiple reproductive fitness components and spatial scales (landscape, territory and nest patch) were considered. 3. We found that birds settled earlier and in higher densities, together suggesting preference, in landscapes with greater shrub cover and height. Yet nest success was not higher in these landscapes; nest success was primarily determined by nest predation rates. Thus landscape preferences did not match nest predation risk. Instead, nestling mass and the number of nesting attempts per pair increased in preferred landscapes, raising the possibility that landscapes were chosen on the basis of food availability rather than safe nest sites. 4. At smaller spatial scales (territory and nest patch), birds preferred different habitat features (i.e. density of potential nest shrubs) that reduced nest predation risk and allowed greater season-long reproductive success. 5. Synthesis and applications. Habitat preferences reflect the integration of multiple environmental factors across multiple spatial scales, and individuals may have more than one option for optimizing fitness via habitat selection strategies. Assessments of habitat quality for management prescriptions should ideally include analysis of diverse fitness consequences across multiple ecologically relevant spatial scales. ?? 2007 The Authors.

How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

NASA Astrophysics Data System (ADS)

Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

2017-12-01

Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

Anomalous dispersion in correlated porous media: a coupled continuous time random walk approach

NASA Astrophysics Data System (ADS)

Comolli, Alessandro; Dentz, Marco

2017-09-01

We study the causes of anomalous dispersion in Darcy-scale porous media characterized by spatially heterogeneous hydraulic properties. Spatial variability in hydraulic conductivity leads to spatial variability in the flow properties through Darcy's law and thus impacts on solute and particle transport. We consider purely advective transport in heterogeneity scenarios characterized by broad distributions of heterogeneity length scales and point values. Particle transport is characterized in terms of the stochastic properties of equidistantly sampled Lagrangian velocities, which are determined by the flow and conductivity statistics. The persistence length scales of flow and transport velocities are imprinted in the spatial disorder and reflect the distribution of heterogeneity length scales. Particle transitions over the velocity length scales are kinematically coupled with the transition time through velocity. We show that the average particle motion follows a coupled continuous time random walk (CTRW), which is fully parameterized by the distribution of flow velocities and the medium geometry in terms of the heterogeneity length scales. The coupled CTRW provides a systematic framework for the investigation of the origins of anomalous dispersion in terms of heterogeneity correlation and the distribution of conductivity point values. We derive analytical expressions for the asymptotic scaling of the moments of the spatial particle distribution and first arrival time distribution (FATD), and perform numerical particle tracking simulations of the coupled CTRW to capture the full average transport behavior. Broad distributions of heterogeneity point values and lengths scales may lead to very similar dispersion behaviors in terms of the spatial variance. Their mechanisms, however are very different, which manifests in the distributions of particle positions and arrival times, which plays a central role for the prediction of the fate of dissolved substances in heterogeneous natural and engineered porous materials. Contribution to the Topical Issue "Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.

Exploratory spatial data analysis of global MODIS active fire data

NASA Astrophysics Data System (ADS)

Oom, D.; Pereira, J. M. C.

2013-04-01

We performed an exploratory spatial data analysis (ESDA) of autocorrelation patterns in the NASA MODIS MCD14ML Collection 5 active fire dataset, for the period 2001-2009, at the global scale. The dataset was screened, resulting in an annual rate of false alarms and non-vegetation fires ranging from a minimum of 3.1% in 2003 to a maximum of 4.4% in 2001. Hot bare soils and gas flares were the major sources of false alarms and non-vegetation fires. The data were aggregated at 0.5° resolution for the global and local spatial autocorrelation Fire counts were found to be positively correlated up to distances of around 200 km, and negatively for larger distances. A value of 0.80 (p = 0.001, α = 0.05) for Moran's I indicates strong spatial autocorrelation between fires at global scale, with 60% of all cells displaying significant positive or negative spatial correlation. Different types of spatial autocorrelation were mapped and regression diagnostics allowed for the identification of spatial outlier cells, with fire counts much higher or lower than expected, considering their spatial context.

An Automatic Instrument to Study the Spatial Scaling Behavior of Emissivity

PubMed Central

Tian, Jing; Zhang, Renhua; Su, Hongbo; Sun, Xiaomin; Chen, Shaohui; Xia, Jun

2008-01-01

In this paper, the design of an automatic instrument for measuring the spatial distribution of land surface emissivity is presented, which makes the direct in situ measurement of the spatial distribution of emissivity possible. The significance of this new instrument lies in two aspects. One is that it helps to investigate the spatial scaling behavior of emissivity and temperature; the other is that, the design of the instrument provides theoretical and practical foundations for the implement of measuring distribution of surface emissivity on airborne or spaceborne. To improve the accuracy of the measurements, the emissivity measurement and its uncertainty are examined in a series of carefully designed experiments. The impact of the variation of target temperature and the environmental irradiance on the measurement of emissivity is analyzed as well. In addition, the ideal temperature difference between hot environment and cool environment is obtained based on numerical simulations. Finally, the scaling behavior of surface emissivity caused by the heterogeneity of target is discussed. PMID:27879735

Spatial analysis of lettuce downy mildew using geostatistics and geographic information systems.

PubMed

Wu, B M; van Bruggen, A H; Subbarao, K V; Pennings, G G

2001-02-01

ABSTRACT The epidemiology of lettuce downy mildew has been investigated extensively in coastal California. However, the spatial patterns of the disease and the distance that Bremia lactucae spores can be transported have not been determined. During 1995 to 1998, we conducted several field- and valley-scale surveys to determine spatial patterns of this disease in the Salinas valley. Geostatistical analyses of the survey data at both scales showed that the influence range of downy mildew incidence at one location on incidence at other locations was between 80 and 3,000 m. A linear relationship was detected between semivariance and lag distance at the field scale, although no single statistical model could fit the semi-variograms at the valley scale. Spatial interpolation by the inverse distance weighting method with a power of 2 resulted in plausible estimates of incidence throughout the valley. Cluster analysis in geographic information systems on the interpolated disease incidence from different dates demonstrated that the Salinas valley could be divided into two areas, north and south of Salinas City, with high and low disease pressure, respectively. Seasonal and spatial trends along the valley suggested that the distinction between the downy mildew conducive and nonconducive areas might be determined by environmental factors.

Confronting weather and climate models with observational data from soil moisture networks over the United States

PubMed Central

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal D.; Balsamo, Gianpaolo; Lawrence, David M.

2018-01-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison. PMID:29645013

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

NASA Technical Reports Server (NTRS)

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;

Confronting weather and climate models with observational data from soil moisture networks over the United States.

PubMed

Dirmeyer, Paul A; Wu, Jiexia; Norton, Holly E; Dorigo, Wouter A; Quiring, Steven M; Ford, Trenton W; Santanello, Joseph A; Bosilovich, Michael G; Ek, Michael B; Koster, Randal D; Balsamo, Gianpaolo; Lawrence, David M

2016-04-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

Multi-scale analysis of a household level agent-based model of landcover change.

PubMed

Evans, Tom P; Kelley, Hugh

2004-08-01

Scale issues have significant implications for the analysis of social and biophysical processes in complex systems. These same scale implications are likewise considerations for the design and application of models of landcover change. Scale issues have wide-ranging effects from the representativeness of data used to validate models to aggregation errors introduced in the model structure. This paper presents an analysis of how scale issues affect an agent-based model (ABM) of landcover change developed for a research area in the Midwest, USA. The research presented here explores how scale factors affect the design and application of agent-based landcover change models. The ABM is composed of a series of heterogeneous agents who make landuse decisions on a portfolio of cells in a raster-based programming environment. The model is calibrated using measures of fit derived from both spatial composition and spatial pattern metrics from multi-temporal landcover data interpreted from historical aerial photography. A model calibration process is used to find a best-fit set of parameter weights assigned to agents' preferences for different landuses (agriculture, pasture, timber production, and non-harvested forest). Previous research using this model has shown how a heterogeneous set of agents with differing preferences for a portfolio of landuses produces the best fit to landcover changes observed in the study area. The scale dependence of the model is explored by varying the resolution of the input data used to calibrate the model (observed landcover), ancillary datasets that affect land suitability (topography), and the resolution of the model landscape on which agents make decisions. To explore the impact of these scale relationships the model is run with input datasets constructed at the following spatial resolutions: 60, 90, 120, 150, 240, 300 and 480 m. The results show that the distribution of landuse-preference weights differs as a function of scale. In addition, with the gradient descent model fitting method used in this analysis the model was not able to converge to an acceptable fit at the 300 and 480 m spatial resolutions. This is a product of the ratio of the input cell resolution to the average parcel size in the landscape. This paper uses these findings to identify scale considerations in the design, development, validation and application of ABMs of landcover change.

Generalization Technique for 2D+SCALE Dhe Data Model

NASA Astrophysics Data System (ADS)

Karim, Hairi; Rahman, Alias Abdul; Boguslawski, Pawel

2016-10-01

Different users or applications need different scale model especially in computer application such as game visualization and GIS modelling. Some issues has been raised on fulfilling GIS requirement of retaining the details while minimizing the redundancy of the scale datasets. Previous researchers suggested and attempted to add another dimension such as scale or/and time into a 3D model, but the implementation of scale dimension faces some problems due to the limitations and availability of data structures and data models. Nowadays, various data structures and data models have been proposed to support variety of applications and dimensionality but lack research works has been conducted in terms of supporting scale dimension. Generally, the Dual Half Edge (DHE) data structure was designed to work with any perfect 3D spatial object such as buildings. In this paper, we attempt to expand the capability of the DHE data structure toward integration with scale dimension. The description of the concept and implementation of generating 3D-scale (2D spatial + scale dimension) for the DHE data structure forms the major discussion of this paper. We strongly believed some advantages such as local modification and topological element (navigation, query and semantic information) in scale dimension could be used for the future 3D-scale applications.

Detecting changes resulting from human pressure in a naturally quick-changing and heterogeneous environment: Spatial and temporal scales of variability in coastal lagoons

NASA Astrophysics Data System (ADS)

Pérez-Ruzafa, A.; Marcos, C.; Pérez-Ruzafa, I. M.; Barcala, E.; Hegazi, M. I.; Quispe, J.

2007-10-01

To detect changes in ecosystems due to human impact, experimental designs must include replicates at the appropriate scale to avoid pseudoreplication. Although coastal lagoons, with their highly variable environmental factors and biological assemblages, are relatively well-studied systems, very little is known about their natural scales of variation. In this study, we investigate the spatio-temporal scales of variability in the Mar Menor coastal lagoon (SE Spain) using structured hierarchical sampling designs, mixed and permutational multi-variate analyses of variance, and ordination multi-variate analyses applied to hydrographical parameters, nutrients, chlorophyll a and ichthyoplankton in the water column, and to macrophyte and fish benthic assemblages. Lagoon processes in the Mar Menor show heterogeneous patterns at different temporal and spatial scales. The water column characteristics (including nutrient concentration) showed small-scale spatio-temporal variability, from 10 0 to 10 1 km and from fortnightly to seasonally. Biological features (chlorophyll a concentration and ichthyoplankton assemblage descriptors) showed monthly changes and spatial patterns at the scale of 10 0 (chlorophyll a) - 10 1 km (ichthyoplankton). Benthic assemblages (macrophytes and fishes) showed significant differences between types of substrates in the same locality and between localities, according to horizontal gradients related with confinement in the lagoon, at the scale of 10 0-10 1 km. The vertical zonation of macrophyte assemblages (at scales of 10 1-10 2 cm) overlaps changes in substrata and horizontal gradients. Seasonal patterns in vegetation biomass were not significant, but the significant interaction between Locality and Season indicated that the seasons of maximum and minimum biomass depend on local environmental conditions. Benthic fish assemblages showed no significant patterns at the monthly scale but did show seasonal patterns.

Multi-scale habitat selection in highly territorial bird species: Exploring the contribution of nest, territory and landscape levels to site choice in breeding rallids (Aves: Rallidae)

NASA Astrophysics Data System (ADS)

Jedlikowski, Jan; Chibowski, Piotr; Karasek, Tomasz; Brambilla, Mattia

2016-05-01

Habitat selection often involves choices made at different spatial scales, but the underlying mechanisms are still poorly understood, and studies that investigate the relative importance of individual scales are rare. We investigated the effect of three spatial scales (landscape, territory, nest-site) on the occurrence pattern of little crake Zapornia parva and water rail Rallus aquaticus at 74 ponds in the Masurian Lakeland, Poland. Habitat structure, food abundance and water chemical parameters were measured at nests and random points within landscape plots (from 300-m to 50-m radius), territory (14-m) and nest-site plots (3-m). Regression analyses suggested that the most relevant scale was territory level, followed by landscape, and finally by nest-site for both species. Variation partitioning confirmed this pattern for water rail, but also highlighted the importance of nest-site (the level explaining the highest share of unique variation) for little crake. The most important variables determining the occurrence of both species were water body fragmentation (landscape), vegetation density (territory) and water depth (at territory level for little crake, and at nest-site level for water rail). Finally, for both species multi-scale models including factors from different levels were more parsimonious than single-scale ones, i.e. habitat selection was likely a multi-scale process. The importance of particular spatial scales seemed more related to life-history traits than to the extent of the scales considered. In the case of our study species, the territory level was highly important likely because both rallids have to obtain all the resources they need (nest site, food and mates) in relatively small areas, the multi-purpose territories they defend.

Estimating ecological integrity in the interior Columbia River basin.

Treesearch

Thomas M. Quigley; Richard W. Haynes; Wendel J. Hann

2001-01-01

The adoption of ecosystem-based management strategies focuses attention on the need for broad scale estimates of ecological conditions; this poses two challenges for the science community: estimating broad scale ecosystem conditions from highly disparate data, often observed at different spatial scales, and interpreting these conditions relative to goals such as...

Effects of input uncertainty on cross-scale crop modeling

NASA Astrophysics Data System (ADS)

Waha, Katharina; Huth, Neil; Carberry, Peter

2014-05-01

The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input data from very little to very detailed information, and compare the models' abilities to represent the spatial variability and temporal variability in crop yields. We display the uncertainty in crop yield simulations from different input data and crop models in Taylor diagrams which are a graphical summary of the similarity between simulations and observations (Taylor, 2001). The observed spatial variability can be represented well from both models (R=0.6-0.8) but APSIM predicts higher spatial variability than LPJmL due to its sensitivity to soil parameters. Simulations with the same crop model, climate and sowing dates have similar statistics and therefore similar skill to reproduce the observed spatial variability. Soil data is less important for the skill of a crop model to reproduce the observed spatial variability. However, the uncertainty in simulated spatial variability from the two crop models is larger than from input data settings and APSIM is more sensitive to input data then LPJmL. Even with a detailed, point-scale crop model and detailed input data it is difficult to capture the complexity and diversity in maize cropping systems.

A Land System representation for global assessments and land-use modeling.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2012-10-01

Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.

Demographic controls of aboveground forest biomass across North America.

PubMed

Vanderwel, Mark C; Zeng, Hongcheng; Caspersen, John P; Kunstler, Georges; Lichstein, Jeremy W

2016-04-01

Ecologists have limited understanding of how geographic variation in forest biomass arises from differences in growth and mortality at continental to global scales. Using forest inventories from across North America, we partitioned continental-scale variation in biomass growth and mortality rates of 49 tree species groups into (1) species-independent spatial effects and (2) inherent differences in demographic performance among species. Spatial factors that were separable from species composition explained 83% and 51% of the respective variation in growth and mortality. Moderate additional variation in mortality (26%) was attributable to differences in species composition. Age-dependent biomass models showed that variation in forest biomass can be explained primarily by spatial gradients in growth that were unrelated to species composition. Species-dependent patterns of mortality explained additional variation in biomass, with forests supporting less biomass when dominated by species that are highly susceptible to competition (e.g. Populus spp.) or to biotic disturbances (e.g. Abies balsamea). © 2016 John Wiley & Sons Ltd/CNRS.

Separating the effects of environment and space on tree species distribution: from population to community.

PubMed

Lin, Guojun; Stralberg, Diana; Gong, Guiquan; Huang, Zhongliang; Ye, Wanhui; Wu, Linfang

2013-01-01

Quantifying the relative contributions of environmental conditions and spatial factors to species distribution can help improve our understanding of the processes that drive diversity patterns. In this study, based on tree inventory, topography and soil data from a 20-ha stem-mapped permanent forest plot in Guangdong Province, China, we evaluated the influence of different ecological processes at different spatial scales using canonical redundancy analysis (RDA) at the community level and multiple linear regression at the species level. At the community level, the proportion of explained variation in species distribution increased with grid-cell sizes, primarily due to a monotonic increase in the explanatory power of environmental variables. At the species level, neither environmental nor spatial factors were important determinants of overstory species' distributions at small cell sizes. However, purely spatial variables explained most of the variation in the distributions of understory species at fine and intermediate cell sizes. Midstory species showed patterns that were intermediate between those of overstory and understory species. At the 20-m cell size, the influence of spatial factors was stronger for more dispersal-limited species, suggesting that much of the spatial structuring in this community can be explained by dispersal limitation. Comparing environmental factors, soil variables had higher explanatory power than did topography for species distribution. However, both topographic and edaphic variables were highly spatial structured. Our results suggested that dispersal limitation has an important influence on fine-intermediate scale (from several to tens of meters) species distribution, while environmental variability facilitates species distribution at intermediate (from ten to tens of meters) and broad (from tens to hundreds of meters) scales.

Spatial scale effect on sediment dynamics in basin-wide floods within a typical agro-watershed: A case study in the hilly loess region of the Chinese Loess Plateau.

PubMed

Zhang, Le-Tao; Li, Zhan-Bin; Wang, Shan-Shan

2016-12-01

Scale issues, which have been extensively studied in the domain of soil erosion, are considerably significant in geomorphologic processes and hydrologic modelling. However, relatively scarce efforts have been made to quantify the spatial scale effect on event-based sediment dynamics in basin-wide floods. To address this issue, sediment-runoff yield data of 44 basin-wide flood events were collected from gauging stations at the Chabagou river basin, a typical agro-basin (unmanaged) in the hilly loess region of the Chinese Loess Plateau. Thus, the spatial scale effect on event-based sediment dynamics was investigated in the basin system across three different spatial scales from sublateral to basin outlet. Results showed that the event-based suspended sediment concentration, as well as the intra- and inter-scale flow-sediment relationships remained spatially constant. Hence, almost all the sediment-laden flows can reach at the detachment-limited maximum concentration across scales, specifically for hyperconcentrated flows. Consequently, limited influence was exerted by upstream sediment-laden flow on downstream sediment output, particularly for major sediment-producing events. However, flood peak discharge instead of total flood runoff amount can better interpret the dynamics of sediment yield across scales. As a composite parameter, the proposed stream energy factor combines flood runoff depth and flood peak discharge, thereby showing more advantages to describe the event-based inter-scale flow-sediment relationship than other flow-related variables. Overall, this study demonstrates the process-specific characteristics of soil erosion by water flows in the basin system. Therefore, event-based sediment control should be oriented by the process to cut off the connectivity of hyperconcentrated flows and redistribute the erosive energy of flowing water in terms of temporality and spatiality. Furthermore, evaluation of soil conservation benefits should be based on the process of runoff regulation to comprehensively assess the efficiency of anti-erosion strategies in sediment control at the basin scale. Copyright © 2016. Published by Elsevier B.V.

A Spatial View of the Interpersonal Structure of Family Interviews: Similarities and Differences Across Counselors.

ERIC Educational Resources Information Center

Friedlander, Myrna L.; Highlen, Pamela S.

1984-01-01

Examined the interpersonal structures of interviews by Ackerman, Bowen, Jackson, and Whitaker with the same family to identify common features across counselors. Multidimensional scaling provided a spatial representation of the hidden structure in the communication patterns of these interviews. Correlations indicated counselors' interactions were…

Quantifying spatial differences in metabolism in headwater streams

Treesearch

Ricardo González-Pinzón; Roy Haggerty; Alba Argerich

2014-01-01

Stream functioning includes simultaneous interaction among solute transport, nutrient processing, and metabolism. Metabolism is measured with methods that have limited spatial representativeness and are highly uncertain. These problems restrict development of methods for up-scaling biological processes that mediate nutrient processing. We used the resazurin–resorufin (...

Spatial perspectives in state-and-transition models: A missing link to land management?

USDA-ARS?s Scientific Manuscript database

Conceptual models of alternative states and thresholds are based largely on observations of ecosystem processes at a few points in space. Because the distribution of alternative states in spatially-structured ecosystems is the result of variations in pattern-process interactions at different scales,...

Blending Pan-European and local hydrological models for water resource assessment in Mediterranean areas: lessons learnt from a mountainous catchment

NASA Astrophysics Data System (ADS)

José Polo, María; José Pérez-Palazón, María; Saénz de Rodrigáñez, Marta; Pimentel, Rafael; Arheimer, Berit

2017-04-01

Global hydrological models provide scientists and technicians with distributed data over medium to large areas from which assessment of water resource planning and use can be easily performed. However, scale conflicts between global models' spatial resolution and the local significant spatial scales in heterogeneous areas usually pose a constraint for the direct use and application of these models' results. The SWICCA (Service for Water Indicators in Climate Change Adaptation) Platform developed under the Copernicus Climate Change Service (C3S) offers a wide range of both climate and hydrological indicators obtained on a global scale with different time and spatial resolutions. Among the different study cases supporting the SWICCA demonstration of local impact assessment, the Sierra Nevada study case (South Spain) is a representative example of mountainous coastal catchments in the Mediterranean region. This work shows the lessons learnt during the study case development to derive local impact indicator tailored to suit the local end-users of water resource in this snow-dominated area. Different approaches were followed to select the most accurate method to downscale the global data and variables to the local level in a highly abrupt topography, in a sequential step approach. 1) SWICCA global climate variable downscaling followed by river flow simulation from a local hydrological model in selected control points in the catchment, together with 2) SWICCA global river flow values downscaling to the control points followed by corrections with local transfer functions were both tested against the available local river flow series of observations during the reference period. This test was performed for the different models and the available spatial resolutions included in the SWICCA platform. From the results, the second option, that is, the use of SWICCA river flow variables, performed the best approximations, once the local transfer functions were applied to the global values and an additional correction was performed based on the relative anomalies obtained instead of the absolute values. This approach was used to derive the future projections of selected local indicators for each end-user in the area under different climate change scenarios. Despite the spatial scale conflicts, the SWICCA river flow indicators (simulated by the E-HYPEv3.1.2 model) succeeded in approximating the observations during the reference period 1970-2000 when provided on a catchment scale, once local transfer functions and further anomaly correction were performed. Satisfactory results were obtained on a monthly scale for river flow in the main stream of the watershed, and on a daily scale for the headwater streams. The accessibility to the hydrological model WiMMed, which includes a snow module, locally validated in the study area has been crucial to downscale the SWICCA results and prove their usefulness.

Spatial scaling patterns and functional redundancies in a changing boreal lake landscape

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Uden, Daniel R.; Johnson, Richard K.

2015-01-01

Global transformations extend beyond local habitats; therefore, larger-scale approaches are needed to assess community-level responses and resilience to unfolding environmental changes. Using longterm data (1996–2011), we evaluated spatial patterns and functional redundancies in the littoral invertebrate communities of 85 Swedish lakes, with the objective of assessing their potential resilience to environmental change at regional scales (that is, spatial resilience). Multivariate spatial modeling was used to differentiate groups of invertebrate species exhibiting spatial patterns in composition and abundance (that is, deterministic species) from those lacking spatial patterns (that is, stochastic species). We then determined the functional feeding attributes of the deterministic and stochastic invertebrate species, to infer resilience. Between one and three distinct spatial patterns in invertebrate composition and abundance were identified in approximately one-third of the species; the remainder were stochastic. We observed substantial differences in metrics between deterministic and stochastic species. Functional richness and diversity decreased over time in the deterministic group, suggesting a loss of resilience in regional invertebrate communities. However, taxon richness and redundancy increased monotonically in the stochastic group, indicating the capacity of regional invertebrate communities to adapt to change. Our results suggest that a refined picture of spatial resilience emerges if patterns of both the deterministic and stochastic species are accounted for. Spatially extensive monitoring may help increase our mechanistic understanding of community-level responses and resilience to regional environmental change, insights that are critical for developing management and conservation agendas in this current period of rapid environmental transformation.

Multi objective climate change impact assessment using multi downscaled climate scenarios

NASA Astrophysics Data System (ADS)

Rana, Arun; Moradkhani, Hamid

2016-04-01

Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional and global scale. In the present study, we have analyzed the changes in precipitation and temperature for future scenario period of 2070-2099 with respect to historical period of 1970-2000 from a set of statistically downscaled GCM projections for Columbia River Basin (CRB). Analysis is performed using 2 different statistically downscaled climate projections namely the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, totaling to 40 different scenarios. Analysis is performed on spatial, temporal and frequency based parameters in the future period at a scale of 1/16th of degree for entire CRB region. Results have indicated in varied degree of spatial change pattern for the entire Columbia River Basin, especially western part of the basin. At temporal scales, winter precipitation has higher variability than summer and vice-versa for temperature. Frequency analysis provided insights into possible explanation to changes in precipitation.

Quantifying Neighborhood-Scale Spatial Variations of Ozone at Open Space and Urban Sites in Boulder, Colorado Using Low-Cost Sensor Technology.

PubMed

Cheadle, Lucy; Deanes, Lauren; Sadighi, Kira; Gordon Casey, Joanna; Collier-Oxandale, Ashley; Hannigan, Michael

2017-09-10

Recent advances in air pollution sensors have led to a new wave of low-cost measurement systems that can be deployed in dense networks to capture small-scale spatio-temporal variations in ozone, a pollutant known to cause negative human health impacts. This study deployed a network of seven low-cost ozone metal oxide sensor systems (UPods) in both an open space and an urban location in Boulder, Colorado during June and July of 2015, to quantify ozone variations on spatial scales ranging from 12 m between UPods to 6.7 km between open space and urban measurement sites with a measurement uncertainty of ~5 ppb. The results showed spatial variability of ozone at both deployment sites, with the largest differences between UPod measurements occurring during the afternoons. The peak median hourly difference between UPods was 6 ppb at 1:00 p.m. at the open space site, and 11 ppb at 4:00 p.m. at the urban site. Overall, the urban ozone measurements were higher than in the open space measurements. This study evaluates the effectiveness of using low-cost sensors to capture microscale spatial and temporal variation of ozone; additionally, it highlights the importance of field calibrations and measurement uncertainty quantification when deploying low-cost sensors.

Detecting small-scale spatial differences and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

NASA Astrophysics Data System (ADS)

Hoffmann, Mathias; Jurisch, Nicole; Garcia Alba, Juana; Albiac Borraz, Elisa; Schmidt, Marten; Huth, Vytas; Rogasik, Helmut; Rieckh, Helene; Verch, Gernot; Sommer, Michael; Augustin, Jürgen

2017-04-01

Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon (ΔSOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial and temporal changes in SOC stocks, particularly pronounced on arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in ΔSOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil-plant-atmosphere system may help to obtain temporal ΔSOC patterns but lack small-scale spatial resolution. To overcome these limitations, this study presents a reliable method to detect both short-term temporal as well as small-scale spatial dynamics of ΔSOC. Therefore, a combination of automatic chamber (AC) measurements of CO2 exchange and empirically modeled aboveground biomass development (NPPshoot) was used. To verify our method, results were compared with ΔSOC observed by soil resampling. AC measurements were performed from 2010 to 2014 under a silage maize/winter fodder rye/sorghum-Sudan grass hybrid/alfalfa crop rotation at a colluvial depression located in the hummocky ground moraine landscape of NE Germany. Widespread in large areas of the formerly glaciated Northern Hemisphere, this depression type is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity in soil properties, such as SOC and nitrogen (Nt). After monitoring the initial stage during 2010, soil erosion was experimentally simulated by incorporating topsoil material from an eroded midslope soil into the plough layer of the colluvial depression. SOC stocks were quantified before and after soil manipulation and at the end of the study period. AC-based ΔSOC values corresponded well with the tendencies and magnitude of the results observed in the repeated soil inventory. The period of maximum plant growth was identified as being most important for the development of spatial differences in annual ΔSOC. Hence, we were able to confirm that AC-based C budgets are able to reveal small-scale spatial and short-term temporal dynamics of ΔSOC.

Impact of spatial variability and sampling design on model performance

NASA Astrophysics Data System (ADS)

Schrape, Charlotte; Schneider, Anne-Kathrin; Schröder, Boris; van Schaik, Loes

2017-04-01

Many environmental physical and chemical parameters as well as species distributions display a spatial variability at different scales. In case measurements are very costly in labour time or money a choice has to be made between a high sampling resolution at small scales and a low spatial cover of the study area or a lower sampling resolution at the small scales resulting in local data uncertainties with a better spatial cover of the whole area. This dilemma is often faced in the design of field sampling campaigns for large scale studies. When the gathered field data are subsequently used for modelling purposes the choice of sampling design and resulting data quality influence the model performance criteria. We studied this influence with a virtual model study based on a large dataset of field information on spatial variation of earthworms at different scales. Therefore we built a virtual map of anecic earthworm distributions over the Weiherbach catchment (Baden-Württemberg in Germany). First of all the field scale abundance of earthworms was estimated using a catchment scale model based on 65 field measurements. Subsequently the high small scale variability was added using semi-variograms, based on five fields with a total of 430 measurements divided in a spatially nested sampling design over these fields, to estimate the nugget, range and standard deviation of measurements within the fields. With the produced maps, we performed virtual samplings of one up to 50 random points per field. We then used these data to rebuild the catchment scale models of anecic earthworm abundance with the same model parameters as in the work by Palm et al. (2013). The results of the models show clearly that a large part of the non-explained deviance of the models is due to the very high small scale variability in earthworm abundance: the models based on single virtual sampling points on average obtain an explained deviance of 0.20 and a correlation coefficient of 0.64. With increasing sampling points per field, we averaged the measured abundance of the sampling within each field to obtain a more representative value of the field average. Doubling the samplings per field strongly improved the model performance criteria (explained deviance 0.38 and correlation coefficient 0.73). With 50 sampling points per field the performance criteria were 0.91 and 0.97 respectively for explained deviance and correlation coefficient. The relationship between number of samplings and performance criteria can be described with a saturation curve. Beyond five samples per field the model improvement becomes rather small. With this contribution we wish to discuss the impact of data variability at sampling scale on model performance and the implications for sampling design and assessment of model results as well as ecological inferences.

Scaling analysis of cloud and rain water in marine stratocumulus and implications for scale-aware microphysical parameterizations

NASA Astrophysics Data System (ADS)

Witte, M.; Morrison, H.; Jensen, J. B.; Bansemer, A.; Gettelman, A.

2017-12-01

The spatial covariance of cloud and rain water (or in simpler terms, small and large drops, respectively) is an important quantity for accurate prediction of the accretion rate in bulk microphysical parameterizations that account for subgrid variability using assumed probability density functions (pdfs). Past diagnoses of this covariance from remote sensing, in situ measurements and large eddy simulation output have implicitly assumed that the magnitude of the covariance is insensitive to grain size (i.e. horizontal resolution) and averaging length, but this is not the case because both cloud and rain water exhibit scale invariance across a wide range of scales - from tens of centimeters to tens of kilometers in the case of cloud water, a range that we will show is primarily limited by instrumentation and sampling issues. Since the individual variances systematically vary as a function of spatial scale, it should be expected that the covariance follows a similar relationship. In this study, we quantify the scaling properties of cloud and rain water content and their covariability from high frequency in situ aircraft measurements of marine stratocumulus taken over the southeastern Pacific Ocean aboard the NSF/NCAR C-130 during the VOCALS-REx field experiment of October-November 2008. First we confirm that cloud and rain water scale in distinct manners, indicating that there is a statistically and potentially physically significant difference in the spatial structure of the two fields. Next, we demonstrate that the covariance is a strong function of spatial scale, which implies important caveats regarding the ability of limited-area models with domains smaller than a few tens of kilometers across to accurately reproduce the spatial organization of precipitation. Finally, we present preliminary work on the development of a scale-aware parameterization of cloud-rain water subgrid covariability based in multifractal analysis intended for application in large-scale model microphysics schemes.

Additive Partitioning of Coral Reef Fish Diversity across Hierarchical Spatial Scales throughout the Caribbean

PubMed Central

Francisco-Ramos, Vanessa; Arias-González, Jesús Ernesto

2013-01-01

There is an increasing need to examine regional patterns of diversity in coral-reef systems since their biodiversity is declining globally. In this sense, additive partitioning might be useful since it quantifies the contribution of alpha and beta to total diversity across different scales. We applied this approach using an unbalanced design across four hierarchical scales (80 sites, 22 subregions, six ecoregions, and the Caribbean basin). Reef-fish species were compiled from the Reef Environmental Education Foundation (REEF) database and distributions were confirmed with published data. Permutation tests were used to compare observed values to those expected by chance. The primary objective was to identify patterns of reef-fish diversity across multiple spatial scales under different scenarios, examining factors such as fisheries and demographic connectivity. Total diversity at the Caribbean scale was attributed to β-diversity (nearly 62% of the species), with the highest β-diversity at the site scale. α¯-diversity was higher than expected by chance in all scenarios and at all studied scales. This suggests that fish assemblages are more homogenous than expected, particularly at the ecoregion scale. Within each ecoregion, diversity was mainly attributed to alpha, except for the Southern ecoregion where there was a greater difference in species among sites. β-components were lower than expected in all ecoregions, indicating that fishes within each ecoregion are a subsample of the same species pool. The scenario involving the effects of fisheries showed a shift in dominance for β-diversity from regions to subregions, with no major changes to the diversity patterns. In contrast, demographic connectivity partially explained the diversity pattern. β-components were low within connectivity regions and higher than expected by chance when comparing between them. Our results highlight the importance of ecoregions as a spatial scale to conserve local and regional coral reef-fish diversity. PMID:24205311

OpenMP parallelization of a gridded SWAT (SWATG)

NASA Astrophysics Data System (ADS)

Zhang, Ying; Hou, Jinliang; Cao, Yongpan; Gu, Juan; Huang, Chunlin

2017-12-01

Large-scale, long-term and high spatial resolution simulation is a common issue in environmental modeling. A Gridded Hydrologic Response Unit (HRU)-based Soil and Water Assessment Tool (SWATG) that integrates grid modeling scheme with different spatial representations also presents such problems. The time-consuming problem affects applications of very high resolution large-scale watershed modeling. The OpenMP (Open Multi-Processing) parallel application interface is integrated with SWATG (called SWATGP) to accelerate grid modeling based on the HRU level. Such parallel implementation takes better advantage of the computational power of a shared memory computer system. We conducted two experiments at multiple temporal and spatial scales of hydrological modeling using SWATG and SWATGP on a high-end server. At 500-m resolution, SWATGP was found to be up to nine times faster than SWATG in modeling over a roughly 2000 km2 watershed with 1 CPU and a 15 thread configuration. The study results demonstrate that parallel models save considerable time relative to traditional sequential simulation runs. Parallel computations of environmental models are beneficial for model applications, especially at large spatial and temporal scales and at high resolutions. The proposed SWATGP model is thus a promising tool for large-scale and high-resolution water resources research and management in addition to offering data fusion and model coupling ability.

Identifying the Threshold of Dominant Controls on Fire Spread in a Boreal Forest Landscape of Northeast China

PubMed Central

Liu, Zhihua; Yang, Jian; He, Hong S.

2013-01-01

The relative importance of fuel, topography, and weather on fire spread varies at different spatial scales, but how the relative importance of these controls respond to changing spatial scales is poorly understood. We designed a “moving window” resampling technique that allowed us to quantify the relative importance of controls on fire spread at continuous spatial scales using boosted regression trees methods. This quantification allowed us to identify the threshold value for fire size at which the dominant control switches from fuel at small sizes to weather at large sizes. Topography had a fluctuating effect on fire spread across the spatial scales, explaining 20–30% of relative importance. With increasing fire size, the dominant control switched from bottom-up controls (fuel and topography) to top-down controls (weather). Our analysis suggested that there is a threshold for fire size, above which fires are driven primarily by weather and more likely lead to larger fire size. We suggest that this threshold, which may be ecosystem-specific, can be identified using our “moving window” resampling technique. Although the threshold derived from this analytical method may rely heavily on the sampling technique, our study introduced an easily implemented approach to identify scale thresholds in wildfire regimes. PMID:23383247

Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics

NASA Astrophysics Data System (ADS)

Xu, Y.; Wang, L.

2017-12-01

Soil moisture is important for agricultural and hydrological studies. However, ground truth soil moisture data for wide area is difficult to achieve. Microwave remote sensing such as Soil Moisture Active Passive (SMAP) can offer a solution for wide coverage. However, existing global soil moisture products only provide observations at coarse spatial resolutions, which often limit their applications in regional agricultural and hydrological studies. This paper therefore aims to generate fine scale soil moisture information and extend soil moisture spatial availability. A statistical downscaling scheme is presented that incorporates multiple fine scale geoinformation data into the downscaling of coarse scale SMAP data in the absence of ground measurement data. Geoinformation data related to soil moisture patterns including digital elevation model (DEM), land surface temperature (LST), land use and normalized difference vegetation index (NDVI) at a fine scale are used as auxiliary environmental variables for downscaling SMAP data. Generalized additive model (GAM) and regression tree are first conducted to derive statistical relationships between SMAP data and auxiliary geoinformation data at an original coarse scale, and residuals are then downscaled to a finer scale via area-to-point kriging (ATPK) by accounting for the spatial correlation information of the input residuals. The results from standard validation scores as well as the triple collocation (TC) method against soil moisture in-situ measurements show that the downscaling method can significantly improve the spatial details of SMAP soil moisture while maintain the accuracy.

Spatial variation in colour morph, spotting and allozyme frequencies in the candy-stripe spider, Enoplognatha ovata (Theridiidae) on two Swedish archipelagos.

PubMed

Oxford, G S; Gunnarsson, B

2006-01-01

The selective significance, if any, of many invertebrate visible polymorphisms is still not fully understood. Here we examine colour- and black spotting-morph frequencies in the spider Enoplognatha ovata in populations on two Swedish archipelagos with respect to different spatial scales and, in one archipelago, against the background of variation at four putative neutral allozyme marker loci. Every population studied was polymorphic for colour and 28 out of 30 contained all three colour morphs--lineata, redimita and ovata. We found no evidence for a breakdown in the traditional colour morph designation previously suggested for other northern European populations of this species. For colour there is no significant heterogeneity at spatial scales greater than between local populations within islands. Black spotting frequencies show a similar lack of pattern over larger spatial scales except that there are significant differences between the Stockholm and Göteborg archipelagos. Measures of population differentiation (theta) within the Stockholm islands for the two visible systems show them to be significantly more differentiated than the neutral markers, suggesting local selection acting on them in a population-specific manner. On the basis of previous observations and the distribution of spotting phenotypes on a European scale, it is argued that thermal selection might operate on black spotting during the juvenile stages favouring more spots in continental climates. It is not clear what selective forces act on colour.

Creative use of pilot points to address site and regional scale heterogeneity in a variable-density model

USGS Publications Warehouse

Dausman, Alyssa M.; Doherty, John; Langevin, Christian D.

2010-01-01

Pilot points for parameter estimation were creatively used to address heterogeneity at both the well field and regional scales in a variable-density groundwater flow and solute transport model designed to test multiple hypotheses for upward migration of fresh effluent injected into a highly transmissive saline carbonate aquifer. Two sets of pilot points were used within in multiple model layers, with one set of inner pilot points (totaling 158) having high spatial density to represent hydraulic conductivity at the site, while a second set of outer points (totaling 36) of lower spatial density was used to represent hydraulic conductivity further from the site. Use of a lower spatial density outside the site allowed (1) the total number of pilot points to be reduced while maintaining flexibility to accommodate heterogeneity at different scales, and (2) development of a model with greater areal extent in order to simulate proper boundary conditions that have a limited effect on the area of interest. The parameters associated with the inner pilot points were log transformed hydraulic conductivity multipliers of the conductivity field obtained by interpolation from outer pilot points. The use of this dual inner-outer scale parameterization (with inner parameters constituting multipliers for outer parameters) allowed smooth transition of hydraulic conductivity from the site scale, where greater spatial variability of hydraulic properties exists, to the regional scale where less spatial variability was necessary for model calibration. While the model is highly parameterized to accommodate potential aquifer heterogeneity, the total number of pilot points is kept at a minimum to enable reasonable calibration run times.

A Local to National Scale Catchment Model Simulation Framework for Hydrological Predictions and Impact Assessments Under Uncertainty

NASA Astrophysics Data System (ADS)

Freer, Jim; Coxon, Gemma; Quinn, Niall; Dunne, Toby; Lane, Rosie; Bates, Paul; Wagener, Thorsten; Woods, Ross; Neal, Jeff; Howden, Nicholas; Musuuza, Jude

2017-04-01

There is a huge challenge in developing hydrological model structures that can be used for hypothesis testing, prediction, impact assessment and risk analyses over a wide range of spatial scales. There are many reasons why this is the case, from computational demands, to how we define and characterize different features and pathway connectivities in the landscape, that differ depending on the objectives of the study. However there is certainly a need more than ever to explore the trade-offs between the complexity of modelling applied (i.e. spatial discretization, levels of process representation, complexity of landscape representation) compared to the benefits realized in terms of predictive capability and robustness of these predictions during hydrological extremes and during change. Furthermore, there is a further balance, particularly associated with prediction uncertainties, in that it is not desirable to have modelling systems that are too complex compared to the observed data that would ever be available to apply them. This is particularly the case when models are applied to quantify national impact assessments, especially if these are based on validation assessments from smaller more detailed case studies. Therefore the hydrological community needs modelling tools and approaches that enable these trade-offs to be explored and to understand the level of representation needed in models to be 'fit-for-purpose' for a given application. This paper presents a catchment scale national modelling framework based on Dynamic-TOPMODEL specifically setup to fulfil these aims. A key component of the modelling framework is it's structural flexibility, as is the ability to assess model outputs using Monte Carlo simulation techniques. The model build has been automated to work at any spatial scale to the national scale, and within that to control the level of spatial discretisation and connectivity of locally accounted landscape elements in the form of hydrological response units (HRU's). This allows for the explicit consideration of spatial rainfall fields, landscape, soils and geological attributes and the spatial connectivity of hydrological flow pathways to explore what level of modelling complexity we need for different prediction problems. We shall present this framework and show how it can be used in flood and drought risk analyses as well as include attributes and features within the landscape to explore societal and climate impacts effectively within an uncertainty analyses framework.

Dendritic GIRK Channels Gate the Integration Window, Plateau Potentials, and Induction of Synaptic Plasticity in Dorsal But Not Ventral CA1 Neurons

PubMed Central

2017-01-01

Studies comparing neuronal activity at the dorsal and ventral poles of the hippocampus have shown that the scale of spatial information increases and the precision with which space is represented declines from the dorsal to ventral end. These dorsoventral differences in neuronal output and spatial representation could arise due to differences in computations performed by dorsal and ventral CA1 neurons. In this study, we tested this hypothesis by quantifying the differences in dendritic integration and synaptic plasticity between dorsal and ventral CA1 pyramidal neurons of rat hippocampus. Using a combination of somatic and dendritic patch-clamp recordings, we show that the threshold for LTP induction is higher in dorsal CA1 neurons and that a G-protein-coupled inward-rectifying potassium channel mediated regulation of dendritic plateau potentials and dendritic excitability underlies this gating. By contrast, similar regulation of LTP is absent in ventral CA1 neurons. Additionally, we show that generation of plateau potentials and LTP induction in dorsal CA1 neurons depends on the coincident activation of Schaffer collateral and temporoammonic inputs at the distal apical dendrites. The ventral CA1 dendrites, however, can generate plateau potentials in response to temporally dispersed excitatory inputs. Overall, our results highlight the dorsoventral differences in dendritic computation that could account for the dorsoventral differences in spatial representation. SIGNIFICANCE STATEMENT The dorsal and ventral parts of the hippocampus encode spatial information at very different scales. Whereas the place-specific firing fields are small and precise at the dorsal end of the hippocampus, neurons at the ventral end have comparatively larger place fields. Here, we show that the dorsal CA1 neurons have a higher threshold for LTP induction and require coincident timing of excitatory synaptic inputs for the generation of dendritic plateau potentials. By contrast, ventral CA1 neurons can integrate temporally dispersed inputs and have a lower threshold for LTP. Together, these dorsoventral differences in the threshold for LTP induction could account for the differences in scale of spatial representation at the dorsal and ventral ends of the hippocampus. PMID:28280255

Dendritic GIRK Channels Gate the Integration Window, Plateau Potentials, and Induction of Synaptic Plasticity in Dorsal But Not Ventral CA1 Neurons.

PubMed

Malik, Ruchi; Johnston, Daniel

2017-04-05

Studies comparing neuronal activity at the dorsal and ventral poles of the hippocampus have shown that the scale of spatial information increases and the precision with which space is represented declines from the dorsal to ventral end. These dorsoventral differences in neuronal output and spatial representation could arise due to differences in computations performed by dorsal and ventral CA1 neurons. In this study, we tested this hypothesis by quantifying the differences in dendritic integration and synaptic plasticity between dorsal and ventral CA1 pyramidal neurons of rat hippocampus. Using a combination of somatic and dendritic patch-clamp recordings, we show that the threshold for LTP induction is higher in dorsal CA1 neurons and that a G-protein-coupled inward-rectifying potassium channel mediated regulation of dendritic plateau potentials and dendritic excitability underlies this gating. By contrast, similar regulation of LTP is absent in ventral CA1 neurons. Additionally, we show that generation of plateau potentials and LTP induction in dorsal CA1 neurons depends on the coincident activation of Schaffer collateral and temporoammonic inputs at the distal apical dendrites. The ventral CA1 dendrites, however, can generate plateau potentials in response to temporally dispersed excitatory inputs. Overall, our results highlight the dorsoventral differences in dendritic computation that could account for the dorsoventral differences in spatial representation. SIGNIFICANCE STATEMENT The dorsal and ventral parts of the hippocampus encode spatial information at very different scales. Whereas the place-specific firing fields are small and precise at the dorsal end of the hippocampus, neurons at the ventral end have comparatively larger place fields. Here, we show that the dorsal CA1 neurons have a higher threshold for LTP induction and require coincident timing of excitatory synaptic inputs for the generation of dendritic plateau potentials. By contrast, ventral CA1 neurons can integrate temporally dispersed inputs and have a lower threshold for LTP. Together, these dorsoventral differences in the threshold for LTP induction could account for the differences in scale of spatial representation at the dorsal and ventral ends of the hippocampus. Copyright © 2017 the authors 0270-6474/17/373940-16$15.00/0.

Grid scale drives the scale and long-term stability of place maps

PubMed Central

Mallory, Caitlin S; Hardcastle, Kiah; Bant, Jason S; Giocomo, Lisa M

2018-01-01

Medial entorhinal cortex (MEC) grid cells fire at regular spatial intervals and project to the hippocampus, where place cells are active in spatially restricted locations. One feature of the grid population is the increase in grid spatial scale along the dorsal-ventral MEC axis. However, the difficulty in perturbing grid scale without impacting the properties of other functionally-defined MEC cell types has obscured how grid scale influences hippocampal coding and spatial memory. Here, we use a targeted viral approach to knock out HCN1 channels selectively in MEC, causing grid scale to expand while leaving other MEC spatial and velocity signals intact. Grid scale expansion resulted in place scale expansion in fields located far from environmental boundaries, reduced long-term place field stability and impaired spatial learning. These observations, combined with simulations of a grid-to-place cell model and position decoding of place cells, illuminate how grid scale impacts place coding and spatial memory. PMID:29335607

Influence of spatial and temporal scales in identifying temperature extremes

NASA Astrophysics Data System (ADS)

van Eck, Christel M.; Friedlingstein, Pierre; Mulder, Vera L.; Regnier, Pierre A. G.

2016-04-01

Extreme heat events are becoming more frequent. Notable are severe heatwaves such as the European heatwave of 2003, the Russian heat wave of 2010 and the Australian heatwave of 2013. Surface temperature is attaining new maxima not only during the summer but also during the winter. The year of 2015 is reported to be a temperature record breaking year for both summer and winter. These extreme temperatures are taking their human and environmental toll, emphasizing the need for an accurate method to define a heat extreme in order to fully understand the spatial and temporal spread of an extreme and its impact. This research aims to explore how the use of different spatial and temporal scales influences the identification of a heat extreme. For this purpose, two near-surface temperature datasets of different temporal scale and spatial scale are being used. First, the daily ERA-Interim dataset of 0.25 degree and a time span of 32 years (1979-2010). Second, the daily Princeton Meteorological Forcing Dataset of 0.5 degree and a time span of 63 years (1948-2010). A temperature is considered extreme anomalous when it is surpassing the 90th, 95th, or the 99th percentile threshold based on the aforementioned pre-processed datasets. The analysis is conducted on a global scale, dividing the world in IPCC's so-called SREX regions developed for the analysis of extreme climate events. Pre-processing is done by detrending and/or subtracting the monthly climatology based on 32 years of data for both datasets and on 63 years of data for only the Princeton Meteorological Forcing Dataset. This results in 6 datasets of temperature anomalies from which the location in time and space of the anomalous warm days are identified. Comparison of the differences between these 6 datasets in terms of absolute threshold temperatures for extremes and the temporal and spatial spread of the extreme anomalous warm days show a dependence of the results on the datasets and methodology used. This stresses the need for a careful selection of data and methodology when identifying heat extremes.

Spatial and temporal synchrony in reptile population dynamics in variable environments.

PubMed

Greenville, Aaron C; Wardle, Glenda M; Nguyen, Vuong; Dickman, Chris R

2016-10-01

Resources are seldom distributed equally across space, but many species exhibit spatially synchronous population dynamics. Such synchrony suggests the operation of large-scale external drivers, such as rainfall or wildfire, or the influence of oasis sites that provide water, shelter, or other resources. However, testing the generality of these factors is not easy, especially in variable environments. Using a long-term dataset (13-22 years) from a large (8000 km(2)) study region in arid Central Australia, we tested firstly for regional synchrony in annual rainfall and the dynamics of six reptile species across nine widely separated sites. For species that showed synchronous spatial dynamics, we then used multivariate follow a multivariate auto-regressive state-space (MARSS) models to predict that regional rainfall would be positively associated with their populations. For asynchronous species, we used MARSS models to explore four other possible population structures: (1) populations were asynchronous, (2) differed between oasis and non-oasis sites, (3) differed between burnt and unburnt sites, or (4) differed between three sub-regions with different rainfall gradients. Only one species showed evidence of spatial population synchrony and our results provide little evidence that rainfall synchronizes reptile populations. The oasis or the wildfire hypotheses were the best-fitting models for the other five species. Thus, our six study species appear generally to be structured in space into one or two populations across the study region. Our findings suggest that for arid-dwelling reptile populations, spatial and temporal dynamics are structured by abiotic events, but individual responses to covariates at smaller spatial scales are complex and poorly understood.

The land-use legacy effect: Towards a mechanistic understanding of time-lagged water quality responses to land use/cover.

PubMed

Martin, Sherry L; Hayes, Daniel B; Kendall, Anthony D; Hyndman, David W

2017-02-01

Numerous studies have linked land use/land cover (LULC) to aquatic ecosystem responses, however only a few have included the dynamics of changing LULC in their analysis. In this study, we explicitly recognize changing LULC by linking mechanistic groundwater flow and travel time models to a historical time series of LULC, creating a land-use legacy map. We then illustrate the utility of legacy maps to explore relationships between dynamic LULC and lake water chemistry. We tested two main concepts about mechanisms linking LULC and lake water chemistry: groundwater pathways are an important mechanism driving legacy effects; and, LULC over multiple spatial scales is more closely related to lake chemistry than LULC over a single spatial scale. We applied statistical models to twelve water chemistry variables, ranging from nutrients to relatively conservative ions, to better understand the roles of biogeochemical reactivity and solubility on connections between LULC and aquatic ecosystem response. Our study illustrates how different areas can have long groundwater pathways that represent different LULC than what can be seen on the landscape today. These groundwater pathways delay the arrival of nutrients and other water quality constituents, thus creating a legacy of historic land uses that eventually reaches surface water. We find that: 1) several water chemistry variables are best fit by legacy LULC while others have a stronger link to current LULC, and 2) single spatial scales of LULC analysis performed worse for most variables. Our novel combination of temporal and spatial scales was the best overall model fit for most variables, including SRP where this model explained 54% of the variation. We show that it is important to explicitly account for temporal and spatial context when linking LULC to ecosystem response. Copyright © 2016. Published by Elsevier B.V.

Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

NASA Astrophysics Data System (ADS)

Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

2017-03-01

Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

Effects of Spatial Patch Arrangement and Scale of Covarying Resources on Growth and Intraspecific Competition of a Clonal Plant

PubMed Central

Wang, Yong-Jian; Shi, Xue-Ping; Meng, Xue-Feng; Wu, Xiao-Jing; Luo, Fang-Li; Yu, Fei-Hai

2016-01-01

Spatial heterogeneity in two co-variable resources such as light and water availability is common and can affect the growth of clonal plants. Several studies have tested effects of spatial heterogeneity in the supply of a single resource on competitive interactions of plants, but none has examined those of heterogeneous distribution of two co-variable resources. In a greenhouse experiment, we grew one (without intraspecific competition) or nine isolated ramets (with competition) of a rhizomatous herb Iris japonica under a homogeneous environment and four heterogeneous environments differing in patch arrangement (reciprocal and parallel patchiness of light and soil water) and patch scale (large and small patches of light and water). Intraspecific competition significantly decreased the growth of I. japonica, but at the whole container level there were no significant interaction effects of competition by spatial heterogeneity or significant effect of heterogeneity on competitive intensity. Irrespective of competition, the growth of I. japonica in the high and the low water patches did not differ significantly in the homogeneous treatments, but it was significantly larger in the high than in the low water patches in the heterogeneous treatments with large patches. For the heterogeneous treatments with small patches, the growth of I. japonica was significantly larger in the high than in the low water patches in the presence of competition, but such an effect was not significant in the absence of competition. Furthermore, patch arrangement and patch scale significantly affected competitive intensity at the patch level. Therefore, spatial heterogeneity in light and water supply can alter intraspecific competition at the patch level and such effects depend on patch arrangement and patch scale. PMID:27375630

Effects of Spatial Patch Arrangement and Scale of Covarying Resources on Growth and Intraspecific Competition of a Clonal Plant.

PubMed

Wang, Yong-Jian; Shi, Xue-Ping; Meng, Xue-Feng; Wu, Xiao-Jing; Luo, Fang-Li; Yu, Fei-Hai

2016-01-01

Spatial heterogeneity in two co-variable resources such as light and water availability is common and can affect the growth of clonal plants. Several studies have tested effects of spatial heterogeneity in the supply of a single resource on competitive interactions of plants, but none has examined those of heterogeneous distribution of two co-variable resources. In a greenhouse experiment, we grew one (without intraspecific competition) or nine isolated ramets (with competition) of a rhizomatous herb Iris japonica under a homogeneous environment and four heterogeneous environments differing in patch arrangement (reciprocal and parallel patchiness of light and soil water) and patch scale (large and small patches of light and water). Intraspecific competition significantly decreased the growth of I. japonica, but at the whole container level there were no significant interaction effects of competition by spatial heterogeneity or significant effect of heterogeneity on competitive intensity. Irrespective of competition, the growth of I. japonica in the high and the low water patches did not differ significantly in the homogeneous treatments, but it was significantly larger in the high than in the low water patches in the heterogeneous treatments with large patches. For the heterogeneous treatments with small patches, the growth of I. japonica was significantly larger in the high than in the low water patches in the presence of competition, but such an effect was not significant in the absence of competition. Furthermore, patch arrangement and patch scale significantly affected competitive intensity at the patch level. Therefore, spatial heterogeneity in light and water supply can alter intraspecific competition at the patch level and such effects depend on patch arrangement and patch scale.

Mapping social values for urban green spaces using Public Participation GIS: the influence of spatial scale and implications for landscape planning.

NASA Astrophysics Data System (ADS)

Ives, Christopher

2015-04-01

Measuring social values for landscapes is an emerging field of research and is critical to the successful management of urban ecosystems. Green open space planning has traditionally relied on rigid standards and metrics without considering the physical requirements of green spaces that are valued for different reasons and by different people. Relating social landscape values to key environmental variables provides a much stronger evidence base for planning landscapes that are both socially desirable and environmentally sustainable. This study spatially quantified residents' values for green space in the Lower Hunter Valley of New South Wales, Australia by enabling participants to mark their values for specific open spaces on interactive paper maps. The survey instrument was designed to evaluate the effect of spatial scale by providing maps of residents' local area at both suburb and municipality scales. The importance of open space values differed depending on whether they were indicated via marker dots or reported on in a general aspatial sense. This suggests that certain open space functions were inadequately provided for in the local area (specifically, cultural significance and health/therapeutic value). Additionally, all value types recorded a greater abundance of marker dots at the finer (suburb) scale compared to the coarser (municipality) scale, but this pattern was more pronounced for some values than others (e.g. physical exercise value). Finally, significant relationships were observed between the abundance of value marker dots in parks and their environmental characteristics (e.g. percentage of vegetation). These results have interesting implications when considering the compatibility between different functions of green spaces and how planners can incorporate information about social values with more traditional approaches to green space planning.

Spatially dependent responses of a large-river fish assemblage to bank stabilization and side channels

USGS Publications Warehouse

Reinhold, Ann Marie; Bramblett, Robert G.; Zale, Alexander V.; Poole, Geoffrey C.; Roberts, David W.

2017-01-01

The alteration of rivers by anthropogenic bank stabilization to prevent the erosion of economically valuable lands and structures has become commonplace. However, such alteration has ambiguous consequences for fish assemblages, especially in large rivers. Because most large, temperate rivers have impoundments, it can be difficult to separate the influences of bank stabilization structures from those of main-stem impoundments, especially because both stabilization structures and impoundments can cause side-channel loss. Few large rivers are free flowing and retain extensive side channels, but the Yellowstone River (our study area) is one such river. We hypothesized that in this river (1) bank stabilization has changed fish assemblage structure by altering habitats, (2) side-channel availability has influenced fish assemblage structure by providing habitat heterogeneity, and (3) the influences of bank stabilization and side channels on fish assemblages were spatially scale dependent. We developed a spatially explicit framework to test these hypotheses. Fish assemblage structure varied with the extent of bank stabilization and the availability of side channels; however, not all assemblage subsets were influenced. Nevertheless, bank stabilization and side channels had different and sometimes opposite influences on the fish assemblage. The effects of side channels on fish were more consistent and widespread than those of bank stabilization; the catches of more fishes were positively correlated with side-channel availability than with the extent of bank stabilization. The influences of bank stabilization and side channels on the relative abundances of fish also varied, depending on species and river bend geomorphology. The variation in river morphology probably contributed to the assemblage differences between stabilized and reference river bends; stabilized alluvial pools were deeper than reference alluvial pools, but the depths of stabilized and reference bluff pools did not differ. The strengths of the relationships among fish assemblages, bank stabilization, and side channels were spatially scale dependent; optimum spatial scales ranged from less than 200 m to 3,200 m up- and downstream, suggesting that bank stabilization and side channels influenced fish assemblages across multiple spatial scales.

Optimal configurations of spatial scale for grid cell firing under noise and uncertainty

PubMed Central

Towse, Benjamin W.; Barry, Caswell; Bush, Daniel; Burgess, Neil

2014-01-01

We examined the accuracy with which the location of an agent moving within an environment could be decoded from the simulated firing of systems of grid cells. Grid cells were modelled with Poisson spiking dynamics and organized into multiple ‘modules’ of cells, with firing patterns of similar spatial scale within modules and a wide range of spatial scales across modules. The number of grid cells per module, the spatial scaling factor between modules and the size of the environment were varied. Errors in decoded location can take two forms: small errors of precision and larger errors resulting from ambiguity in decoding periodic firing patterns. With enough cells per module (e.g. eight modules of 100 cells each) grid systems are highly robust to ambiguity errors, even over ranges much larger than the largest grid scale (e.g. over a 500 m range when the maximum grid scale is 264 cm). Results did not depend strongly on the precise organization of scales across modules (geometric, co-prime or random). However, independent spatial noise across modules, which would occur if modules receive independent spatial inputs and might increase with spatial uncertainty, dramatically degrades the performance of the grid system. This effect of spatial uncertainty can be mitigated by uniform expansion of grid scales. Thus, in the realistic regimes simulated here, the optimal overall scale for a grid system represents a trade-off between minimizing spatial uncertainty (requiring large scales) and maximizing precision (requiring small scales). Within this view, the temporary expansion of grid scales observed in novel environments may be an optimal response to increased spatial uncertainty induced by the unfamiliarity of the available spatial cues. PMID:24366144

Classification of Farmland Landscape Structure in Multiple Scales

NASA Astrophysics Data System (ADS)

Jiang, P.; Cheng, Q.; Li, M.

2017-12-01

Farmland is one of the basic terrestrial resources that support the development and survival of human beings and thus plays a crucial role in the national security of every country. Pattern change is the intuitively spatial representation of the scale and quality variation of farmland. Through the characteristic development of spatial shapes as well as through changes in system structures, functions and so on, farmland landscape patterns may indicate the landscape health level. Currently, it is still difficult to perform positioning analyses of landscape pattern changes that reflect the landscape structure variations of farmland with an index model. Depending on a number of spatial properties such as locations and adjacency relations, distance decay, fringe effect, and on the model of patch-corridor-matrix that is applied, this study defines a type system of farmland landscape structure on the national, provincial, and city levels. According to such a definition, the classification model of farmland landscape-structure type at the pixel scale is developed and validated based on mathematical-morphology concepts and on spatial-analysis methods. Then, the laws that govern farmland landscape-pattern change in multiple scales are analyzed from the perspectives of spatial heterogeneity, spatio-temporal evolution, and function transformation. The result shows that the classification model of farmland landscape-structure type can reflect farmland landscape-pattern change and its effects on farmland production function. Moreover, farmland landscape change in different scales displayed significant disparity in zonality, both within specific regions and in urban-rural areas.

Multi-Decadal Pathfinder Data Sets of Global Land Biophysical Variables from AVHRR and MODIS and their Use in GCM Studies of Biogeophysics and Biogeochemistry

NASA Technical Reports Server (NTRS)

Myneni, Ranga

2003-01-01

The problem of how the scale, or spatial resolution, of reflectance data impacts retrievals of vegetation leaf area index (LAI) and fraction absorbed photosynthetically active radiation (PAR) has been investigated. We define the goal of scaling as the process by which it is established that LAI and FPAR values derived from coarse resolution sensor data equal the arithmetic average of values derived independently from fine resolution sensor data. The increasing probability of land cover mixtures with decreasing resolution is defined as heterogeneity, which is a key concept in scaling studies. The effect of pixel heterogeneity on spectral reflectances and LAI/FPAR retrievals is investigated with 1 km Advanced Very High Resolution Radiometer (AVHRR) data aggregated to different coarse spatial resolutions. It is shown that LAI retrieval errors at coarse resolution are inversely related to the proportion of the dominant land cover in such pixel. Further, large errors in LAI retrievals are incurred when forests are minority biomes in non-forest pixels compared to when forest biomes are mixed with one another, and vice-versa. A physically based technique for scaling with explicit spatial resolution dependent radiative transfer formulation is developed. The successful application of this theory to scaling LAI retrievals from AVHRR data of different resolutions is demonstrated

Assessing the Spatial Scale Effect of Anthropogenic Factors on Species Distribution

PubMed Central

Mangiacotti, Marco; Scali, Stefano; Sacchi, Roberto; Bassu, Lara; Nulchis, Valeria; Corti, Claudia

2013-01-01

Patch context is a way to describe the effect that the surroundings exert on a landscape patch. Despite anthropogenic context alteration may affect species distributions by reducing the accessibility to suitable patches, species distribution modelling have rarely accounted for its effects explicitly. We propose a general framework to statistically detect the occurrence and the extent of such a factor, by combining presence-only data, spatial distribution models and information-theoretic model selection procedures. After having established the spatial resolution of the analysis on the basis of the species characteristics, a measure of anthropogenic alteration that can be quantified at increasing distance from each patch has to be defined. Then the distribution of the species is modelled under competing hypotheses: H0, assumes that the distribution is uninfluenced by the anthropogenic variables; H1, assumes the effect of alteration at the species scale (resolution); and H2, H3 … Hn add the effect of context alteration at increasing radii. Models are compared using the Akaike Information Criterion to establish the best hypothesis, and consequently the occurrence (if any) and the spatial scale of the anthropogenic effect. As a study case we analysed the distribution data of two insular lizards (one endemic and one naturalised) using four alternative hypotheses: no alteration (H0), alteration at the species scale (H1), alteration at two context scales (H2 and H3). H2 and H3 performed better than H0 and H1, highlighting the importance of context alteration. H2 performed better than H3, setting the spatial scale of the context at 1 km. The two species respond differently to context alteration, the introduced lizard being more tolerant than the endemic one. The proposed approach supplies reliably and interpretable results, uses easily available data on species distribution, and allows the assessing of the spatial scale at which human disturbance produces the heaviest effects. PMID:23825669

Imaging multi-scale dynamics in vivo with spiral volumetric optoacoustic tomography

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; Fehm, Thomas F.; Ford, Steven J.; Gottschalk, Sven; Razansky, Daniel

2017-03-01

Imaging dynamics in living organisms is essential for the understanding of biological complexity. While multiple imaging modalities are often required to cover both microscopic and macroscopic spatial scales, dynamic phenomena may also extend over different temporal scales, necessitating the use of different imaging technologies based on the trade-off between temporal resolution and effective field of view. Optoacoustic (photoacoustic) imaging has been shown to offer the exclusive capability to link multiple spatial scales ranging from organelles to entire organs of small animals. Yet, efficient visualization of multi-scale dynamics remained difficult with state-of-the-art systems due to inefficient trade-offs between image acquisition and effective field of view. Herein, we introduce a spiral volumetric optoacoustic tomography (SVOT) technique that provides spectrally-enriched high-resolution optical absorption contrast across multiple spatio-temporal scales. We demonstrate that SVOT can be used to monitor various in vivo dynamics, from video-rate volumetric visualization of cardiac-associated motion in whole organs to high-resolution imaging of pharmacokinetics in larger regions. The multi-scale dynamic imaging capability thus emerges as a powerful and unique feature of the optoacoustic technology that adds to the multiple advantages of this technology for structural, functional and molecular imaging.

Polymorphic mountain whitefish (Prosopium williamsoni) in a coastal riverscape: size class assemblages, distribution, and habitat associations

USGS Publications Warehouse

Starr, James C.; Torgersen, Christian E.

2015-01-01

We compared the assemblage structure, spatial distributions, and habitat associations of mountain whitefish (Prosopium williamsoni) morphotypes and size classes. We hypothesised that morphotypes would have different spatial distributions and would be associated with different habitat features based on feeding behaviour and diet. Spatially continuous sampling was conducted over a broad extent (29 km) in the Calawah River, WA (USA). Whitefish were enumerated via snorkelling in three size classes: small (10–29 cm), medium (30–49 cm), and large (≥50 cm). We identified morphotypes based on head and snout morphology: a pinocchio form that had an elongated snout and a normal form with a blunted snout. Large size classes of both morphotypes were distributed downstream of small and medium size classes, and normal whitefish were distributed downstream of pinocchio whitefish. Ordination of whitefish assemblages with nonmetric multidimensional scaling revealed that normal whitefish size classes were associated with higher gradient and depth, whereas pinocchio whitefish size classes were positively associated with pool area, distance upstream, and depth. Reach-scale generalised additive models indicated that normal whitefish relative density was associated with larger substrate size in downstream reaches (R2 = 0.64), and pinocchio whitefish were associated with greater stream depth in the reaches farther upstream (R2 = 0.87). These results suggest broad-scale spatial segregation (1–10 km), particularly between larger and more phenotypically extreme individuals. These results provide the first perspective on spatial distributions and habitat relationships of polymorphic mountain whitefish.

Spatial and temporal aspects of chromatic adaptation and their functional significance for colour constancy.

PubMed

Werner, Annette

2014-11-01

Illumination in natural scenes changes at multiple temporal and spatial scales: slow changes in global illumination occur in the course of a day, and we encounter fast and localised illumination changes when visually exploring the non-uniform light field of three-dimensional scenes; in addition, very long-term chromatic variations may come from the environment, like for example seasonal changes. In this context, I consider the temporal and spatial properties of chromatic adaptation and discuss their functional significance for colour constancy in three-dimensional scenes. A process of fast spatial tuning in chromatic adaptation is proposed as a possible sensory mechanism for linking colour constancy to the spatial structure of a scene. The observed middlewavelength selectivity of this process is particularly suitable for adaptation to the mean chromaticity and the compensation of interreflections in natural scenes. Two types of sensory colour constancy are distinguished, based on the functional differences of their temporal and spatial scales: a slow type, operating at a global scale for the compensation of the ambient illumination; and a fast colour constancy, which is locally restricted and well suited to compensate region-specific variations in the light field of three dimensional scenes. Copyright © 2014 Elsevier B.V. All rights reserved.

Conspecific and Heterospecific Plant Densities at Small-Scale Can Drive Plant-Pollinator Interactions

PubMed Central

Janovský, Zdeněk; Mikát, Michael; Hadrava, Jiří; Horčičková, Eva; Kmecová, Kateřina; Požárová, Doubravka; Smyčka, Jan; Herben, Tomáš

2013-01-01

Generalist pollinators are important in many habitats, but little research has been done on small-scale spatial variation in interactions between them and the plants that they visit. Here, using a spatially explicit approach, we examined whether multiple species of flowering plants occurring within a single meadow showed spatial structure in their generalist pollinator assemblages. We report the results for eight plant species for which at least 200 individual visits were recorded. We found that for all of these species, the proportions of their general pollinator assemblages accounted for by particular functional groups showed spatial heterogeneity at the scale of tens of metres. This heterogeneity was connected either with no or only subtle changes of vegetation and flowering species composition. In five of these species, differences in conspecific plant density influenced the pollinator communities (with greater dominance of main pollinators at low-conspecific plant densities). The density of heterospecific plant individuals influenced the pollinator spectrum in one case. Our results indicate that the picture of plant-pollinator interactions provided by averaging data within large plots may be misleading and that within-site spatial heterogeneity should be accounted for in terms of sampling effort allocation and analysis. Moreover, spatially structured plant-pollinator interactions may have important ecological and evolutionary consequences, especially for plant population biology. PMID:24204818

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir.

PubMed

Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-09-23

The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies.

Extended-range high-resolution dynamical downscaling over a continental-scale spatial domain with atmospheric and surface nudging

NASA Astrophysics Data System (ADS)

Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.

2014-12-01

Extended-range high-resolution mesoscale simulations with limited-area atmospheric models when applied to downscale regional analysis fields over large spatial domains can provide valuable information for many applications including the weather-dependent renewable energy industry. Long-term simulations over a continental-scale spatial domain, however, require mechanisms to control the large-scale deviations in the high-resolution simulated fields from the coarse-resolution driving fields. As enforcement of the lateral boundary conditions is insufficient to restrict such deviations, large scales in the simulated high-resolution meteorological fields are therefore spectrally nudged toward the driving fields. Different spectral nudging approaches, including the appropriate nudging length scales as well as the vertical profiles and temporal relaxations for nudging, have been investigated to propose an optimal nudging strategy. Impacts of time-varying nudging and generation of hourly analysis estimates are explored to circumvent problems arising from the coarse temporal resolution of the regional analysis fields. Although controlling the evolution of the atmospheric large scales generally improves the outputs of high-resolution mesoscale simulations within the surface layer, the prognostically evolving surface fields can nevertheless deviate from their expected values leading to significant inaccuracies in the predicted surface layer meteorology. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil moisture, and snow conditions, toward their expected values obtained from a high-resolution offline surface scheme is therefore proposed to limit any considerable deviation. Finally, wind speed and temperature at wind turbine hub height predicted by different spectrally nudged extended-range simulations are compared against observations to demonstrate possible improvements achievable using higher spatiotemporal resolution.

Enabling global collaborations through policy engagement and CMS applications

NASA Astrophysics Data System (ADS)

Escobar, V. M.; Sepulveda Carlo, E.; Delgado Arias, S.

2015-12-01

Different spatial scales prompt different discussions among carbon data stakeholders. NASA's Carbon Monitoring System (CMS) initiative has enabled collaboration opportunities with stakeholders whose data needs and requirements are unique to the spatial scope of their work: from county to the international scale. At the very local level, the Sonoma County Agricultural Preservation and Open Space District leverages CMS high-resolution biomass estimates to develop a Monitoring, Reporting, and Verification (MRV) system in support of the District's 10-year land stewardship plan and the California's Global Warming Solutions Act (AB32). On the eastern coast, at the state level, the Maryland Department of Natural Resources utilizes the same high-resolution biomass estimates on a larger scale to better strategize in achieving the goal of 40% canopy cover statewide by 2020. At a regional scale that encompasses the three states of Maryland, Delaware, and Pennsylvania, LiDAR data collection of the Chesapeake Bay watershed dominate the stakeholder discussions. By collaborating with the U.S. Geological Survey's 3-D Elevation Program (3DEP), high-resolution LiDAR data will fill critical data gaps to help implement watershed protection strategies such as increasing riparian forest buffers to reduce runoff. Outside of the U.S., the World Resources Institute seeks to harness CMS reforestation products and technical expertise in addressing land restoration priorities specific to each Latin American country. CMS applications efforts expand beyond forest carbon examples discussed above to include carbon markets, ocean acidification, national greenhouse gas inventory, and wetlands. The broad array of case studies and lessons learned through CMS Applications in scaling carbon science for policy development at different spatial scales is providing unique opportunities that leverage science through policy needs.

Spatial variation of dissolved organic matter composition and characteristics in an urbanized watershed

NASA Astrophysics Data System (ADS)

Hsieh, C.; Li, M.

2013-12-01

Dissolved organic matter (DOM) is a chemically complex mixture of organic polymers that plays an important role in river ecosystems and originates from various sources. Some DOMs are autochthonous originating through phytoplankton and microbial activity in situ. On the other hand, some DOMs are allochthonous which are transported to river from the surrounding watershed by natural or anthropogenic activities. The studies of DOM in river are usually conducted at the watershed scale; however, factors of local spatial scale affecting DOM composition also need to take into consideration for the study of DOM in an urbanized watershed. Through increasing urbanization, changes in a watershed occur not only in land use patterns but also in river channel characteristics. The objective of this study is to investigate effects of different river channel characteristics and patterns on changes in DOM source and composition. In this study, we chose three tributaries of Tamsui river in Taiwan according to its land use pattern and river channel characteristics. At each sub-basin, river water samples were sampled from three study sites. River water DOM was measured by using optical measurements of UV absorption and fluorescence spectroscopy. Water samples were also collected for laboratory analysis of different water quality parameters. From our study sites, they are from three sub-basins which are in the similar physical environments but with different river channel types: the highly channelized Keelung river, the less channelized Xindian river, and less channelized Dahan river with five human-made wetlands. From the upstream to the urbanized downstream, composition of DOM showed variation among different sampled sites. In all three sub-basins, the trends of 5-day biochemical oxygen demand (BOD5) and suspended solids (SS) are also different. The changes in DOM source and composition as well as different water quality parmaters occur at the local spatial-scale depended on their river channel characters in urbanized watersheds. Based on our result, it indicates river channel characters which can have effects on biogeochemical processes of DOM. This knowledge can help us in understanding biogeochemical processes controlled or manipulated by anthropogenic activities at different spatial scales, and help us to make an integrative river health management in a watershed.

Land use and climate affect Black Tern, Northern Harrier, and Marsh Wren abundance in the Prairie Pothole Region of the United States

USGS Publications Warehouse

Forcey, Greg M.; Thogmartin, Wayne E.; Linz, George M.; McKann, Patrick C.

2014-01-01

Bird populations are influenced by many environmental factors at both large and small scales. Our study evaluated the influences of regional climate and land-use variables on the Northern Harrier (Circus cyaneus), Black Tern (Childonias niger), and Marsh Wren (Cistothorus palustris) in the prairie potholes of the upper Midwest of the United States. These species were chosen because their diverse habitat preference represent the spectrum of habitat conditions present in the Prairie Potholes, ranging from open prairies to dense cattail marshes. We evaluated land-use covariates at three logarithmic spatial scales (1,000 ha, 10,000 ha, and 100,000 ha) and constructed models a priori using information from published habitat associations and climatic influences. The strongest influences on the abundance of each of the three species were the percentage of wetland area across all three spatial scales and precipitation in the year preceding that when bird surveys were conducted. Even among scales ranging over three orders of magnitude the influence of spatial scale was small, as models with the same variables expressed at different scales were often in the best model subset. Examination of the effects of large-scale environmental variables on wetland birds elucidated relationships overlooked in many smaller-scale studies, such as the influences of climate and habitat variables at landscape scales. Given the spatial variation in the abundance of our focal species within the prairie potholes, our model predictions are especially useful for targeting locations, such as northeastern South Dakota and central North Dakota, where management and conservation efforts would be optimally beneficial. This modeling approach can also be applied to other species and geographic areas to focus landscape conservation efforts and subsequent small-scale studies, especially in constrained economic climates.

Sex Differences in Spatial Memory in Brown-Headed Cowbirds: Males Outperform Females on a Touchscreen Task

PubMed Central

Guigueno, Mélanie F.; MacDougall-Shackleton, Scott A.; Sherry, David F.

2015-01-01

Spatial cognition in females and males can differ in species in which there are sex-specific patterns in the use of space. Brown-headed cowbirds are brood parasites that show a reversal of sex-typical space use often seen in mammals. Female cowbirds, search for, revisit and parasitize hosts nests, have a larger hippocampus than males and have better memory than males for a rewarded location in an open spatial environment. In the current study, we tested female and male cowbirds in breeding and non-breeding conditions on a touchscreen delayed-match-to-sample task using both spatial and colour stimuli. Our goal was to determine whether sex differences in spatial memory in cowbirds generalizes to all spatial tasks or is task-dependant. Both sexes performed better on the spatial than on the colour touchscreen task. On the spatial task, breeding males outperformed breeding females. On the colour task, females and males did not differ, but females performed better in breeding condition than in non-breeding condition. Although female cowbirds were observed to outperform males on a previous larger-scale spatial task, males performed better than females on a task testing spatial memory in the cowbirds’ immediate visual field. Spatial abilities in cowbirds can favour males or females depending on the type of spatial task, as has been observed in mammals, including humans. PMID:26083573

Consistency of Aquarius version-4 sea surface salinity with Argo products on various spatial and temporal scales

NASA Astrophysics Data System (ADS)

Lee, T.

2016-12-01

Understanding the accuracies of satellite-derived sea surface salinity (SSS) measurements in depicting temporal changes and the dependence of the accuracies on spatio-temporal scales are important to applications, capability assessment, and future mission design. This study quantifies the consistency between Aquarius Version-4 monthly gridded SSS (released in October 2015) with two widely used Argo monthly gridded near-surface salinity products. The analysis focused on their consistency in depicting temporal changes (including seasonal and non-seasonal) on various spatial scales: 1°x1°, 3°x3°, and 10°x10°. Globally averaged standard deviation (STD) values for Aquarius-Argo salinity differences on these three spatial scales are 0.16, 0.14, 0.09 psu, compared to those between the two Argo products of 0.10, 0.09, and 0.04 psu. Aquarius SSS compare better with Argo data on non-seasonal (e.g., interannual and intraseasonal) than for seasonal time scales. The seasonal Aquarius-Argo SSS differences are mostly concentrated at high latitudes. The Aquarius team is making active efforts to further reduce these high-latitude seasonal biases. The consistency between Aquarius and Argo salinity is similar to that between the two Argo products in the tropics and subtropics for non-seasonal signals, and in the tropics for seasonal signals. Therefore, the representativeness errors of the Argo products for various spatial scales (related to sampling and gridding) need to be taken into account when estimating the uncertainty of Aquarius SSS. The globally averaged uncertainty of large-scale (10°x10°) non-seasonal Aquarius SSS is approximately 0.04 psu. These estimates reflect the significant improvements of Aquarius Version-4 SSS over the previous versions. The estimates can be used as baseline requirements for future ocean salinity missions from space.

The spatial scale for cisco recruitment dynamics in Lake Superior during 1978-2007

USGS Publications Warehouse

Rook, Benjamin J.; Hansen, Michael J.; Gorman, Owen T.

2012-01-01

The cisco Coregonus artedi was once the most abundant fish species in the Great Lakes, but currently cisco populations are greatly reduced and management agencies are attempting to restore the species throughout the basin. To increase understanding of the spatial scale at which density‐independent and density‐dependent factors influence cisco recruitment dynamics in the Great Lakes, we used a Ricker stock–recruitment model to identify and quantify the appropriate spatial scale for modeling age‐1 cisco recruitment dynamics in Lake Superior. We found that the recruitment variation of ciscoes in Lake Superior was best described by a five‐parameter regional model with separate stock–recruitment relationships for the western, southern, eastern, and northern regions. The spatial scale for modeling was about 260 km (range = 230–290 km). We also found that the density‐independent recruitment rate and the rate of compensatory density dependence varied among regions at different rates. The density‐independent recruitment rate was constant among regions (3.6 age‐1 recruits/spawner), whereas the rate of compensatory density dependence varied 16‐fold among regions (range = −0.2 to −2.9/spawner). Finally, we found that peak recruitment and the spawning stock size that produced peak recruitment varied among regions. Both peak recruitment (0.5–7.1 age‐1 recruits/ha) and the spawning stock size that produced peak recruitment (0.3–5.3 spawners/ha) varied 16‐fold among regions. Our findings support the hypothesis that the factors driving cisco recruitment operate within four different regions of Lake Superior, suggest that large‐scale abiotic factors are more important than small‐scale biotic factors in influencing cisco recruitment, and suggest that fishery managers throughout Lake Superior and the entire Great Lakes basin should address cisco restoration and management efforts on a regional scale in each lake.

Environmental characteristics drive variation in Amazonian understorey bird assemblages

PubMed Central

Magnusson, William E.; Anderson, Marti J.; Schlegel, Martin; Pe’er, Guy; Henle, Klaus

2017-01-01

Tropical bird assemblages display patterns of high alpha and beta diversity and, as tropical birds exhibit strong habitat specificity, their spatial distributions are generally assumed to be driven primarily by environmental heterogeneity and interspecific interactions. However, spatial distributions of some Amazonian forest birds are also often restricted by large rivers and other large-scale topographic features, suggesting that dispersal limitation may also play a role in driving species’ turnover. In this study, we evaluated the effects of environmental characteristics, topographic and spatial variables on variation in local assemblage structure and diversity of birds in an old-growth forest in central Amazonia. Birds were mist-netted in 72 plots distributed systematically across a 10,000 ha reserve in each of three years. Alpha diversity remained stable through time, but species composition changed. Spatial variation in bird-assemblage structure was significantly related to environmental and topographic variables but not strongly related to spatial variables. At a broad scale, we found bird assemblages to be significantly distinct between two watersheds that are divided by a central ridgeline. We did not detect an effect of the ridgeline per se in driving these patterns, indicating that most birds are able to fly across it, and that differences in assemblage structure between watersheds may be due to unmeasured environmental variables or unique combinations of measured variables. Our study indicates that complex geography and landscape features can act together with environmental variables to drive changes in the diversity and composition of tropical bird assemblages at local scales, but highlights that we still know very little about what makes different parts of tropical forest suitable for different species. PMID:28225774

Exploring the Linkage between Urban Flood Risk and Spatial Patterns in Small Urbanized Catchments of Beijing, China

PubMed Central

Yao, Lei; Chen, Liding; Wei, Wei

2017-01-01

In the context of global urbanization, urban flood risk in many cities has become a serious environmental issue, threatening the health of residents and the environment. A number of hydrological studies have linked urban flooding issues closely to the spectrum of spatial patterns of urbanization, but relatively little attention has been given to small-scale catchments within the realm of urban systems. This study aims to explore the hydrological effects of small-scaled urbanized catchments assigned with various landscape patterns. Twelve typical residential catchments in Beijing were selected as the study areas. Total Impervious Area (TIA), Directly Connected Impervious Area (DCIA), and a drainage index were used as the catchment spatial metrics. Three scenarios were designed as different spatial arrangement of catchment imperviousness. Runoff variables including total and peak runoff depth (Qt and Qp) were simulated by using Strom Water Management Model (SWMM). The relationship between catchment spatial patterns and runoff variables were determined, and the results demonstrated that, spatial patterns have inherent influences on flood risks in small urbanized catchments. Specifically: (1) imperviousness acts as an effective indicator in affecting both Qt and Qp; (2) reducing the number of rainwater inlets appropriately will benefit the catchment peak flow mitigation; (3) different spatial concentrations of impervious surfaces have inherent influences on Qp. These findings provide insights into the role of urban spatial patterns in driving rainfall-runoff processes in small urbanized catchments, which is essential for urban planning and flood management. PMID:28264521

Exploring the Linkage between Urban Flood Risk and Spatial Patterns in Small Urbanized Catchments of Beijing, China.

PubMed

Yao, Lei; Chen, Liding; Wei, Wei

2017-02-28

In the context of global urbanization, urban flood risk in many cities has become a serious environmental issue, threatening the health of residents and the environment. A number of hydrological studies have linked urban flooding issues closely to the spectrum of spatial patterns of urbanization, but relatively little attention has been given to small-scale catchments within the realm of urban systems. This study aims to explore the hydrological effects of small-scaled urbanized catchments assigned with various landscape patterns. Twelve typical residential catchments in Beijing were selected as the study areas. Total Impervious Area ( TIA ), Directly Connected Impervious Area ( DCIA ), and a drainage index were used as the catchment spatial metrics. Three scenarios were designed as different spatial arrangement of catchment imperviousness. Runoff variables including total and peak runoff depth ( Q t and Q p ) were simulated by using Strom Water Management Model (SWMM). The relationship between catchment spatial patterns and runoff variables were determined, and the results demonstrated that, spatial patterns have inherent influences on flood risks in small urbanized catchments. Specifically: (1) imperviousness acts as an effective indicator in affecting both Q t and Q p ; (2) reducing the number of rainwater inlets appropriately will benefit the catchment peak flow mitigation; (3) different spatial concentrations of impervious surfaces have inherent influences on Q p . These findings provide insights into the role of urban spatial patterns in driving rainfall-runoff processes in small urbanized catchments, which is essential for urban planning and flood management.

Spatial ability in secondary school students: intra-sex differences based on self-selection for physical education.

PubMed

Tlauka, Michael; Williams, Jennifer; Williamson, Paul

2008-08-01

Past research has demonstrated consistent sex differences with men typically outperforming women on tests of spatial ability. However, less is known about intra-sex effects. In the present study, two groups of female students (physical education and non-physical education secondary students) and two corresponding groups of male students explored a large-scale virtual shopping centre. In a battery of tasks, spatial knowledge of the shopping centre as well as mental rotation ability were tested. Additional variables considered were circulating testosterone levels, the ratio of 2D:4D digit length, and computer experience. The results revealed both sex and intra-sex differences in spatial ability. Variables related to virtual navigation and computer ability and experience were found to be the most powerful predictors of group membership. Our results suggest that in female and male secondary students, participation in physical education and spatial skill are related.

Navigating in small-scale space: the role of landmarks and resource monitoring in understanding saddleback tamarin travel.

PubMed

Garber, Paul A; Porter, Leila M

2014-05-01

Recent studies of spatial memory in wild nonhuman primates indicate that foragers may rely on a combination of navigational strategies to locate nearby and distant feeding sites. When traveling in large-scale space, tamarins are reported to encode spatial information in the form of a route-based map. However, little is known concerning how wild tamarins navigate in small-scale space (between feeding sites located at a distance of ≤60 m). Therefore, we collected data on range use, diet, and the angle and distance traveled to visit sequential feeding sites in the same group of habituated Bolivian saddleback tamarins (Saguinus fuscicollis weddelli) in 2009 and 2011. For 7-8 hr a day for 54 observation days, we recorded the location of the study group at 10 min intervals using a GPS unit. We then used GIS software to map and analyze the monkeys' movements and travel paths taken between feeding sites. Our results indicate that in small-scale space the tamarins relied on multiple spatial strategies. In 31% of cases travel was route-based. In the remaining 69% of cases, however, the tamarins appeared to attend to the spatial positions of one or more near-to-site landmarks to relocate feeding sites. In doing so they approached the same feeding site from a mean of 4.5 different directions, frequently utilized different arboreal pathways, and traveled approximately 30% longer than then the straight-line distance. In addition, the monkeys' use of non-direct travel paths allowed them to monitor insect and fruit availability in areas within close proximity of currently used food patches. We conclude that the use of an integrated spatial strategy (route-based travel and attention to near-to-goal landmarks) provides tamarins with the opportunity to relocate productive feeding sites as well as monitor the availability of nearby resources in small-scale space. © 2013 Wiley Periodicals, Inc.

Lagrangian coherent structures separate dynamically distinct regions in fluid flows.

PubMed

Kelley, Douglas H; Allshouse, Michael R; Ouellette, Nicholas T

2013-07-01

Using filter-space techniques, we study the scale-to-scale transport of energy in a quasi-two-dimensional, weakly turbulent fluid flow averaged along the trajectories of fluid elements. We find that although the spatial mean of this Lagrangian-averaged flux is nearly unchanged from its Eulerian counterpart, the spatial structure of the scale-to-scale energy flux changes significantly. In particular, its features appear to correlate with the positions of Lagrangian coherent structures (LCS's). We show that the LCS's tend to lie at zeros of the scale-to-scale flux, and therefore that the LCS's separate regions that have qualitatively different dynamics. Since LCS's are also known to be impenetrable barriers to advection and mixing, we therefore find that the fluid on either side of an LCS is both kinematically and dynamically distinct. Our results extend the utility of LCS's by making clear the role they play in the flow dynamics in addition to the kinematics.

A multi-scale approach to monitor urban carbon-dioxide emissions in the atmosphere over Vancouver, Canada

NASA Astrophysics Data System (ADS)

Christen, A.; Crawford, B.; Ketler, R.; Lee, J. K.; McKendry, I. G.; Nesic, Z.; Caitlin, S.

2015-12-01

Measurements of long-lived greenhouse gases in the urban atmosphere are potentially useful to constrain and validate urban emission inventories, or space-borne remote-sensing products. We summarize and compare three different approaches, operating at different scales, that directly or indirectly identify, attribute and quantify emissions (and uptake) of carbon dioxide (CO2) in urban environments. All three approaches are illustrated using in-situ measurements in the atmosphere in and over Vancouver, Canada. Mobile sensing may be a promising way to quantify and map CO2 mixing ratios at fine scales across heterogenous and complex urban environments. We developed a system for monitoring CO2 mixing ratios at street level using a network of mobile CO2 sensors deployable on vehicles and bikes. A total of 5 prototype sensors were built and simultaneously used in a measurement campaign across a range of urban land use types and densities within a short time frame (3 hours). The dataset is used to aid in fine scale emission mapping in combination with simultaneous tower-based flux measurements. Overall, calculated CO2 emissions are realistic when compared against a spatially disaggregated scale emission inventory. The second approach is based on mass flux measurements of CO2 using a tower-based eddy covariance (EC) system. We present a continuous 7-year long dataset of CO2 fluxes measured by EC at the 28m tall flux tower 'Vancouver-Sunset'. We show how this dataset can be combined with turbulent source area models to quantify and partition different emission processes at the neighborhood-scale. The long-term EC measurements are within 10% of a spatially disaggregated scale emission inventory. Thirdly, at the urban scale, we present a dataset of CO2 mixing ratios measured using a tethered balloon system in the urban boundary layer above Vancouver. Using a simple box model, net city-scale CO2 emissions can be determined using measured rate of change of CO2 mixing ratios, estimated CO2 advection and entrainment fluxes. Daily city-scale emissions totals predicted by the model are within 32% of a spatially scaled municipal greenhouse gas inventory. In summary, combining information from different approaches and scales is a promising approach to establish long-term emission monitoring networks in cities.

Spatiotemporal correlation structure of the Earth's surface temperature

NASA Astrophysics Data System (ADS)

Fredriksen, Hege-Beate; Rypdal, Kristoffer; Rypdal, Martin

2015-04-01

We investigate the spatiotemporal temperature variability for several gridded instrumental and climate model data sets. The temporal variability is analysed by estimating the power spectral density and studying the differences between local and global temperatures, land and sea, and among local temperature records at different locations. The spatiotemporal correlation structure is analysed through cross-spectra that allow us to compute frequency-dependent spatial autocorrelation functions (ACFs). Our results are then compared to theoretical spectra and frequency-dependent spatial ACFs derived from a fractional stochastic-diffusive energy balance model (FEBM). From the FEBM we expect both local and global temperatures to have a long-range persistent temporal behaviour, and the spectral exponent (β) is expected to increase by a factor of two when going from local to global scales. Our comparison of the average local spectrum and the global spectrum shows good agreement with this model, although the FEBM has so far only been studied for a pure land planet and a pure ocean planet, respectively, with no seasonal forcing. Hence it cannot capture the substantial variability among the local spectra, in particular between the spectra for land and sea, and for equatorial and non-equatorial temperatures. Both models and observation data show that land temperatures in general have a low persistence, while sea surface temperatures show a higher, and also more variable degree of persistence. Near the equator the spectra deviate from the power-law shape expected from the FEBM. Instead we observe large variability at time scales of a few years due to ENSO, and a flat spectrum at longer time scales, making the spectrum more reminiscent of that of a red noise process. From the frequency-dependent spatial ACFs we observe that the spatial correlation length increases with increasing time scale, which is also consistent with the FEBM. One consequence of this is that longer-lasting structures must also be wider in space. The spatial correlation length is also observed to be longer for land than for sea. The climate model simulations studied are mainly CMIP5 control runs of length 500-1000 yr. On time scales up to several centuries we do not observe that the difference between the local and global spectral exponents vanish. This also follows from the FEBM and shows that the dynamics is spatiotemporal (not just temporal) even on these time scales.

Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality

PubMed Central

Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; MacEachren, Alan M

2008-01-01

Background Kulldorff's spatial scan statistic and its software implementation – SaTScan – are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. Results We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. Conclusion The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. Method We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit. PMID:18992163

Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality.

PubMed

Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; Maceachren, Alan M

2008-11-07

Kulldorff's spatial scan statistic and its software implementation - SaTScan - are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit.

Multiple Point Statistics algorithm based on direct sampling and multi-resolution images

NASA Astrophysics Data System (ADS)

Julien, S.; Renard, P.; Chugunova, T.

2017-12-01

Multiple Point Statistics (MPS) has become popular for more than one decade in Earth Sciences, because these methods allow to generate random fields reproducing highly complex spatial features given in a conceptual model, the training image, while classical geostatistics techniques based on bi-point statistics (covariance or variogram) fail to generate realistic models. Among MPS methods, the direct sampling consists in borrowing patterns from the training image to populate a simulation grid. This latter is sequentially filled by visiting each of these nodes in a random order, and then the patterns, whose the number of nodes is fixed, become narrower during the simulation process, as the simulation grid is more densely informed. Hence, large scale structures are caught in the beginning of the simulation and small scale ones in the end. However, MPS may mix spatial characteristics distinguishable at different scales in the training image, and then loose the spatial arrangement of different structures. To overcome this limitation, we propose to perform MPS simulation using a decomposition of the training image in a set of images at multiple resolutions. Applying a Gaussian kernel onto the training image (convolution) results in a lower resolution image, and iterating this process, a pyramid of images depicting fewer details at each level is built, as it can be done in image processing for example to lighten the space storage of a photography. The direct sampling is then employed to simulate the lowest resolution level, and then to simulate each level, up to the finest resolution, conditioned to the level one rank coarser. This scheme helps reproduce the spatial structures at any scale of the training image and then generate more realistic models. We illustrate the method with aerial photographies (satellite images) and natural textures. Indeed, these kinds of images often display typical structures at different scales and are well-suited for MPS simulation techniques.

Regional Management Units for Marine Turtles: A Novel Framework for Prioritizing Conservation and Research across Multiple Scales

PubMed Central

Wallace, Bryan P.; DiMatteo, Andrew D.; Hurley, Brendan J.; Finkbeiner, Elena M.; Bolten, Alan B.; Chaloupka, Milani Y.; Hutchinson, Brian J.; Abreu-Grobois, F. Alberto; Amorocho, Diego; Bjorndal, Karen A.; Bourjea, Jerome; Bowen, Brian W.; Dueñas, Raquel Briseño; Casale, Paolo; Choudhury, B. C.; Costa, Alice; Dutton, Peter H.; Fallabrino, Alejandro; Girard, Alexandre; Girondot, Marc; Godfrey, Matthew H.; Hamann, Mark; López-Mendilaharsu, Milagros; Marcovaldi, Maria Angela; Mortimer, Jeanne A.; Musick, John A.; Nel, Ronel; Pilcher, Nicolas J.; Seminoff, Jeffrey A.; Troëng, Sebastian; Witherington, Blair; Mast, Roderic B.

2010-01-01

Background Resolving threats to widely distributed marine megafauna requires definition of the geographic distributions of both the threats as well as the population unit(s) of interest. In turn, because individual threats can operate on varying spatial scales, their impacts can affect different segments of a population of the same species. Therefore, integration of multiple tools and techniques — including site-based monitoring, genetic analyses, mark-recapture studies and telemetry — can facilitate robust definitions of population segments at multiple biological and spatial scales to address different management and research challenges. Methodology/Principal Findings To address these issues for marine turtles, we collated all available studies on marine turtle biogeography, including nesting sites, population abundances and trends, population genetics, and satellite telemetry. We georeferenced this information to generate separate layers for nesting sites, genetic stocks, and core distributions of population segments of all marine turtle species. We then spatially integrated this information from fine- to coarse-spatial scales to develop nested envelope models, or Regional Management Units (RMUs), for marine turtles globally. Conclusions/Significance The RMU framework is a solution to the challenge of how to organize marine turtles into units of protection above the level of nesting populations, but below the level of species, within regional entities that might be on independent evolutionary trajectories. Among many potential applications, RMUs provide a framework for identifying data gaps, assessing high diversity areas for multiple species and genetic stocks, and evaluating conservation status of marine turtles. Furthermore, RMUs allow for identification of geographic barriers to gene flow, and can provide valuable guidance to marine spatial planning initiatives that integrate spatial distributions of protected species and human activities. In addition, the RMU framework — including maps and supporting metadata — will be an iterative, user-driven tool made publicly available in an online application for comments, improvements, download and analysis. PMID:21253007

QUALITY ASSURANCE AND QUALITY CONTROL IN THE DEVELOPMENT AND APPLICATION OF THE AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT (AGWA) TOOL

EPA Science Inventory

Planning and assessment in land and water resource management are evolving from simple, local-scale problems toward complex, spatially explicit regional ones. Such problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and t...

Modeling and Spatially Distributing Forest Net Primary Production at the Regional Scale

Treesearch

R.A. Mickler; T.S. Earnhardt; J.A. Moore

2002-01-01

Abstract - Forest, agricultural, rangeland, wetland, and urban landscapes have different rates of carbon sequestration and total carbon sequestration potential under alternative management options. Changes in the proportion and spatial distribution of land use could enhance or degrade that area’s ability to sequester carbon in terrestrial ecosystems...

Den use and selection by northern flying squirrels in fragmented landscapes

Treesearch

Sanjay Pyare; Winston P. Smith; Colin S. Shanley

2010-01-01

We studied den use and den-habitat selection by the Prince of Wales Island flying squirrel (Glaucomys sabrinus griseifrons) at multiple spatial scales in fragmented temperate rain-forest habitats because of the role dens play in the distribution, reproduction, and population density of this endemic subspecies. We observed differences in spatial...

Evidence of territoriality and species interactions from spatial point-pattern analyses of subarctic-nesting geese

USGS Publications Warehouse

Reiter, Matthew E.; Andersen, David E.

2013-01-01

Quantifying spatial patterns of bird nests and nest fate provides insights into processes influencing a species’ distribution. At Cape Churchill, Manitoba, Canada, recent declines in breeding Eastern Prairie Population Canada geese (Branta canadensis interior) has coincided with increasing populations of nesting lesser snow geese (Chen caerulescens caerulescens) and Ross’s geese (Chen rossii). We conducted a spatial analysis of point patterns using Canada goose nest locations and nest fate, and lesser snow goose nest locations at two study areas in northern Manitoba with different densities and temporal durations of sympatric nesting Canada and lesser snow geese. Specifically, we assessed (1) whether Canada geese exhibited territoriality and at what scale and nest density; and (2) whether spatial patterns of Canada goose nest fate were associated with the density of nesting lesser snow geese as predicted by the protective-association hypothesis. Between 2001 and 2007, our data suggest that Canada geese were territorial at the scale of nearest neighbors, but were aggregated when considering overall density of conspecifics at slightly broader spatial scales. The spatial distribution of nest fates indicated that lesser snow goose nest proximity and density likely influence Canada goose nest fate. Our analyses of spatial point patterns suggested that continued changes in the distribution and abundance of breeding lesser snow geese on the Hudson Bay Lowlands may have impacts on the reproductive performance of Canada geese, and subsequently the spatial distribution of Canada goose nests.

Spatial variability of soils in a seasonally dry tropical forest

NASA Astrophysics Data System (ADS)

Pulla, Sandeep; Riotte, Jean; Suresh, Hebbalalu; Dattaraja, Handanakere; Sukumar, Raman

2016-04-01

Soil structures communities of plants and soil organisms in tropical forests. Understanding the controls of soil spatial variability can therefore potentially inform efforts towards forest restoration. We studied the relationship between soils and lithology, topography, vegetation and fire in a seasonally dry tropical forest in southern India. We extensively sampled soil (available nutrients, Al, pH, and moisture), rocks, relief, woody vegetation, and spatial variation in fire burn frequency in a permanent 50-ha plot. Lower elevation soils tended to be less moist and were depleted in several nutrients and clay. The availability of several nutrients was, in turn, linked to whole-rock chemical composition differences since some lithologies were associated with higher elevations, while the others tended to dominate lower elevations. We suggest that local-scale topography in this region has been shaped by the spatial distribution of lithologies, which differ in their susceptibility to weathering. Nitrogen availability was uncorrelated with the presence of trees belonging to Fabaceae, a family associated with N-fixing species. No effect of burning on soil parameters could be discerned at this scale.

Watershed-Scale Heterogeneity of the Biophysical Controls on Soil Respiration

NASA Astrophysics Data System (ADS)

Riveros, D. A.; Pacific, V. J.; McGlynn, B. L.; Welsch, D. L.; Epstein, H. E.; Muth, D. J.; Marshall, L.; Wraith, J.

2006-12-01

Large gaps exist in our understanding of the variability of soil respiration response to changing hydrologic conditions across spatial and temporal scales. Determining the linkages between the hydrologic cycle and the biophysical controls of soil respiration from the local point, to the plot, to the watershed scale is critical to understanding the dynamics of net ecosystem CO2 exchange (NEE). To study the biophysical controls of soil respiration, we measured soil CO2 concentration, soil CO2 flux, dissolved CO2 in stream water, soil moisture, soil temperature, groundwater dynamics, and precipitation at 20-minute intervals throughout the growing season at 4 sites and at weekly intervals at 62 sites covering the range of topographic position, slope, aspect, land cover, and upslope accumulated area conditions in a 555-ha subalpine watershed in central Montana. Our goal was to quantify watershed-scale heterogeneity in soil CO2 concentrations and surface efflux and gain understanding of the biophysical controls on soil respiration. We seek to improve our ability to evaluate and predict soil respiration responses to a dynamic hydrologic cycle across multiple temporal and spatial scales. We found that time lags between biophysical controls and soil respiration can occur from hourly to daily scales. The sensitivity of soil respiration to changes in environmental conditions is controlled by the antecedent soil moisture and by topographic position. At the watershed scale, significant differences in soil respiration exist between upland (dry) and lowland (wet) sites. However, differences in the magnitude and timing of soil respiration also exist within upland settings due to heterogeneity in soil temperature, soil moisture, and soil organic matter. Finally, we used a process-based model to simulate respiration at different times of the year across spatial locations. Our simulations highlight the importance of autotrophic and heterotrophic respiration (production) over diffusivity and soil physical properties (transport). Our work begins to address the disconnect between point, footprint, watershed scale estimates of ecosystem respiration and the role of a dynamic hydrologic cycle.

Validation of Satellite Retrieved Land Surface Variables

NASA Technical Reports Server (NTRS)

Lakshmi, Venkataraman; Susskind, Joel

1999-01-01

The effective use of satellite observations of the land surface is limited by the lack of high spatial resolution ground data sets for validation of satellite products. Recent large scale field experiments include FIFE, HAPEX-Sahel and BOREAS which provide us with data sets that have large spatial coverage and long time coverage. It is the objective of this paper to characterize the difference between the satellite estimates and the ground observations. This study and others along similar lines will help us in utilization of satellite retrieved data in large scale modeling studies.

Observations and Modelling of Winds and Waves during the Surface Wave Dynamics Experiment. Report 1. Intensive Observation Period IOP-1, 20-31 October 1990

DTIC Science & Technology

1993-04-01

wave buoy provided by SEATEX, Norway (Figure 3). The modified Mills-cross array was designed to provide spatial estimates of the variation in wave, wind... designed for SWADE to examine the wave physics at different spatial and temporal scales, and the usefulness of a nested system. Each grid is supposed to...field specification. SWADE Model This high-resolution grid was designed to simulate the small scale wave physics and to improve and verify the source

Spatial genetic structure in wild cardoon, the ancestor of cultivated globe artichoke: Limited gene flow, fragmentation and population history.

PubMed

Rau, D; Rodriguez, M; Rapposelli, E; Murgia, M L; Papa, R; Brown, A H D; Attene, G

2016-12-01

Nuclear and chloroplast markers and phenotypic characters were integrated to analyse the population genetic structure of wild cardoon, Cynara cardunculus var. sylvestris, the ancestor of cultivated globe artichoke, Cynara cardunculus var. scolymus on the island of Sardinia, Italy. The spatial scale ranged from a few metres to ∼200km. Wild cardoon appears to be genetically fragmented, with significant genetic divergence at various scales, indicating that gene flow is insufficient to counterbalance the effects of genetic drift or founder effects. Divergence between populations was higher for chloroplast (40%) than for nuclear markers (15%), suggesting that gene flow via seed was lower than via pollen. Two main genetic groups were detected; these correlated with differences in flowering time, capitula size, glossiness, and anthocyanin pigmentation. A complex population structure of wild cardoon emerged over small spatial scales, likely resulting from the interplay between gene dispersal, colonisation history and selective forces. Indeed, Sardinia appears to be a 'hybrid zone' of different gene pools. The island has unique diverse germplasm that has originated from hybridisation among different gene pools. The sampling of seeds from a few plants but from many sites is suggested as the best strategy to harvest the genetic diversity of wild cardoon. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Spatial structure and distribution of small pelagic fish in the northwestern Mediterranean Sea.

PubMed

Saraux, Claire; Fromentin, Jean-Marc; Bigot, Jean-Louis; Bourdeix, Jean-Hervé; Morfin, Marie; Roos, David; Van Beveren, Elisabeth; Bez, Nicolas

2014-01-01

Understanding the ecological and anthropogenic drivers of population dynamics requires detailed studies on habitat selection and spatial distribution. Although small pelagic fish aggregate in large shoals and usually exhibit important spatial structure, their dynamics in time and space remain unpredictable and challenging. In the Gulf of Lions (north-western Mediterranean), sardine and anchovy biomasses have declined over the past 5 years causing an important fishery crisis while sprat abundance rose. Applying geostatistical tools on scientific acoustic surveys conducted in the Gulf of Lions, we investigated anchovy, sardine and sprat spatial distributions and structures over 10 years. Our results show that sardines and sprats were more coastal than anchovies. The spatial structure of the three species was fairly stable over time according to variogram outputs, while year-to-year variations in kriged maps highlighted substantial changes in their location. Support for the McCall's basin hypothesis (covariation of both population density and presence area with biomass) was found only in sprats, the most variable of the three species. An innovative method to investigate species collocation at different scales revealed that globally the three species strongly overlap. Although species often co-occurred in terms of presence/absence, their biomass density differed at local scale, suggesting potential interspecific avoidance or different sensitivity to local environmental characteristics. Persistent favourable areas were finally detected, but their environmental characteristics remain to be determined.

Predicting above-ground density and distribution of small mammal prey species at large spatial scales

PubMed Central

2017-01-01

Grassland and shrub-steppe ecosystems are increasingly threatened by anthropogenic activities. Loss of native habitats may negatively impact important small mammal prey species. Little information, however, is available on the impact of habitat variability on density of small mammal prey species at broad spatial scales. We examined the relationship between small mammal density and remotely-sensed environmental covariates in shrub-steppe and grassland ecosystems in Wyoming, USA. We sampled four sciurid and leporid species groups using line transect methods, and used hierarchical distance-sampling to model density in response to variation in vegetation, climate, topographic, and anthropogenic variables, while accounting for variation in detection probability. We created spatial predictions of each species’ density and distribution. Sciurid and leporid species exhibited mixed responses to vegetation, such that changes to native habitat will likely affect prey species differently. Density of white-tailed prairie dogs (Cynomys leucurus), Wyoming ground squirrels (Urocitellus elegans), and leporids correlated negatively with proportion of shrub or sagebrush cover and positively with herbaceous cover or bare ground, whereas least chipmunks showed a positive correlation with shrub cover and a negative correlation with herbaceous cover. Spatial predictions from our models provide a landscape-scale metric of above-ground prey density, which will facilitate the development of conservation plans for these taxa and their predators at spatial scales relevant to management. PMID:28520757

Archaeal ammonia oxidizers respond to soil factors at smaller spatial scales than the overall archaeal community does in a high Arctic polar oasis.

PubMed

Banerjee, Samiran; Kennedy, Nabla; Richardson, Alan E; Egger, Keith N; Siciliano, Steven D

2016-06-01

Archaea are ubiquitous and highly abundant in Arctic soils. Because of their oligotrophic nature, archaea play an important role in biogeochemical processes in nutrient-limited Arctic soils. With the existing knowledge of high archaeal abundance and functional potential in Arctic soils, this study employed terminal restriction fragment length polymorphism (t-RFLP) profiling and geostatistical analysis to explore spatial dependency and edaphic determinants of the overall archaeal (ARC) and ammonia-oxidizing archaeal (AOA) communities in a high Arctic polar oasis soil. ARC communities were spatially dependent at the 2-5 m scale (P < 0.05), whereas AOA communities were dependent at the ∼1 m scale (P < 0.0001). Soil moisture, pH, and total carbon content were key edaphic factors driving both the ARC and AOA community structure. However, AOA evenness had simultaneous correlations with dissolved organic nitrogen and mineral nitrogen, indicating a possible niche differentiation for AOA in which dry mineral and wet organic soil microsites support different AOA genotypes. Richness, evenness, and diversity indices of both ARC and AOA communities showed high spatial dependency along the landscape and resembled scaling of edaphic factors. The spatial link between archaeal community structure and soil resources found in this study has implications for predictive understanding of archaea-driven processes in polar oases.

Long Term trends in Meridional ISO Activity as seen in CMIP5 Simulations

NASA Astrophysics Data System (ADS)

Srivastava, G.; Chakraborty, A.; Nanjundaiah, R. S.

2016-12-01

Active and break phases of Indian Summer Monsoon (ISM) are manifested as subseasonal increase and decrease of convection. Major part of this intra-seasonal variability comes from low-frequency oscillations. Previous studies showed that northward propagating convective cloud bands are associated with these low-frequency intra-seasonal oscillations. Therefore, a thorough understanding of their spatial extent, location and intensity will be useful to understand and model the ISM. In this study, we have used Continous Wavelet Transform (CWT) technique to estimate the spatial extent (scale), center and intensity of these poleward propagating oscillatory systems. Using observation datasets, we show that scale, centre and intensity of these nothward propagating modes show different characteristics during floods and droughts of ISM. We have analysed different scenarios of CMIP5 and find that the change in mean ISM is related to changes in scale, center and intensity of northward propagations. We further show using AGCM simulations that SST over different regions of the world can modulate ISO over the Indian region.

Progress towards the use of publicly available data networks to conduct cross-scale historical reconstructions of carbon dynamics in US Drylands

NASA Astrophysics Data System (ADS)

Washington-Allen, R. A.; Landolt, K.; Emanuel, R. E.; Therrell, M. D.; Nagle, N.; Grissino-Mayer, H. D.; Poulter, B.

2016-12-01

Emergent scale properties of water-limited or Dryland ecosystem's carbon flux are unknown at spatial scales from local to global and time scales of 10 - 1000 years or greater. The width of a tree ring is a metric of production that has been correlated with the amount of precipitation. This relationship has been used to reconstruct rainfall and fire histories in the Drylands of the southwestern US. The normalized difference vegetation index (NDVI) is globally measured by selected satellite sensors and is highly correlated with the fraction of solar radiation which is absorbed for photosynthesis by plants (FPAR), as well as with vegetation biomass, net primary productivity (NPP), and tree ring width. Publicly available web-based archives of free NDVI and tree ring data exist and have allowed historical temporal reconstructions of carbon dynamics for the past 300 to 500 years. Climate and tree ring databases have been used to spatially reconstruct drought dynamics for the last 500 years in the western US. In 2007, we hypothesized that NDVI and tree ring width could be used to spatially reconstruct carbon dynamics in US Drylands. In 2015, we succeeded with a 300-year historical spatial reconstruction of NPP in California using a Blue Oak tree ring chronology. Online eddy covariance flux tower measures of NPP are well correlated with satellite measures of NPP. This suggests that net ecosystem exchange (NEE = NPP - soil Respiration) could be historically reconstructed across Drylands. Ongoing research includes 1) scaling historical spatial reconstruction to US Drylands, 2) comparing the use of single versus multiple tree ring species (r2 = 68) and 3) use of the eddy flux tower network, remote sensing, and tree ring data to historically spatially reconstruct Dryland NEE.

Similarity and scale in catchment storm response

NASA Technical Reports Server (NTRS)

Wood, Eric F.; Sivapalan, Murugesu; Beven, Keith

1993-01-01

Until recently, very little progress had been made in understanding the relationship between small-scale variability of topography, soil, and rainfalls and the storm response seen at the catchment scale. The work reviewed here represents the first attempt at a systematic theoretical framework for such understanding in the context of surface runoff generation by different processes. The parameterization of hydrological processes over a range of scales is examined, and the concept of the 'representative elementary area' (REA) is introduced. The REA is a fundamental scale for catchment modeling at which continuum assumptions can be applied for the spatially variable controls and parameters, and spatial patterns no longer have to be considered explicitly. The investigation of scale leads into the concept of hydrologic similarity in which the effects of the environmental controls on runoff generation and flood frequency response be investigated independently of catchment scale. The paper reviews the authors' initial results and hopefully will motivate others to also investigate the issues of hydrologic scale and similarity.

Mercury and methylmercury stream concentrations in a Coastal Plain watershed: A multi-scale simulation analysis

USGS Publications Warehouse

Knightes, Christopher D.; Golden, Heather E.; Journey, Celeste A.; Davis, Gary M.; Conrads, Paul; Marvin-DiPasquale, Mark; Brigham, Mark E.; Bradley, Paul M.

2014-01-01

Mercury is a ubiquitous global environmental toxicant responsible for most US fish advisories. Processes governing mercury concentrations in rivers and streams are not well understood, particularly at multiple spatial scales. We investigate how insights gained from reach-scale mercury data and model simulations can be applied at broader watershed scales using a spatially and temporally explicit watershed hydrology and biogeochemical cycling model, VELMA. We simulate fate and transport using reach-scale (0.1 km2) study data and evaluate applications to multiple watershed scales. Reach-scale VELMA parameterization was applied to two nested sub-watersheds (28 km2 and 25 km2) and the encompassing watershed (79 km2). Results demonstrate that simulated flow and total mercury concentrations compare reasonably to observations at different scales, but simulated methylmercury concentrations are out-of-phase with observations. These findings suggest that intricacies of methylmercury biogeochemical cycling and transport are under-represented in VELMA and underscore the complexity of simulating mercury fate and transport.

An operational methodology for riparian land cover fine scale regional mapping for the study of landscape influence on river ecological status

NASA Astrophysics Data System (ADS)

Tormos, T.; Kosuth, P.; Souchon, Y.; Villeneuve, B.; Durrieu, S.; Chandesris, A.

2010-12-01

Preservation and restoration of river ecosystems require an improved understanding of the mechanisms through which they are influenced by landscape at multiple spatial scales and particularly at river corridor scale considering the role of riparian vegetation for regulating and protecting river ecological status and the relevance of this specific area for implementing efficient and realistic strategies. Assessing correctly this influence over large river networks involves accurate broad scale (i.e. at least regional) information on Land Cover within Riparian Areas (LCRA). As the structure of land cover along rivers is generally not accessible using moderate-scale satellite imagery, finer spatial resolution imagery and specific mapping techniques are needed. For this purpose we developed a generic multi-scale Object Based Image Analysis (OBIA) scheme able to produce LCRA maps in different geographic context by exploiting information available from very high spatial resolution imagery (satellite or airborne) and/or metric to decametric spatial thematic data on a given study zone thanks to fuzzy expert knowledge classification rules. A first experimentation was carried out on the Herault river watershed (southern of France), a 2650 square kilometers basin that presents a contrasted landscape (different ecoregions) and a total stream length of 1150 Km, using high and very high multispectral remotely-sensed images (10m Spot5 multispectral images and 0.5m aerial photography) and existing spatial thematic data. Application of the OBIA scheme produced a detailed (22 classes) LCRA map with an overall accuracy of 89% and a Kappa index of 83% according to a land cover pressures typology (six categories). A second experimentation (using the same data sources) was carried out on a larger test zone, a part of the Normandy river network (25 000 square kilometers basin; 6000 km long river network; 155 ecological stations). This second work aimed at elaborating a robust statistical eco-regional model to study links between land cover spatial indicators calculated at local and watershed scales, and river ecological status assessed with macroinvertebrate indicators. Application of the OBIA scheme produced a detailed (62 classes) LCRA map which allowed the model to highlight influence of specific land use patterns: (i) the significant beneficial effect of 20-m riparian tree vegetation strip near a station and 20-m riparian grassland strip along the upstream network of a station and (ii) the negative impact on river ecological status of urban areas and roads on the upstream flood plain of a station. Results of these two experimentations highlight that (i) the application of an OBIA scheme using multi-source spatial data provides an efficient approach for mapping and monitoring LCRA that can be implemented operationally at regional or national scale and (ii) and the interest of using LCRA-maps derived from very high spatial resolution imagery (satellite or airborne) and/or metric spatial thematic data to study landscape influence on river ecological status and support managers in the definition of optimized riparian preservation and restoration strategies.

Spatial and Temporal Scales of Surface Water-Groundwater Interactions

NASA Astrophysics Data System (ADS)

Boano, F.

2016-12-01

The interfaces between surface water and groundwater (i.e., river and lake sediments) represent hotspots for nutrient transformation in watersheds. This intense biochemical activity stems from the peculiar physicochemical properties of these interface areas. Here, the exchange of water and nutrients between surface and subsurface environments creates an ecotone region that can support the presence of different microbial species responsible for nutrient transformation. Previous studies have elucidated that water exchange between rivers and aquifers is organized in a complex system of nested flow cells. Each cell entails a range of residence timescales spanning multiple order of magnitudes, providing opportunities for different biochemical reactions to occur. Physically-bases models represent useful tools to deal with the wide range of spatial and temporal scales that characterize surface-subsurface water exchange. This contribution will present insights about how hydrodynamic processes control scale organization for surface water - groundwater interactions. The specific focus will be the influence of exchange processes on microbial activity and nutrient transformation, discussing how groundwater flow at watershed scale controls flow conditions and hence constrain microbial reactions at much smaller scales.

Variation in soil carbon dioxide efflux at two spatial scales in a topographically complex boreal forest

USGS Publications Warehouse

Kelsey, Katharine C.; Wickland, Kimberly P.; Striegl, Robert G.; Neff, Jason C.

2012-01-01

Carbon dynamics of high-latitude regions are an important and highly uncertain component of global carbon budgets, and efforts to constrain estimates of soil-atmosphere carbon exchange in these regions are contingent on accurate representations of spatial and temporal variability in carbon fluxes. This study explores spatial and temporal variability in soilatmosphere carbon dynamics at both fine and coarse spatial scales in a high-elevation, permafrost-dominated boreal black spruce forest. We evaluate the importance of landscape-level investigations of soil-atmosphere carbon dynamics by characterizing seasonal trends in soil-atmosphere carbon exchange, describing soil temperature-moisture-respiration relations, and quantifying temporal and spatial variability at two spatial scales: the plot scale (0–5 m) and the landscape scale (500–1000 m). Plot-scale spatial variability (average variation on a given measurement day) in soil CO2 efflux ranged from a coefficient of variation (CV) of 0.25 to 0.69, and plot-scale temporal variability (average variation of plots across measurement days) in efflux ranged from a CV of 0.19 to 0.36. Landscape-scale spatial and temporal variability in efflux was represented by a CV of 0.40 and 0.31, respectively, indicating that plot-scale spatial variability in soil respiration is as great as landscape-scale spatial variability at this site. While soil respiration was related to soil temperature at both the plot- and landscape scale, landscape-level descriptions of soil moisture were necessary to define soil respiration-moisture relations. Soil moisture variability was also integral to explaining temporal variability in soil respiration. Our results have important implications for research efforts in high-latitude regions where remote study sites make landscape-scale field campaigns challenging.

Spatial extrapolation of lysimeter results using thermal infrared imaging

NASA Astrophysics Data System (ADS)

Voortman, B. R.; Bosveld, F. C.; Bartholomeus, R. P.; Witte, J. P. M.

2016-12-01

Measuring evaporation (E) with lysimeters is costly and prone to numerous errors. By comparing the energy balance and the remotely sensed surface temperature of lysimeters with those of the undisturbed surroundings, we were able to assess the representativeness of lysimeter measurements and to quantify differences in evaporation caused by spatial variations in soil moisture content. We used an algorithm (the so called 3T model) to spatially extrapolate the measured E of a reference lysimeter based on differences in surface temperature, net radiation and soil heat flux. We tested the performance of the 3T model on measurements with multiple lysimeters (47.5 cm inner diameter) and micro lysimeters (19.2 cm inner diameter) installed in bare sand, moss and natural dry grass. We developed different scaling procedures using in situ measurements and remotely sensed surface temperatures to derive spatially distributed estimates of Rn and G and explored the physical soundness of the 3T model. Scaling of Rn and G considerably improved the performance of the 3T model for the bare sand and moss experiments (Nash-Sutcliffe efficiency (NSE) increasing from 0.45 to 0.89 and from 0.81 to 0.94, respectively). For the grass surface, the scaling procedures resulted in a poorer performance of the 3T model (NSE decreasing from 0.74 to 0.70), which was attributed to effects of shading and the difficulty to correct for differences in emissivity between dead and living biomass. The 3T model is physically unsound if the field scale average air temperature, measured at an arbitrarily chosen reference height, is used as input to the model. The proposed measurement system is relatively cheap, since it uses a zero tension (freely draining) lysimeter which results are extrapolated by the 3T model to the unaffected surroundings. The system is promising for bridging the gap between ground observations and satellite based estimates of E.

Strong Predictability Of Spatially Distributed Physical Habitat Preferences For O. Mykiss Spawning Across Three Spatial Scales

NASA Astrophysics Data System (ADS)

Kammel, L.; Pasternack, G. B.; Wyrick, J. R.; Massa, D.; Bratovich, P.; Johnson, T.

2012-12-01

Currently accepted perception assumes Oncorhynchus mykiss prefer different ranges of similar physical habitat elements for spawning than Chinook salmon (Oncorhynchus tshawytscha), taking into account their difference in size. While there is increasing research interest regarding O. mykiss habitat use and migratory behavior, research conducted to date distinguishing the physical habitat conditions utilized for O. mykiss spawning has not provided quantified understanding of their spawning habitat preferences. The purpose of this study was to use electivity indices and other measures to assess the physical habitat characteristics preferred for O. mykiss spawning in terms of both 1-m scale microhabitat attributes, and landforms at different spatial scales from 0.1-100 times channel width. The testbed for this study was the 37.5-km regulated gravel-cobble Lower Yuba River (LYR). Using spatially distributed 2D hydrodynamic model results, substrate mapping, and a census of O. mykiss redds from two years of observation, micro- and meso-scale representations of physical habitat were tested for their ability to predict spawning habitat preference and avoidance. Overall there was strong stratification of O. mykiss redd occurrence for all representation types of physical habitat. A strong preference of hydraulic conditions was shown for mean water column velocities of 1.18-2.25 ft/s, and water depths of 1.25-2.76 ft. There was a marked preference for the two most upstream alluvial reaches of the LYR (out of 8 total reaches), accounting for 92% of all redds observed. The preferred morphological units (MUs) for O. mykiss spawning were more variable than for Chinook salmon and changed with increasing discharge, demonstrating that O. mykiss shift spawning to different MUs in order to utilize their preferred hydraulic conditions. The substrate range preferred for O. mykiss spawning was within 32-90 mm. Overall, O. mykiss spawning behavior was highly predictable and required a holistic blend of hydraulic and geomorphic representations to explain.

Untangling the contribution of aspect, drainage position and elevation to the spatial variability of fine surface fuels in south east Australian forests

NASA Astrophysics Data System (ADS)

Sheridan, Gary; nyman, petter; Duff, Tom; Baillie, Craig; Bovill, William; Lane, Patrick; Tolhurst, Kevin

2015-04-01

The prediction of fuel moisture content is important for estimating the rate of spread of wildfires, the ignition probability of firebrands, and for the efficient scheduling of prescribed fire. The moisture content of fine surface fuels varies spatially at large scales (10's to 100's km) due to variation in meteorological variables (eg. temperature, relative humidity, precipitation). At smaller scales (100's of metres) in steep topography spatial variability is attributed to topographic influences that include differences in radiation due to aspect and slope, differences in precipitation, temperature and relative humidity due to elevation, and differences in soil moisture due to hillslope drainage position. Variable forest structure and canopy shading adds further to the spatial variability in surface fuel moisture. In this study we aim to combine daily 5km resolution gridded weather data with 20m resolution DEM and vegetation structure data to predict the spatial variability of fine surface fuels in steep topography. Microclimate stations were established in south east Australia to monitor surface fine fuel moisture continuously (every 15 minutes) using newly developed instrumented litter packs, in addition to temperature and relative humidity measurements inside the litter pack, and measurement of precipitation and energy inputs above and below the forest canopy. Microclimate stations were established across a gradient of aspect (5 stations), drainage position (7 stations), elevation (15 stations), and canopy cover conditions (6 stations). The data from this extensive network of microclimate stations across a broad spectrum of topographic conditions is being analysed to enable the downscaling of gridded weather data to spatial scales that are relevant to the connectivity of wildfire fuels and to the scheduling and outcome of prescribed fires. The initial results from the first year of this study are presented here.

Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways

DOE PAGES

Jones, B.; O’Neill, B. C.

2016-07-29

Here we report that the projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatiallymore » explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.« less

Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, B.; O’Neill, B. C.

Here we report that the projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatiallymore » explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.« less

Diverse responses of different structured forest to drought in Southwest China through remotely sensed data

NASA Astrophysics Data System (ADS)

Xu, Peipei; Zhou, Tao; Zhao, Xiang; Luo, Hui; Gao, Shan; Li, Zheng; Cao, Leyao

2018-07-01

Global climate change leads to gradual increases in the frequency, intensity, and duration of extreme drought events. Human activities such as afforestation and deforestation have led to spatial variation in forest structure, causing forests to exhibit an age-spatial structure relationship. Thus, it is of great importance to accurately evaluate the effects of drought stress on forest ecosystems with different forest age structures. Because the spatial heterogeneity varies with drought stress intensity, forest age, there are still a lot of uncertainties in current studies. In this study, based on the field measurement, and the proxy index of stand age (based on forest canopy height from LiDAR and stock volume from inventory) at the regional scale, we analyzed the different drought responses of forest ecosystems with various forest ages across different scales in Yunnan province, southwest China from 2001 to 2014. At the local scale, significant differences in the effects of drought stress were found among forests with various ages, suggesting that older forests suffer more under drought stress than younger forests. At the regional scale, the investigation statistics of forest damage indicated a maximum damage ratio in the forest with tall trees (>32 m), whereas damage was minimal in the forest with short trees (<25 m). The stock volume of the forest exhibited the same pattern, that is, the forest damage ratio increased as the stock volume increased. These data demonstrate that the responses of forest drought could be affected by forest age. Under drought stress, older forests show greater vulnerability and risk of damage, which will require special attention for forest managers, as well as improved risk assessments, in the context of future climate change.

Large-scale runoff generation - parsimonious parameterisation using high-resolution topography

NASA Astrophysics Data System (ADS)

Gong, L.; Halldin, S.; Xu, C.-Y.

2011-08-01

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3" (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

Large-scale runoff generation - parsimonious parameterisation using high-resolution topography

NASA Astrophysics Data System (ADS)

Gong, L.; Halldin, S.; Xu, C.-Y.

2010-09-01

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting a very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TGR only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3'' (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

How Spatial Heterogeneity of Cover Affects Patterns of Shrub Encroachment into Mesic Grasslands

PubMed Central

Montané, Francesc; Casals, Pere; Dale, Mark R. T.

2011-01-01

We used a multi-method approach to analyze the spatial patterns of shrubs and cover types (plant species, litter or bare soil) in grassland-shrubland ecotones. This approach allows us to assess how fine-scale spatial heterogeneity of cover types affects the patterns of Cytisus balansae shrub encroachment into mesic mountain grasslands (Catalan Pyrenees, Spain). Spatial patterns and the spatial associations between juvenile shrubs and different cover types were assessed in mesic grasslands dominated by species with different palatabilities (palatable grass Festuca nigrescens and unpalatable grass Festuca eskia). A new index, called RISES (“Relative Index of Shrub Encroachment Susceptibility”), was proposed to calculate the chances of shrub encroachment into a given grassland, combining the magnitude of the spatial associations and the surface area for each cover type. Overall, juveniles showed positive associations with palatable F. nigrescens and negative associations with unpalatable F. eskia, although these associations shifted with shrub development stage. In F. eskia grasslands, bare soil showed a low scale of pattern and positive associations with juveniles. Although the highest RISES values were found in F. nigrescens plots, the number of juvenile Cytisus was similar in both types of grasslands. However, F. nigrescens grasslands showed the greatest number of juveniles in early development stage (i.e. height<10 cm) whereas F. eskia grasslands showed the greatest number of juveniles in late development stages (i.e. height>30 cm). We concluded that in F. eskia grasslands, where establishment may be constrained by the dominant cover type, the low scale of pattern on bare soil may result in higher chances of shrub establishment and survival. In contrast, although grasslands dominated by the palatable F. nigrescens may be more susceptible to shrub establishment; current grazing rates may reduce juvenile survival. PMID:22174858

Spatial heterogeneity in parasite infections at different spatial scales in an intertidal bivalve.

PubMed

Thieltges, David W; Reise, Karsten

2007-01-01

Spatial heterogeneities in the abundance of free-living organisms as well as in infection levels of their parasites are a common phenomenon, but knowledge on parasitism in invertebrate intermediate hosts in this respect is scarce. We investigated the spatial pattern of four dominant trematode species which utilize a common intertidal bivalve, the cockle Cerastoderma edule, as second intermediate host in their life cycles. Sampling of cockles from the same cohort at 15 sites in the northern Wadden Sea (North Sea) over a distance of 50 km revealed a conspicuous spatial heterogeneity in infection levels in all four species over the total sample as well as among and within sampling sites. Whereas multiple regression analyses indicated the density of first intermediate upstream hosts to be the strongest determinant of infection levels in cockles, the situation within sites was more complex with no single strong predictor variable. However, host size was positively and host density negatively correlated with infection levels and there was an indication of differential susceptibility of cockle hosts. Small-scale differences in physical properties of the habitat in the form of residual water at low tide resulted in increased infection levels of cockles which we experimentally transferred into pools. A complex interplay of these factors may be responsible for within-site heterogeneities. At larger spatial scales, these factors may be overridden by the strong effect of upstream hosts. In contrast to first intermediate trematode hosts, there was no indication for inter-specific interactions. In other terms, the recruitment of trematodes in second intermediate hosts seems to be largely controlled by pre-settlement processes both among and within host populations.

Partial Least Square Discriminant Analysis Based on Normalized Two-Stage Vegetation Indices for Mapping Damage from Rice Diseases Using PlanetScope Datasets.

PubMed

Shi, Yue; Huang, Wenjiang; Ye, Huichun; Ruan, Chao; Xing, Naichen; Geng, Yun; Dong, Yingying; Peng, Dailiang

2018-06-11

In recent decades, rice disease co-epidemics have caused tremendous damage to crop production in both China and Southeast Asia. A variety of remote sensing based approaches have been developed and applied to map diseases distribution using coarse- to moderate-resolution imagery. However, the detection and discrimination of various disease species infecting rice were seldom assessed using high spatial resolution data. The aims of this study were (1) to develop a set of normalized two-stage vegetation indices (VIs) for characterizing the progressive development of different diseases with rice; (2) to explore the performance of combined normalized two-stage VIs in partial least square discriminant analysis (PLS-DA); and (3) to map and evaluate the damage caused by rice diseases at fine spatial scales, for the first time using bi-temporal, high spatial resolution imagery from PlanetScope datasets at a 3 m spatial resolution. Our findings suggest that the primary biophysical parameters caused by different disease (e.g., changes in leaf area, pigment contents, or canopy morphology) can be captured using combined normalized two-stage VIs. PLS-DA was able to classify rice diseases at a sub-field scale, with an overall accuracy of 75.62% and a Kappa value of 0.47. The approach was successfully applied during a typical co-epidemic outbreak of rice dwarf (Rice dwarf virus, RDV), rice blast ( Magnaporthe oryzae ), and glume blight ( Phyllosticta glumarum ) in Guangxi Province, China. Furthermore, our approach highlighted the feasibility of the method in capturing heterogeneous disease patterns at fine spatial scales over the large spatial extents.

A Simple Iterative Model Accurately Captures Complex Trapline Formation by Bumblebees Across Spatial Scales and Flower Arrangements

PubMed Central

Reynolds, Andrew M.; Lihoreau, Mathieu; Chittka, Lars

2013-01-01

Pollinating bees develop foraging circuits (traplines) to visit multiple flowers in a manner that minimizes overall travel distance, a task analogous to the travelling salesman problem. We report on an in-depth exploration of an iterative improvement heuristic model of bumblebee traplining previously found to accurately replicate the establishment of stable routes by bees between flowers distributed over several hectares. The critical test for a model is its predictive power for empirical data for which the model has not been specifically developed, and here the model is shown to be consistent with observations from different research groups made at several spatial scales and using multiple configurations of flowers. We refine the model to account for the spatial search strategy of bees exploring their environment, and test several previously unexplored predictions. We find that the model predicts accurately 1) the increasing propensity of bees to optimize their foraging routes with increasing spatial scale; 2) that bees cannot establish stable optimal traplines for all spatial configurations of rewarding flowers; 3) the observed trade-off between travel distance and prioritization of high-reward sites (with a slight modification of the model); 4) the temporal pattern with which bees acquire approximate solutions to travelling salesman-like problems over several dozen foraging bouts; 5) the instability of visitation schedules in some spatial configurations of flowers; 6) the observation that in some flower arrays, bees' visitation schedules are highly individually different; 7) the searching behaviour that leads to efficient location of flowers and routes between them. Our model constitutes a robust theoretical platform to generate novel hypotheses and refine our understanding about how small-brained insects develop a representation of space and use it to navigate in complex and dynamic environments. PMID:23505353

Mueller matrix microscopy on a Morpho butterfly

NASA Astrophysics Data System (ADS)

Arteaga, Oriol; Kuntman, Ertan; Antó, Joan; Pascual, Esther; Canillas, Adolf; Bertran, Enric

2015-04-01

The brilliant iridescent colouring in male Morpho butterflies is due to the microstrutures and nanostructures present in the wing scales, rather than pigments. In this work Mueller matrix microscopy is used to investigate the polarization properties of butterfly wing scales in reflection and transmission. It is found that the top layer of more transparent scales (cover scales) have very different polarimetric properties from the ground iridescent scales. Images with high spatial resolution showing the retarding and diattenuating optical properties for both types of scales are provided.

Scale-dependent geomorphic responses to active restoration and implications for cutthroat trout

NASA Astrophysics Data System (ADS)

Salant, N.; Miller, S. W.

2009-12-01

The predominant goal of instream habitat restoration is to increase the diversity, density and/or biomass of aquatic organisms through enhanced physical heterogeneity and increased food availability. In physically homogenized systems, habitat restoration is most commonly achieved at the reach-scale through the addition of structures or channel reconfiguration. Despite the completion of over 6,000 restoration projects in the United States, studies of fish responses to habitat restoration have largely produced equivocal results. Paradoxically, restoration monitoring overwhelmingly focuses on fish response without understanding how these responses link to the physical variables being altered and the scale at which geomorphic changes occur. Our study investigates whether instream habitat restoration affects geomorphic conditions at spatial scales relevant to the organism of interest (i.e. the spatial scale of the variables limiting to that organism). We measure the effects of active restoration on geomorphic metrics at three spatial scales (local, unit, and reach) using a before-after-control-impact design in a historically disturbed and heavily managed cutthroat trout stream. Observed trout habitat preferences (for spawning and juvenile/adult residence) are used to identify the limiting physical variables and are compared to the scale of spatially explicit geomorphic responses. Four reaches representing three different stages of restoration (before, one month and one year after) are surveyed for local-scale physical conditions, unit- and reach-scale morphology, resident fish use, and redd locations. Local-scale physical metrics include depth, nearbed and average velocity, overhead cover, particle size, and water quality metrics. Point measurements stratified by morphological unit are used to determine physical variability among unit types. Habitat complexity and availability are assessed at the reach-scale from topographic surveys and unit maps. Our multi-scale, process-based approach evaluates whether a commonly used restoration strategy creates geomorphic heterogeneity at scales relevant to fish diversity and microhabitat utilization, an understanding that will improve the efficiency and success of future restoration projects.

Scale effects on the evapotranspiration estimation over a water-controlled Mediterranean ecosystem and its influence on hydrological modelling

NASA Astrophysics Data System (ADS)

Carpintero, Elisabet; González-Dugo, María P.; José Polo, María; Hain, Christopher; Nieto, Héctor; Gao, Feng; Andreu, Ana; Kustas, William; Anderson, Martha

2017-04-01

The integration of currently available satellite data into surface energy balance models can provide estimates of evapotranspiration (ET) with spatial and temporal resolutions determined by sensor characteristics. The use of data fusion techniques may increase the temporal resolution of these estimates using multiple satellites, providing a more frequent ET monitoring for hydrological purposes. The objective of this work is to analyze the effects of pixel resolution on the estimation of evapotranspiration using different remote sensing platforms, and to provide continuous monitoring of ET over a water-controlled ecosystem, the Holm oak savanna woodland known as dehesa. It is an agroforestry system with a complex canopy structure characterized by widely-spaced oak trees combined with crops, pasture and shrubs. The study was carried out during two years, 2013 and 2014, combining ET estimates at different spatial and temporal resolutions and applying data fusion techniques for a frequent monitoring of water use at fine spatial resolution. A global and daily ET product at 5 km resolution, developed with the ALEXI model using MODIS day-night temperature difference (Anderson et al., 2015a) was used as a starting point. The associated flux disaggregation scheme, DisALEXI (Norman et al., 2003), was later applied to constrain higher resolution ET from both MODIS and Landsat 7/8 images. The Climate Forecast System Reanalysis (CFSR) provided the meteorological data. Finally, a data fusion technique, the STARFM model (Gao et al., 2006), was applied to fuse MODIS and Landsat ET maps in order to obtain daily ET at 30 m resolution. These estimates were validated and analyzed at two different scales: at local scale over a dehesa experimental site and at watershed scale with a predominant Mediterranean oak savanna landscape, both located in Southern Spain. Local ET estimates from the modeling system were validated with measurements provided by an eddy covariance tower installed in the dehesa (38 ° 12 'N, 4 ° 17' W, 736 m a.s.l.). The results supported the ability of ALEXI/DisALEXI model to accurately estimate turbulent and radiative fluxes over this complex landscape, both at 1 Km and at 30 m spatial resolution. The application of the STARFM model gave significant improvement in capturing the spatio-temporal heterogeneity of ET over the different seasons, compared with traditional interpolation methods using MODIS and Landsat ET data. At basin scale, the physically-based distributed hydrological model WiMMed has been applied to evaluate ET estimates. This model focuses on the spatial interpolation of the meteorological variables and the physical modelling of the daily water balance at the cell and watershed scale, using daily streamflow rates measured at the watershed outlet for final comparison.

Getting the Big Picture: Development of Spatial Scaling Abilities

ERIC Educational Resources Information Center

Frick, Andrea; Newcombe, Nora S.

2012-01-01

Spatial scaling is an integral aspect of many spatial tasks that involve symbol-to-referent correspondences (e.g., map reading, drawing). In this study, we asked 3-6-year-olds and adults to locate objects in a two-dimensional spatial layout using information from a second spatial representation (map). We examined how scaling factor and reference…

Rice evapotranspiration at the field and canopy scales under water-saving irrigation

NASA Astrophysics Data System (ADS)

Liu, Xiaoyin; Xu, Junzeng; Yang, Shihong; Zhang, Jiangang

2018-04-01

Evapotranspiration (ET) is an important process of land surface water and thermal cycling, with large temporal and spatial variability. To reveal the effect of water-saving irrigation (WSI) on rice ET at different spatial scales and understand the cross spatial scale difference, rice ET under WSI condition at canopy (ETCML) and field scale (ETEC) were measured simultaneously by mini-lysimeter and eddy covariance (EC) in the rice season of 2014. To overcome the shortage of energy balance deficit by EC system, and evaluate the influence of energy balance closure degree on ETEC, ETEC was corrected as {ET}_{EC}^{*} by energy balance closure correction according to the evaporative fraction. Seasonal average daily ETEC, {ET}_{EC}^{*} and ETCML of rice under WSI practice were estimated as 3.12, 4.03 and 4.35 mm day-1, smaller than the values reported in flooded paddy fields. Daily ETEC, {ET}_{EC}^{*} and ETCML varied in a similar trends and reached the maximum in late tillering, then decreased along with the crop growth in late season. The value of ETEC was much lower than ETCML, and was frequently 1-2 h lagged behind ETCML. It indicated that the energy balance deficit resulted in underestimation of crop ET by EC system. The corrected value of {ET}_{EC}^{*} matched ETCML much better than ETEC, with a smaller RMSE (0.086 mm h-1) and higher R 2 (0.843) and IOA (0.961). The time lapse between {ET}_{EC}^{*} and ETCML was mostly shortened to less than 0.5 h. The multiple stepwise regression analysis indicated that net radiation ( R n) is the dominant factor for rice ET, and soil moisture ( θ) is another significant factor ( p < 0.01) in WSI rice fields. The difference between ETCML and {ET}_{EC}^{*} ({ET}_{CML} - {ET}_{EC}^{*}) were significantly ( p < 0.05) correlated with R n, air temperature ( T a), and air vapor pressure deficit ( D), and its partial correlation coefficients to R n and T a were slightly greater than D. Thus, R n, T a and D are important variables for understanding the spatial scale effect of rice ET in WSI fields, and for its cross scale conversion.

Four-dimensional soil moisture response during an extreme rainfall event at the Landscape Evolution Observatory

NASA Astrophysics Data System (ADS)

Troch, Peter A.; Niu, Guo-Yue; Gevaert, Anouk; Teuling, Adriaan; Uijlenhoet, Remko; Pasetto, Damiano; Paniconi, Claudio; Putti, Mario

2014-05-01

The Landscape Evolution Observatory (LEO) at Biosphere 2-The University of Arizona consists of three identical, sloping, 333 m2 convergent landscapes inside a 5,000 m2 environmentally controlled facility. These engineered landscapes contain 1-meter depth of basaltic tephra, ground to homogenous loamy sand. Each landscape contains a spatially dense sensor and sampler network capable of resolving meter-scale lateral heterogeneity and sub-meter scale vertical heterogeneity in moisture, energy and carbon states and fluxes. The density of sensors and frequency at which they can be polled allows for data collection at spatial and temporal scales that are impossible in natural field settings. Each ~600 metric ton landscape has load cells embedded into the structure to measure changes in total system mass with 0.05% full-scale repeatability (equivalent to less than 1 cm of precipitation). This facilitates the real time accounting of hydrological partitioning at the hillslope scale. Each hillslope is equipped with an engineered rain system capable of raining at rates between 3 and 45 mm/hr in a range of spatial patterns. We observed the spatial and temporal evolution of the soil moisture content at 496 5-TM Decagon sensors distributed over 5 different depths during a low-intensity long-duration rainfall experiment in February 2013. This presentation will focus on our modeling efforts to reveal subsurface hydraulic heterogeneity required to explain observed rainfall-runoff dynamics at the hillslope scale.

Multiscale Spatial Assessment of Determinant Factors of Land Use Change: Study at Urban Area of Yogyakarta

NASA Astrophysics Data System (ADS)

Susilo, Bowo

2017-12-01

Studies of land use change have been undertaken by different researchers using various methods. Among those methods, modelling is widely utilized. Modelling land use change required several components remarked as model variables. Those represent any conditions or factors which considered relevant or have some degree of correlation to the changes of land use. Variables which have significant correlation to land use change are referred as determinant factors or driving forces. Those factors as well as changes of land use are distributed across space and therefore referred as spatial determinant factors. The main objective of the research was to examine land use change and its determinant factors. Area and location of land use change were analysed based on three different years of land use maps, which are 1993, 2000 and 2007. Spatial and temporal analysis were performed which emphasize to the influence of scale to both of analysis’s. Urban area of Yogyakarta was selected as study area. Study area covered three different districts (kabupaten), involving 20 sub districts and totally consists of 74 villages. Result of this study shows that during 14 years periods (1993 to 2007), there were about 1,460 hectares of land use change had been taken place. Dominant type of land use change is agricultural to residential. The uses of different spatial and temporal scale in analysis were able to reveal different factors related to land use change. In general, factors influencing the quantities of land use change in the study area were population growth and the availability of land. The use of data with different spatial resolution can reveal the presence of various factors associated with the location of the change. Locations of land use change were influenced or determined by accessibility factors.

Negligible influence of spatial autocorrelation in the assessment of fire effects in a mixed conifer forest

USGS Publications Warehouse

van Mantgem, P.J.; Schwilk, D.W.

2009-01-01

Fire is an important feature of many forest ecosystems, although the quantification of its effects is compromised by the large scale at which fire occurs and its inherent unpredictability. A recurring problem is the use of subsamples collected within individual burns, potentially resulting in spatially autocorrelated data. Using subsamples from six different fires (and three unburned control areas) we show little evidence for strong spatial autocorrelation either before or after burning for eight measures of forest conditions (both fuels and vegetation). Additionally, including a term for spatially autocorrelated errors provided little improvement for simple linear models contrasting the effects of early versus late season burning. While the effects of spatial autocorrelation should always be examined, it may not always greatly influence assessments of fire effects. If high patch scale variability is common in Sierra Nevada mixed conifer forests, even following more than a century of fire exclusion, treatments designed to encourage further heterogeneity in forest conditions prior to the reintroduction of fire will likely be unnecessary.

Soil maps as data input for soil erosion models: errors related to map scales

NASA Astrophysics Data System (ADS)

van Dijk, Paul; Sauter, Joëlle; Hofstetter, Elodie

2010-05-01

Soil erosion rates depend in many ways on soil and soil surface characteristics which vary in space and in time. To account for spatial variations of soil features, most distributed soil erosion models require data input derived from soil maps. Ideally, the level of spatial detail contained in the applied soil map should correspond to the objective of the modelling study. However, often the model user has only one soil map available which is then applied without questioning its suitability. The present study seeks to determine in how far soil map scale can be a source of error in erosion model output. The study was conducted on two different spatial scales, with for each of them a convenient soil erosion model: a) the catchment scale using the physically-based Limbourg Soil Erosion Model (LISEM), and b) the regional scale using the decision-tree expert model MESALES. The suitability of the applied soil map was evaluated with respect to an imaginary though realistic study objective for both models: the definition of erosion control measures at strategic locations at the catchment scale; the identification of target areas for the definition of control measures strategies at the regional scale. Two catchments were selected to test the sensitivity of LISEM to the spatial detail contained in soil maps: one catchment with relatively little contrast in soil texture, dominated by loess-derived soil (south of the Alsace), and one catchment with strongly contrasted soils at the limit between the Alsatian piedmont and the loess-covered hills of the Kochersberg. LISEM was run for both catchments using different soil maps ranging in scale from 1/25 000 to 1/100 000 to derive soil related input parameters. The comparison of the output differences was used to quantify the map scale impact on the quality of the model output. The sensitivity of MESALES was tested on the Haut-Rhin county for which two soil maps are available for comparison: 1/50 000 and 1/100 000. The order of resulting target areas (communes) was compared to evaluate the error induced by using the coarser soil data at 1/100 000. Results shows that both models are sensitive to the soil map scale used for model data input. A low sensitivity was found for the catchment with relatively homogeneous soil textures and the use of 1/100 000 soil maps seems allowed. The results for the catchment with strong soil texture variations showed significant differences depending on soil map scale on 75% of the catchment area. Here, the use of 1/100 000 soil map will indeed lead to wrong erosion diagnostics and will hamper the definition of a sound erosion control strategy. The regional scale model MESALES proved to be very sensitive to soil information. The two soil related model parameters (crusting sensitivity, and soil erodibility) reacted very often in the same direction therewith amplifying the change in the final erosion hazard class. The 1/100 000 soil map yielded different results on 40% of the sloping area compared to the 1/50 000 map. Significant differences in the order of target areas were found as well. The present study shows that the degree of sensitivity of the model output to soil map scale is rather variable and depends partly on the spatial variability of soil texture within the study area. Soil (textural) diversity needs to be accounted for to assure a fruitful use of soil erosion models. In some situations this might imply that additional soil data need to be collected in the field to refine the available soil map.

Multi-Scale Modeling in Morphogenesis: A Critical Analysis of the Cellular Potts Model

PubMed Central

Voss-Böhme, Anja

2012-01-01

Cellular Potts models (CPMs) are used as a modeling framework to elucidate mechanisms of biological development. They allow a spatial resolution below the cellular scale and are applied particularly when problems are studied where multiple spatial and temporal scales are involved. Despite the increasing usage of CPMs in theoretical biology, this model class has received little attention from mathematical theory. To narrow this gap, the CPMs are subjected to a theoretical study here. It is asked to which extent the updating rules establish an appropriate dynamical model of intercellular interactions and what the principal behavior at different time scales characterizes. It is shown that the longtime behavior of a CPM is degenerate in the sense that the cells consecutively die out, independent of the specific interdependence structure that characterizes the model. While CPMs are naturally defined on finite, spatially bounded lattices, possible extensions to spatially unbounded systems are explored to assess to which extent spatio-temporal limit procedures can be applied to describe the emergent behavior at the tissue scale. To elucidate the mechanistic structure of CPMs, the model class is integrated into a general multiscale framework. It is shown that the central role of the surface fluctuations, which subsume several cellular and intercellular factors, entails substantial limitations for a CPM's exploitation both as a mechanistic and as a phenomenological model. PMID:22984409

L-band Soil Moisture Mapping using Small UnManned Aerial Systems

NASA Astrophysics Data System (ADS)

Dai, E.

2015-12-01

Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, and impacts water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 promises to provide global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions as low as 5 km for some products. However, there exists a need for measurements of soil moisture on smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters (i.e., the height of the platform) .Compared with various other proposed methods of validation based on either situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed (~km scale) coverage at very high spatial resolution (~15 m) suitable for scaling scale studies, and at comparatively low operator cost. The LDCR on Tempest unit can supply the soil moisture mapping with different resolution which is of order the Tempest altitude.

Spatial Variability of Sources and Mixing State of Atmospheric Particles in a Metropolitan Area.

PubMed

Ye, Qing; Gu, Peishi; Li, Hugh Z; Robinson, Ellis S; Lipsky, Eric; Kaltsonoudis, Christos; Lee, Alex K Y; Apte, Joshua S; Robinson, Allen L; Sullivan, Ryan C; Presto, Albert A; Donahue, Neil M

2018-05-30

Characterizing intracity variations of atmospheric particulate matter has mostly relied on fixed-site monitoring and quantifying variability in terms of different bulk aerosol species. In this study, we performed ground-based mobile measurements using a single-particle mass spectrometer to study spatial patterns of source-specific particles and the evolution of particle mixing state in 21 areas in the metropolitan area of Pittsburgh, PA. We selected sampling areas based on traffic density and restaurant density with each area ranging from 0.2 to 2 km 2 . Organics dominate particle composition in all of the areas we sampled while the sources of organics differ. The contribution of particles from traffic and restaurant cooking varies greatly on the neighborhood scale. We also investigate how primary and aged components in particles mix across the urban scale. Lastly we quantify and map the particle mixing state for all areas we sampled and discuss the overall pattern of mixing state evolution and its implications. We find that in the upwind and downwind of the urban areas, particles are more internally mixed while in the city center, particle mixing state shows large spatial heterogeneity that is mostly driven by emissions. This study is to our knowledge, the first study to perform fine spatial scale mapping of particle mixing state using ground-based mobile measurement and single-particle mass spectrometry.

Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling.

PubMed

Stoy, Paul C; Quaife, Tristan

2015-01-01

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.

Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling

PubMed Central

Stoy, Paul C.; Quaife, Tristan

2015-01-01

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes. PMID:26067835

Signatures of Penumbral Magnetic Fields at Very High Spatial Resolution

NASA Astrophysics Data System (ADS)

Langhans, K.

2006-12-01

Full Stokes spectro-polarimetry, together with refined techniques to interpret the measurements and continual modeling efforts, have improved our understanding of sunspot penumbrae in the last years. In spite of this progress, an improvement in the spatial resolution of the observations is clearly needed to establish in a more direct way the fine structure of the penumbra. The discovery of dark penumbral cores by tet{l3 Sc02} suggests that we are starting to resolve the fundamental scales of the penumbra. Spectro-polarimetric measurements that are sensitive to the magnetic field in both the photosphere and higher layers, and obtained at a spatial resolution approaching 0.1 arcsec, may therefore allow us to draw firm conclusions about the fine scale organization of penumbral magnetic fields. In this paper I will discuss recent polarization measurements at very high spatial resolution, trying to reconcile the different scenarios put forward to explain the structure of the penumbra.

Community assembly of the ferns of Florida.

PubMed

Sessa, Emily B; Chambers, Sally M; Li, Daijiang; Trotta, Lauren; Endara, Lorena; Burleigh, J Gordon; Baiser, Benjamin

2018-03-01

Many ecological and evolutionary processes shape the assembly of organisms into local communities from a regional pool of species. We analyzed phylogenetic and functional diversity to understand community assembly of the ferns of Florida at two spatial scales. We built a phylogeny for 125 of the 141 species of ferns in Florida using five chloroplast markers. We calculated mean pairwise dissimilarity (MPD) and mean nearest taxon distance (MNTD) from phylogenetic distances and functional trait data for both spatial scales and compared the results to null models to assess significance. Our results for over vs. underdispersion in functional and phylogenetic diversity differed depending on spatial scale and metric considered. At the county scale, MPD revealed evidence for phylogenetic overdispersion, while MNTD revealed phylogenetic and functional underdispersion, and at the conservation area scale, MPD revealed phylogenetic and functional underdispersion while MNTD revealed evidence only of functional underdispersion. Our results are consistent with environmental filtering playing a larger role at the smaller, conservation area scale. The smaller spatial units are likely composed of fewer local habitat types that are selecting for closely related species, with the larger-scale units more likely to be composed of multiple habitat types that bring together a larger pool of species from across the phylogeny. Several aspects of fern biology, including their unique physiology and water relations and the importance of the independent gametophyte stage of the life cycle, make ferns highly sensitive to local, microhabitat conditions. © 2018 The Authors. American Journal of Botany is published by Wiley Periodicals, Inc. on behalf of the Botanical Society of America.

Linking Time and Space Scales in Distributed Hydrological Modelling - a case study for the VIC model

NASA Astrophysics Data System (ADS)

Melsen, Lieke; Teuling, Adriaan; Torfs, Paul; Zappa, Massimiliano; Mizukami, Naoki; Clark, Martyn; Uijlenhoet, Remko

2015-04-01

One of the famous paradoxes of the Greek philosopher Zeno of Elea (~450 BC) is the one with the arrow: If one shoots an arrow, and cuts its motion into such small time steps that at every step the arrow is standing still, the arrow is motionless, because a concatenation of non-moving parts does not create motion. Nowadays, this reasoning can be refuted easily, because we know that motion is a change in space over time, which thus by definition depends on both time and space. If one disregards time by cutting it into infinite small steps, motion is also excluded. This example shows that time and space are linked and therefore hard to evaluate separately. As hydrologists we want to understand and predict the motion of water, which means we have to look both in space and in time. In hydrological models we can account for space by using spatially explicit models. With increasing computational power and increased data availability from e.g. satellites, it has become easier to apply models at a higher spatial resolution. Increasing the resolution of hydrological models is also labelled as one of the 'Grand Challenges' in hydrology by Wood et al. (2011) and Bierkens et al. (2014), who call for global modelling at hyperresolution (~1 km and smaller). A literature survey on 242 peer-viewed articles in which the Variable Infiltration Capacity (VIC) model was used, showed that the spatial resolution at which the model is applied has decreased over the past 17 years: From 0.5 to 2 degrees when the model was just developed, to 1/8 and even 1/32 degree nowadays. On the other hand the literature survey showed that the time step at which the model is calibrated and/or validated remained the same over the last 17 years; mainly daily or monthly. Klemeš (1983) stresses the fact that space and time scales are connected, and therefore downscaling the spatial scale would also imply downscaling of the temporal scale. Is it worth the effort of downscaling your model from 1 degree to 1/24 degree, if in the end you only look at monthly runoff? In this study an attempt is made to link time and space scales in the VIC model, to study the added value of a higher spatial resolution-model for different time steps. In order to do this, four different VIC models were constructed for the Thur basin in North-Eastern Switzerland (1700 km²), a tributary of the Rhine: one lumped model, and three spatially distributed models with a resolution of respectively 1x1 km, 5x5 km, and 10x10 km. All models are run at an hourly time step and aggregated and calibrated for different time steps (hourly, daily, monthly, yearly) using a novel Hierarchical Latin Hypercube Sampling Technique (Vořechovský, 2014). For each time and space scale, several diagnostics like Nash-Sutcliffe efficiency, Kling-Gupta efficiency, all the quantiles of the discharge etc., are calculated in order to compare model performance over different time and space scales for extreme events like floods and droughts. Next to that, the effect of time and space scale on the parameter distribution can be studied. In the end we hope to find a link for optimal time and space scale combinations.

Spatial Scaling of Environmental Variables Improves Species-Habitat Models of Fishes in a Small, Sand-Bed Lowland River

PubMed Central

Radinger, Johannes; Wolter, Christian; Kail, Jochem

2015-01-01

Habitat suitability and the distinct mobility of species depict fundamental keys for explaining and understanding the distribution of river fishes. In recent years, comprehensive data on river hydromorphology has been mapped at spatial scales down to 100 m, potentially serving high resolution species-habitat models, e.g., for fish. However, the relative importance of specific hydromorphological and in-stream habitat variables and their spatial scales of influence is poorly understood. Applying boosted regression trees, we developed species-habitat models for 13 fish species in a sand-bed lowland river based on river morphological and in-stream habitat data. First, we calculated mean values for the predictor variables in five distance classes (from the sampling site up to 4000 m up- and downstream) to identify the spatial scale that best predicts the presence of fish species. Second, we compared the suitability of measured variables and assessment scores related to natural reference conditions. Third, we identified variables which best explained the presence of fish species. The mean model quality (AUC = 0.78, area under the receiver operating characteristic curve) significantly increased when information on the habitat conditions up- and downstream of a sampling site (maximum AUC at 2500 m distance class, +0.049) and topological variables (e.g., stream order) were included (AUC = +0.014). Both measured and assessed variables were similarly well suited to predict species’ presence. Stream order variables and measured cross section features (e.g., width, depth, velocity) were best-suited predictors. In addition, measured channel-bed characteristics (e.g., substrate types) and assessed longitudinal channel features (e.g., naturalness of river planform) were also good predictors. These findings demonstrate (i) the applicability of high resolution river morphological and instream-habitat data (measured and assessed variables) to predict fish presence, (ii) the importance of considering habitat at spatial scales larger than the sampling site, and (iii) that the importance of (river morphological) habitat characteristics differs depending on the spatial scale. PMID:26569119