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.
Income inequality and income segregation.
Reardon, Sean F; Bischoff, Kendra
2011-01-01
This article investigates how the growth in income inequality from 1970 to 2000 affected patterns of income segregation along three dimensions: the spatial segregation of poverty and affluence, race-specific patterns of income segregation, and the geographic scale of income segregation. The evidence reveals a robust relationship between income inequality and income segregation, an effect that is larger for black families than for white families. In addition, income inequality affects income segregation primarily through its effect on the large-scale spatial segregation of affluence rather than by affecting the spatial segregation of poverty or by altering small-scale patterns of income segregation.
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.
Perception of scale in forest management planning: Challenges and implications
Swee May Tang; Eric J. Gustafson
1997-01-01
Forest management practices imposed at one spatial scale may affect the patterns and processes of ecosystems at other scales. These impacts and feedbacks on the functioning of ecosystems across spatial scales are not well understood. We examined the effects of silvicultural manipulations simulated at two spatial scales of management planning on landscape pattern and...
Nolen, Matthew S.; Magoulick, Daniel D.; DiStefano, Robert J.; Imhoff, Emily M.; Wagner, Brian K.
2014-01-01
We found that a range of environmental variables were important in predicting crayfish distribution and abundance at multiple spatial scales and their importance was species-, response variable- and scale dependent. We would encourage others to examine the influence of spatial scale on species distribution and abundance patterns.
Going the distance: spatial scale of athletic experience affects the accuracy of path integration.
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.
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.
Community shifts under climate change: mechanisms at multiple scales.
Gornish, Elise S; Tylianakis, Jason M
2013-07-01
Processes that drive ecological dynamics differ across spatial scales. Therefore, the pathways through which plant communities and plant-insect relationships respond to changing environmental conditions are also expected to be scale-dependent. Furthermore, the processes that affect individual species or interactions at single sites may differ from those affecting communities across multiple sites. We reviewed and synthesized peer-reviewed literature to identify patterns in biotic or abiotic pathways underpinning changes in the composition and diversity of plant communities under three components of climate change (increasing temperature, CO2, and changes in precipitation) and how these differ across spatial scales. We also explored how these changes to plants affect plant-insect interactions. The relative frequency of biotic vs. abiotic pathways of climate effects at larger spatial scales often differ from those at smaller scales. Local-scale studies show variable responses to climate drivers, often driven by biotic factors. However, larger scale studies identify changes to species composition and/or reduced diversity as a result of abiotic factors. Differing pathways of climate effects can result from different responses of multiple species, habitat effects, and differing effects of invasions at local vs. regional to global scales. Plant community changes can affect higher trophic levels as a result of spatial or phenological mismatch, foliar quality changes, and plant abundance changes, though studies on plant-insect interactions at larger scales are rare. Climate-induced changes to plant communities will have considerable effects on community-scale trophic exchanges, which may differ from the responses of individual species or pairwise interactions.
NASA Astrophysics Data System (ADS)
Peng, Yu; Wang, Qinghui; Fan, Min
2017-11-01
When assessing re-vegetation project performance and optimizing land management, identification of the key ecological factors inducing vegetation degradation has crucial implications. Rainfall, temperature, elevation, slope, aspect, land use type, and human disturbance are ecological factors affecting the status of vegetation index. However, at different spatial scales, the key factors may vary. Using Helin County, Inner-Mongolia, China as the study site and combining remote sensing image interpretation, field surveying, and mathematical methods, this study assesses key ecological factors affecting vegetation degradation under different spatial scales in a semi-arid agro-pastoral ecotone. It indicates that the key factors are different at various spatial scales. Elevation, rainfall, and temperature are identified as crucial for all spatial extents. Elevation, rainfall and human disturbance are key factors for small-scale quadrats of 300 m × 300 m and 600 m × 600 m, temperature and land use type are key factors for a medium-scale quadrat of 1 km × 1 km, and rainfall, temperature, and land use are key factors for large-scale quadrats of 2 km × 2 km and 5 km × 5 km. For this region, human disturbance is not the key factor for vegetation degradation across spatial scales. It is necessary to consider spatial scale for the identification of key factors determining vegetation characteristics. The eco-restoration programs at various spatial scales should identify key influencing factors according their scales so as to take effective measurements. The new understanding obtained in this study may help to explore the forces which driving vegetation degradation in the degraded regions in the world.
Charles H. (Hobie) Perry; Kevin J. Horn; R. Quinn Thomas; Linda H. Pardo; Erica A.H. Smithwick; Doug Baldwin; Gregory B. Lawrence; Scott W. Bailey; Sabine Braun; Christopher M. Clark; Mark Fenn; Annika Nordin; Jennifer N. Phelan; Paul G. Schaberg; Sam St. Clair; Richard Warby; Shaun Watmough; Steven S. Perakis
2015-01-01
The abundance of temporally and spatially consistent Forest Inventory and Analysis data facilitates hierarchical/multilevel analysis to investigate factors affecting tree growth, scaling from plot-level to continental scales. Herein we use FIA tree and soil inventories in conjunction with various spatial climate and soils data to estimate species-specific responses of...
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.
Sampling scales define occupancy and underlying occupancy-abundance relationships in animals.
Steenweg, Robin; Hebblewhite, Mark; Whittington, Jesse; Lukacs, Paul; McKelvey, Kevin
2018-01-01
Occupancy-abundance (OA) relationships are a foundational ecological phenomenon and field of study, and occupancy models are increasingly used to track population trends and understand ecological interactions. However, these two fields of ecological inquiry remain largely isolated, despite growing appreciation of the importance of integration. For example, using occupancy models to infer trends in abundance is predicated on positive OA relationships. Many occupancy studies collect data that violate geographical closure assumptions due to the choice of sampling scales and application to mobile organisms, which may change how occupancy and abundance are related. Little research, however, has explored how different occupancy sampling designs affect OA relationships. We develop a conceptual framework for understanding how sampling scales affect the definition of occupancy for mobile organisms, which drives OA relationships. We explore how spatial and temporal sampling scales, and the choice of sampling unit (areal vs. point sampling), affect OA relationships. We develop predictions using simulations, and test them using empirical occupancy data from remote cameras on 11 medium-large mammals. Surprisingly, our simulations demonstrate that when using point sampling, OA relationships are unaffected by spatial sampling grain (i.e., cell size). In contrast, when using areal sampling (e.g., species atlas data), OA relationships are affected by spatial grain. Furthermore, OA relationships are also affected by temporal sampling scales, where the curvature of the OA relationship increases with temporal sampling duration. Our empirical results support these predictions, showing that at any given abundance, the spatial grain of point sampling does not affect occupancy estimates, but longer surveys do increase occupancy estimates. For rare species (low occupancy), estimates of occupancy will quickly increase with longer surveys, even while abundance remains constant. Our results also clearly demonstrate that occupancy for mobile species without geographical closure is not true occupancy. The independence of occupancy estimates from spatial sampling grain depends on the sampling unit. Point-sampling surveys can, however, provide unbiased estimates of occupancy for multiple species simultaneously, irrespective of home-range size. The use of occupancy for trend monitoring needs to explicitly articulate how the chosen sampling scales define occupancy and affect the occupancy-abundance relationship. © 2017 by the Ecological Society of America.
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...
Burstiness in Viral Bursts: How Stochasticity Affects Spatial Patterns in Virus-Microbe Dynamics
NASA Astrophysics Data System (ADS)
Lin, Yu-Hui; Taylor, Bradford P.; Weitz, Joshua S.
Spatial patterns emerge in living systems at the scale of microbes to metazoans. These patterns can be driven, in part, by the stochasticity inherent to the birth and death of individuals. For microbe-virus systems, infection and lysis of hosts by viruses results in both mortality of hosts and production of viral progeny. Here, we study how variation in the number of viral progeny per lysis event affects the spatial clustering of both viruses and microbes. Each viral ''burst'' is initially localized at a near-cellular scale. The number of progeny in a single lysis event can vary in magnitude between tens and thousands. These perturbations are not accounted for in mean-field models. Here we developed individual-based models to investigate how stochasticity affects spatial patterns in virus-microbe systems. We measured the spatial clustering of individuals using pair correlation functions. We found that increasing the burst size of viruses while maintaining the same production rate led to enhanced clustering. In this poster we also report on preliminary analysis on the evolution of the burstiness of viral bursts given a spatially distributed host community.
The scale of landscape fragmentation affects herbivore response to vegetation heterogeneity.
Banks, John E
1998-11-01
Using alternating bands of weeds and broccoli I experimentally manipulated vegetation composition and the spatial scale at which the landscape was fragmented in a factorial design. This experimental approach allowed me to distinguish the effect of spatial scale from that of simple crop heterogeneity on crop herbivores. The importance of scale depended on which insect species were examined. Cabbage aphids (Brevicoryne brassicae) were influenced by vegetation composition at all tested scales of fragmentation; cabbage butterflies (Pieris rapae) were not affected by scale or by composition and flea beetles (Phyllotreta cruciferae) revealed a striking dependence on scale of fragmentation as well as an interaction between scale and composition. This approach shows the importance of dissecting out the effects of scale from other aspects of landscape manipulation, and emphasizes the challenge of developing a theory that will enable prediction of species-specific responses to scale.
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 ...
Record, Sydne; Strecker, Angela; Tuanmu, Mao-Ning; Beaudrot, Lydia; Zarnetske, Phoebe; Belmaker, Jonathan; Gerstner, Beth
2018-01-01
There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species' responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. We systematically reviewed SDM studies published from 2003-2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis.
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.
Non-native salmonids affect amphibian occupancy at multiple spatial scales
David S. Pilliod; Blake R. Hossack; Peter F. Bahls; Evelyn L. Bull; Paul Stephen Corn; Grant Hokit; Bryce A. Maxell; James C. Munger; Aimee Wyrick
2010-01-01
The introduction of non-native species into aquatic environments has been linked with local extinctions and altered distributions of native species. We investigated the effect of non-native salmonids on the occupancy of two native amphibians, the long-toed salamander (Ambystoma macrodactylum) and Columbia spotted frog (Rana luteiventris), across three spatial scales:...
Growns, Ivor; Astles, Karen; Gehrke, Peter
2006-03-01
We studied the multiscale (sites, river reaches and rivers) and short-term temporal (monthly) variability in a freshwater fish assemblage. We found that small-scale spatial variation and short-term temporal variability significantly influenced fish community structure in the Macquarie and Namoi Rivers. However, larger scale spatial differences between rivers were the largest source of variation in the data. The interaction between temporal change and spatial variation in fish community structure, whilst statistically significant, was smaller than the variation between rivers. This suggests that although the fish communities within each river changed between sampling occasions, the underlying differences between rivers were maintained. In contrast, the strongest interaction between temporal and spatial effects occurred at the smallest spatial scale, at the level of individual sites. This means whilst the composition of the fish assemblage at a given site may fluctuate, the magnitude of these changes is unlikely to affect larger scale differences between reaches within rivers or between rivers. These results suggest that sampling at any time within a single season will be sufficient to show spatial differences that occur over large spatial scales, such as comparisons between rivers or between biogeographical regions.
NASA Astrophysics Data System (ADS)
Korres, W.; Reichenau, T. G.; Schneider, K.
2013-08-01
Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.
1. We investigated the potential of cross-scale interactions to affect the outcome of density reduction in a large-scale silvicultural experiment. 2. We measured tree growth and intrinsic water-use efficiency (iWUE) based on stable carbon isotopes (13C) to investigate the...
Soil Moisture fusion across scales using a multiscale nonstationary Spatial Hierarchical Model
NASA Astrophysics Data System (ADS)
Kathuria, D.; Mohanty, B.; Katzfuss, M.
2017-12-01
Soil moisture (SM) datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors, on the other hand, provide observations on a finer spatial scale (meter scale or less) but are sparsely available. SM is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables and these interactions change dynamically with footprint scales. Past literature has largely focused on the scale specific effect of these covariates on soil moisture. The present study proposes a robust Multiscale-Nonstationary Spatial Hierarchical Model (MN-SHM) which can assimilate SM from point to RS footprints. The spatial structure of SM across footprints is modeled by a class of scalable covariance functions whose nonstationary depends on atmospheric forcings (such as precipitation) and surface physical controls (such as topography, soil-texture and vegetation). The proposed model is applied to fuse point and airborne ( 1.5 km) SM data obtained during the SMAPVEX12 campaign in the Red River watershed in Southern Manitoba, Canada with SMOS ( 30km) data. It is observed that precipitation, soil-texture and vegetation are the dominant factors which affect the SM distribution across various footprint scales (750 m, 1.5 km, 3 km, 9 km,15 km and 30 km). We conclude that MN-SHM handles the change of support problems easily while retaining reasonable predictive accuracy across multiple spatial resolutions in the presence of surface heterogeneity. The MN-SHM can be considered as a complex non-stationary extension of traditional geostatistical prediction methods (such as Kriging) for fusing multi-platform multi-scale datasets.
Disentangling how landscape spatial and temporal heterogeneity affects Savanna birds.
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.
Disentangling How Landscape Spatial and Temporal Heterogeneity Affects Savanna Birds
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
USDA-ARS?s Scientific Manuscript database
This paper aims to investigate how surface soil moisture data assimilation affects each hydrologic process and how spatially varying inputs affect the potential capability of surface soil moisture assimilation at the watershed scale. The Ensemble Kalman Filter (EnKF) is coupled with a watershed scal...
Robbins, Neil E.
2016-01-01
Water is the most limiting resource on land for plant growth, and its uptake by plants is affected by many abiotic stresses, such as salinity, cold, heat, and drought. While much research has focused on exploring the molecular mechanisms underlying the cellular signaling events governing water-stress responses, it is also important to consider the role organismal structure plays as a context for such responses. The regulation of growth in plants occurs at two spatial scales: the cell and the organ. In this review, we focus on how the regulation of growth at these different spatial scales enables plants to acclimate to water-deficit stress. The cell wall is discussed with respect to how the physical properties of this structure affect water loss and how regulatory mechanisms that affect wall extensibility maintain growth under water deficit. At a higher spatial scale, the architecture of the root system represents a highly dynamic physical network that facilitates access of the plant to a heterogeneous distribution of water in soil. We discuss the role differential growth plays in shaping the structure of this system and the physiological implications of such changes. PMID:27503468
Scaling biodiversity responses to hydrological regimes.
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.
Water balance model for Kings Creek
NASA Technical Reports Server (NTRS)
Wood, Eric F.
1990-01-01
Particular attention is given to the spatial variability that affects the representation of water balance at the catchment scale in the context of macroscale water-balance modeling. Remotely sensed data are employed for parameterization, and the resulting model is developed so that subgrid spatial variability is preserved and therefore influences the grid-scale fluxes of the model. The model permits the quantitative evaluation of the surface-atmospheric interactions related to the large-scale hydrologic water balance.
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.
Effect of Variable Spatial Scales on USLE-GIS Computations
NASA Astrophysics Data System (ADS)
Patil, R. J.; Sharma, S. K.
2017-12-01
Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.
Scribner, Kim T.; Lowe, Winsor H.; Landguth, Erin L.; Luikart, Gordon; Infante, Dana M.; Whelan, Gary; Muhlfeld, Clint C.
2015-01-01
Environmental variation and landscape features affect ecological processes in fluvial systems; however, assessing effects at management-relevant temporal and spatial scales is challenging. Genetic data can be used with landscape models and traditional ecological assessment data to identify biodiversity hotspots, predict ecosystem responses to anthropogenic effects, and detect impairments to underlying processes. We show that by combining taxonomic, demographic, and genetic data of species in complex riverscapes, managers can better understand the spatial and temporal scales over which environmental processes and disturbance influence biodiversity. We describe how population genetic models using empirical or simulated genetic data quantify effects of environmental processes affecting species diversity and distribution. Our summary shows that aquatic assessment initiatives that use standardized data sets to direct management actions can benefit from integration of genetic data to improve the predictability of disturbance–response relationships of river fishes and their habitats over a broad range of spatial and temporal scales.
Remote sensing, global warming, and vector-borne disease
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wood, B.; Beck, L.; Dister, S.
1997-12-31
The relationship between climate change and the pattern of vector-borne disease can be viewed at a variety of spatial and temporal scales. At one extreme are changes such as global warming, which are continental in scale and occur over periods of years, decades, or longer. At the opposite extreme are changes associated with severe weather events, which can occur at local and regional scales over periods of days, weeks, or months. Key ecological factors affecting the distribution of vector-borne diseases include temperature, precipitation, and habitat availability, and their impact on vectors, pathogens, reservoirs, and hosts. Global warming can potentially altermore » these factors, thereby affecting the spatial and temporal patterns of disease.« less
Multiscale Study of Currents Affected by Topography
2015-09-30
1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Multiscale Study of Currents Affected by Topography ...the effects of topography on the ocean general and regional circulation with a focus on the wide range of scales of interactions. The small-scale...details of the topography and the waves, eddies, drag, and turbulence it generates (at spatial scales ranging from meters to mesoscale) interact in the
Agetsuma, Naoki; Koda, Ryosuke; Tsujino, Riyou; Agetsuma-Yanagihara, Yoshimi
2015-02-01
Population densities of wildlife species tend to be correlated with resource productivity of habitats. However, wildlife density has been greatly modified by increasing human influences. For effective conservation, we must first identify the significant factors that affect wildlife density, and then determine the extent of the areas in which the factors should be managed. Here, we propose a protocol that accomplishes these two tasks. The main threats to wildlife are thought to be habitat alteration and hunting, with increases in alien carnivores being a concern that has arisen recently. Here, we examined the effect of these anthropogenic disturbances, as well as natural factors, on the local density of Yakushima macaques (Macaca fuscata yakui). We surveyed macaque densities at 30 sites across their habitat using data from 403 automatic cameras. We quantified the effect of natural vegetation (broad-leaved forest, mixed coniferous/broad-leaved forest, etc.), altered vegetation (forestry area and agricultural land), hunting pressure, and density of feral domestic dogs (Canis familiaris). The effect of each vegetation type was analyzed at numerous spatial scales (between 150 and 3,600-m radii from the camera locations) to determine the best scale for explaining macaque density (effective spatial scale). A model-selection procedure (generalized linear mixed model) was used to detect significant factors affecting macaque density. We detected that the most effective spatial scale was 400 m in radius, a scale that corresponded to group range size of the macaques. At this scale, the amount of broad-leaved forest was selected as a positive factor, whereas mixed forest and forestry area were selected as negative factors for macaque density. This study demonstrated the importance of the simultaneous evaluation of all possible factors of wildlife population density at the appropriate spatial scale. © 2014 Wiley Periodicals, Inc.
Implications of construction method and spatial scale on measures of the built environment.
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.
Exploring the effect of the spatial scale of fishery management.
Takashina, Nao; Baskett, Marissa L
2016-02-07
For any spatially explicit management, determining the appropriate spatial scale of management decisions is critical to success at achieving a given management goal. Specifically, managers must decide how much to subdivide a given managed region: from implementing a uniform approach across the region to considering a unique approach in each of one hundred patches and everything in between. Spatially explicit approaches, such as the implementation of marine spatial planning and marine reserves, are increasingly used in fishery management. Using a spatially explicit bioeconomic model, we quantify how the management scale affects optimal fishery profit, biomass, fishery effort, and the fraction of habitat in marine reserves. We find that, if habitats are randomly distributed, the fishery profit increases almost linearly with the number of segments. However, if habitats are positively autocorrelated, then the fishery profit increases with diminishing returns. Therefore, the true optimum in management scale given cost to subdivision depends on the habitat distribution pattern. Copyright © 2015 Elsevier Ltd. All rights reserved.
Brand, John; Johnson, Aaron P
2014-01-01
In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks.
Brand, John; Johnson, Aaron P.
2014-01-01
In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks. PMID:25520675
Kenneth J. Ruzicka; Klaus J. Puettmann; J. Renée Brooks
2017-01-01
Summary1. We investigated the potential of cross-scale interactions to affect the outcome of density reduction in a large-scale silvicultural experiment to better understand options for managing forests under climate change. 2. We measured tree growth and intrinsic water-use efficiency (iWUE) based on stable carbon isotopes (δ...
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...
Separating spatial search and efficiency rates as components of predation risk
DeCesare, Nicholas J.
2012-01-01
Predation risk is an important driver of ecosystems, and local spatial variation in risk can have population-level consequences by affecting multiple components of the predation process. I use resource selection and proportional hazard time-to-event modelling to assess the spatial drivers of two key components of risk—the search rate (i.e. aggregative response) and predation efficiency rate (i.e. functional response)—imposed by wolves (Canis lupus) in a multi-prey system. In my study area, both components of risk increased according to topographic variation, but anthropogenic features affected only the search rate. Predicted models of the cumulative hazard, or risk of a kill, underlying wolf search paths validated well with broad-scale variation in kill rates, suggesting that spatial hazard models provide a means of scaling up from local heterogeneity in predation risk to population-level dynamics in predator–prey systems. Additionally, I estimated an integrated model of relative spatial predation risk as the product of the search and efficiency rates, combining the distinct contributions of spatial heterogeneity to each component of risk. PMID:22977145
Liang, Jia Xin; Li, Xin Ju
2018-02-01
With remote sensing images from 1985, 2000 Lantsat 5 TM and 2015 Lantsat 8 OLI as data sources, we tried to select the suitable research scale and examine the temporal-spatial diffe-rentiation with such scale in the Nansihu Lake wetland by using landscape pattern vulnerability index constructed by sensitivity index and adaptability index, and combined with space statistics such as semivariogram and spatial autocorrelation. The results showed that 1 km × 1 km equidistant grid was the suitable research scale, which could eliminate the influence of spatial heterogeneity induced by random factors. From 1985 to 2015, the landscape pattern vulnerability in the Nansihu Lake wetland deteriorated gradually. The high-risk area of landscape pattern vulnerability dramatically expanded with time. The spatial heterogeneity of landscape pattern vulnerability increased, and the influence of non-structural factors on landscape pattern vulnerability strengthened. Spatial variability affected by spatial autocorrelation slightly weakened. Landscape pattern vulnerability had strong general spatial positive correlation, with the significant form of spatial agglomeration. The positive spatial autocorrelation continued to increase and the phenomenon of spatial concentration was more and more obvious over time. The local autocorrelation mainly based on high-high accumulation zone and low-low accumulation zone had stronger spatial autocorrelation among neighboring space units. The high-high accumulation areas showed the strongest level of significance, and the significant level of low-low accumulation zone increased with time. Natural factors, such as temperature and precipitation, affected water-level and landscape distribution, and thus changed the landscape patterns vulnerability of Nansihu Lake wetland. The dominant driver for the deterioration of landscape patterns vulnerability was human activities, including social economy activity and policy system.
Lobo, Elena; Dalling, James W
2014-03-07
Treefall gaps play an important role in tropical forest dynamics and in determining above-ground biomass (AGB). However, our understanding of gap disturbance regimes is largely based either on surveys of forest plots that are small relative to spatial variation in gap disturbance, or on satellite imagery, which cannot accurately detect small gaps. We used high-resolution light detection and ranging data from a 1500 ha forest in Panama to: (i) determine how gap disturbance parameters are influenced by study area size, and the criteria used to define gaps; and (ii) to evaluate how accurately previous ground-based canopy height sampling can determine the size and location of gaps. We found that plot-scale disturbance parameters frequently differed significantly from those measured at the landscape-level, and that canopy height thresholds used to define gaps strongly influenced the gap-size distribution, an important metric influencing AGB. Furthermore, simulated ground surveys of canopy height frequently misrepresented the true location of gaps, which may affect conclusions about how relatively small canopy gaps affect successional processes and contribute to the maintenance of diversity. Across site comparisons need to consider how gap definition, scale and spatial resolution affect characterizations of gap disturbance, and its inferred importance for carbon storage and community composition.
Wan, Jinhong; Yan, Denghua; Fu, Guobin; Hao, Lu; Yue, Yaojie; Li, Ruoxi; Li, Yunpeng; Liu, Jiangang; Deng, Jun
2016-01-01
In China, Zou Zhe (Memorials to the Throne, or Palace Memorials), an official communication to the emperors of China by local officials, offers an opportunity to reconstruct the spatial-temporal distributions of droughts at a high-resolution. A 223-year, 1689–1911, time series of drought events was reconstructed in this study based on 2494 pieces of Zou Zhe. The results show that: 1) on the temporal scale, the drought affected areas, i.e., number of affected counties, showed three peak periods during the last 223 years and nine extreme drought years with more than 300 counties affected have been identified; 2) on the spatial scale, there existed three drought-prone areas in China, i.e., Gansu province and Ningxia Hui Autonomous Region in Northwest China, Shandong, Hebei, and Henan provinces and Tianjin in the North China, and Anhui and Jiangsu provinces in Jianghuai area, respectively; 3) the drought-prone areas have been expanding from North China to South China since the second half of 19th century; 4) on the seasonal scale, summer witnessed the largest number of drought events. Meanwhile, the uncertainties of the results were also discussed, i.e. what caused the spatial-temporal distribution of drought. The results of this study can be used to mitigate the adverse effects of extreme weather events on food increasing and stable production. PMID:26836807
Wan, Jinhong; Yan, Denghua; Fu, Guobin; Hao, Lu; Yue, Yaojie; Li, Ruoxi; Li, Yunpeng; Liu, Jiangang; Deng, Jun
2016-01-01
In China, Zou Zhe (Memorials to the Throne, or Palace Memorials), an official communication to the emperors of China by local officials, offers an opportunity to reconstruct the spatial-temporal distributions of droughts at a high-resolution. A 223-year, 1689-1911, time series of drought events was reconstructed in this study based on 2494 pieces of Zou Zhe. The results show that: 1) on the temporal scale, the drought affected areas, i.e., number of affected counties, showed three peak periods during the last 223 years and nine extreme drought years with more than 300 counties affected have been identified; 2) on the spatial scale, there existed three drought-prone areas in China, i.e., Gansu province and Ningxia Hui Autonomous Region in Northwest China, Shandong, Hebei, and Henan provinces and Tianjin in the North China, and Anhui and Jiangsu provinces in Jianghuai area, respectively; 3) the drought-prone areas have been expanding from North China to South China since the second half of 19th century; 4) on the seasonal scale, summer witnessed the largest number of drought events. Meanwhile, the uncertainties of the results were also discussed, i.e. what caused the spatial-temporal distribution of drought. The results of this study can be used to mitigate the adverse effects of extreme weather events on food increasing and stable production.
Cornell, K.L.; Donovan, T.M.
2010-01-01
Understanding how spatial habitat patterns influence abundance and dynamics of animal populations is a primary goal in landscape ecology. We used an information-theoretic approach to investigate the association between habitat patterns at multiple spatial scales and demographic patterns for black-throated blue warblers (Dendroica caerulescens) at 20 study sites in west-central Vermont, USA from 2002 to 2005. Sites were characterized by: (1) territory-scale shrub density, (2) patch-scale shrub density occurring within 25 ha of territories, and (3) landscape-scale habitat patterns occurring within 5 km radius extents of territories. We considered multiple population parameters including abundance, age ratios, and annual fecundity. Territory-scale shrub density was most important for determining abundance and age ratios, but landscape-scale habitat structure strongly influenced reproductive output. Sites with higher territory-scale shrub density had higher abundance, and were more likely to be occupied by older, more experienced individuals compared to sites with lower shrub density. However, annual fecundity was higher on sites located in contiguously forested landscapes where shrub density was lower than the fragmented sites. Further, effects of habitat pattern at one spatial scale depended on habitat conditions at different scales. For example, abundance increased with increasing territory-scale shrub density, but this effect was much stronger in fragmented landscapes than in contiguously forested landscapes. These results suggest that habitat pattern at different spatial scales affect demographic parameters in different ways, and that effects of habitat patterns at one spatial scale depends on habitat conditions at other scales. ?? Springer Science+Business Media B.V. 2009.
Scale dependent inference in landscape genetics
Samuel A. Cushman; Erin L. Landguth
2010-01-01
Ecological relationships between patterns and processes are highly scale dependent. This paper reports the first formal exploration of how changing scale of research away from the scale of the processes governing gene flow affects the results of landscape genetic analysis. We used an individual-based, spatially explicit simulation model to generate patterns of genetic...
Human seizures couple across spatial scales through travelling wave dynamics
NASA Astrophysics Data System (ADS)
Martinet, L.-E.; Fiddyment, G.; Madsen, J. R.; Eskandar, E. N.; Truccolo, W.; Eden, U. T.; Cash, S. S.; Kramer, M. A.
2017-04-01
Epilepsy--the propensity toward recurrent, unprovoked seizures--is a devastating disease affecting 65 million people worldwide. Understanding and treating this disease remains a challenge, as seizures manifest through mechanisms and features that span spatial and temporal scales. Here we address this challenge through the analysis and modelling of human brain voltage activity recorded simultaneously across microscopic and macroscopic spatial scales. We show that during seizure large-scale neural populations spanning centimetres of cortex coordinate with small neural groups spanning cortical columns, and provide evidence that rapidly propagating waves of activity underlie this increased inter-scale coupling. We develop a corresponding computational model to propose specific mechanisms--namely, the effects of an increased extracellular potassium concentration diffusing in space--that support the observed spatiotemporal dynamics. Understanding the multi-scale, spatiotemporal dynamics of human seizures--and connecting these dynamics to specific biological mechanisms--promises new insights to treat this devastating disease.
Influence of landscape-scale factors in limiting brook trout populations in Pennsylvania streams
Kocovsky, P.M.; Carline, R.F.
2006-01-01
Landscapes influence the capacity of streams to produce trout through their effect on water chemistry and other factors at the reach scale. Trout abundance also fluctuates over time; thus, to thoroughly understand how spatial factors at landscape scales affect trout populations, one must assess the changes in populations over time to provide a context for interpreting the importance of spatial factors. We used data from the Pennsylvania Fish and Boat Commission's fisheries management database to investigate spatial factors that affect the capacity of streams to support brook trout Salvelinus fontinalis and to provide models useful for their management. We assessed the relative importance of spatial and temporal variation by calculating variance components and comparing relative standard errors for spatial and temporal variation. We used binary logistic regression to predict the presence of harvestable-length brook trout and multiple linear regression to assess the mechanistic links between landscapes and trout populations and to predict population density. The variance in trout density among streams was equal to or greater than the temporal variation for several streams, indicating that differences among sites affect population density. Logistic regression models correctly predicted the absence of harvestable-length brook trout in 60% of validation samples. The r 2-value for the linear regression model predicting density was 0.3, indicating low predictive ability. Both logistic and linear regression models supported buffering capacity against acid episodes as an important mechanistic link between landscapes and trout populations. Although our models fail to predict trout densities precisely, their success at elucidating the mechanistic links between landscapes and trout populations, in concert with the importance of spatial variation, increases our understanding of factors affecting brook trout abundance and will help managers and private groups to protect and enhance populations of wild brook trout. ?? Copyright by the American Fisheries Society 2006.
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
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
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
Spatial scale of similarity as an indicator of metacommunity stability in exploited marine systems.
Shackell, Nancy L; Fisher, Jonathan A D; Frank, Kenneth T; Lawton, Peter
2012-01-01
The spatial scale of similarity among fish communities is characteristically large in temperate marine systems: connectivity is enhanced by high rates of dispersal during the larval/juvenile stages and the increased mobility of large-bodied fish. A larger spatial scale of similarity (low beta diversity) is advantageous in heavily exploited systems because locally depleted populations are more likely to be "rescued" by neighboring areas. We explored whether the spatial scale of similarity changed from 1970 to 2006 due to overfishing of dominant, large-bodied groundfish across a 300 000-km2 region of the Northwest Atlantic. Annually, similarities among communities decayed slowly with increasing geographic distance in this open system, but through time the decorrelation distance declined by 33%, concomitant with widespread reductions in biomass, body size, and community evenness. The decline in connectivity stemmed from an erosion of community similarity among local subregions separated by distances as small as 100 km. Larger fish, of the same species, contribute proportionally more viable offspring, so observed body size reductions will have affected maternal output. The cumulative effect of nonlinear maternal influences on egg/larval quality may have compromised the spatial scale of effective larval dispersal, which may account for the delayed recovery of certain member species. Our study adds strong support for using the spatial scale of similarity as an indicator of metacommunity stability both to understand the spatial impacts of exploitation and to refine how spatial structure is used in management plans.
NASA Astrophysics Data System (ADS)
Villegas, J. C.; Salazar, J. F.; Arias, P. A.; León, J. D.
2017-12-01
Land cover transformation is currently one of the most important challenges in tropical South America. These transformations occur both because of climate-related ecological perturbations, as well as in response to ongoing socio-economic processes. A fundamental difference between those two drivers is the spatial and temporal scale at which they operate. However, when considered in a larger context, both drivers affect the ability of ecosystems to provide fundamental services to society. In this work, we use a multi-scale approach to identify key-mechanisms through which land cover transformation significantly affects ecological, hydrological and ecoclimatological dynamics, potentially leading to loss of societally-critical regulation services. We propose a suite of examples spanning multiple spatial and temporal scales that illustrate the effects of land cover trnasformations in ecological, hydrological, biogeochemical and climatic functions in tropical South America. These examples highlight important global-change-effects management challenges, as well as the need to consider the feedbacks and interactions between multi-scale processes.
NASA Technical Reports Server (NTRS)
Rigney, Matt; Jedlovec, Gary; LaFontaine, Frank; Shafer, Jaclyn
2010-01-01
Heat and moisture exchange between ocean surface and atmosphere plays an integral role in short-term, regional NWP. Current SST products lack both spatial and temporal resolution to accurately capture small-scale features that affect heat and moisture flux. NASA satellite is used to produce high spatial and temporal resolution SST analysis using an OI technique.
Lobo, Elena; Dalling, James W.
2014-01-01
Treefall gaps play an important role in tropical forest dynamics and in determining above-ground biomass (AGB). However, our understanding of gap disturbance regimes is largely based either on surveys of forest plots that are small relative to spatial variation in gap disturbance, or on satellite imagery, which cannot accurately detect small gaps. We used high-resolution light detection and ranging data from a 1500 ha forest in Panama to: (i) determine how gap disturbance parameters are influenced by study area size, and the criteria used to define gaps; and (ii) to evaluate how accurately previous ground-based canopy height sampling can determine the size and location of gaps. We found that plot-scale disturbance parameters frequently differed significantly from those measured at the landscape-level, and that canopy height thresholds used to define gaps strongly influenced the gap-size distribution, an important metric influencing AGB. Furthermore, simulated ground surveys of canopy height frequently misrepresented the true location of gaps, which may affect conclusions about how relatively small canopy gaps affect successional processes and contribute to the maintenance of diversity. Across site comparisons need to consider how gap definition, scale and spatial resolution affect characterizations of gap disturbance, and its inferred importance for carbon storage and community composition. PMID:24452032
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.
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
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.
Improving left spatial neglect through music scale playing.
Bernardi, Nicolò Francesco; Cioffi, Maria Cristina; Ronchi, Roberta; Maravita, Angelo; Bricolo, Emanuela; Zigiotto, Luca; Perucca, Laura; Vallar, Giuseppe
2017-03-01
The study assessed whether the auditory reference provided by a music scale could improve spatial exploration of a standard musical instrument keyboard in right-brain-damaged patients with left spatial neglect. As performing music scales involves the production of predictable successive pitches, the expectation of the subsequent note may facilitate patients to explore a larger extension of space in the left affected side, during the production of music scales from right to left. Eleven right-brain-damaged stroke patients with left spatial neglect, 12 patients without neglect, and 12 age-matched healthy participants played descending scales on a music keyboard. In a counterbalanced design, the participants' exploratory performance was assessed while producing scales in three feedback conditions: With congruent sound, no-sound, or random sound feedback provided by the keyboard. The number of keys played and the timing of key press were recorded. Spatial exploration by patients with left neglect was superior with congruent sound feedback, compared to both Silence and Random sound conditions. Both the congruent and incongruent sound conditions were associated with a greater deceleration in all groups. The frame provided by the music scale improves exploration of the left side of space, contralateral to the right hemisphere, damaged in patients with left neglect. Performing a scale with congruent sounds may trigger at some extent preserved auditory and spatial multisensory representations of successive sounds, thus influencing the time course of space scanning, and ultimately resulting in a more extensive spatial exploration. These findings offer new perspectives also for the rehabilitation of the disorder. © 2015 The British Psychological Society.
River eutrophication: irrigated vs. non-irrigated agriculture through different spatial scales.
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.
Temporal and spatial scaling of the genetic structure of a vector-borne plant pathogen.
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.
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.
Regional hydro-climatic impacts of contemporary Amazonian deforestation
NASA Astrophysics Data System (ADS)
Khanna, Jaya
More than 17% of the Amazon rainforest has been cleared in the past three decades triggering important climatological and societal impacts. This thesis is devoted to identifying and explaining the regional hydroclimatic impacts of this change employing multidecadal satellite observations and numerical simulations providing an integrated perspective on this topic. The climatological nature of this study motivated the implementation and application of a cloud detection technique to a new geostationary satellite dataset. The resulting sub daily, high spatial resolution, multidecadal time series facilitated the detection of trends and variability in deforestation triggered cloud cover changes. The analysis was complemented by satellite precipitation, reanalysis and ground based datasets and attribution with the variable resolution Ocean-Land-Atmosphere-Model. Contemporary Amazonian deforestation affects spatial scales of hundreds of kilometers. But, unlike the well-studied impacts of a few kilometers scale deforestation, the climatic response to contemporary, large scale deforestation is neither well observed nor well understood. Employing satellite datasets, this thesis shows a transition in the regional hydroclimate accompanying increasing scales of deforestation, with downwind deforested regions receiving 25% more and upwind deforested regions receiving 25% less precipitation from the deforested area mean. Simulations robustly reproduce these shifts when forced with increasing deforestation alone, suggesting a negligible role of large-scale decadal climate variability in causing the shifts. Furthermore, deforestation-induced surface roughness variations are found necessary to reproduce the observed spatial patterns in recent times illustrating the strong scale-sensitivity of the climatic response to Amazonian deforestation. This phenomenon, inconsequential during the wet season, is found to substantially affect the regional hydroclimate in the local dry and parts of transition seasons, hence occurring in atmospheric conditions otherwise less conducive to thermal convection. Evidence of this phenomenon is found at two large scale deforested areas considered in this thesis. Hence, the 'dynamical' mechanism, which affects the seasons most important for regional ecology, emerges as an impactful convective triggering mechanism. The phenomenon studied in this thesis provides context for thinking about the climate of a future, more patchily forested Amazonia, by articulating relationships between climate and spatial scales of deforestation.
Herbivore-induced plant volatiles and tritrophic interactions across spatial scales.
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.
Goldstein, R.M.; Carlisle, D.M.; Meador, M.R.; Short, T.M.
2007-01-01
The environmental setting (e.g., climate, topography, geology) and land use affect stream physical characteristics singly and cumulatively. At broad geographic scales, we determined the importance of environmental setting and land use in explaining variation in stream physical characteristics. We hypothesized that as the spatial scale decreased from national to regional, land use would explain more of the variation in stream physical characteristics because environmental settings become more homogeneous. At a national scale, stepwise linear regression indicated that environmental setting was more important in explaining variability in stream physical characteristics. Although statistically discernible, the amount of variation explained by land use was not remarkable due to low partial correlations. At level II ecoregion spatial scales (southeastern USA plains, central USA plains, and a combination of the western Cordillera and the western interior basins and ranges), environmental setting variables were again more important predictors of stream physical characteristics, however, as the spatial scale decreased from national to regional, the portion of variability in stream physical characteristics explained by basin land use increased. Development of stream habitat indicators of land use will depend upon an understanding of relations between stream physical characteristics and environmental factors at multiple spatial scales. Smaller spatial scales will be necessary to reduce the confounding effects of variable environmental settings before the effects of land use can be reliably assessed. ?? Springer Science+Business Media B.V. 2006.
Effects of spatial scale of sampling on food web structure
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
Spatially explicit animal response to composition of habitat
Benjamin P. Pauli; Nicholas P. McCann; Patrick A. Zollner; Robert Cummings; Jonathan H. Gilbert; Eric J. Gustafson
2013-01-01
Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-...
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.
Network analysis reveals multiscale controls on streamwater chemistry
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
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.
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.
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.
Richard F. Miller; Emily K. Heyerdahl
2008-01-01
Coarse-scale estimates of fire intervals across the mountain big sagebrush (Artemisia tridentata spp. vaseyana (Rydb.) Beetle) alliance range from decades to centuries. However, soil depth and texture can affect the abundance and continuity of fine fuels and vary at fine spatial scales, suggesting fire regimes may vary at similar scales. We explored...
Plot-scale field experiment of surface hydrologic processes with EOS implications
NASA Technical Reports Server (NTRS)
Laymon, Charles A.; Macari, Emir J.; Costes, Nicholas C.
1992-01-01
Plot-scale hydrologic field studies were initiated at NASA Marshall Space Flight Center to a) investigate the spatial and temporal variability of surface and subsurface hydrologic processes, particularly as affected by vegetation, and b) develop experimental techniques and associated instrumentation methodology to study hydrologic processes at increasingly large spatial scales. About 150 instruments, most of which are remotely operated, have been installed at the field site to monitor ground atmospheric conditions, precipitation, interception, soil-water status, and energy flux. This paper describes the nature of the field experiment, instrumentation and sampling rationale, and presents preliminary findings.
Influence of landscape and social interactions on transmission of disease in a social cervid.
Vander Wal, Eric; Paquet, Paul C; Andrés, José A
2012-03-01
The mechanisms of pathogen transmission are often social behaviours. These occur at local scales and are affected by landscape-scale population structure. Host populations frequently exist in patchy and isolated environments that create a continuum of genetic and social familiarity. Such variability has an important multispatial effect on pathogen spread. We assessed elk dispersal (i.e. likelihood of interdeme pathogen transmission) through spatially explicit genetic analyses. At a landscape scale, the elk population was composed of one cluster within a southeast-to-northwest cline spanning three spatially discrete subpopulations of elk across two protected areas in Manitoba (Canada). Genetic data are consistent with spatial variability in apparent prevalence of bovine tuberculosis (TB) in elk. Given the existing population structure, between-subpopulation spread of disease because of elk dispersal is unlikely. Furthermore, to better understand the risk of spread and distribution of the TB, we used a combination of close-contact logging biotelemetry and genetic data, which highlights how social intercourse may affect pathogen transmission. Our results indicate that close-contact interaction rate and duration did not covary with genetic relatedness. Thus, direct elk-to-elk transmission of disease is unlikely to be constrained to related individuals. That social intercourse in elk is not limited to familial groups provides some evidence pathogen transmission may be density-dependent. We show that the combination of landscape-scale genetics, relatedness and local-scale social behaviours is a promising approach to understand and predict landscape-level pathogen transmission within our system and within all social ungulate systems affected by transmissible diseases. © 2012 Blackwell Publishing Ltd.
Silver hake tracks changes in Northwest Atlantic circulation.
Nye, Janet A; Joyce, Terrence M; Kwon, Young-Oh; Link, Jason S
2011-08-02
Recent studies documenting shifts in spatial distribution of many organisms in response to a warming climate highlight the need to understand the mechanisms underlying species distribution at large spatial scales. Here we present one noteworthy example of remote oceanographic processes governing the spatial distribution of adult silver hake, Merluccius bilinearis, a commercially important fish in the Northeast US shelf region. Changes in spatial distribution of silver hake over the last 40 years are highly correlated with the position of the Gulf Stream. These changes in distribution are in direct response to local changes in bottom temperature on the continental shelf that are responding to the same large scale circulation change affecting the Gulf Stream path, namely changes in the Atlantic meridional overturning circulation (AMOC). If the AMOC weakens, as is suggested by global climate models, silver hake distribution will remain in a poleward position, the extent to which could be forecast at both decadal and multidecadal scales.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gershenzon, Naum I.; Soltanian, Mohamad Reza; Ritzi, Robert W.
Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations andmore » probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.« less
Gershenzon, Naum I.; Soltanian, Mohamad Reza; Ritzi, Robert W.; ...
2015-10-23
Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations andmore » probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.« less
Multi-scale analysis of a household level agent-based model of landcover change.
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.
Cross-scale interactions affect tree growth and intrinsic water ...
1. We investigated the potential of cross-scale interactions to affect the outcome of density reduction in a large-scale silvicultural experiment. 2. We measured tree growth and intrinsic water-use efficiency (iWUE) based on stable carbon isotopes (13C) to investigate the impacts of thinning across a range of progressively finer spatial scales: site, stand, hillslope position, and neighborhood position. In particular, we focused on the influence of thinning beyond the boundaries of thinned stands to include impacts on downslope and neighboring stands across sites varying in soil moisture. 3. Trees at the wet site responded to thinning with increased growth when compared with trees at the dry site. Additionally, trees in thinned stands at the dry site responded with increased iWUE while trees in thinned stands at the wet site showed no difference in iWUE compared to unthinned stands. 4. We hypothesized that water is not the primary limiting factor for growth at our sites, but that thinning released other resources, such as growing space or nutrients to drive the growth response. At progressively finer spatial scales we found that the responses of trees was not driven by hillslope location (i.e., downslope of thinning) but to changes in local neighborhood tree density. 5. The results of this study demonstrated that water can be viewed as an “agent” that allows us to investigate cross-scale interactions as it links coarse to finer spatial scales and vice ver
NASA Astrophysics Data System (ADS)
Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.
2016-12-01
In the Brazilian rainforest-savanna transition zone, vegetation change has the potential to significantly affect precipitation patterns. Deforestation, in particular, can affect precipitation patterns by increasing land surface albedo, increasing aerosol loading to the atmosphere, changing land surface roughness, and reducing transpiration. Understanding land surface-precipitation couplings in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching and agriculture, hydropower generation, and drinking water management. Simulations suggest complex, scale-dependent interactions between precipitation and land cover. For example, the size and distribution of deforested patches has been found to affect precipitation patterns. We take an empirical approach to ask: (1) what are the dominant spatial and temporal length scales of precipitation coupling in the Brazilian rainforest-savanna transition zone? (2) How do these length scales change over time? (3) How does the connectivity of precipitation change over time? The answers to these questions will help address fundamental questions about the impacts of deforestation on precipitation. We use rain gauge data from 1100 rain gauges intermittently covering the period 1980 - 2013, a period of intensive land cover change in the region. The dominant spatial and temporal length scales of precipitation coupling are resolved using transfer entropy, a metric from information theory. Connectivity of the emergent network of couplings is quantified using network statistics. Analyses using transfer entropy and network statistics reveal the spatial and temporal interdependencies of rainfall events occurring in different parts of the study domain.
Immediate and delayed recall of a small-scale spatial array.
Tlauka, Michael; Donaldson, Phillip; Bonnar, Daniel
2015-01-01
The study examined people's spatial memory of a small-scale array of objects. Earlier work has primarily relied on short-retention intervals, and to date it is not known whether performance is affected by longer intervals between learning and recall. In the present investigation, university students studied seven target objects. Recall was tested immediately after learning and after an interval of seven days. Performance was found to be similar in the immediate and delayed conditions, and the results suggested that recall was facilitated by egocentric and intrinsic cues. The findings are discussed with reference to recent investigations that have shown task parameters can influence spatial recall.
APPLICATIONS OF FISHER INFORMATION TO THE MANAGEMENT OF SUSTAINABLE ENVIRONMENTAL SYSTEMS
All organisms alter their surroundings, and humans now have the ability to affect environments at increasingly larger temporal and spatial scales. Indeed, mechanical and engineering advances of the 20th century greatly enhanced the scale of human activities, particular...
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.
Luiz, Amom Mendes; Sawaya, Ricardo J.
2018-01-01
Ecological communities are complex entities that can be maintained and structured by niche-based processes such as environmental conditions, and spatial processes such as dispersal. Thus, diversity patterns may be shaped simultaneously at different spatial scales by very distinct processes. Herein we assess whether and how functional, taxonomic, and phylogenetic beta diversities of frog tadpoles are explained by environmental and/or spatial predictors. We implemented a distance–based redundancy analysis to explore variation in components of beta diversity explained by pure environmental and pure spatial predictors, as well as their interactions, at both fine and broad spatial scales. Our results indicated important but complex roles of spatial and environmental predictors in structuring phylogenetic, taxonomic and functional beta diversities. The pure fine-scales spatial fraction was more important in structuring all beta diversity components, especially to functional and taxonomical spatial turnover. Environmental variables such as canopy cover and vegetation structure were important predictors of all components, but especially to functional and taxonomic beta diversity. We emphasize that distinct factors related to environment and space are affecting distinct components of beta diversity in different ways. Although weaker, phylogenetic beta diversity, which is structured more on biogeographical scales, and thus can be represented by spatially structured processes, was more related to broad spatial processes than other components. However, selected fine-scale spatial predictors denoted negative autocorrelation, which may be revealing the existence of differences in unmeasured habitat variables among samples. Although overall important, local environmental-based processes explained better functional and taxonomic beta diversity, as these diversity components carry an important ecological value. We highlight the importance of assessing different components of diversity patterns at different scales by spatially explicit models in order to improve our understanding of community structure and help to unravel the complex nature of biodiversity. PMID:29672575
Scale dependence of the diversity-stability relationship in a temperate grassland.
Zhang, Yunhai; He, Nianpeng; Loreau, Michel; Pan, Qingmin; Han, Xingguo
2018-05-01
A positive relationship between biodiversity and ecosystem stability has been reported in many ecosystems; however, it has yet to be determined whether and how spatial scale affects this relationship. Here, for the first time, we assessed the effects of alpha, beta and gamma diversity on ecosystem stability and the scale dependence of the slope of the diversity-stability relationship.By employing a long-term (33 years) dataset from a temperate grassland, northern China, we calculated the all possible spatial scales with the complete combination from the basic 1-m 2 plots.Species richness was positively associated with ecosystem stability through species asynchrony and overyielding at all spatial scales (1, 2, 3, 4 and 5 m 2 ). Both alpha and beta diversity were positively associated with gamma stability.Moreover, the slope of the diversity-area relationship was significantly higher than that of the stability-area relationship, resulting in a decline of the slope of the diversity-stability relationship with increasing area. Synthesis. With the positive species diversity effect on ecosystem stability from small to large spatial scales, our findings demonstrate the need to maintain a high biodiversity and biotic heterogeneity as insurance against the risks incurred by ecosystems in the face of global environmental changes.
Štursová, Martina; Bárta, Jiří; Šantrůčková, Hana; Baldrian, Petr
2016-12-01
Forests are recognised as spatially heterogeneous ecosystems. However, knowledge of the small-scale spatial variation in microbial abundance, community composition and activity is limited. Here, we aimed to describe the heterogeneity of environmental properties, namely vegetation, soil chemical composition, fungal and bacterial abundance and community composition, and enzymatic activity, in the topsoil in a small area (36 m 2 ) of a highly heterogeneous regenerating temperate natural forest, and to explore the relationships among these variables. The results demonstrated a high level of spatial heterogeneity in all properties and revealed differences between litter and soil. Fungal communities had substantially higher beta-diversity than bacterial communities, which were more uniform and less spatially autocorrelated. In litter, fungal communities were affected by vegetation and appeared to be more involved in decomposition. In the soil, chemical composition affected both microbial abundance and the rates of decomposition, whereas the effect of vegetation was small. Importantly, decomposition appeared to be concentrated in hotspots with increased activity of multiple enzymes. Overall, forest topsoil should be considered a spatially heterogeneous environment in which the mean estimates of ecosystem-level processes and microbial community composition may confound the existence of highly specific microenvironments. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Jakobsson, Anna; Lázaro, Amparo; Totland, Orjan
2009-07-01
Local flower density can affect pollen limitation and plant reproductive success through changes in pollinator visitation and availability of compatible pollen. Many studies have investigated the relationship between conspecific density and pollen limitation among populations, but less is known about within-population relationships and the effect of heterospecific flower density. In addition, few studies have explicitly assessed how the spatial scales at which flowers are monitored affect relationships. We investigated the effect of floral neighborhood on pollen limitation at four spatial scales in the self-incompatible herbs Armeria maritima spp. maritima and Ranunculus acris spp. acris. Moreover, we measured pollen deposition in Armeria and pollinator visits to Ranunculus. There was substantial variation in pollen limitation among Armeria individuals, and 25% of this variation was explained by the density of compatible and heterospecific flowers within a 3 m circle. Deposition of compatible pollen was affected by the density of compatible and incompatible inflorescences within a 0.5 m circle, and deposition of heterospecific pollen was affected by the density of heterospecific flowers within a 2 m circle. In Ranunculus, the number of pollinator visits was affected by both conspecific and heterospecific flower densities. This did not, however, result in effects of the floral neighborhood on pollen limitation, probably due to an absence of pollen limitation at the population level. Our study shows that considerable variation in pollen limitation may occur among individuals of a population, and that this variation is partly explained by floral neighborhood density. Such individual-based measures provide an important link between pollen limitation theory, which predicts ecological and evolutionary causes and consequences for individual plants, and studies of the effects of landscape fragmentation on plant species persistence. Our study also highlights the importance of considering multiple spatial scales to understand the spatial extent of pollination processes within a population.
Ellingson, A.R.; Andersen, D.C.
2002-01-01
1. The hypothesis that the habitat-scale spatial distribution of the, Apache cicada Diceroprocta apache Davis is unaffected by the presence of the invasive exotic saltcedar Tamarix ramosissima was tested using data from 205 1-m2 quadrats placed within the flood-plain of the Bill Williams River, Arizona, U.S.A. Spatial dependencies within and between cicada density and habitat variables were estimated using Moran's I and its bivariate analogue to discern patterns and associations at spatial scales from 1 to 30 m. 2. Apache cicadas were spatially aggregated in high-density clusters averaging 3m in diameter. A positive association between cicada density, estimated by exuvial density, and the per cent canopy cover of a native tree, Goodding's willow Salix gooddingii, was detected in a non-spatial correlation analysis. No non-spatial association between cicada density and saltcedar canopy cover was detected. 3. Tests for spatial cross-correlation using the bivariate IYZ indicated the presence of a broad-scale negative association between cicada density and saltcedar canopy cover. This result suggests that large continuous stands of saltcedar are associated with reduced cicada density. In contrast, positive associations detected at spatial scales larger than individual quadrats suggested a spill-over of high cicada density from areas featuring Goodding's willow canopy into surrounding saltcedar monoculture. 4. Taken together and considered in light of the Apache cicada's polyphagous habits, the observed spatial patterns suggest that broad-scale factors such as canopy heterogeneity affect cicada habitat use more than host plant selection. This has implications for management of lower Colorado River riparian woodlands to promote cicada presence and density through maintenance or creation of stands of native trees as well as manipulation of the characteristically dense and homogeneous saltcedar canopies.
Ellingson, A.R.; Andersen, D.C.
2002-01-01
1. The hypothesis that the habitat-scale spatial distribution of the Apache cicada Diceroprocta apache Davis is unaffected by the presence of the invasive exotic saltcedar Tamarix ramosissima was tested using data from 205 1-m2 quadrats placed within the flood-plain of the Bill Williams River, Arizona, U.S.A. Spatial dependencies within and between cicada density and habitat variables were estimated using Moran's I and its bivariate analogue to discern patterns and associations at spatial scales from 1 to 30 m.2. Apache cicadas were spatially aggregated in high-density clusters averaging 3 m in diameter. A positive association between cicada density, estimated by exuvial density, and the per cent canopy cover of a native tree, Goodding's willow Salix gooddingii, was detected in a non-spatial correlation analysis. No non-spatial association between cicada density and saltcedar canopy cover was detected.3. Tests for spatial cross-correlation using the bivariate IYZ indicated the presence of a broad-scale negative association between cicada density and saltcedar canopy cover. This result suggests that large continuous stands of saltcedar are associated with reduced cicada density. In contrast, positive associations detected at spatial scales larger than individual quadrats suggested a spill-over of high cicada density from areas featuring Goodding's willow canopy into surrounding saltcedar monoculture.4. Taken together and considered in light of the Apache cicada's polyphagous habits, the observed spatial patterns suggest that broad-scale factors such as canopy heterogeneity affect cicada habitat use more than host plant selection. This has implications for management of lower Colorado River riparian woodlands to promote cicada presence and density through maintenance or creation of stands of native trees as well as manipulation of the characteristically dense and homogeneous saltcedar canopies.
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.
Cross-Scale Molecular Analysis of Chemical Heterogeneity in Shale Rocks
Hao, Zhao; Bechtel, Hans A.; Kneafsey, Timothy; ...
2018-02-07
The organic and mineralogical heterogeneity in shale at micrometer and nanometer spatial scales contributes to the quality of gas reserves, gas flow mechanisms and gas production. Here, we demonstrate two molecular imaging approaches based on infrared spectroscopy to obtain mineral and kerogen information at these mesoscale spatial resolutions in large-sized shale rock samples. The first method is a modified microscopic attenuated total reflectance measurement that utilizes a large germanium hemisphere combined with a focal plane array detector to rapidly capture chemical images of shale rock surfaces spanning hundreds of micrometers with micrometer spatial resolution. The second method, synchrotron infrared nano-spectroscopy,more » utilizes a metallic atomic force microscope tip to obtain chemical images of micrometer dimensions but with nanometer spatial resolution. This chemically "deconvoluted" imaging at the nano-pore scale is then used to build a machine learning model to generate a molecular distribution map across scales with a spatial span of 1000 times, which enables high-throughput geochemical characterization in greater details across the nano-pore and micro-grain scales and allows us to identify co-localization of mineral phases with chemically distinct organics and even with gas phase sorbents. Finally, this characterization is fundamental to understand mineral and organic compositions affecting the behavior of shales.« less
Cross-Scale Molecular Analysis of Chemical Heterogeneity in Shale Rocks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hao, Zhao; Bechtel, Hans A.; Kneafsey, Timothy
The organic and mineralogical heterogeneity in shale at micrometer and nanometer spatial scales contributes to the quality of gas reserves, gas flow mechanisms and gas production. Here, we demonstrate two molecular imaging approaches based on infrared spectroscopy to obtain mineral and kerogen information at these mesoscale spatial resolutions in large-sized shale rock samples. The first method is a modified microscopic attenuated total reflectance measurement that utilizes a large germanium hemisphere combined with a focal plane array detector to rapidly capture chemical images of shale rock surfaces spanning hundreds of micrometers with micrometer spatial resolution. The second method, synchrotron infrared nano-spectroscopy,more » utilizes a metallic atomic force microscope tip to obtain chemical images of micrometer dimensions but with nanometer spatial resolution. This chemically "deconvoluted" imaging at the nano-pore scale is then used to build a machine learning model to generate a molecular distribution map across scales with a spatial span of 1000 times, which enables high-throughput geochemical characterization in greater details across the nano-pore and micro-grain scales and allows us to identify co-localization of mineral phases with chemically distinct organics and even with gas phase sorbents. Finally, this characterization is fundamental to understand mineral and organic compositions affecting the behavior of shales.« less
The effects of habitat connectivity and regional heterogeneity on artificial pond metacommunities.
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.
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.
AIR TOXICS MODELING FROM LOCAL TO REGIONAL SCALES TO SUPPORT THE 2002 MULTIPOLLUTANT ASSESSMENT
This research focuses on developing models that can describe the chemical and physical processes affecting concentrations of toxic air pollutants in the atmosphere, at spatial scales, ranging from local (< 1 km) to regional (36 km). One objective of this task is to extend the ca...
NASA Astrophysics Data System (ADS)
Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.
2013-12-01
Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at fine-spatial scales (sub-meter to 10-meter) shows greater temperature variability with warmer mean temperatures. This is inconsistent with the inherent assumption made in current species distribution models that fine-scale variability is static, implying that current projections of future species ranges may be biased -- the direction and magnitude requiring further study. While we focus our findings on the cross-scaling characteristics of temporal and spatial variability, we also compare the mean-variance relationship between 1) experimental climate manipulations and observed conditions and 2) temporal versus spatial variance, i.e., variability in a time-series at one location vs. variability across a landscape at a single time. The former informs the rich debate concerning the ability to experimentally mimic a warmer future. The latter informs space-for-time study design and analyses, as well as species persistence via a combined spatiotemporal probability of suitable future habitat.
NASA Astrophysics Data System (ADS)
Fan, Linfeng; Lehmann, Peter; Or, Dani
2016-03-01
Spatial variations in soil properties affect key hydrological processes, yet their role in soil mechanical response to hydro-mechanical loading is rarely considered. This study aims to fill this gap by systematically quantifying effects of spatial variations in soil type and initial water content on rapid rainfall-induced shallow landslide predictions at the hillslope- and catchment-scales. We employed a physically-based landslide triggering model that considers mechanical interactions among soil columns governed by strength thresholds. At the hillslope scale, we found that the emergence of weak regions induced by spatial variations of soil type and initial water content resulted in early triggering of landslides with smaller volumes of released mass relative to a homogeneous slope. At the catchment scale, initial water content was linked to a topographic wetness index, whereas soil type varied deterministically with soil depth considering spatially correlated stochastic components. Results indicate that a strong spatial organization of initial water content delays landslide triggering, whereas spatially linked soil type with soil depth promoted landslide initiation. Increasing the standard deviation and correlation length of the stochastic component of soil type increases landslide volume and hastens onset of landslides. The study illustrates that for similar external boundary conditions and mean soil properties, landslide characteristics vary significantly with soil variability, hence it must be considered for improved landslide model predictions.
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
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.
Thematic and spatial resolutions affect model-based predictions of tree species distribution.
Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei
2013-01-01
Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.
Thematic and Spatial Resolutions Affect Model-Based Predictions of Tree Species Distribution
Liang, Yu; He, Hong S.; Fraser, Jacob S.; Wu, ZhiWei
2013-01-01
Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution. PMID:23861828
Spatial distribrrtion of soil carbon in southern New England hardwood forest landscapes
Aletta A. Davis; Mark H. Stolt; Jana E. Compton
2004-01-01
Understanding soil organic C (SOC) spatial variability is critical when developing C budgets, explaining the cause and effects of climate change, and for basic ecosystem characterization. We investigated delineations of four soil series to elucidate teh factors that affect the size, distribution, and varibility of SOC pools from horizon to landscape scales. These soils...
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,…
Hoos, A.B.; McMahon, G.
2009-01-01
Understanding how nitrogen transport across the landscape varies with landscape characteristics is important for developing sound nitrogen management policies. We used a spatially referenced regression analysis (SPARROW) to examine landscape characteristics influencing delivery of nitrogen from sources in a watershed to stream channels. Modelled landscape delivery ratio varies widely (by a factor of 4) among watersheds in the southeastern United States - higher in the western part (Tennessee, Alabama, and Mississippi) than in the eastern part, and the average value for the region is lower compared to other parts of the nation. When we model landscape delivery ratio as a continuous function of local-scale landscape characteristics, we estimate a spatial pattern that varies as a function of soil and climate characteristics but exhibits spatial structure in residuals (observed load minus predicted load). The spatial pattern of modelled landscape delivery ratio and the spatial pattern of residuals coincide spatially with Level III ecoregions and also with hydrologic landscape regions. Subsequent incorporation into the model of these frameworks as regional scale variables improves estimation of landscape delivery ratio, evidenced by reduced spatial bias in residuals, and suggests that cross-scale processes affect nitrogen attenuation on the landscape. The model-fitted coefficient values are logically consistent with the hypothesis that broad-scale classifications of hydrologic response help to explain differential rates of nitrogen attenuation, controlling for local-scale landscape characteristics. Negative model coefficients for hydrologic landscape regions where the primary flow path is shallow ground water suggest that a lower fraction of nitrogen mass will be delivered to streams; this relation is reversed for regions where the primary flow path is overland flow.
Hoos, Anne B.; McMahon, Gerard
2009-01-01
Understanding how nitrogen transport across the landscape varies with landscape characteristics is important for developing sound nitrogen management policies. We used a spatially referenced regression analysis (SPARROW) to examine landscape characteristics influencing delivery of nitrogen from sources in a watershed to stream channels. Modelled landscape delivery ratio varies widely (by a factor of 4) among watersheds in the southeastern United States—higher in the western part (Tennessee, Alabama, and Mississippi) than in the eastern part, and the average value for the region is lower compared to other parts of the nation. When we model landscape delivery ratio as a continuous function of local-scale landscape characteristics, we estimate a spatial pattern that varies as a function of soil and climate characteristics but exhibits spatial structure in residuals (observed load minus predicted load). The spatial pattern of modelled landscape delivery ratio and the spatial pattern of residuals coincide spatially with Level III ecoregions and also with hydrologic landscape regions. Subsequent incorporation into the model of these frameworks as regional scale variables improves estimation of landscape delivery ratio, evidenced by reduced spatial bias in residuals, and suggests that cross-scale processes affect nitrogen attenuation on the landscape. The model-fitted coefficient values are logically consistent with the hypothesis that broad-scale classifications of hydrologic response help to explain differential rates of nitrogen attenuation, controlling for local-scale landscape characteristics. Negative model coefficients for hydrologic landscape regions where the primary flow path is shallow ground water suggest that a lower fraction of nitrogen mass will be delivered to streams; this relation is reversed for regions where the primary flow path is overland flow.
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 the diversity–stability relationship in a temperate grassland
Zhang, Yunhai; He, Nianpeng; Loreau, Michel; Pan, Qingmin; Han, Xingguo
2018-01-01
A positive relationship between biodiversity and ecosystem stability has been reported in many ecosystems; however, it has yet to be determined whether and how spatial scale affects this relationship. Here, for the first time, we assessed the effects of alpha, beta and gamma diversity on ecosystem stability and the scale dependence of the slope of the diversity–stability relationship.By employing a long-term (33 years) dataset from a temperate grassland, northern China, we calculated the all possible spatial scales with the complete combination from the basic 1-m2 plots.Species richness was positively associated with ecosystem stability through species asynchrony and overyielding at all spatial scales (1, 2, 3, 4 and 5 m2). Both alpha and beta diversity were positively associated with gamma stability.Moreover, the slope of the diversity–area relationship was significantly higher than that of the stability–area relationship, resulting in a decline of the slope of the diversity–stability relationship with increasing area.Synthesis. With the positive species diversity effect on ecosystem stability from small to large spatial scales, our findings demonstrate the need to maintain a high biodiversity and biotic heterogeneity as insurance against the risks incurred by ecosystems in the face of global environmental changes. PMID:29725139
Speciation has a spatial scale that depends on levels of gene flow.
Kisel, Yael; Barraclough, Timothy G
2010-03-01
Area is generally assumed to affect speciation rates, but work on the spatial context of speciation has focused mostly on patterns of range overlap between emerging species rather than on questions of geographical scale. A variety of geographical theories of speciation predict that the probability of speciation occurring within a given region should (1) increase with the size of the region and (2) increase as the spatial extent of intraspecific gene flow becomes smaller. Using a survey of speciation events on isolated oceanic islands for a broad range of taxa, we find evidence for both predictions. The probability of in situ speciation scales with island area in bats, carnivorous mammals, birds, flowering plants, lizards, butterflies and moths, and snails. Ferns are an exception to these findings, but they exhibit high frequencies of polyploid and hybrid speciation, which are expected to be scale independent. Furthermore, the minimum island size for speciation correlates across groups with the strength of intraspecific gene flow, as is estimated from a meta-analysis of published population genetic studies. These results indicate a general geographical model of speciation rates that are dependent on both area and gene flow. The spatial scale of population divergence is an important but neglected determinant of broad-scale diversity patterns.
NASA Astrophysics Data System (ADS)
Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca
2017-04-01
The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of land-use/land-cover changes and river regulation on network-scale connectivity.
Fine-Scale Analysis Reveals Cryptic Landscape Genetic Structure in Desert Tortoises
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.
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.
Persistence of canine distemper virus in the Greater Yellowstone ecosystem's carnivore community.
Almberg, Emily S; Cross, Paul C; Smith, Douglas W
2010-10-01
Canine distemper virus (CDV) is an acute, highly immunizing pathogen that should require high densities and large populations of hosts for long-term persistence, yet CDV persists among terrestrial carnivores with small, patchily distributed groups. We used CDV in the Greater Yellowstone ecosystem's (GYE) wolves (Canis lupus) and coyotes (Canis latrans) as a case study for exploring how metapopulation structure, host demographics, and multi-host transmission affect the critical community size and spatial scale required for CDV persistence. We illustrate how host spatial connectivity and demographic turnover interact to affect both local epidemic dynamics, such as the length and variation in inter-epidemic periods, and pathogen persistence using stochastic, spatially explicit susceptible-exposed-infectious-recovered simulation models. Given the apparent absence of other known persistence mechanisms (e.g., a carrier or environmental state, densely populated host, chronic infection, or a vector), we suggest that CDV requires either large spatial scales or multi-host transmission for persistence. Current GYE wolf populations are probably too small to support endemic CDV. Coyotes are a plausible reservoir host, but CDV would still require 50000-100000 individuals for moderate persistence (> 50% over 10 years), which would equate to an area of 1-3 times the size of the GYE (60000-200000 km2). Coyotes, and carnivores in general, are not uniformly distributed; therefore, this is probably a gross underestimate of the spatial scale of CDV persistence. However, the presence of a second competent host species can greatly increase the probability of long-term CDV persistence at much smaller spatial scales. Although no management of CDV is currently recommended for the GYE, wolf managers in the region should expect periodic but unpredictable CDV-related population declines as often as every 2-5 years. Awareness and monitoring of such outbreaks will allow corresponding adjustments in management activities such as regulated public harvest, creating a smooth transition to state wolf management and conservation after > 30 years of being protected by the Endangered Species Act.
Nicola1 Zaccarelli; Petrosillo; Irene; Giovanni Zurlini; KurtHans Riitters
2008-01-01
Land-use change is one of the major factors affecting global environmental change and represents a primary human effect on natural systems. Taking into account the scales and patterns of human land uses as source/sink disturbance systems, we describe a framework to characterize and interpret the spatial patterns of disturbances along a continuum of scales in a panarchy...
Teachers' Rooms Environmental Assessment Scale: Development and Psychometric Evaluation
ERIC Educational Resources Information Center
Arslan, Suna
2016-01-01
Teachers' rooms are important parts of educational environments, as the quality of the physical-spatial and psychosocial conditions may affect the personal and occupational developments of teachers as well as the education processes. In Study 1 (n = 245), a Teachers' Rooms-Environmental Assessment Scale (TREAS) measure of the current conditions of…
How Spatial Heterogeneity of Cover Affects Patterns of Shrub Encroachment into Mesic Grasslands
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
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.
Short-term rainfall: its scaling properties over Portugal
NASA Astrophysics Data System (ADS)
de Lima, M. Isabel P.
2010-05-01
The characterization of rainfall at a variety of space- and time-scales demands usually that data from different origins and resolution are explored. Different tools and methodologies can be used for this purpose. In regions where the spatial variation of rain is marked, the study of the scaling structure of rainfall can lead to a better understanding of the type of events affecting that specific area, which is essential for many engineering applications. The relevant factors affecting rain variability, in time and space, can lead to contrasting statistics which should be carefully taken into account in design procedures and decision making processes. One such region is Mainland Portugal; the territory is located in the transitional region between the sub-tropical anticyclone and the subpolar depression zones and is characterized by strong north-south and east-west rainfall gradients. The spatial distribution and seasonal variability of rain are particularly influenced by the characteristics of the global circulation. One specific feature is the Atlantic origin of many synoptic disturbances in the context of the regional geography (e.g. latitude, orography, oceanic and continental influences). Thus, aiming at investigating the statistical signature of rain events of different origins, resulting from the large number of mechanisms and factors affecting the rainfall climate over Portugal, scale-invariant analyses of the temporal structure of rain from several locations in mainland Portugal were conducted. The study used short-term rainfall time series. Relevant scaling ranges were identified and characterized that help clarifying the small-scale behaviour and statistics of this process.
Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior
Parsons, Russell A.; Linn, Rodman Ray; Pimont, Francois; ...
2017-06-18
Here, landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model,more » FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.« less
Numerical investigation of aggregated fuel spatial pattern impacts on fire behavior
DOE Office of Scientific and Technical Information (OSTI.GOV)
Parsons, Russell A.; Linn, Rodman Ray; Pimont, Francois
Here, landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model,more » FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.« less
This study is based on the assumption that land cover change and rainfall spatial variability affect the r-ainfall-runoff relationships on the watershed. Hydrologic response is an integrated indicator of watershed condition, and changes in land cover may affect the overall health...
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.
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.
NASA Astrophysics Data System (ADS)
Rouholahnejad, E.; Kirchner, J. W.
2016-12-01
Evapotranspiration (ET) is a key process in land-climate interactions and affects the dynamics of the atmosphere at local and regional scales. In estimating ET, most earth system models average over considerable sub-grid heterogeneity in land surface properties, precipitation (P), and potential evapotranspiration (PET). This spatial averaging could potentially bias ET estimates, due to the nonlinearities in the underlying relationships. In addition, most earth system models ignore lateral redistribution of water within and between grid cells, which could potentially alter both local and regional ET. Here we present a first attempt to quantify the effects of spatial heterogeneity and lateral redistribution on grid-cell-averaged ET as seen from the atmosphere over heterogeneous landscapes. Using a Budyko framework to express ET as a function of P and PET, we quantify how sub-grid heterogeneity affects average ET at the scale of typical earth system model grid cells. We show that averaging over sub-grid heterogeneity in P and PET, as typical earth system models do, leads to overestimates of average ET. We use a similar approach to quantify how lateral redistribution of water could affect average ET, as seen from the atmosphere. We show that where the aridity index P/PET increases with altitude, gravitationally driven lateral redistribution will increase average ET, implying that models that neglect lateral moisture redistribution will underestimate average ET. In contrast, where the aridity index P/PET decreases with altitude, gravitationally driven lateral redistribution will decrease average ET. This approach yields a simple conceptual framework and mathematical expressions for determining whether, and how much, spatial heterogeneity and lateral redistribution can affect regional ET fluxes as seen from the atmosphere. This analysis provides the basis for quantifying heterogeneity and redistribution effects on ET at regional and continental scales, which will be the focus of future work.
NASA Astrophysics Data System (ADS)
Siewert, Matthias; Hugelius, Gustaf
2017-04-01
Permafrost-affected soils store large amounts of soil organic carbon (SOC). Mapping of this SOC provides a first order spatial input variable for research that relates carbon stored in permafrost regions to carbon cycle dynamics. High-resolution satellite imagery is becoming increasingly available even in circum-polar regions. The presented research highlights findings of high-resolution mapping efforts of SOC from five study areas in the northern circum-polar permafrost region. These study areas are located in Siberia (Kytalyk, Spasskaya Pad /Neleger, Lena delta), Northern Sweden (Abisko) and Northwestern Canada (Herschel Island). Our high spatial resolution analyses show how geomorphology has a strong influence on the distribution of SOC. This is organized at different spatial scales. Periglacial landforms and processes dictate local scale SOC distribution due to patterned ground. Such landforms are non-sorted circles and ice-wedge polygons of different age and scale. Palsas and peat plateaus are formed and can cover larger areas in Sub-Arctic environments. Study areas that have not been affected by Pleistocene glaciation feature ice-rich Yedoma sediments that dominate the local relief through thermokarst formation and create landscape scale macro environments that dictate the distribution of SOC. A general trend indicates higher SOC storage in Arctic tundra soils compared to forested Boreal or Sub-Arctic taiga soils. Yet, due to the shallower active layer depth in the Arctic, much of the SOC may be permanently frozen and thus not be available to ecosystem processes. Significantly more SOC is stored in soils compared to vegetation, indicating that vegetation growth and incorporation of the carbon into the plant phytomass alone will not be able to offset SOC released from permafrost. This contribution also addresses advances in thematic mapping methods and digital soil mapping of SOC in permafrost terrain. In particular machine-learning methods, such as support vector machines, artificial neural networks and random forests show promising results as a toolbox for mapping permafrost-affected soils. Yet, these new methods do not decrease our dependency from soil pedon data from the field. In contrary, soil pedon data represents an urgent research priority. Statistical analyses are provided as an indication for best practice of soil pedon sampling for the quantification and the model representation of SOC stored in permafrost-affected soils.
Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil
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.
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.
Bayesian Hierarchical Modeling for Big Data Fusion in Soil Hydrology
NASA Astrophysics Data System (ADS)
Mohanty, B.; Kathuria, D.; Katzfuss, M.
2016-12-01
Soil moisture datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors on the other hand provide observations on a finer spatial scale (meter scale or less) but are sparsely available. Soil moisture is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables. Hydrologic processes usually occur at a scale of 1 km or less and therefore spatially ubiquitous and temporally periodic soil moisture products at this scale are required to aid local decision makers in agriculture, weather prediction and reservoir operations. Past literature has largely focused on downscaling RS soil moisture for a small extent of a field or a watershed and hence the applicability of such products has been limited. The present study employs a spatial Bayesian Hierarchical Model (BHM) to derive soil moisture products at a spatial scale of 1 km for the state of Oklahoma by fusing point scale Mesonet data and coarse scale RS data for soil moisture and its auxiliary covariates such as precipitation, topography, soil texture and vegetation. It is seen that the BHM model handles change of support problems easily while performing accurate uncertainty quantification arising from measurement errors and imperfect retrieval algorithms. The computational challenge arising due to the large number of measurements is tackled by utilizing basis function approaches and likelihood approximations. The BHM model can be considered as a complex Bayesian extension of traditional geostatistical prediction methods (such as Kriging) for large datasets in the presence of uncertainties.
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.
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.
NASA Astrophysics Data System (ADS)
Chen, J. M.; Chen, X.; Ju, W.
2013-03-01
Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shaanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modeled at the 1 km resolution is reduced from 14.8 g C m-2 yr-1 to 4.8 g C m-2 yr-1 in comparison with NPP modeled at 30 m resolution, where the mean NPP is 668 g C m-2 yr-1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI), elevation and aspect have small and additive effects on improving the spatial scaling between these two resolutions.
NASA Astrophysics Data System (ADS)
Chen, J. M.; Chen, X.; Ju, W.
2013-07-01
Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modelled at the 1 km resolution is reduced from 14.8 g C m-2 yr-1 to 4.8 g C m-2 yr-1 in comparison with NPP modelled at 30 m resolution, where the mean NPP is 668 g C m-2 yr-1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI) and elevation have small and additive effects on improving the spatial scaling between these two resolutions.
Muko, Soyoka; Shimatani, Ichiro K; Nozawa, Yoko
2014-07-01
Spatial distributions of individuals are conventionally analysed by representing objects as dimensionless points, in which spatial statistics are based on centre-to-centre distances. However, if organisms expand without overlapping and show size variations, such as is the case for encrusting corals, interobject spacing is crucial for spatial associations where interactions occur. We introduced new pairwise statistics using minimum distances between objects and demonstrated their utility when examining encrusting coral community data. We also calculated the conventional point process statistics and the grid-based statistics to clarify the advantages and limitations of each spatial statistical method. For simplicity, coral colonies were approximated by disks in these demonstrations. Focusing on short-distance effects, the use of minimum distances revealed that almost all coral genera were aggregated at a scale of 1-25 cm. However, when fragmented colonies (ramets) were treated as a genet, a genet-level analysis indicated weak or no aggregation, suggesting that most corals were randomly distributed and that fragmentation was the primary cause of colony aggregations. In contrast, point process statistics showed larger aggregation scales, presumably because centre-to-centre distances included both intercolony spacing and colony sizes (radius). The grid-based statistics were able to quantify the patch (aggregation) scale of colonies, but the scale was strongly affected by the colony size. Our approach quantitatively showed repulsive effects between an aggressive genus and a competitively weak genus, while the grid-based statistics (covariance function) also showed repulsion although the spatial scale indicated from the statistics was not directly interpretable in terms of ecological meaning. The use of minimum distances together with previously proposed spatial statistics helped us to extend our understanding of the spatial patterns of nonoverlapping objects that vary in size and the associated specific scales. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.
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.
Forecasting Influenza Outbreaks in Boroughs and Neighborhoods of New York City.
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.
Space and time scales of shoreline change at Cape Cod National Seashore, MA, USA
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.
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.
Cooke, Georgina M; Schlub, Timothy E; Sherwin, William B; Ord, Terry J
2016-01-01
Quantifying the spatial scale of population connectivity is important for understanding the evolutionary potential of ecologically divergent populations and for designing conservation strategies to preserve those populations. For marine organisms like fish, the spatial scale of connectivity is generally set by a pelagic larval phase. This has complicated past estimates of connectivity because detailed information on larval movements are difficult to obtain. Genetic approaches provide a tractable alternative and have the added benefit of estimating directly the reproductive isolation of populations. In this study, we leveraged empirical estimates of genetic differentiation among populations with simulations and a meta-analysis to provide a general estimate of the spatial scale of genetic connectivity in marine environments. We used neutral genetic markers to first quantify the genetic differentiation of ecologically-isolated adult populations of a land dwelling fish, the Pacific leaping blenny (Alticus arnoldorum), where marine larval dispersal is the only probable means of connectivity among populations. We then compared these estimates to simulations of a range of marine dispersal scenarios and to collated FST and distance data from the literature for marine fish across diverse spatial scales. We found genetic connectivity at sea was extensive among marine populations and in the case of A. arnoldorum, apparently little affected by the presence of ecological barriers. We estimated that ~5000 km (with broad confidence intervals ranging from 810-11,692 km) was the spatial scale at which evolutionarily meaningful barriers to gene flow start to occur at sea, although substantially shorter distances are also possible for some taxa. In general, however, such a large estimate of connectivity has important implications for the evolutionary and conservation potential of many marine fish communities.
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.
Torné-Noguera, Anna; Rodrigo, Anselm; Arnan, Xavier; Osorio, Sergio; Barril-Graells, Helena; da Rocha-Filho, Léo Correia; Bosch, Jordi
2014-01-01
Understanding biodiversity distribution is a primary goal of community ecology. At a landscape scale, bee communities are affected by habitat composition, anthropogenic land use, and fragmentation. However, little information is available on local-scale spatial distribution of bee communities within habitats that are uniform at the landscape scale. We studied a bee community along with floral and nesting resources over a 32 km2 area of uninterrupted Mediterranean scrubland. Our objectives were (i) to analyze floral and nesting resource composition at the habitat scale. We ask whether these resources follow a geographical pattern across the scrubland at bee-foraging relevant distances; (ii) to analyze the distribution of bee composition across the scrubland. Bees being highly mobile organisms, we ask whether bee composition shows a homogeneous distribution or else varies spatially. If so, we ask whether this variation is irregular or follows a geographical pattern and whether bees respond primarily to flower or to nesting resources; and (iii) to establish whether body size influences the response to local resource availability and ultimately spatial distribution. We obtained 6580 specimens belonging to 98 species. Despite bee mobility and the absence of environmental barriers, our bee community shows a clear geographical pattern. This pattern is mostly attributable to heterogeneous distribution of small (<55 mg) species (with presumed smaller foraging ranges), and is mostly explained by flower resources rather than nesting substrates. Even then, a large proportion (54.8%) of spatial variability remains unexplained by flower or nesting resources. We conclude that bee communities are strongly conditioned by local effects and may exhibit spatial heterogeneity patterns at a scale as low as 500–1000 m in patches of homogeneous habitat. These results have important implications for local pollination dynamics and spatial variation of plant-pollinator networks. PMID:24824445
Torné-Noguera, Anna; Rodrigo, Anselm; Arnan, Xavier; Osorio, Sergio; Barril-Graells, Helena; da Rocha-Filho, Léo Correia; Bosch, Jordi
2014-01-01
Understanding biodiversity distribution is a primary goal of community ecology. At a landscape scale, bee communities are affected by habitat composition, anthropogenic land use, and fragmentation. However, little information is available on local-scale spatial distribution of bee communities within habitats that are uniform at the landscape scale. We studied a bee community along with floral and nesting resources over a 32 km2 area of uninterrupted Mediterranean scrubland. Our objectives were (i) to analyze floral and nesting resource composition at the habitat scale. We ask whether these resources follow a geographical pattern across the scrubland at bee-foraging relevant distances; (ii) to analyze the distribution of bee composition across the scrubland. Bees being highly mobile organisms, we ask whether bee composition shows a homogeneous distribution or else varies spatially. If so, we ask whether this variation is irregular or follows a geographical pattern and whether bees respond primarily to flower or to nesting resources; and (iii) to establish whether body size influences the response to local resource availability and ultimately spatial distribution. We obtained 6580 specimens belonging to 98 species. Despite bee mobility and the absence of environmental barriers, our bee community shows a clear geographical pattern. This pattern is mostly attributable to heterogeneous distribution of small (<55 mg) species (with presumed smaller foraging ranges), and is mostly explained by flower resources rather than nesting substrates. Even then, a large proportion (54.8%) of spatial variability remains unexplained by flower or nesting resources. We conclude that bee communities are strongly conditioned by local effects and may exhibit spatial heterogeneity patterns at a scale as low as 500-1000 m in patches of homogeneous habitat. These results have important implications for local pollination dynamics and spatial variation of plant-pollinator networks.
Predator-guided sampling reveals biotic structure in the bathypelagic.
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).
The spatial scaling of species interaction networks.
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.
Ecotoxicology and spatial modeling in population dynamics: an illustration with brown trout.
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.
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.
2011-01-01
Background Natural communities are structured by intra-guild competition, predation or parasitism and the abiotic environment. We studied the relative importance of these factors in two host-social parasite ecosystems in three ant communities in Europe (Bavaria) and North America (New York, West Virginia). We tested how these factors affect colony demography, life-history and the spatial pattern of colonies, using a large sample size of more than 1000 colonies. The strength of competition was measured by the distance to the nearest competitor. Distance to the closest social parasite colony was used as a measure of parasitism risk. Nest sites (i.e., sticks or acorns) are limited in these forest ecosystems and we therefore included nest site quality as an abiotic factor in the analysis. In contrast to previous studies based on local densities, we focus here on the positioning and spatial patterns and we use models to compare our predictions to random expectations. Results Colony demography was universally affected by the size of the nest site with larger and more productive colonies residing in larger nest sites of higher quality. Distance to the nearest competitor negatively influenced host demography and brood production in the Bavarian community, pointing to an important role of competition, while social parasitism was less influential in this community. The New York community was characterized by the highest habitat variability, and productive colonies were clustered in sites of higher quality. Colonies were clumped on finer spatial scales, when we considered only the nearest neighbors, but more regularly distributed on coarser scales. The analysis of spatial positioning within plots often produced different results compared to those based on colony densities. For example, while host and slavemaker densities are often positively correlated, slavemakers do not nest closer to potential host colonies than expected by random. Conclusions The three communities are differently affected by biotic and abiotic factors. Some of the differences can be attributed to habitat differences and some to differences between the two slavemaking-host ecosystems. The strong effect of competition in the Bavarian community points to the scarcity of resources in this uniform habitat compared to the other more diverse sites. The decrease in colony aggregation with scale indicates fine-scale resource hotspots: colonies are locally aggregated in small groups. Our study demonstrates that species relationships vary across scales and spatial patterns can provide important insights into species interactions. These results could not have been obtained with analyses based on local densities alone. Previous studies focused on social parasitism and its effect on host colonies. The broader approach taken here, considering several possible factors affecting colony demography and not testing each one in isolation, shows that competition and environmental variability can have a similar strong impact on demography and life-history of hosts. We conclude that the effects of parasites or predators should be studied in parallel to other ecological influences. PMID:21443778
Scharf, Inon; Fischer-Blass, Birgit; Foitzik, Susanne
2011-03-28
Natural communities are structured by intra-guild competition, predation or parasitism and the abiotic environment. We studied the relative importance of these factors in two host-social parasite ecosystems in three ant communities in Europe (Bavaria) and North America (New York, West Virginia). We tested how these factors affect colony demography, life-history and the spatial pattern of colonies, using a large sample size of more than 1000 colonies. The strength of competition was measured by the distance to the nearest competitor. Distance to the closest social parasite colony was used as a measure of parasitism risk. Nest sites (i.e., sticks or acorns) are limited in these forest ecosystems and we therefore included nest site quality as an abiotic factor in the analysis. In contrast to previous studies based on local densities, we focus here on the positioning and spatial patterns and we use models to compare our predictions to random expectations. Colony demography was universally affected by the size of the nest site with larger and more productive colonies residing in larger nest sites of higher quality. Distance to the nearest competitor negatively influenced host demography and brood production in the Bavarian community, pointing to an important role of competition, while social parasitism was less influential in this community. The New York community was characterized by the highest habitat variability, and productive colonies were clustered in sites of higher quality. Colonies were clumped on finer spatial scales, when we considered only the nearest neighbors, but more regularly distributed on coarser scales. The analysis of spatial positioning within plots often produced different results compared to those based on colony densities. For example, while host and slavemaker densities are often positively correlated, slavemakers do not nest closer to potential host colonies than expected by random. The three communities are differently affected by biotic and abiotic factors. Some of the differences can be attributed to habitat differences and some to differences between the two slavemaking-host ecosystems. The strong effect of competition in the Bavarian community points to the scarcity of resources in this uniform habitat compared to the other more diverse sites. The decrease in colony aggregation with scale indicates fine-scale resource hotspots: colonies are locally aggregated in small groups. Our study demonstrates that species relationships vary across scales and spatial patterns can provide important insights into species interactions. These results could not have been obtained with analyses based on local densities alone. Previous studies focused on social parasitism and its effect on host colonies. The broader approach taken here, considering several possible factors affecting colony demography and not testing each one in isolation, shows that competition and environmental variability can have a similar strong impact on demography and life-history of hosts. We conclude that the effects of parasites or predators should be studied in parallel to other ecological influences.
Coates, Peter S.; Prochazka, Brian G.; Ricca, Mark A.; Wann, Gregory T.; Aldridge, Cameron L.; Hanser, Steven E.; Doherty, Kevin E.; O'Donnell, Michael S.; Edmunds, David R.; Espinosa, Shawn P.
2017-08-10
Population ecologists have long recognized the importance of ecological scale in understanding processes that guide observed demographic patterns for wildlife species. However, directly incorporating spatial and temporal scale into monitoring strategies that detect whether trajectories are driven by local or regional factors is challenging and rarely implemented. Identifying the appropriate scale is critical to the development of management actions that can attenuate or reverse population declines. We describe a novel example of a monitoring framework for estimating annual rates of population change for greater sage-grouse (Centrocercus urophasianus) within a hierarchical and spatially nested structure. Specifically, we conducted Bayesian analyses on a 17-year dataset (2000–2016) of lek counts in Nevada and northeastern California to estimate annual rates of population change, and compared trends across nested spatial scales. We identified leks and larger scale populations in immediate need of management, based on the occurrence of two criteria: (1) crossing of a destabilizing threshold designed to identify significant rates of population decline at a particular nested scale; and (2) crossing of decoupling thresholds designed to identify rates of population decline at smaller scales that decouple from rates of population change at a larger spatial scale. This approach establishes how declines affected by local disturbances can be separated from those operating at larger scales (for example, broad-scale wildfire and region-wide drought). Given the threshold output from our analysis, this adaptive management framework can be implemented readily and annually to facilitate responsive and effective actions for sage-grouse populations in the Great Basin. The rules of the framework can also be modified to identify populations responding positively to management action or demonstrating strong resilience to disturbance. Similar hierarchical approaches might be beneficial for other species occupying landscapes with heterogeneous disturbance and climatic regimes.
NASA Astrophysics Data System (ADS)
Nambu, Ryogen; Saito, Hajime; Tanaka, Yoshio; Higano, Junya; Kuwahara, Hisami
2012-03-01
There are many studies on spatial distributions of Asari clam Ruditapes philippinarum adults on tidal flats but few have dealt with spatial distributions of newly settled Asari clam (<0.3 mm shell length, indicative of settlement patterns) in relation to physical/topographical conditions on tidal flats. We examined small-scale spatial distributions of newly settled individuals on the Matsunase tidal flat, central Japan, during the low spring tides on two days 29th-30th June 2007, together with the shear stress from waves and currents on the flat. The characteristics of spatial distribution of newly settled Asari clam markedly varied depending on both of hydrodynamic and topographical conditions on the tidal flat. Using generalized linear models (GLMs), factors responsible for affecting newly settled Asari clam density and its spatial distribution were distinguished between sampling days, with "crest" sites always having a negative influence each on the density and the distribution on both sampling days. The continuously recorded data for the wave-current flows at the "crest" site on the tidal flat showed that newly settled Asari clam, as well as bottom sediment particles, at the "crest" site to be easily displaced. Small-scale spatial distributions of newly settled Asari clam changed with more advanced benthic stages in relation to the wave shear stress.
Using GPS TEC measurements to probe ionospheric spatial spectra at mid-latitudes
NASA Astrophysics Data System (ADS)
Lay, E. H.; Parker, P. A.; Light, M. E.; Carrano, C. S.; Debchoudhury, S.; Haaser, R. A.
2017-12-01
The physics of how random ionospheric structure causes signal degradation is well understood as weak forward scattering through an effective diffraction grating created by plasma irregularities in the ionosphere. However, the spatial scale spectrum of those irregularities required for input into scintillation models and models of traveling ionospheric disturbances is poorly characterized, particularly at the kilometer to tens of kilometer scale lengths important for very-high-frequency (VHF) scintillation prediction. Furthermore, the majority of characterization studies have been performed in low-latitude or high-latitude regions where geomagnetic activity dominates the physical processes. At mid-latitudes, tropospheric and geomagnetic phenomena compete in disturbing the ionosphere, and it is not well understood how these multiple sources affect the drivers that influence the spatial spectrum. In this study, we are interested in mid-latitude electron density irregularities on the order of 10s of kilometers that would affect VHF signals. Data from the GPS networks Japan GEONET and the Plate Boundary Observatory (PBO, UNAVCO) in the western United States were analyzed for this study. Japan GEONET is a dense network of GPS receivers (station spacing of tens of km), with fairly evenly spaced positions over all of Japan. The PBO, on the other hand, has several pockets of extremely dense coverage (station spacing within a few km), but is less dense on average. We analyze a day with a large solar storm (2015/03/17, St. Patrick's Day Storm) to allow high scintillation potential at mid-latitudes, a day with low geomagnetic activity and low thunderstorm activity (2016/01/31), and a day with low geomagnetic activity and high thunderstorm activity (2015/08/02). We then perform two-dimensional spatial analyses on the TEC data from these two networks on scale lengths of 20 to 200 km to infer the spatial scale spectra.
Knispel, Alexis L; McLachlan, Stéphane M
2010-01-01
Genetically modified herbicide-tolerant (GMHT) oilseed rape (OSR; Brassica napus L.) was approved for commercial cultivation in Canada in 1995 and currently represents over 95% of the OSR grown in western Canada. After a decade of widespread cultivation, GMHT volunteers represent an increasing management problem in cultivated fields and are ubiquitous in adjacent ruderal habitats, where they contribute to the spread of transgenes. However, few studies have considered escaped GMHT OSR populations in North America, and even fewer have been conducted at large spatial scales (i.e. landscape scales). In particular, the contribution of landscape structure and large-scale anthropogenic dispersal processes to the persistence and spread of escaped GMHT OSR remains poorly understood. We conducted a multi-year survey of the landscape-scale distribution of escaped OSR plants adjacent to roads and cultivated fields. Our objective was to examine the long-term dynamics of escaped OSR at large spatial scales and to assess the relative importance of landscape and localised factors to the persistence and spread of these plants outside of cultivation. From 2005 to 2007, we surveyed escaped OSR plants along roadsides and field edges at 12 locations in three agricultural landscapes in southern Manitoba where GMHT OSR is widely grown. Data were analysed to examine temporal changes at large spatial scales and to determine factors affecting the distribution of escaped OSR plants in roadside and field edge habitats within agricultural landscapes. Additionally, we assessed the potential for seed dispersal between escaped populations by comparing the relative spatial distribution of roadside and field edge OSR. Densities of escaped OSR fluctuated over space and time in both roadside and field edge habitats, though the proportion of GMHT plants was high (93-100%). Escaped OSR was positively affected by agricultural landscape (indicative of cropping intensity) and by the presence of an adjacent field planted to OSR. Within roadside habitats, escaped OSR was also strongly associated with large-scale variables, including road surface (indicative of traffic intensity) and distance to the nearest grain elevator. Conversely, within field edges, OSR density was affected by localised crop management practices such as mowing, soil disturbance and herbicide application. Despite the proximity of roadsides and field edges, there was little evidence of spatial aggregation among escaped OSR populations in these two habitats, especially at very fine spatial scales (i.e. <100 m), suggesting that natural propagule exchange is infrequent. Escaped OSR populations were persistent at large spatial and temporal scales, and low density in a given landscape or year was not indicative of overall extinction. As a result of ongoing cultivation and transport of OSR crops, escaped GMHT traits will likely remain predominant in agricultural landscapes. While escaped OSR in field edge habitats generally results from local seeding and management activities occurring at the field-scale, distribution patterns within roadside habitats are determined in large part by seed transport occurring at the landscape scale and at even larger regional scales. Our findings suggest that these large-scale anthropogenic dispersal processes are sufficient to enable persistence despite limited natural seed dispersal. This widespread dispersal is likely to undermine field-scale management practices aimed at eliminating escaped and in-field GMHT OSR populations. Agricultural transport and landscape-scale cropping patterns are important determinants of the distribution of escaped GM crops. At the regional level, these factors ensure ongoing establishment and spread of escaped GMHT OSR despite limited local seed dispersal. Escaped populations thus play an important role in the spread of transgenes and have substantial implications for the coexistence of GM and non-GM production systems. Given the large-scale factors driving the spread of escaped transgenes, localised co-existence measures may be impracticable where they are not commensurate with regional dispersal mechanisms. To be effective, strategies aimed at reducing contamination from GM crops should be multi-scale in approach and be developed and implemented at both farm and landscape levels of organisation. Multiple stakeholders should thus be consulted, including both GM and non-GM farmers, as well as seed developers, processors, transporters and suppliers. Decisions to adopt GM crops require thoughtful and inclusive consideration of the risks and responsibilities inherent in this new technology.
Corn rootworms (Coleoptera: Chrysomelidae) in space and time
NASA Astrophysics Data System (ADS)
Park, Yong-Lak
Spatial dispersion is a main characteristic of insect populations. Dispersion pattern provides useful information for developing effective sampling and scouting programs because it affects sampling accuracy, efficiency, and precision. Insect dispersion, however, is dynamic in space and time and largely dependent upon interactions among insect, plant and environmental factors. This study investigated the spatial and temporal dynamics of corn rootworm dispersion at different spatial scales by using the global positioning system, the geographic information system, and geostatistics. Egg dispersion pattern was random or uniform in 8-ha cornfields, but could be aggregated at a smaller scale. Larval dispersion pattern was aggregated regardless of spatial scales used in this study. Soil moisture positively affected corn rootworm egg and larval dispersions. Adult dispersion tended to be aggregated during peak population period and random or uniform early and late in the season and corn plant phenology was a major factor to determine dispersion patterns. The dispersion pattern of root injury by corn rootworm larval feeding was aggregated and the degree of aggregation increased as the root injury increased within the range of root injury observed in microscale study. Between-year relationships in dispersion among eggs, larvae, adult, and environment provided a strategy that could predict potential root damage the subsequent year. The best prediction map for the subsequent year's potential root damage was the dispersion maps of adults during population peaked in the cornfield. The prediction map was used to develop site-specific pest management that can reduce chemical input and increase control efficiency by controlling pests only where management is needed. This study demonstrated the spatio-temporal dynamics of insect population and spatial interactions among insects, plants, and environment.
Kevin M. Potter
2018-01-01
As a pervasive disturbance agent operating at many spatial and temporal scales, wildland fire is a key abiotic factor affecting forest health both positively and negatively. In some ecosystems, for example, wildland fires have been essential for regulating processes that maintain forest health (Lundquist and others 2011). Wildland fire is an important ecological...
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.
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
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.
Persistence of canine distemper virus in the Greater Yellowstone Ecosystem's carnivore community
Almberg, E.S.; Cross, P.C.; Smith, D.W.
2010-01-01
Canine distemper virus (CDV) is an acute, highly immunizing pathogen that should require high densities and large populations of hosts for long-term persistence, yet CDV persists among terrestrial carnivores with small, patchily distributed groups. We used CDV in the Greater Yellowstone ecosystem's (GYE) wolves (Canis lupus) and coyotes (Canis latrans) as a case study for exploring how metapopulation structure, host demographics, and multi-host transmission affect the critical community size and spatial scale required for CDV persistence. We illustrate how host spatial connectivity and demographic turnover interact to affect both local epidemic dynamics, such as the length and variation in inter-epidemic periods, and pathogen persistence using stochastic, spatially explicit susceptible-exposed-infectious-recovered simulation models. Given the apparent absence of other known persistence mechanisms (e.g., a carrier or environmental state, densely populated host, chronic infection, or a vector), we suggest that CDV requires either large spatial scales or multi-host transmission for persistence. Current GYE wolf populations are probably too small to support endemic CDV. Coyotes are a plausible reservoir host, but CDV would still require 50 000-100 000 individuals for moderate persistence (>50% over 10 years), which would equate to an area of 1-3 times the size of the GYE (60000-200000 km2). Coyotes, and carnivores in general, are not uniformly distributed; therefore, this is probably a gross underestimate of the spatial scale of CDV persistence. However, the presence of a second competent host species can greatly increase the probability of long-term CDV persistence at much smaller spatial scales. Although no management of CDV is currently recommended for the GYE, wolf managers in the region should expect periodic but unpredictable CDV-related population declines as often as every 2-5 years. Awareness and monitoring of such outbreaks will allow corresponding adjustments in management activities such as regulated public harvest, creating a smooth transition to state wolf management and conservation after >30 years of being protected by the Endangered Species Act. ?? 2010 by the Ecological Society of America.
Selecting for extinction: nonrandom disease-associated extinction homogenizes amphibian biotas.
Smith, Kevin G; Lips, Karen R; Chase, Jonathan M
2009-10-01
Studying the patterns in which local extinctions occur is critical to understanding how extinctions affect biodiversity at local, regional and global spatial scales. To understand the importance of patterns of extinction at a regional spatial scale, we use data from extirpations associated with a widespread pathogenic agent of amphibian decline, Batrachochytrium dendrobatidis (Bd) as a model system. We apply novel null model analyses to these data to determine whether recent extirpations associated with Bd have resulted in selective extinction and homogenization of diverse tropical American amphibian biotas. We find that Bd-associated extinctions in this region were nonrandom and disproportionately, but not exclusively, affected low-occupancy and endemic species, resulting in homogenization of the remnant amphibian fauna. The pattern of extirpations also resulted in phylogenetic homogenization at the family level and ecological homogenization of reproductive mode and habitat association. Additionally, many more species were extirpated from the region than would be expected if extirpations occurred randomly. Our results indicate that amphibian declines in this region are an extinction filter, reducing regional amphibian biodiversity to highly similar relict assemblages and ultimately causing amplified biodiversity loss at regional and global scales.
Validating spatial structure in canopy water content using geostatistics
NASA Technical Reports Server (NTRS)
Sanderson, E. W.; Zhang, M. H.; Ustin, S. L.; Rejmankova, E.; Haxo, R. S.
1995-01-01
Heterogeneity in ecological phenomena are scale dependent and affect the hierarchical structure of image data. AVIRIS pixels average reflectance produced by complex absorption and scattering interactions between biogeochemical composition, canopy architecture, view and illumination angles, species distributions, and plant cover as well as other factors. These scales affect validation of pixel reflectance, typically performed by relating pixel spectra to ground measurements acquired at scales of 1m(exp 2) or less (e.g., field spectra, foilage and soil samples, etc.). As image analysis becomes more sophisticated, such as those for detection of canopy chemistry, better validation becomes a critical problem. This paper presents a methodology for bridging between point measurements and pixels using geostatistics. Geostatistics have been extensively used in geological or hydrogeolocial studies but have received little application in ecological studies. The key criteria for kriging estimation is that the phenomena varies in space and that an underlying controlling process produces spatial correlation between the measured data points. Ecological variation meets this requirement because communities vary along environmental gradients like soil moisture, nutrient availability, or topography.
Assessing the Spatial Scale Effect of Anthropogenic Factors on Species Distribution
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
Spatial structure and scaling of macropores in hydrological process at small catchment scale
NASA Astrophysics Data System (ADS)
Silasari, Rasmiaditya; Broer, Martine; Blöschl, Günter
2013-04-01
During rainfall events, the formation of overland flow can occur under the circumstances of saturation excess and/or infiltration excess. These conditions are affected by the soil moisture state which represents the soil water content in micropores and macropores. Macropores act as pathway for the preferential flows and have been widely studied locally. However, very little is known about their spatial structure and conductivity of macropores and other flow characteristic at the catchment scale. This study will analyze these characteristics to better understand its importance in hydrological processes. The research will be conducted in Petzenkirchen Hydrological Open Air Laboratory (HOAL), a 64 ha catchment located 100 km west of Vienna. The land use is divided between arable land (87%), pasture (5%), forest (6%) and paved surfaces (2%). Video cameras will be installed on an agricultural field to monitor the overland flow pattern during rainfall events. A wireless soil moisture network is also installed within the monitored area. These field data will be combined to analyze the soil moisture state and the responding surface runoff occurrence. The variability of the macropores spatial structure of the observed area (field scale) then will be assessed based on the topography and soil data. Soil characteristics will be supported with laboratory experiments on soil matrix flow to obtain proper definitions of the spatial structure of macropores and its variability. A coupled physically based distributed model of surface and subsurface flow will be used to simulate the variability of macropores spatial structure and its effect on the flow behaviour. This model will be validated by simulating the observed rainfall events. Upscaling from field scale to catchment scale will be done to understand the effect of macropores variability on larger scales by applying spatial stochastic methods. The first phase in this study is the installation and monitoring configuration of video cameras and soil moisture monitoring equipment to obtain the initial data of overland flow occurrence and soil moisture state relationships.
Forecasting climate change impacts on plant populations over large spatial extents
Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; ...
2016-10-24
Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less
Forecasting climate change impacts on plant populations over large spatial extents
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.
Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less
Forecasting climate change impacts on plant populations over large spatial extents
Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; Homer, Collin G.; Kleinhesselink, Andrew R.; Adler, Peter B.
2016-01-01
Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.
Scales of snow depth variability in high elevation rangeland sagebrush
NASA Astrophysics Data System (ADS)
Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.
2017-09-01
In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.
NASA Astrophysics Data System (ADS)
Sakaizawa, Ryosuke; Kawai, Takaya; Sato, Toru; Oyama, Hiroyuki; Tsumune, Daisuke; Tsubono, Takaki; Goto, Koichi
2018-03-01
The target seas of tidal-current models are usually semi-closed bays, minimally affected by ocean currents. For these models, tidal currents are simulated in computational domains with a spatial scale of a couple hundred kilometers or less, by setting tidal elevations at their open boundaries. However, when ocean currents cannot be ignored in the sea areas of interest, such as in open seas near coastlines, it is necessary to include ocean-current effects in these tidal-current models. In this study, we developed a numerical method to analyze tidal currents near coasts by incorporating pre-calculated ocean-current velocities. First, a large regional-scale simulation with a spatial scale of several thousand kilometers was conducted and temporal changes in the ocean-current velocity at each grid point were stored. Next, the spatially and temporally interpolated ocean-current velocity was incorporated as forcing into the cross terms of the convection term of a tidal-current model having computational domains with spatial scales of hundreds of kilometers or less. Then, we applied this method to the diffusion of dissolved CO2 in a sea area off Tomakomai, Japan, and compared the numerical results and measurements to validate the proposed method.
Forecasting Influenza Outbreaks in Boroughs and Neighborhoods of New York City
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
Torroba-Balmori, Paloma; Budde, Katharina B; Heer, Katrin; González-Martínez, Santiago C; Olsson, Sanna; Scotti-Saintagne, Caroline; Casalis, Maxime; Sonké, Bonaventure; Dick, Christopher W; Heuertz, Myriam
2017-01-01
The analysis of fine-scale spatial genetic structure (FSGS) within populations can provide insights into eco-evolutionary processes. Restricted dispersal and locally occurring genetic drift are the primary causes for FSGS at equilibrium, as described in the isolation by distance (IBD) model. Beyond IBD expectations, spatial, environmental or historical factors can affect FSGS. We examined FSGS in seven African and Neotropical populations of the late-successional rain forest tree Symphonia globulifera L. f. (Clusiaceae) to discriminate the influence of drift-dispersal vs. landscape/ecological features and historical processes on FSGS. We used spatial principal component analysis and Bayesian clustering to assess spatial genetic heterogeneity at SSRs and examined its association with plastid DNA and habitat features. African populations (from Cameroon and São Tomé) displayed a stronger FSGS than Neotropical populations at both marker types (mean Sp = 0.025 vs. Sp = 0.008 at SSRs) and had a stronger spatial genetic heterogeneity. All three African populations occurred in pronounced altitudinal gradients, possibly restricting animal-mediated seed dispersal. Cyto-nuclear disequilibria in Cameroonian populations also suggested a legacy of biogeographic history to explain these genetic patterns. Conversely, Neotropical populations exhibited a weaker FSGS, which may reflect more efficient wide-ranging seed dispersal by Neotropical bats and other dispersers. The population from French Guiana displayed an association of plastid haplotypes with two morphotypes characterized by differential habitat preferences. Our results highlight the importance of the microenvironment for eco-evolutionary processes within persistent tropical tree populations.
Torroba-Balmori, Paloma; Budde, Katharina B.; Heer, Katrin; González-Martínez, Santiago C.; Olsson, Sanna; Scotti-Saintagne, Caroline; Sonké, Bonaventure; Dick, Christopher W.
2017-01-01
The analysis of fine-scale spatial genetic structure (FSGS) within populations can provide insights into eco-evolutionary processes. Restricted dispersal and locally occurring genetic drift are the primary causes for FSGS at equilibrium, as described in the isolation by distance (IBD) model. Beyond IBD expectations, spatial, environmental or historical factors can affect FSGS. We examined FSGS in seven African and Neotropical populations of the late-successional rain forest tree Symphonia globulifera L. f. (Clusiaceae) to discriminate the influence of drift-dispersal vs. landscape/ecological features and historical processes on FSGS. We used spatial principal component analysis and Bayesian clustering to assess spatial genetic heterogeneity at SSRs and examined its association with plastid DNA and habitat features. African populations (from Cameroon and São Tomé) displayed a stronger FSGS than Neotropical populations at both marker types (mean Sp = 0.025 vs. Sp = 0.008 at SSRs) and had a stronger spatial genetic heterogeneity. All three African populations occurred in pronounced altitudinal gradients, possibly restricting animal-mediated seed dispersal. Cyto-nuclear disequilibria in Cameroonian populations also suggested a legacy of biogeographic history to explain these genetic patterns. Conversely, Neotropical populations exhibited a weaker FSGS, which may reflect more efficient wide-ranging seed dispersal by Neotropical bats and other dispersers. The population from French Guiana displayed an association of plastid haplotypes with two morphotypes characterized by differential habitat preferences. Our results highlight the importance of the microenvironment for eco-evolutionary processes within persistent tropical tree populations. PMID:28771629
Improved Flux Formulations for Unsteady Low Mach Number Flows
2012-06-01
it requires the resolution of disparate time scales. Unsteady effects may arise from a combination of hydrodynamic effects in which pressure...including rotorcraft flows, jets and shear layers include a combination of both acoustic and hydrodynamic effects. Furthermore these effects may be...preconditioning parameter used for time scaling also affects the dissipation for the spatial flux, hydrodynamic unsteady effects (such as vortex propagation
Huang, Ni; Wang, Li; Guo, Yiqiang; Hao, Pengyu; Niu, Zheng
2014-01-01
To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m(-2) s(-1). The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China.
Huang, Ni; Wang, Li; Guo, Yiqiang; Hao, Pengyu; Niu, Zheng
2014-01-01
To examine the method for estimating the spatial patterns of soil respiration (Rs) in agricultural ecosystems using remote sensing and geographical information system (GIS), Rs rates were measured at 53 sites during the peak growing season of maize in three counties in North China. Through Pearson's correlation analysis, leaf area index (LAI), canopy chlorophyll content, aboveground biomass, soil organic carbon (SOC) content, and soil total nitrogen content were selected as the factors that affected spatial variability in Rs during the peak growing season of maize. The use of a structural equation modeling approach revealed that only LAI and SOC content directly affected Rs. Meanwhile, other factors indirectly affected Rs through LAI and SOC content. When three greenness vegetation indices were extracted from an optical image of an environmental and disaster mitigation satellite in China, enhanced vegetation index (EVI) showed the best correlation with LAI and was thus used as a proxy for LAI to estimate Rs at the regional scale. The spatial distribution of SOC content was obtained by extrapolating the SOC content at the plot scale based on the kriging interpolation method in GIS. When data were pooled for 38 plots, a first-order exponential analysis indicated that approximately 73% of the spatial variability in Rs during the peak growing season of maize can be explained by EVI and SOC content. Further test analysis based on independent data from 15 plots showed that the simple exponential model had acceptable accuracy in estimating the spatial patterns of Rs in maize fields on the basis of remotely sensed EVI and GIS-interpolated SOC content, with R2 of 0.69 and root-mean-square error of 0.51 µmol CO2 m−2 s−1. The conclusions from this study provide valuable information for estimates of Rs during the peak growing season of maize in three counties in North China. PMID:25157827
Pattern formation--A missing link in the study of ecosystem response to environmental changes.
Meron, Ehud
2016-01-01
Environmental changes can affect the functioning of an ecosystem directly, through the response of individual life forms, or indirectly, through interspecific interactions and community dynamics. The feasibility of a community-level response has motivated numerous studies aimed at understanding the mutual relationships between three elements of ecosystem dynamics: the abiotic environment, biodiversity and ecosystem function. Since ecosystems are inherently nonlinear and spatially extended, environmental changes can also induce pattern-forming instabilities that result in spatial self-organization of life forms and resources. This, in turn, can affect the relationships between these three elements, and make the response of ecosystems to environmental changes far more complex. Responses of this kind can be expected in dryland ecosystems, which show a variety of self-organizing vegetation patterns along the rainfall gradient. This paper describes the progress that has been made in understanding vegetation patterning in dryland ecosystems, and the roles it plays in ecosystem response to environmental variability. The progress has been achieved by modeling pattern-forming feedbacks at small spatial scales and up-scaling their effects to large scales through model studies. This approach sets the basis for integrating pattern formation theory into the study of ecosystem dynamics and addressing ecologically significant questions such as the dynamics of desertification, restoration of degraded landscapes, biodiversity changes along environmental gradients, and shrubland-grassland transitions. Copyright © 2015 Elsevier Inc. All rights reserved.
Development of resource shed delineation in aquatic ecosystems
Environmental issues in aquatic ecosystems of high management priority involve spatially explicit phenomena that occur over vast areas. A "landscape" perspective is thus necessary, including an understanding of how ecological phenomena at a local scale are affected by physical fo...
Tan, Xiangping; Xie, Baoni; Wang, Junxing; He, Wenxiang; Wang, Xudong; Wei, Gehong
2014-01-01
Here the spatial distribution of soil enzymatic properties in agricultural land was evaluated on a county-wide (567 km(2)) scale in Changwu, Shaanxi Province, China. The spatial variations in activities of five hydrolytic enzymes were examined using geostatistical methods. The relationships between soil enzyme activities and other soil properties were evaluated using both an integrated total enzyme activity index (TEI) and the geometric mean of enzyme activities (GME). At the county scale, soil invertase, phosphatase, and catalase activities were moderately spatially correlated, whereas urease and dehydrogenase activities were weakly spatially correlated. Correlation analysis showed that both TEI and GME were better correlated with selected soil physicochemical properties than single enzyme activities. Multivariate regression analysis showed that soil OM content had the strongest positive effect while soil pH had a negative effect on the two enzyme activity indices. In addition, total phosphorous content had a positive effect on TEI and GME in orchard soils, whereas alkali-hydrolyzable nitrogen and available potassium contents, respectively, had negative and positive effects on these two enzyme indices in cropland soils. The results indicate that land use changes strongly affect soil enzyme activities in agricultural land, where TEI provides a sensitive biological indicator for soil quality.
Over 150 years of long-term fertilization alters spatial scaling of microbial biodiversity
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
Multiscale habitat selection of wetland birds in the northern Gulf Coast
Pickens, Bradley A.; King, Sammy L.
2014-01-01
The spatial scale of habitat selection has become a prominent concept in ecology, but has received less attention in coastal ecology. In coastal marshes, broad-scale marsh types are defined by vegetation composition over thousands of hectares, water-level management is applied over hundreds of hectares, and fine-scale habitat is depicted by tens of meters. Individually, these scales are known to affect wetland fauna, but studies have not examined all three spatial scales simultaneously. We investigated wetland bird habitat selection at the three scales and compared single- and multiscale models. From 2009 to 2011, we surveyed marsh birds (i.e., Rallidae, bitterns, grebes), shorebirds, and wading birds in fresh and intermediate (oligohaline) coastal marsh in Louisiana and Texas, USA. Within each year, six repeated surveys of wintering, resident, and migratory breeding birds were conducted at > 100 points (n = 304). The results revealed fine-scale factors, primarily water depth, were consistently better predictors than marsh type or management. However, 10 of 11 species had improved models with the three scales combined. Birds with a linear association with water depth were, correspondingly, most abundant with deeper fresh marsh and permanently impounded water. Conversely, intermediate marsh had a greater abundance of shallow water species, such as king rail Rallus elegans, least bittern Ixobrychus exilis, and sora Porzana carolina. These birds had quadratic relationships with water depth or no relationship. Overall, coastal birds were influenced by multiple scales corresponding with hydrological characteristics. The effects suggest the timing of drawdowns and interannual variability in spring water levels can greatly affect wetland bird abundance.
Spatial organization of chromatin domains and compartments in single chromosomes
NASA Astrophysics Data System (ADS)
Wang, Siyuan; Su, Jun-Han; Beliveau, Brian; Bintu, Bogdan; Moffitt, Jeffrey; Wu, Chao-Ting; Zhuang, Xiaowei
The spatial organization of chromatin critically affects genome function. Recent chromosome-conformation-capture studies have revealed topologically associating domains (TADs) as a conserved feature of chromatin organization, but how TADs are spatially organized in individual chromosomes remains unknown. Here, we developed an imaging method for mapping the spatial positions of numerous genomic regions along individual chromosomes and traced the positions of TADs in human interphase autosomes and X chromosomes. We observed that chromosome folding deviates from the ideal fractal-globule model at large length scales and that TADs are largely organized into two compartments spatially arranged in a polarized manner in individual chromosomes. Active and inactive X chromosomes adopt different folding and compartmentalization configurations. These results suggest that the spatial organization of chromatin domains can change in response to regulation.
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.
GIS based procedure of cumulative environmental impact assessment.
Balakrishna Reddy, M; Blah, Baiantimon
2009-07-01
Scale and spatial limits of impact assessment study in a GIS platform are two very important factors that could have a bearing on the genuineness and quality of impact assessment. While effect of scale has been documented and well understood, no significant study has been carried out on spatial considerations in an impact assessment study employing GIS technique. A novel technique of impact assessment demonstrable through GIS approach termed hereby as 'spatial data integrated GIS impact assessment method (SGIAM)' is narrated in this paper. The technique makes a fundamental presumption that the importance of environmental impacts is dependent, among other things, on spatial distribution of the effects of the proposed action and of the affected receptors in a study area. For each environmental component considered (e.g., air quality), impact indices are calculated through aggregation of impact indicators which are measures of the severity of the impact. The presence and spread of environmental descriptors are suitably quantified through modeling techniques and depicted. The environmental impact index is calculated from data exported from ArcINFO, thus giving significant importance to spatial data in the impact assessment exercise.
Distributed Lag Models: Examining Associations between the Built Environment and Health
Baek, Jonggyu; Sánchez, Brisa N.; Berrocal, Veronica J.; Sanchez-Vaznaugh, Emma V.
2016-01-01
Built environment factors constrain individual level behaviors and choices, and thus are receiving increasing attention to assess their influence on health. Traditional regression methods have been widely used to examine associations between built environment measures and health outcomes, where a fixed, pre-specified spatial scale (e.g., 1 mile buffer) is used to construct environment measures. However, the spatial scale for these associations remains largely unknown and misspecifying it introduces bias. We propose the use of distributed lag models (DLMs) to describe the association between built environment features and health as a function of distance from the locations of interest and circumvent a-priori selection of a spatial scale. Based on simulation studies, we demonstrate that traditional regression models produce associations biased away from the null when there is spatial correlation among the built environment features. Inference based on DLMs is robust under a range of scenarios of the built environment. We use this innovative application of DLMs to examine the association between the availability of convenience stores near California public schools, which may affect children’s dietary choices both through direct access to junk food and exposure to advertisement, and children’s body mass index z-scores (BMIz). PMID:26414942
Modeling the effect of spatial policies on ecosystem services and human wellbeing
NASA Astrophysics Data System (ADS)
Geneletti, D.
2012-04-01
Land use conversions rank among the most significant drivers of change in ecosystem services worldwide, affecting human wellbeing and threatening the survival of other species. Hence, predicting the effects of land use decisions on ecosystem services has emerged as a crucial need in land management. Research addressing the link between land use changes and ecosystem services has grown significantly in the last few years, even though it has rarely addressed the tools that most countries use to regulate the development of land: spatial plans. Spatial plans aim at implementing an overall strategy through regulations ("spatial policies") concerning the physical organization of land. The paper presents a methodology aimed at empirically exploring how the implementation of different spatial policies can affect a set of ecosystem services in the future (water purification, soil conservation, habitat for species, carbon sequestration and timber production). Particularly, the study addressed the following three research questions: Q1: What are the effects of different spatial policies on the production of services through time? Q2: How changes in the production affect the actual benefits, hence human wellbeing? Q3: What are the tradeoffs between different ecosystem services and wellbeing constituents, and how are they affected by the spatial scale of analysis? The methodology is based on the generation of land use scenarios that simulate the implementation of different spatial policies through time. For each scenario, the production of key ecosystem services (e.g., water filtration, soil retention) is modeled and compared (Q1). The effects on the constituents of wellbeing (adequate livelihoods, health, etc) are then assessed by looking at spatially-resolved socioeconomic variables that estimate the appropriation of services by different groups of beneficiaries (Q2). Finally, the geographical and temporal patterns of tradeoffs are studied by disaggregating the results at different levels (from regional to sub-municipal) (Q3). The study area is represented by The Araucanía (southern Chile), a region rich in natural resources, but affected by widespread poverty. Conclusions on the potential contribution of the approach to support spatial planning processes are provided.
Editorial: Spatial arrangement of faults and opening-mode fractures
NASA Astrophysics Data System (ADS)
Laubach, Stephen E.; Lamarche, Juliette; Gauthier, Bertand D. M.; Dunne, William M.
2018-03-01
This issue of the Journal of Structural Geology titled Spatial arrangement of faults and opening-mode fractures explores a fundamental characteristic of fault and fracture arrays. The pattern of fault and opening-mode fracture positions in space defines structural heterogeneity and anisotropy in a rock volume, governs how faults and fractures affect fluid flow, and impacts our understanding of the initiation, propagation and interactions during the formation of fracture patterns. This special issue highlights recent progress with respect to characterizing and understanding the spatial arrangements of fault and fracture patterns, providing examples over a wide range of scales and structural settings.
Souza, Danielle G; Santos, Jean C; Oliveira, Marcondes A; Tabarelli, Marcelo
2016-10-01
Impacts of habitat loss and fragmentation on specialist herbivores have been rarely addressed. Here we examine the structure of plant and galling insect assemblages in a fragmented landscape of the Atlantic forest to verify a potential impoverishment of these assemblages mediated by edge effects. Saplings and galling insects were recorded once within a 0.1-ha area at habitat level, covering forest interior stands, forest edges, and small fragments. A total of 1,769 saplings from 219 tree species were recorded across all three habitats, with differences in terms of sapling abundance and species richness. Additionally, edge-affected habitats exhibited reduced richness of both host-plant and galling insects at plot and habitat spatial scale. Attack levels also differed among forest types at habitat spatial scale (21.1% of attacked stems in forest interior, 12.4% in small fragments but only 8.5% in forest edges). Plot ordination resulted in three clearly segregated clusters: one formed by forest interior, one by small fragments, and another formed by edge plots. Finally, the indicator species analysis identified seven and one indicator plant species in forest interior and edge-affected habitats, respectively. Consequently, edge effects lead to formation of distinct taxonomic groups and also an impoverished assemblage of plants and galling insects at multiple spatial scales. The results of the present study indicate that fragmentation-related changes in plant assemblages can have a cascade effects on specialist herbivores. Accordingly, hyperfragmented landscapes may not be able to retain an expressive portion of tropical biodiversity. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Klein, Brennan J; Li, Zhi; Durgin, Frank H
2016-04-01
What is the natural reference frame for seeing large-scale spatial scenes in locomotor action space? Prior studies indicate an asymmetric angular expansion in perceived direction in large-scale environments: Angular elevation relative to the horizon is perceptually exaggerated by a factor of 1.5, whereas azimuthal direction is exaggerated by a factor of about 1.25. Here participants made angular and spatial judgments when upright or on their sides to dissociate egocentric from allocentric reference frames. In Experiment 1, it was found that body orientation did not affect the magnitude of the up-down exaggeration of direction, suggesting that the relevant orientation reference frame for this directional bias is allocentric rather than egocentric. In Experiment 2, the comparison of large-scale horizontal and vertical extents was somewhat affected by viewer orientation, but only to the extent necessitated by the classic (5%) horizontal-vertical illusion (HVI) that is known to be retinotopic. Large-scale vertical extents continued to appear much larger than horizontal ground extents when observers lay sideways. When the visual world was reoriented in Experiment 3, the bias remained tied to the ground-based allocentric reference frame. The allocentric HVI is quantitatively consistent with differential angular exaggerations previously measured for elevation and azimuth in locomotor space. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Klein, Brennan J.; Li, Zhi; Durgin, Frank H.
2015-01-01
What is the natural reference frame for seeing large-scale spatial scenes in locomotor action space? Prior studies indicate an asymmetric angular expansion in perceived direction in large-scale environments: Angular elevation relative to the horizon is perceptually exaggerated by a factor of 1.5, whereas azimuthal direction is exaggerated by a factor of about 1.25. Here participants made angular and spatial judgments when upright or on their sides in order to dissociate egocentric from allocentric reference frames. In Experiment 1 it was found that body orientation did not affect the magnitude of the up-down exaggeration of direction, suggesting that the relevant orientation reference frame for this directional bias is allocentric rather than egocentric. In Experiment 2, the comparison of large-scale horizontal and vertical extents was somewhat affected by viewer orientation, but only to the extent necessitated by the classic (5%) horizontal-vertical illusion (HVI) that is known to be retinotopic. Large-scale vertical extents continued to appear much larger than horizontal ground extents when observers lay sideways. When the visual world was reoriented in Experiment 3, the bias remained tied to the ground-based allocentric reference frame. The allocentric HVI is quantitatively consistent with differential angular exaggerations previously measured for elevation and azimuth in locomotor space. PMID:26594884
Functional diversity response to hardwood forest management varies across taxa and spatial scales.
Murray, Bryan D; Holland, Jeffrey D; Summerville, Keith S; Dunning, John B; Saunders, Michael R; Jenkins, Michael A
2017-06-01
Contemporary forest management offers a trade-off between the potential positive effects of habitat heterogeneity on biodiversity, and the potential harm to mature forest communities caused by habitat loss and perforation of the forest canopy. While the response of taxonomic diversity to forest management has received a great deal of scrutiny, the response of functional diversity is largely unexplored. However, functional diversity may represent a more direct link between biodiversity and ecosystem function. To examine how forest management affects diversity at multiple spatial scales, we analyzed a long-term data set that captured changes in taxonomic and functional diversity of moths (Lepidoptera), longhorned beetles (Coleoptera: Cerambycidae), and breeding birds in response to contemporary silvicultural systems in oak-hickory hardwood forests. We used these data sets to address the following questions: how do even- and uneven-aged silvicultural systems affect taxonomic and functional diversity at the scale of managed landscapes compared to the individual harvested and unharvested forest patches that comprise the landscapes, and how do these silvicultural systems affect the functional similarity of assemblages at the scale of managed landscapes and patches? Due to increased heterogeneity within landscapes, we expected even-aged silviculture to increase and uneven-aged silviculture to decrease functional diversity at the landscape level regardless of impacts at the patch level. Functional diversity responses were taxon-specific with respect to the direction of change and time since harvest. Responses were also consistent across patch and landscape levels within each taxon. Moth assemblage species richness, functional richness, and functional divergence were negatively affected by harvesting, with stronger effects resulting from uneven-aged than even-aged management. Longhorned beetle assemblages exhibited a peak in species richness two years after harvesting, while functional diversity metrics did not differ between harvested and unharvested patches and managed landscapes. The species and functional richness of breeding bird assemblages increased in response to harvesting with more persistent effects in uneven- than in even-aged managed landscapes. For moth and bird assemblages, species turnover was driven by species with more extreme trait combinations. Our study highlights the variability of multi-taxon functional diversity in response to forest management across multiple spatial scales. © 2017 by the Ecological Society of America.
Urban watersheds are notoriously difficult to model due to their complex, small-scale combinations of landscape and land use characteristics including impervious surfaces that ultimately affect the hydrologic system. We utilized EPA’s Visualizing Ecosystem Land Management A...
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
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.
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.
Porous media flux sensitivity to pore-scale geostatistics: A bottom-up approach
NASA Astrophysics Data System (ADS)
Di Palma, P. R.; Guyennon, N.; Heße, F.; Romano, E.
2017-04-01
Macroscopic properties of flow through porous media can be directly computed by solving the Navier-Stokes equations at the scales related to the actual flow processes, while considering the porous structures in an explicit way. The aim of this paper is to investigate the effects of the pore-scale spatial distribution on seepage velocity through numerical simulations of 3D fluid flow performed by the lattice Boltzmann method. To this end, we generate multiple random Gaussian fields whose spatial correlation follows an assigned semi-variogram function. The Exponential and Gaussian semi-variograms are chosen as extreme-cases of correlation for short distances and statistical properties of the resulting porous media (indicator field) are described using the Matèrn covariance model, with characteristic lengths of spatial autocorrelation (pore size) varying from 2% to 13% of the linear domain. To consider the sensitivity of the modeling results to the geostatistical representativeness of the domain as well as to the adopted resolution, porous media have been generated repetitively with re-initialized random seeds and three different resolutions have been tested for each resulting realization. The main difference among results is observed between the two adopted semi-variograms, indicating that the roughness (short distances autocorrelation) is the property mainly affecting the flux. However, computed seepage velocities show additionally a wide variability (about three orders of magnitude) for each semi-variogram model in relation to the assigned correlation length, corresponding to pore sizes. The spatial resolution affects more the results for short correlation lengths (i.e., small pore sizes), resulting in an increasing underestimation of the seepage velocity with the decreasing correlation length. On the other hand, results show an increasing uncertainty as the correlation length approaches the domain size.
A multi-scale conceptual model of fire and disease interactions in North American forests
NASA Astrophysics Data System (ADS)
Varner, J. M.; Kreye, J. K.; Sherriff, R.; Metz, M.
2013-12-01
One aspect of global change with increasing attention is the interactions between irruptive pests and diseases and wildland fire behavior and effects. These pests and diseases affect fire behavior and effects in spatially and temporally complex ways. Models of fire and pathogen interactions have been constructed for individual pests or diseases, but to date, no synthesis of this complexity has been attempted. Here we synthesize North American fire-pathogen interactions into syndromes with similarities in spatial extent and temporal duration. We base our models on fire interactions with three examples: sudden oak death (caused by the pathogen Phytopthora ramorum) and the native tree tanoak (Notholithocarpus densiflorus); mountain pine beetle (Dendroctonus ponderosae) and western Pinus spp.; and hemlock woolly adelgid (Adelges tsugae) on Tsuga spp. We evaluate each across spatial (severity of attack from branch to landscape scale) and temporal scales (from attack to decades after) and link each change to its coincident effects on fuels and potential fire behavior. These syndromes differ in their spatial and temporal severity, differentially affecting windows of increased or decreased community flammability. We evaluate these models with two examples: the recently emergent ambrosia beetle-vectored laurel wilt (caused by the pathogen Raffaelea lauricola) in native members of the Lauraceae and the early 20th century chestnut blight (caused by the pathogen Cryphonectria parasitica) that led to the decline of American chestnut (Castanea dentata). Some changes (e.g., reduced foliar moisture content) have short-term consequences for potential fire behavior while others (functional extirpation) have more complex indirect effects on community flammability. As non-native emergent diseases and pests continue, synthetic models that aid in prediction of fire behavior and effects will enable the research and management community to prioritize mitigation efforts to realized effects.
The Effect of Furnishing on Perceived Spatial Dimensions and Spaciousness of Interior Space
von Castell, Christoph; Oberfeld, Daniel; Hecht, Heiko
2014-01-01
Despite the ubiquity of interior space design, there is virtually no scientific research on the influence of furnishing on the perception of interior space. We conducted two experiments in which observers were asked to estimate the spatial dimensions (size of the room dimensions in meters and centimeters) and to judge subjective spaciousness of various rooms. Experiment 1 used true-to-scale model rooms with a square surface area. Furnishing affected both the perceived height and the spaciousness judgments. The furnished room was perceived as higher but less spacious. In Experiment 2, rooms with different square surface areas and constant physical height were presented in virtual reality. Furnishing affected neither the perceived spatial dimensions nor the perceived spaciousness. Possible reasons for this discrepancy, such as the influence of the presentation medium, are discussed. Moreover, our results suggest a compression of perceived height and depth with decreasing surface area of the room. PMID:25409456
The effect of furnishing on perceived spatial dimensions and spaciousness of interior space.
von Castell, Christoph; Oberfeld, Daniel; Hecht, Heiko
2014-01-01
Despite the ubiquity of interior space design, there is virtually no scientific research on the influence of furnishing on the perception of interior space. We conducted two experiments in which observers were asked to estimate the spatial dimensions (size of the room dimensions in meters and centimeters) and to judge subjective spaciousness of various rooms. Experiment 1 used true-to-scale model rooms with a square surface area. Furnishing affected both the perceived height and the spaciousness judgments. The furnished room was perceived as higher but less spacious. In Experiment 2, rooms with different square surface areas and constant physical height were presented in virtual reality. Furnishing affected neither the perceived spatial dimensions nor the perceived spaciousness. Possible reasons for this discrepancy, such as the influence of the presentation medium, are discussed. Moreover, our results suggest a compression of perceived height and depth with decreasing surface area of the room.
Effects of scale and logging on landscape structure in a forest mosaic.
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.
Representative Sinusoids for Hepatic Four-Scale Pharmacokinetics Simulations
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
Monitoring survival rates of landbirds at varying spatial scales: An application of the MAPS Program
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.
NASA Technical Reports Server (NTRS)
Mcgwire, K.; Friedl, M.; Estes, J. E.
1993-01-01
This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.
NASA Astrophysics Data System (ADS)
Trujillo, E.; Giometto, M. G.; Leonard, K. C.; Maksym, T. L.; Meneveau, C. V.; Parlange, M. B.; Lehning, M.
2014-12-01
Sea ice-atmosphere interactions are major drivers of patterns of sea ice drift and deformations in the Polar regions, and affect snow erosion and deposition at the surface. Here, we combine analyses of sea ice surface topography at very high-resolutions (1-10 cm), and Large Eddy Simulations (LES) to study surface drag and snow erosion and deposition patterns from process scales to floe scales (1 cm - 100 m). The snow/ice elevations were obtained using a Terrestrial Laser Scanner during the SIPEX II (Sea Ice Physics and Ecosystem eXperiment II) research voyage to East Antarctica (September-November 2012). LES are performed on a regular domain adopting a mixed pseudo-spectral/finite difference spatial discretization. A scale-dependent dynamic subgrid-scale model based on Lagrangian time averaging is adopted to determine the eddy-viscosity in the bulk of the flow. Effects of larger-scale features of the surface on wind flows (those features that can be resolved in the LES) are accounted for through an immersed boundary method. Conversely, drag forces caused by subgrid-scale features of the surface should be accounted for through a parameterization. However, the effective aerodynamic roughness parameter z0 for snow/ice is not known. Hence, a novel dynamic approach is utilized, in which z0 is determined using the constraint that the total momentum flux (drag) must be independent on grid-filter scale. We focus on three ice floe surfaces. The first of these surfaces (October 6, 2012) is used to test the performance of the model, validate the algorithm, and study the spatial distributed fields of resolved and modeled stress components. The following two surfaces, scanned at the same location before and after a snow storm event (October 20/23, 2012), are used to propose an application to study how spatially resolved mean flow and turbulence relates to observed patterns of snow erosion and deposition. We show how erosion and deposition patterns are correlated with the computed stresses, with modeled stresses having higher explanatory power. Deposition is mainly occurring in wake regions of specific ridges that strongly affect wind flow patterns. These larger ridges also lock in place elongated streaks of relatively high speeds with axes along the stream-wise direction, and which are largely responsible for the observed erosion.
Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary
2015-01-01
Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis.
NASA Astrophysics Data System (ADS)
Govind, Ajit; Chen, Jing Ming; Margolis, Hank; Ju, Weimin; Sonnentag, Oliver; Giasson, Marc-André
2009-04-01
SummaryA spatially explicit, process-based hydro-ecological model, BEPS-TerrainLab V2.0, was developed to improve the representation of ecophysiological, hydro-ecological and biogeochemical processes of boreal ecosystems in a tightly coupled manner. Several processes unique to boreal ecosystems were implemented including the sub-surface lateral water fluxes, stratification of vegetation into distinct layers for explicit ecophysiological representation, inclusion of novel spatial upscaling strategies and biogeochemical processes. To account for preferential water fluxes common in humid boreal ecosystems, a novel scheme was introduced based on laboratory analyses. Leaf-scale ecophysiological processes were upscaled to canopy-scale by explicitly considering leaf physiological conditions as affected by light and water stress. The modified model was tested with 2 years of continuous measurements taken at the Eastern Old Black Spruce Site of the Fluxnet-Canada Research Network located in a humid boreal watershed in eastern Canada. Comparison of the simulated and measured ET, water-table depth (WTD), volumetric soil water content (VSWC) and gross primary productivity (GPP) revealed that BEPS-TerrainLab V2.0 simulates hydro-ecological processes with reasonable accuracy. The model was able to explain 83% of the ET, 92% of the GPP variability and 72% of the WTD dynamics. The model suggests that in humid ecosystems such as eastern North American boreal watersheds, topographically driven sub-surface baseflow is the main mechanism of soil water partitioning which significantly affects the local-scale hydrological conditions.
Spatial and temporal variations of evapotranspiration, groundwater and precipitation in Amazonia
NASA Astrophysics Data System (ADS)
Niu, J.; Riley, W. J.; Shen, C.; Melack, J. M.; Qiu, H.
2017-12-01
We used wavelet coherence analysis to investigate the effects of precipitation (P) and groundwater dynamics (total water storage anomaly, TWSA) on evapotranspiration (ET) at kilometer, sub-basin, and whole basin scales in the Amazon basin. The Amazon-scale averaged ET, P, and TWSA have about the same annual periodicity. The phase lag between ET and P (ΦET-P) is 1 to 3 months, and between ET and TWSA (ΦET-TWSA) is 3 to 7 months. The phase patterns have a south-north divide due to significant variation in climatic conditions. The correlation between ΦET-P and ΦET-TWSA is affected by the aridity index (the ratio between potential ET (PET) and P, PET / P), of each sub-basin, as determined using the Budyko framework at the sub-basin level. The spatial structure of ΦET-P is negatively correlated with the spatial structure of annual ET. At Amazon-scale during a drought year (e.g., 2010), both phases decreased, while in the subsequent years, ΦET-TWSA increased, indicating strong groundwater effects on ET immediately following dry years Amazon-wide.
Farm-scale variation of soil quality indices and association with edaphic properties
USDA-ARS?s Scientific Manuscript database
Soil organisms are indicators of dynamic soil quality because their community structure and population density are sensitive to management changes. However, edaphic properties can also affect soil organisms and high spatial variability can confound their utility for soil evaluation. In the present...
Using a Freshwater Lake Model Coupled with WRF for Dynamical Downscaling Applications
The ability to represent extremes in temperature and precipitation in regional climates (including those affected by inland lakes) has become an area of focus as regional climate models (RCMs) simulate smaller temporal and spatial scales. When using the Weather Research and Fore...
Isolation predicts compositional change after discrete disturbances in a global meta-study
USDA-ARS?s Scientific Manuscript database
Globally, anthropogenic disturbances are occurring at unprecedented rates and over extensive spatial and temporal scales. Human activities also affect natural disturbances, prompting shifts in their timing and intensities. Thus, there is an urgent need to understand and predict the response of ecosy...
Effects Of Spatial Variability In Marshes On Coastal Erosion Under Storm Conditions
NASA Astrophysics Data System (ADS)
Lunghino, B.; Suckale, J.; Fringer, O. B.; Maldonado, S.; Ferreira, C.; Marras, S.; Mandel, T.
2016-12-01
To quantify the contribution of marshes in protecting coastlines, engineers and planners need to evaluate how variability in marsh characteristics and storm conditions affect erosion in the inundation zone. Previous studies show that spatial patterns in marshes significantly affect flow and sediment transport under normal tidal conditions [1, 2]. This study investigates the effect of spatial variability on floodplain sediment transport under a range of extreme hydrodynamic conditions that occur during storm events. We model the hydrodynamics of storm surge conditions on an idealized coastal floodplain by solving the 2D shallow water equations. We approximate the effect of vegetation on hydrodynamics as a constant drag coefficient. The model calculates suspended sediment transport with the advection-diffusion equation and updates morphology with erosional and depositional fluxes. We conduct numerical experiments in which we vary both the scale of the storm event and the spatial patterns of vegetation and evaluate the impact on erosion and deposition on the floodplain. We find that the alongshore extent of the vegetation is the primary control on the net volume of sediment eroded. Scour occurs in narrow channels between vegetated areas, but this does not significantly alter the net volume of sediment transported. Deposition occurs in vegetated areas under the full range of flow velocities we test. These results suggest that resolving all variability in vegetation is not necessary to quantify net sediment transport volumes at the floodplain scale. Increasing the scale of the storm event does not alter the role of spatial variability. References [1] Meire, D. W., Kondziolka, J. M., and Nepf, H. M. Interaction between neighboring vegetation patches: Impact on flow and deposition. Water Resources Research 50, 5 (2014), 3809-3825. [2] Temmerman, S., Bouma, T., Govers, G., Wang, Z., De Vries, M., and Her- man, P. Impact of vegetation on flow routing and sedimentation patterns: Three-dimensional modeling for a tidal marsh. Journal of Geophysical Research: Earth Surface 110, F4 (2005).
NASA Astrophysics Data System (ADS)
Ward, John; Kaczan, David
2014-11-01
Water poverty in the Niger River Basin is a function of physical constraints affecting access and supply, and institutional arrangements affecting the ability to utilise the water resource. This distinction reflects the complexity of water poverty and points to the need to look beyond technical and financial means alone to reduce its prevalence and severity. Policy decisions affecting water resources are generally made at a state or national level. Hydrological and socio-economic evaluations at these levels, or at the basin level, cannot be presumed to be concordant with the differentiation of poverty or livelihood vulnerability at more local levels. We focus on three objectives: first, the initial mapping of observed poverty, using two health metrics and a household assets metric; second, the estimation of factors which potentially influence the observed poverty patterns; and third, a consideration of spatial non-stationarity, which identifies spatial correlates of poverty in the places where their effects appear most severe. We quantify the extent to which different levels of analysis influence these results. Comparative analysis of correlates of poverty at basin, national and local levels shows limited congruence. Variation in water quantity, and the presence of irrigation and dams had either limited or no significant correlation with observed variation in poverty measures across levels. Education and access to improved water quality were the only variables consistently significant and spatially stable across the entire basin. At all levels, education is the most consistent non-water correlate of poverty while access to protected water sources is the strongest water related correlate. The analysis indicates that landscape and scale matter for understanding water-poverty linkages and for devising policy concerned with alleviating water poverty. Interactions between environmental, social and institutional factors are complex and consequently a comprehensive understanding of poverty and its causes requires analysis at multiple spatial resolutions.
Identifying, characterizing and predicting spatial patterns of lacustrine groundwater discharge
NASA Astrophysics Data System (ADS)
Tecklenburg, Christina; Blume, Theresa
2017-10-01
Lacustrine groundwater discharge (LGD) can significantly affect lake water balances and lake water quality. However, quantifying LGD and its spatial patterns is challenging because of the large spatial extent of the aquifer-lake interface and pronounced spatial variability. This is the first experimental study to specifically study these larger-scale patterns with sufficient spatial resolution to systematically investigate how landscape and local characteristics affect the spatial variability in LGD. We measured vertical temperature profiles around a 0.49 km2 lake in northeastern Germany with a needle thermistor, which has the advantage of allowing for rapid (manual) measurements and thus, when used in a survey, high spatial coverage and resolution. Groundwater inflow rates were then estimated using the heat transport equation. These near-shore temperature profiles were complemented with sediment temperature measurements with a fibre-optic cable along six transects from shoreline to shoreline and radon measurements of lake water samples to qualitatively identify LGD patterns in the offshore part of the lake. As the hydrogeology of the catchment is sufficiently homogeneous (sandy sediments of a glacial outwash plain; no bedrock control) to avoid patterns being dominated by geological discontinuities, we were able to test the common assumptions that spatial patterns of LGD are mainly controlled by sediment characteristics and the groundwater flow field. We also tested the assumption that topographic gradients can be used as a proxy for gradients of the groundwater flow field. Thanks to the extensive data set, these tests could be carried out in a nested design, considering both small- and large-scale variability in LGD. We found that LGD was concentrated in the near-shore area, but alongshore variability was high, with specific regions of higher rates and higher spatial variability. Median inflow rates were 44 L m-2 d-1 with maximum rates in certain locations going up to 169 L m-2 d-1. Offshore LGD was negligible except for two local hotspots on steep steps in the lake bed topography. Large-scale groundwater inflow patterns were correlated with topography and the groundwater flow field, whereas small-scale patterns correlated with grain size distributions of the lake sediment. These findings confirm results and assumptions of theoretical and modelling studies more systematically than was previously possible with coarser sampling designs. However, we also found that a significant fraction of the variance in LGD could not be explained by these controls alone and that additional processes need to be considered. While regression models using these controls as explanatory variables had limited power to predict LGD rates, the results nevertheless encourage the use of topographic indices and sediment heterogeneity as an aid for targeted campaigns in future studies of groundwater discharge to lakes.
Estimating planktonic diversity through spatial dominance patterns in a model ocean.
Soccodato, Alice; d'Ovidio, Francesco; Lévy, Marina; Jahn, Oliver; Follows, Michael J; De Monte, Silvia
2016-10-01
In the open ocean, the observation and quantification of biodiversity patterns is challenging. Marine ecosystems are indeed largely composed by microbial planktonic communities whose niches are affected by highly dynamical physico-chemical conditions, and whose observation requires advanced methods for morphological and molecular classification. Optical remote sensing offers an appealing complement to these in-situ techniques. Global-scale coverage at high spatiotemporal resolution is however achieved at the cost of restrained information on the local assemblage. Here, we use a coupled physical and ecological model ocean simulation to explore one possible metrics for comparing measures performed on such different scales. We show that a large part of the local diversity of the virtual plankton ecosystem - corresponding to what accessible by genomic methods - can be inferred from crude, but spatially extended, information - as conveyed by remote sensing. Shannon diversity of the local community is indeed highly correlated to a 'seascape' index, which quantifies the surrounding spatial heterogeneity of the most abundant functional group. The error implied in drastically reducing the resolution of the plankton community is shown to be smaller in frontal regions as well as in regions of intermediate turbulent energy. On the spatial scale of hundreds of kms, patterns of virtual plankton diversity are thus largely sustained by mixing communities that occupy adjacent niches. We provide a proof of principle that in the open ocean information on spatial variability of communities can compensate for limited local knowledge, suggesting the possibility of integrating in-situ and satellite observations to monitor biodiversity distribution at the global scale. Copyright © 2016 Elsevier B.V. All rights reserved.
Dynamics of the spatial scale of visual attention revealed by brain event-related potentials
NASA Technical Reports Server (NTRS)
Luo, Y. J.; Greenwood, P. M.; Parasuraman, R.
2001-01-01
The temporal dynamics of the spatial scaling of attention during visual search were examined by recording event-related potentials (ERPs). A total of 16 young participants performed a search task in which the search array was preceded by valid cues that varied in size and hence in precision of target localization. The effects of cue size on short-latency (P1 and N1) ERP components, and the time course of these effects with variation in cue-target stimulus onset asynchrony (SOA), were examined. Reaction time (RT) to discriminate a target was prolonged as cue size increased. The amplitudes of the posterior P1 and N1 components of the ERP evoked by the search array were affected in opposite ways by the size of the precue: P1 amplitude increased whereas N1 amplitude decreased as cue size increased, particularly following the shortest SOA. The results show that when top-down information about the region to be searched is less precise (larger cues), RT is slowed and the neural generators of P1 become more active, reflecting the additional computations required in changing the spatial scale of attention to the appropriate element size to facilitate target discrimination. In contrast, the decrease in N1 amplitude with cue size may reflect a broadening of the spatial gradient of attention. The results provide electrophysiological evidence that changes in the spatial scale of attention modulate neural activity in early visual cortical areas and activate at least two temporally overlapping component processes during visual search.
NASA Astrophysics Data System (ADS)
König, Sara; Firle, Anouk-Letizia; Koehnke, Merlin; Banitz, Thomas; Frank, Karin
2017-04-01
In general ecology, there is an ongoing debate about the influence of fragmentation on extinction thresholds. Whether this influence is positive or negative depends on the considered type of fragmentation: whereas habitat fragmentation often has a negative influence on population extinction thresholds, spatially fragmented disturbances are observed to have mostly positive effects on the extinction probability. Besides preventing population extinction, in soil systems ecology we are interested in analyzing how ecosystem functions are maintained despite disturbance events. Here, we analyzed the influence of disturbance size and fragmentation on the functional resilience of a microbial soil ecosystem. As soil is a highly heterogeneous environment exposed to disturbances of different spatial configurations, the identification of critical disturbance characteristics for maintaining its functions is crucial. We used the numerical simulation model eColony considering bacterial growth, degradation and dispersal for analyzing the dynamic response of biodegradation examplary for an important microbial ecosystem service to disturbance events of different spatial configurations. We systematically varied the size and the degree of fragmentation of the affected area (disturbance pattern). We found that the influence of the disturbance size on functional recovery and biodegradation performance highly depends on the spatial fragmentation of the disturbance. Generally, biodegradation performance decreases with increasing clumpedness and increasing size of the affected area. After spatially correlated disturbance events, biodegradation performance decreases linear with increasing disturbance size. After spatially fragmented disturbance events, on the other hand, an increase in disturbance size has no influence on the biodegradation performance until a critical disturbance size is reached. Is the affected area bigger than this critical size, the functional performance decreases dramatically. Under recurrent disturbance events, this threshold is shifted to lower disturbance sizes. The more frequent disturbances are recurring, the lower is the critical disturbance size. Our simulation results indicate the importance of spatial characteristics of disturbance events for the functional resilience of microbial ecosystems. Critical values for disturbance size and fragmentation emerge from an interplay between both characteristics. In consequence, a precise definition of the specific disturbance regime is necessary for analysing functional resilience. With this study, we show that we need to consider the influence of fragmentation in terrestrial environments not only on population extincions but also on the resilience of ecosystem functions. Moreover, spatial disturbance characteristics - which are widely discussed on landscape scale - are an important factor on smaller scales, too.
Scaling identity connects human mobility and social interactions.
Deville, Pierre; Song, Chaoming; Eagle, Nathan; Blondel, Vincent D; Barabási, Albert-László; Wang, Dashun
2016-06-28
Massive datasets that capture human movements and social interactions have catalyzed rapid advances in our quantitative understanding of human behavior during the past years. One important aspect affecting both areas is the critical role space plays. Indeed, growing evidence suggests both our movements and communication patterns are associated with spatial costs that follow reproducible scaling laws, each characterized by its specific critical exponents. Although human mobility and social networks develop concomitantly as two prolific yet largely separated fields, we lack any known relationships between the critical exponents explored by them, despite the fact that they often study the same datasets. Here, by exploiting three different mobile phone datasets that capture simultaneously these two aspects, we discovered a new scaling relationship, mediated by a universal flux distribution, which links the critical exponents characterizing the spatial dependencies in human mobility and social networks. Therefore, the widely studied scaling laws uncovered in these two areas are not independent but connected through a deeper underlying reality.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Naughton, M.J.; Bourke, W.; Browning, G.L.
The convergence of spectral model numerical solutions of the global shallow-water equations is examined as a function of the time step and the spectral truncation. The contributions to the errors due to the spatial and temporal discretizations are separately identified and compared. Numerical convergence experiments are performed with the inviscid equations from smooth (Rossby-Haurwitz wave) and observed (R45 atmospheric analysis) initial conditions, and also with the diffusive shallow-water equations. Results are compared with the forced inviscid shallow-water equations case studied by Browning et al. Reduction of the time discretization error by the removal of fast waves from the solution usingmore » initialization is shown. The effects of forcing and diffusion on the convergence are discussed. Time truncation errors are found to dominate when a feature is large scale and well resolved; spatial truncation errors dominate for small-scale features and also for large scale after the small scales have affected them. Possible implications of these results for global atmospheric modeling are discussed. 31 refs., 14 figs., 4 tabs.« less
Scaling identity connects human mobility and social interactions
Deville, Pierre; Song, Chaoming; Eagle, Nathan; Blondel, Vincent D.; Barabási, Albert-László; Wang, Dashun
2016-01-01
Massive datasets that capture human movements and social interactions have catalyzed rapid advances in our quantitative understanding of human behavior during the past years. One important aspect affecting both areas is the critical role space plays. Indeed, growing evidence suggests both our movements and communication patterns are associated with spatial costs that follow reproducible scaling laws, each characterized by its specific critical exponents. Although human mobility and social networks develop concomitantly as two prolific yet largely separated fields, we lack any known relationships between the critical exponents explored by them, despite the fact that they often study the same datasets. Here, by exploiting three different mobile phone datasets that capture simultaneously these two aspects, we discovered a new scaling relationship, mediated by a universal flux distribution, which links the critical exponents characterizing the spatial dependencies in human mobility and social networks. Therefore, the widely studied scaling laws uncovered in these two areas are not independent but connected through a deeper underlying reality. PMID:27274050
REACH-SCALE GEOMORPHOLOGY AFFECTS ORGANIC MATTER AND CONSUMER Ä 13C IN A FORESTED PIEDMONT STREAM
We investigated seasonal (spring, autumn) and spatial variation of stream organic matter and consumer δ 13C in a Piedmont stream. Sites were sampled along a continuum and fit into two geomorphic categories: high-gradient, rock-bed ("rock") or low-gradient, sand-bed...
How will the changing industrial forest landscape affect forest sustainability?
Eric J. Gustafson; Craig Loehle
2008-01-01
Large-scale divestiture of commercial forestlands is occurring in the United States. Furthermore, increasing demand for cellulose for bioenergy may modify forest management practices widely enough to impact the spatial characteristics of forested landscapes. We used the HARVEST timber harvest simulator to investigate the potential consequences of divestiture and...
Burke, Ariane; Levavasseur, Guillaume; James, Patrick M A; Guiducci, Dario; Izquierdo, Manuel Arturo; Bourgeon, Lauriane; Kageyama, Masa; Ramstein, Gilles; Vrac, Mathieu
2014-08-01
The Last Glacial Maximum (LGM) was a global climate event, which had significant repercussions for the spatial distribution and demographic history of prehistoric populations. In Eurasia, the LGM coincides with a potential bottleneck for modern humans and may mark the divergence date for Asian and European populations (Keinan et al., 2007). In this research, the impact of climate variability on human populations in the Iberian Peninsula during the Last Glacial Maximum (LGM) is examined with the aid of downscaled high-resolution (16 × 16 km) numerical climate experiments. Human sensitivity to short time-scale (inter-annual) climate variability during this key time period, which follows the initial modern human colonisation of Eurasia and the extinction of the Neanderthals, is tested using the spatial distribution of archaeological sites. Results indicate that anatomically modern human populations responded to small-scale spatial patterning in climate variability, specifically inter-annual variability in precipitation levels as measured by the standard precipitation index. Climate variability at less than millennial scale, therefore, is shown to be an important component of ecological risk, one that played a role in regulating the spatial behaviour of prehistoric human populations and consequently affected their social networks. Copyright © 2014 Elsevier Ltd. All rights reserved.
Climates Past, Present, and Yet-to-Come Shape Climate Change Vulnerabilities.
Nadeau, Christopher P; Urban, Mark C; Bridle, Jon R
2017-10-01
Climate change is altering life at multiple scales, from genes to ecosystems. Predicting the vulnerability of populations to climate change is crucial to mitigate negative impacts. We suggest that regional patterns of spatial and temporal climatic variation scaled to the traits of an organism can predict where and why populations are most vulnerable to climate change. Specifically, historical climatic variation affects the sensitivity and response capacity of populations to climate change by shaping traits and the genetic variation in those traits. Present and future climatic variation can affect both climate change exposure and population responses. We provide seven predictions for how climatic variation might affect the vulnerability of populations to climate change and suggest key directions for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.
Opinion strength influences the spatial dynamics of opinion formation
Baumgaertner, Bert O.; Tyson, Rebecca T.; Krone, Stephen M.
2016-01-01
Opinions are rarely binary; they can be held with different degrees of conviction, and this expanded attitude spectrum can affect the influence one opinion has on others. Our goal is to understand how different aspects of influence lead to recognizable spatio-temporal patterns of opinions and their strengths. To do this, we introduce a stochastic spatial agent-based model of opinion dynamics that includes a spectrum of opinion strengths and various possible rules for how the opinion strength of one individual affects the influence that this individual has on others. Through simulations, we find that even a small amount of amplification of opinion strength through interaction with like-minded neighbors can tip the scales in favor of polarization and deadlock. PMID:28529381
Shorebird roost-site selection at two temporal scales: Is human disturbance a factor?
Peters, K.A.; Otis, D.L.
2007-01-01
1. Roost-site selection in shorebirds is governed by ambient factors, including environmental conditions and human disturbance. Determination of the extent to which these factors affect roost use and the associated implications for shorebird habitat protection is important for conservation strategies and informed management of human recreational use of these habitats. Shorebird conservation as a whole is a high priority world-wide because a large proportion of shorebird species is in decline. However, little is understood about the consistency of roost use by different species, what conditions affect species-specific roost-site selection, and at what spatial and temporal scales conditions influence selection. 2. We studied high-tide roost-site selection by eight species of non-breeding shorebirds on a critically important stopover and wintering refuge. We calculated spatial and temporal variability in roost use for each species based on counts and consistency of incidence. We then examined roost-site selection in relation to structural, environmental and human disturbance factors, and how this varied across spatial and temporal scales. 3. Most roosts were used less than 50% of the time, although larger roosts were used more consistently. This varied among species, with red knot Calidris canutus tending to concentrate at a few roosts and American oystercatcher Haematopus palliatus, dowitcher Limnodromus griseus and Limnodromus scolopaceus and ruddy turnstone Arenaria interpres more diffusely distributed among roosts. 4. At an annual scale, the principal factors affecting shorebird presence at roosts were roost length (size), local region, substrate and aspect. The extent and direction of these effects varied among species. Among years, red knots avoided roosts that had high average boat activity within 1000 m, but disturbance did not appear to be a factor for other species. 5. Daily roost use was influenced primarily by wind speed and the ability of roosts to provide shelter from the wind. Only dowitchers appeared to track daily disturbance, avoiding prospective roosts when boat activity within 100 m was high. 6. Synthesis and applications. Our findings emphasize the need to consider species-specific differences in temporal- and spatial-scale effects of roost-site selection factors, including human disturbance, when employing conservation measures for shorebirds. We suggest that conservation management should aim to provide a wide range of potential roosts (both natural and artificial) that could be used under different wind conditions and that are within reasonable travelling distance of preferred feeding areas. Roost use is often highly variable, and monitoring efforts must take this into account before making inferences about changes in use or selection of roost sites. ?? 2006 The Authors.
NASA Astrophysics Data System (ADS)
Betterle, A.; Schirmer, M.; Botter, G.
2017-12-01
Streamflow dynamics strongly influence anthropogenic activities and the ecological functions of riverine and riparian habitats. However, the widespread lack of direct discharge measurements often challenges the set-up of conscious and effective decision-making processes, including droughts and floods protection, water resources management and river restoration practices. By characterizing the spatial correlation of daily streamflow timeseries at two arbitrary locations, this study provides a method to evaluate how spatially variable catchment-scale hydrological process affects the resulting streamflow dynamics along and across river systems. In particular, streamflow spatial correlation is described analytically as a function of morphological, climatic and vegetation properties in the contributing catchments, building on a joint probabilistic description of flow dynamics at pairs of outlets. The approach enables an explicit linkage between similarities of flow dynamics and spatial patterns of hydrologically relevant features of climate and landscape. Therefore, the method is suited to explore spatial patterns of streamflow dynamics across geomorphoclimatic gradients. In particular, we show how the streamflow correlation can be used at the continental scale to individuate catchment pairs with similar hydrological dynamics, thereby providing a useful tool for the estimate of flow duration curves in poorly gauged areas.
Spatial variation in disease resistance: from molecules to metapopulations
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
NASA Astrophysics Data System (ADS)
Bergström, Per; Lindegarth, Susanne; Lindegarth, Mats
2013-10-01
Human pressures on coastal seas are increasing and methods for sustainable management, including spatial planning and mitigative actions, are therefore needed. In coastal areas worldwide, the development of mussel farming as an economically and ecologically sustainable industry requires geographic information on the growth and potential production capacity. In practice this means that coherent maps of temporally stable spatial patterns of growth need to be available in the planning process and that maps need to be based on mechanistic or empirical models. Therefore, as a first step towards development of models of growth, we assessed empirically the fundamental requirement that there are temporally consistent spatial patterns of growth in the blue mussel, Mytilus edulis. Using a pilot study we designed and dimensioned a transplant experiment, where the spatial consistency in the growth of mussels was evaluated at two resolutions. We found strong temporal and scale-dependent spatial variability in growth but patterns suggested that spatial patterns were uncoupled between growth of shell and that of soft tissue. Spatial patterns of shell growth were complex and largely inconsistent among years. Importantly, however, the growth of soft tissue was qualitatively consistent among years at the scale of km. The results suggest that processes affecting the whole coastal area cause substantial differences in growth of soft tissue among years but that factors varying at the scale of km create strong and persistent spatial patterns of growth, with a potential doubling of productivity by identifying the most suitable locations. We conclude that the observed spatial consistency provides a basis for further development of predictive modelling and mapping of soft tissue growth in these coastal areas. Potential causes of observed patterns, consequences for mussel-farming as a tool for mitigating eutrophication, aspects of precision of modelling and sampling of mussel growth as well as ecological functions in general are discussed.
Pangle, Luke A.; DeLong, Stephen B.; Abramson, Nate; Adams, John; Barron-Gafford, Greg A.; Breshears, David D.; Brooks, Paul D.; Chorover, Jon; Dietrich, William E.; Dontsova, Katerina; Durcik, Matej; Espeleta, Javier; Ferré, T.P.A.; Ferriere, Regis; Henderson, Whitney; Hunt, Edward A.; Huxman, Travis E.; Millar, David; Murphy, Brendan; Niu, Guo-Yue; Pavao-Zuckerman, Mitch; Pelletier, Jon D.; Rasmussen, Craig; Ruiz, Joaquin; Saleska, Scott; Schaap, Marcel; Sibayan, Michael; Troch, Peter A.; Tuller, Markus; van Haren, Joost; Zeng, Xubin
2015-01-01
Zero-order drainage basins, and their constituent hillslopes, are the fundamental geomorphic unit comprising much of Earth's uplands. The convergent topography of these landscapes generates spatially variable substrate and moisture content, facilitating biological diversity and influencing how the landscape filters precipitation and sequesters atmospheric carbon dioxide. In light of these significant ecosystem services, refining our understanding of how these functions are affected by landscape evolution, weather variability, and long-term climate change is imperative. In this paper we introduce the Landscape Evolution Observatory (LEO): a large-scale controllable infrastructure consisting of three replicated artificial landscapes (each 330 m2 surface area) within the climate-controlled Biosphere 2 facility in Arizona, USA. At LEO, experimental manipulation of rainfall, air temperature, relative humidity, and wind speed are possible at unprecedented scale. The Landscape Evolution Observatory was designed as a community resource to advance understanding of how topography, physical and chemical properties of soil, and biological communities coevolve, and how this coevolution affects water, carbon, and energy cycles at multiple spatial scales. With well-defined boundary conditions and an extensive network of sensors and samplers, LEO enables an iterative scientific approach that includes numerical model development and virtual experimentation, physical experimentation, data analysis, and model refinement. We plan to engage the broader scientific community through public dissemination of data from LEO, collaborative experimental design, and community-based model development.
Architectural Implications for Spatial Object Association Algorithms*
Kumar, Vijay S.; Kurc, Tahsin; Saltz, Joel; Abdulla, Ghaleb; Kohn, Scott R.; Matarazzo, Celeste
2013-01-01
Spatial object association, also referred to as crossmatch of spatial datasets, is the problem of identifying and comparing objects in two or more datasets based on their positions in a common spatial coordinate system. In this work, we evaluate two crossmatch algorithms that are used for astronomical sky surveys, on the following database system architecture configurations: (1) Netezza Performance Server®, a parallel database system with active disk style processing capabilities, (2) MySQL Cluster, a high-throughput network database system, and (3) a hybrid configuration consisting of a collection of independent database system instances with data replication support. Our evaluation provides insights about how architectural characteristics of these systems affect the performance of the spatial crossmatch algorithms. We conducted our study using real use-case scenarios borrowed from a large-scale astronomy application known as the Large Synoptic Survey Telescope (LSST). PMID:25692244
Howeth, Jennifer G; Leibold, Mathew A
2010-09-01
1. Recent studies indicate that large-scale spatial processes can alter local community structuring mechanisms to determine local and regional assemblages of predators and their prey. In metacommunities, this may occur when the functional diversity represented in the regional predator species pool interacts with the rate of prey dispersal among local communities to affect prey species diversity and trait composition at multiple scales. 2. Here, we test for effects of prey dispersal rate and spatially and temporally heterogeneous predation from functionally dissimilar predators on prey structure in pond mesocosm metacommunities. An experimental metacommunity consisted of three pond mesocosm communities supporting two differentially size-selective invertebrate predators and their zooplankton prey. In each metacommunity, two communities maintained constant predation and supported either Gyrinus sp. (Coleoptera) or Notonecta ungulata (Hemiptera) predators generating a spatial prey refuge while the third community supported alternating predation from Gyrinus sp. and N. ungulata generating a temporal prey refuge. Mesocosm metacommunities were connected at either low (0.7% day(-1)) or high (10% day(-1)) planktonic prey dispersal. The diversity, composition and body size of zooplankton prey were measured at local and regional (metacommunity) scales. 3. Metacommunities experiencing the low prey dispersal rate supported the greatest regional prey species diversity (H') and evenness (J'). Neither dispersal rate nor predation regime affected local prey diversity or evenness. The spatial prey refuge at low dispersal maintained the largest difference in species composition and body size diversity between communities under Gyrinus and Notonecta predation, suggesting that species sorting was operating at the low dispersal rate. There was no effect of dispersal rate on species diversity or body size distribution in the temporal prey refuge. 4. The frequency distribution, but not the range, of prey body sizes within communities depended upon prey dispersal rate and predator identity. Taken together, these results demonstrate that prey dispersal rate can moderate the strength of predation to influence prey species diversity and the local frequency distribution of prey traits in metacommunities supporting ecologically different predators.
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
NASA Astrophysics Data System (ADS)
Marra, Francesco; Morin, Efrat
2018-02-01
Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial-temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances 1.5-2.8 km and rarely exceeding 5 km, and time-correlation distances 1.8-6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques.
Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé
2016-01-01
The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes.
Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé
2016-01-01
The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes. PMID:27074044
Hill, Richard; Saetnan, Eli R; Scullion, John; Gwynn-Jones, Dylan; Ostle, Nick; Edwards, Arwyn
2016-06-01
Microbial responses to Arctic climate change could radically alter the stability of major stores of soil carbon. However, the sensitivity of plot-scale experiments simulating climate change effects on Arctic heathland soils to potential confounding effects of spatial and temporal changes in soil microbial communities is unknown. Here, the variation in heathland soil bacterial communities at two survey sites in Sweden between spring and summer 2013 and at scales between 0-1 m and, 1-100 m and between sites (> 100 m) were investigated in parallel using 16S rRNA gene T-RFLP and amplicon sequencing. T-RFLP did not reveal spatial structuring of communities at scales < 100 m in any site or season. However, temporal changes were striking. Amplicon sequencing corroborated shifts from r- to K-selected taxon-dominated communities, influencing in silico predictions of functional potential. Network analyses reveal temporal keystone taxa, with a spring betaproteobacterial sub-network centred upon a Burkholderia operational taxonomic unit (OTU) and a reconfiguration to a summer sub-network centred upon an alphaproteobacterial OTU. Although spatial structuring effects may not confound comparison between plot-scale treatments, temporal change is a significant influence. Moreover, the prominence of two temporally exclusive keystone taxa suggests that the stability of Arctic heathland soil bacterial communities could be disproportionally influenced by seasonal perturbations affecting individual taxa. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.
Scale dependent behavioral responses to human development by a large predator, the puma.
Wilmers, Christopher C; Wang, Yiwei; Nickel, Barry; Houghtaling, Paul; Shakeri, Yasaman; Allen, Maximilian L; Kermish-Wells, Joe; Yovovich, Veronica; Williams, Terrie
2013-01-01
The spatial scale at which organisms respond to human activity can affect both ecological function and conservation planning. Yet little is known regarding the spatial scale at which distinct behaviors related to reproduction and survival are impacted by human interference. Here we provide a novel approach to estimating the spatial scale at which a top predator, the puma (Puma concolor), responds to human development when it is moving, feeding, communicating, and denning. We find that reproductive behaviors (communication and denning) require at least a 4× larger buffer from human development than non-reproductive behaviors (movement and feeding). In addition, pumas give a wider berth to types of human development that provide a more consistent source of human interference (neighborhoods) than they do to those in which human presence is more intermittent (arterial roads with speeds >35 mph). Neighborhoods were a deterrent to pumas regardless of behavior, while arterial roads only deterred pumas when they were communicating and denning. Female pumas were less deterred by human development than males, but they showed larger variation in their responses overall. Our behaviorally explicit approach to modeling animal response to human activity can be used as a novel tool to assess habitat quality, identify wildlife corridors, and mitigate human-wildlife conflict.
Occurrence and persistence of magnetic elements in the quiet Sun
NASA Astrophysics Data System (ADS)
Giannattasio, F.; Berrilli, F.; Consolini, G.; Del Moro, D.; Gošić, M.; Bellot Rubio, L.
2018-03-01
Context. Turbulent convection efficiently transports energy up to the solar photosphere, but its multi-scale nature and dynamic properties are still not fully understood. Several works in the literature have investigated the emergence of patterns of convective and magnetic nature in the quiet Sun at spatial and temporal scales from granular to global. Aims: To shed light on the scales of organisation at which turbulent convection operates, and its relationship with the magnetic flux therein, we studied characteristic spatial and temporal scales of magnetic features in the quiet Sun. Methods: Thanks to an unprecedented data set entirely enclosing a supergranule, occurrence and persistence analysis of magnetogram time series were used to detect spatial and long-lived temporal correlations in the quiet Sun and to investigate their nature. Results: A relation between occurrence and persistence representative for the quiet Sun was found. In particular, highly recurrent and persistent patterns were detected especially in the boundary of the supergranular cell. These are due to moving magnetic elements undergoing motion that behaves like a random walk together with longer decorrelations ( 2 h) with respect to regions inside the supergranule. In the vertices of the supegranular cell the maximum observed occurrence is not associated with the maximum persistence, suggesting that there are different dynamic regimes affecting the magnetic elements.
Das Gupta, Sanatan; Mackenzie, M. Derek
2016-01-01
Fire in boreal ecosystems is known to affect CO2 efflux from forest soils, which is commonly termed soil respiration (Rs). However, there is limited information on how fire and recovery from this disturbance affects spatial variation in Rs. The main objective of this study was to quantify the spatial variability of Rs over the growing season in a boreal aspen (Populus tremuloides Michx.) fire chronosequence. The chronosequence included three stands in northern Alberta; a post fire stand (1 year old, PF), a stand at canopy closure (9 years old, CC), and a mature stand (72 years old, MA). Soil respiration, temperature and moisture were measured monthly from May to August using an intensive spatial sampling protocol (n = 42, minimum lag = 2 m). Key aboveground and belowground properties were measured one time at each sampling point. No spatial structure was detected in Rs of the PF stand during the peak growing season (June and July), whereas Rs was auto-correlated at a scale of < 6 m in the CC and MA stands. The PF stand had the lowest mean Rs (4.60 μmol C m-2 s-1) followed by the CC (5.41 μmol C m-2 s-1), and the MA (7.32 μmol C m-2 s-1) stand. Forest floor depth was the only aboveground factor that influenced the spatial pattern of Rs in all three stands and was strongest in the PF stand. Enzyme activity and fine root biomass, on the other hand, were the significant belowground factors driving the spatial pattern of Rs in the CC and MA stands. Persistent joint aboveground and belowground control on Rs in the CC and MA stands indicates a tight spatial coupling, which was not observed in the PF stand. Overall, the current study suggests that fire in the boreal aspen ecosystem alters the spatial structure of Rs and that fine scale heterogeneity develops quickly as stands reach the canopy closure phase (<10 years). PMID:27832089
Das Gupta, Sanatan; Mackenzie, M Derek
2016-01-01
Fire in boreal ecosystems is known to affect CO2 efflux from forest soils, which is commonly termed soil respiration (Rs). However, there is limited information on how fire and recovery from this disturbance affects spatial variation in Rs. The main objective of this study was to quantify the spatial variability of Rs over the growing season in a boreal aspen (Populus tremuloides Michx.) fire chronosequence. The chronosequence included three stands in northern Alberta; a post fire stand (1 year old, PF), a stand at canopy closure (9 years old, CC), and a mature stand (72 years old, MA). Soil respiration, temperature and moisture were measured monthly from May to August using an intensive spatial sampling protocol (n = 42, minimum lag = 2 m). Key aboveground and belowground properties were measured one time at each sampling point. No spatial structure was detected in Rs of the PF stand during the peak growing season (June and July), whereas Rs was auto-correlated at a scale of < 6 m in the CC and MA stands. The PF stand had the lowest mean Rs (4.60 μmol C m-2 s-1) followed by the CC (5.41 μmol C m-2 s-1), and the MA (7.32 μmol C m-2 s-1) stand. Forest floor depth was the only aboveground factor that influenced the spatial pattern of Rs in all three stands and was strongest in the PF stand. Enzyme activity and fine root biomass, on the other hand, were the significant belowground factors driving the spatial pattern of Rs in the CC and MA stands. Persistent joint aboveground and belowground control on Rs in the CC and MA stands indicates a tight spatial coupling, which was not observed in the PF stand. Overall, the current study suggests that fire in the boreal aspen ecosystem alters the spatial structure of Rs and that fine scale heterogeneity develops quickly as stands reach the canopy closure phase (<10 years).
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.
Multi-scale Homogenization of Caddisfly Metacomminities in Human-modified Landscapes
NASA Astrophysics Data System (ADS)
Simião-Ferreira, Juliana; Nogueira, Denis Silva; Santos, Anna Claudia; De Marco, Paulo; Angelini, Ronaldo
2018-04-01
The multiple scale of stream networks spatial organization reflects the hierarchical arrangement of streams habitats with increasingly levels of complexity from sub-catchments until entire hydrographic basins. Through these multiple spatial scales, local stream habitats form nested subsets of increasingly landscape scale and habitat size with varying contributions of both alpha and beta diversity for the regional diversity. Here, we aimed to test the relative importance of multiple nested hierarchical levels of spatial scales while determining alpha and beta diversity of caddisflies in regions with different levels of landscape degradation in a core Cerrado area in Brazil. We used quantitative environmental variables to test the hypothesis that landscape homogenization affects the contribution of alpha and beta diversity of caddisflies to regional diversity. We found that the contribution of alpha and beta diversity for gamma diversity varied according to landscape degradation. Sub-catchments with more intense agriculture had lower diversity at multiple levels, markedly alpha and beta diversities. We have also found that environmental predictors mainly associated with water quality, channel size, and habitat integrity (lower scores indicate stream degradation) were related to community dissimilarity at the catchment scale. For an effective management of the headwater biodiversity of caddisfly, towards the conservation of these catchments, heterogeneous streams with more pristine riparian vegetation found within the river basin need to be preserved in protected areas. Additionally, in the most degraded areas the restoration of riparian vegetation and size increase of protected areas will be needed to accomplish such effort.
Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary
2015-01-01
Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis. PMID:25806784
Hernández-Ceballos, M A; Skjøth, C A; García-Mozo, H; Bolívar, J P; Galán, C
2014-12-01
Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.
NASA Astrophysics Data System (ADS)
Hernández-Ceballos, M. A.; Skjøth, C. A.; García-Mozo, H.; Bolívar, J. P.; Galán, C.
2014-12-01
Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1 ° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.
The ability to understand and manage ecological changes caused by anthropogenic stressors is often impeded by a lack of sufficient information to resolve pattern and change with sufficient resolution and extent. Increasingly, different types of environmental data are available t...
USDA-ARS?s Scientific Manuscript database
The abundance and composition of arthropod communities in agricultural landscapes vary across space and time, responding to environmental features, resources and behavioral cues. As “second-generation” bioenergy feedstocks continue to develop, knowledge is needed about the broader scale ecological i...
Explaining abrupt spatial transitions in agro-ecosystem responses to periods of extended drought
USDA-ARS?s Scientific Manuscript database
During the 1930’s, the North American central grassland region (CGR) experienced an extreme multi-year drought that resulted in broad scale plant mortality, massive dust storms and losses of soil and nutrients. Southern mixed grasslands were among the worst affected and experienced severe broad scal...
Chen, Peii; Hreha, Kimberly; Kong, Yekyung; Barrett, A. M.
2015-01-01
Objective To examine the impact of spatial neglect on rehabilitation outcome, risk of falls, and discharge disposition in stroke survivors. Design Inception cohort Setting Inpatient rehabilitation facility (IRF) Participants 108 individuals with unilateral brain damage after their first stroke were assessed at the times of IRF admission and discharge. At admission, 74 of them (68.5%) demonstrated symptoms of spatial neglect, as measured with the Kessler Foundation Neglect Assessment Process (KF-NAP™). Interventions Usual and standard IRF care. Main Outcome Measures Functional Independence Measure (FIM™), Conley Scale, number of falls, length of stay (LOS), and discharge disposition. Results The greater severity of spatial neglect (higher KF-NAP scores) at IRF admission, the lower FIM scores at admission as well as at discharge. Higher KF-NAP scores also correlated with greater LOS and slower FIM improvement rate. The presence of spatial neglect (KF-NAP > 0), but not Conley Scale scores, predicted falls such that participants with spatial neglect fell 6.5 times more often than those without symptoms. More severe neglect, by KF-NAP scores at IRF admission, reduced the likelihood of returning home at discharge. A model that took spatial neglect and other demographic, socioeconomic, and clinical factors into account predicted home discharge. Rapid FIM improvement during IRF stay and lower annual income level were significant predictors of home discharge. Conclusions Spatial neglect following a stroke is a prevalent problem, and may negatively affect rehabilitation outcome, risk of falls, and length of hospital stay. PMID:25862254
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
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.
Configuration of the thermal landscape determines thermoregulatory performance of ectotherms
Sears, Michael W.; Angilletta, Michael J.; Schuler, Matthew S.; Borchert, Jason; Dilliplane, Katherine F.; Stegman, Monica; Rusch, Travis W.; Mitchell, William A.
2016-01-01
Although most organisms thermoregulate behaviorally, biologists still cannot easily predict whether mobile animals will thermoregulate in natural environments. Current models fail because they ignore how the spatial distribution of thermal resources constrains thermoregulatory performance over space and time. To overcome this limitation, we modeled the spatially explicit movements of animals constrained by access to thermal resources. Our models predict that ectotherms thermoregulate more accurately when thermal resources are dispersed throughout space than when these resources are clumped. This prediction was supported by thermoregulatory behaviors of lizards in outdoor arenas with known distributions of environmental temperatures. Further, simulations showed how the spatial structure of the landscape qualitatively affects responses of animals to climate. Biologists will need spatially explicit models to predict impacts of climate change on local scales. PMID:27601639
(In) Sensitivity to spatial distortion in natural scenes
Bex, Peter J.
2010-01-01
The perception of object structure in the natural environment is remarkably stable under large variation in image size and projection, especially given our insensitivity to spatial position outside the fovea. Sensitivity to periodic spatial distortions that were introduced into one quadrant of gray-scale natural images was measured in a 4AFC task. Observers were able to detect the presence of distortions in unfamiliar images even though they did not significantly affect the amplitude spectrum. Sensitivity depended on the spatial period of the distortion and on the image structure at the location of the distortion. The results suggest that the detection of distortion involves decisions made in the late stages of image perception and is based on an expectation of the typical structure of natural scenes. PMID:20462324
NASA Astrophysics Data System (ADS)
Huang, Yuxia; Mao, Mengchai; Zhang, Zong; Zhou, Hui; Zhao, Yang; Duan, Lian; Kreplin, Ute; Xiao, Xiang; Zhu, Chaozhe
2017-01-01
Functional near-infrared spectroscopy (fNIRS) is being increasingly applied to affective and social neuroscience research; however, the reliability of this method is still unclear. This study aimed to evaluate the test-retest reliability of the fNIRS-based prefrontal response to emotional stimuli. Twenty-six participants viewed unpleasant and neutral pictures, and were simultaneously scanned by fNIRS in two sessions three weeks apart. The reproducibility of the prefrontal activation map was evaluated at three spatial scales (mapwise, clusterwise, and channelwise) at both the group and individual levels. The influence of the time interval was also explored and comparisons were made between longer (intersession) and shorter (intrasession) time intervals. The reliabilities of the activation map at the group level for the mapwise (up to 0.88, the highest value appeared in the intersession assessment) and clusterwise scales (up to 0.91, the highest appeared in the intrasession assessment) were acceptable, indicating that fNIRS may be a reliable tool for emotion studies, especially for a group analysis and under larger spatial scales. However, it should be noted that the individual-level and the channelwise fNIRS prefrontal responses were not sufficiently stable. Future studies should investigate which factors influence reliability, as well as the validity of fNIRS used in emotion studies.
Large-Scale Circulation and Climate Variability. Chapter 5
NASA Technical Reports Server (NTRS)
Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.
2017-01-01
The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.
[Maintaining mechanism of species diversity of land plant communities].
Shang, Wenyan; Wu, Gang; Fu, Xiao; Liu, Yang
2005-03-01
The maintaining mechanism of species diversity of land plant communities is a key and advancing edge in biodiversity study. Botanists and ecologists have presented many hypotheses and theories with controversies, and no general theory system was available. In this paper, the problem was reviewed mainly on two scales. The first was big spatial scale, aiming at the physical and natural factors that affect the species diversity, including histories and ages of plant communities, gradient changes such as latitude gradient, water gradient, altitude gradient and soil nutrients gradient, area effect, and isolation; and the second was concentrated on a special plant community, and mainly discussed the relationships of biodiversity with biotic factors (primary productivity, relationship between species, and gap dynamics) and abiotic factors (succession, disturbance and spatial heterogeneity, and human activity).
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.
Lopez-Darias, Marta; Schoener, Thomas W; Spiller, David A; Losos, Jonathan B
2012-12-01
Although abiotic and biotic factors can interact to shape the spatial niche of a species, studies that explore the interactive effects of both at a local scale are rare. We demonstrate that one of the main axes (perch height) characterizing the spatial niche of a common lizard, Anolis sagrei, varies according to the interactive effects of weather and the activity of a larger predatory lizard, Leiocephalus carinatus. Results were completely consistent: no matter how favorable the weather conditions for using the ground (mainly characterized by temperature, humidity, wind speed, rain), A. sagrei did not do so if the predator was present. Hence, great behavioral plasticity enabled A. sagrei to adjust its use of space very quickly. To the best of our knowledge, these results constitute the first field demonstration for anoles (and possibly for other animals as well) of how time-varying environmental conditions and predator presence interact to produce short-term changes in utilization along a major niche axis.
Cross-modal links among vision, audition, and touch in complex environments.
Ferris, Thomas K; Sarter, Nadine B
2008-02-01
This study sought to determine whether performance effects of cross-modal spatial links that were observed in earlier laboratory studies scale to more complex environments and need to be considered in multimodal interface design. It also revisits the unresolved issue of cross-modal cuing asymmetries. Previous laboratory studies employing simple cues, tasks, and/or targets have demonstrated that the efficiency of processing visual, auditory, and tactile stimuli is affected by the modality, lateralization, and timing of surrounding cues. Very few studies have investigated these cross-modal constraints in the context of more complex environments to determine whether they scale and how complexity affects the nature of cross-modal cuing asymmetries. Amicroworld simulation of battlefield operations with a complex task set and meaningful visual, auditory, and tactile stimuli was used to investigate cuing effects for all cross-modal pairings. Significant asymmetric performance effects of cross-modal spatial links were observed. Auditory cues shortened response latencies for collocated visual targets but visual cues did not do the same for collocated auditory targets. Responses to contralateral (rather than ipsilateral) targets were faster for tactually cued auditory targets and each visual-tactile cue-target combination, suggesting an inhibition-of-return effect. The spatial relationships between multimodal cues and targets significantly affect target response times in complex environments. The performance effects of cross-modal links and the observed cross-modal cuing asymmetries need to be examined in more detail and considered in future interface design. The findings from this study have implications for the design of multimodal and adaptive interfaces and for supporting attention management in complex, data-rich domains.
NASA Astrophysics Data System (ADS)
Mayes, M. T.; Estes, L. D.; Gago, X.; Debats, S. R.; Caylor, K. K.; Manfreda, S.; Oudemans, P.; Ciraolo, G.; Maltese, A.; Nadal, M.; Estrany, J.
2016-12-01
Leaf area is an important ecosystem variable that relates to vegetation biomass, productivity, water and nutrient use in natural and agricultural systems globally. Since the 1980s, optical satellite image-based estimates of leaf area based on indices such as Normalized Difference Vegetation Index (NDVI) have greatly improved understanding of vegetation structure, function, and responses to disturbance at landscape (10^3 km2) to continental (10^6 km2) spatial scales. However, at landscape scales, satellites have failed to capture many leaf area patterns indicative of vegetation succession, crop types, stress and other conditions important for ecological processes. Small drones (UAS - unmanned aerial systems) offer new means for assessing leaf area and vegetation structure at higher spatial resolutions (<1 m) and land cover features such as substrate exposure that may affect estimates of vegetation structure in satellite data. Yet it is unclear how differences in spatial and spectral resolution between UAS and satellite data affect their relationships to each other, and to common field measurements of leaf area (e.g. LiCOR photosensors) and land cover. Constraining these relationships is important for leveraging UAS data to improve scaling of field data on leaf area and biomass to satellite data from Landsat, Sentinel-2, and increasing numbers of commercial sensors. Here, we quantify relationships among field, UAS and satellite estimates of vegetation leaf area and biomass in three case study landscapes spanning semi-arid Mediterranean (Matera, Southern Italy and Mallorca, Spain) and North American temperate ecosystems (New Jersey, USA). We assess how land cover and sensor spectral characteristics affect UAS and satellite-derived NDVI, leaf-area and biomass estimates. Then, we assess the fidelity of UAS, WorldView-2, and Landsat leaf-area and biomass estimates to field-measured landscape changes and variability, including vegetation recovery from fire (Mallorca), and leaf-area and biomass variability due to orchard type and agro-ecosystem management (Matera, New Jersey). Finally, we highlight promising ways forward for improving field data collection and the use of UAS observations to monitor vegetation leaf-area and biomass change at landscape scales in natural and agricultural systems.
NASA Astrophysics Data System (ADS)
Fan, Linfeng; Lehmann, Peter; Or, Dani
2015-04-01
Naturally-occurring spatial variations in soil properties (e.g., soil depth, moisture, and texture) affect key hydrological processes and potentially the mechanical response of soil to hydromechanical loading (relative to the commonly-assumed uniform soil mantle). We quantified the effects of soil spatial variability on the triggering of rainfall-induced shallow landslides at the hillslope- and catchment-scales, using a physically-based landslide triggering model that considers interacting soil columns with mechanical strength thresholds (represented by the Fiber Bundle Model). The spatial variations in soil properties are represented as Gaussian random distributions and the level of variation is characterized by the coefficient of variation and correlation lengths of soil properties (i.e., soil depth, soil texture and initial water content in this study). The impacts of these spatial variations on landslide triggering characteristics were measured by comparing the times to triggering and landslide volumes for heterogeneous soil properties and homogeneous cases. Results at hillslope scale indicate that for spatial variations of an individual property (without cross correlation), the increasing of coefficient of variation introduces weak spots where mechanical damage is accelerated and leads to earlier onset of landslide triggering and smaller volumes. Increasing spatial correlation length of soil texture and initial water content also induces early landslide triggering and small released volumes due to the transition of failure mode from brittle to ductile failure. In contrast, increasing spatial correlation length of soil depth "reduces" local steepness and postpones landslide triggering. Cross-correlated soil properties generally promote landslide initiation, but depending on the internal structure of spatial distribution of each soil property, landslide triggering may be reduced. The effects of cross-correlation between initial water content and soil texture were investigated in detail at the catchment scale by incorporating correlations of both variables with topography. Results indicate that the internal structure of the spatial distribution of each soil property together with their interplays determine the overall performance of the coupled spatial variability. This study emphasizes the importance of both the randomness and spatial structure of soil properties on landslide triggering and characteristics.
NASA Astrophysics Data System (ADS)
Lievana, A.; Ladah, L. B.; Lavin, M. F.; Filonov, A. E.; Tapia, F. J.; Leichter, J.; Valencia Gasti, J. A.
2016-02-01
Physical transport processes, such as nonlinear internal waves, operating within the coastal ocean of Baja California, Mexico, are diverse, variable and operate on a variety of temporal and spatial scales. Understanding the influence of nonlinear internal waves, in part responsible for the exchange of water properties between coastal and offshore environments, on the structure of intertidal communities is important for the generation of working ecological models. The relationship between the supply of ecological subsidies associated with physical transport processes that operate on relatively short spatial and temporal scales, such as the internal tide, and intertidal community structure must be understood as processes that operate on distinct spatial and temporal scales may be prone to react uniquely as the climate changes. We designed an experiment to quantify recruitment and adult survivorship of Chthamalus sp. whose settlement was associated with internal wave activity in the nearby ocean and found that the number of settlers was a robust predictor of the number of adults observed, indicating that post-settlement processes such as competition and predation are not likely to significantly affect the structure of the intertidal barnacle community resulting from internal-wave forced settlement.
Map scale effects on estimating the number of undiscovered mineral deposits
Singer, D.A.; Menzie, W.D.
2008-01-01
Estimates of numbers of undiscovered mineral deposits, fundamental to assessing mineral resources, are affected by map scale. Where consistently defined deposits of a particular type are estimated, spatial and frequency distributions of deposits are linked in that some frequency distributions can be generated by processes randomly in space whereas others are generated by processes suggesting clustering in space. Possible spatial distributions of mineral deposits and their related frequency distributions are affected by map scale and associated inclusions of non-permissive or covered geological settings. More generalized map scales are more likely to cause inclusion of geologic settings that are not really permissive for the deposit type, or that include unreported cover over permissive areas, resulting in the appearance of deposit clustering. Thus, overly generalized map scales can cause deposits to appear clustered. We propose a model that captures the effects of map scale and the related inclusion of non-permissive geologic settings on numbers of deposits estimates, the zero-inflated Poisson distribution. Effects of map scale as represented by the zero-inflated Poisson distribution suggest that the appearance of deposit clustering should diminish as mapping becomes more detailed because the number of inflated zeros would decrease with more detailed maps. Based on observed worldwide relationships between map scale and areas permissive for deposit types, mapping at a scale with twice the detail should cut permissive area size of a porphyry copper tract to 29% and a volcanic-hosted massive sulfide tract to 50% of their original sizes. Thus some direct benefits of mapping an area at a more detailed scale are indicated by significant reductions in areas permissive for deposit types, increased deposit density and, as a consequence, reduced uncertainty in the estimate of number of undiscovered deposits. Exploration enterprises benefit from reduced areas requiring detailed and expensive exploration, and land-use planners benefit from reduced areas of concern. ?? 2008 International Association for Mathematical Geology.
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
Architectural Implications for Spatial Object Association Algorithms
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kumar, V S; Kurc, T; Saltz, J
2009-01-29
Spatial object association, also referred to as cross-match of spatial datasets, is the problem of identifying and comparing objects in two or more datasets based on their positions in a common spatial coordinate system. In this work, we evaluate two crossmatch algorithms that are used for astronomical sky surveys, on the following database system architecture configurations: (1) Netezza Performance Server R, a parallel database system with active disk style processing capabilities, (2) MySQL Cluster, a high-throughput network database system, and (3) a hybrid configuration consisting of a collection of independent database system instances with data replication support. Our evaluation providesmore » insights about how architectural characteristics of these systems affect the performance of the spatial crossmatch algorithms. We conducted our study using real use-case scenarios borrowed from a large-scale astronomy application known as the Large Synoptic Survey Telescope (LSST).« less
NASA Astrophysics Data System (ADS)
Harvey, J. W.; Packman, A. I.
2010-12-01
Surface water and groundwater flow interact with the channel geomorphology and sediments in ways that determine how material is transported, stored, and transformed in stream corridors. Solute and sediment transport affect important ecological processes such as carbon and nutrient dynamics and stream metabolism, processes that are fundamental to stream health and function. Many individual mechanisms of transport and storage of solute and sediment have been studied, including surface water exchange between the main channel and side pools, hyporheic flow through shallow and deep subsurface flow paths, and sediment transport during both baseflow and floods. A significant challenge arises from non-linear and scale-dependent transport resulting from natural, fractal fluvial topography and associated broad, multi-scale hydrologic interactions. Connections between processes and linkages across scales are not well understood, imposing significant limitations on system predictability. The whole-stream tracer experimental approach is popular because of the spatial averaging of heterogeneous processes; however the tracer results, implemented alone and analyzed using typical models, cannot usually predict transport beyond the very specific conditions of the experiment. Furthermore, the results of whole stream tracer experiments tend to be biased due to unavoidable limitations associated with sampling frequency, measurement sensitivity, and experiment duration. We recommend that whole-stream tracer additions be augmented with hydraulic and topographic measurements and also with additional tracer measurements made directly in storage zones. We present examples of measurements that encompass interactions across spatial and temporal scales and models that are transferable to a wide range of flow and geomorphic conditions. These results show how the competitive effects between the different forces driving hyporheic flow, operating at different spatial scales, creates a situation where hyporheic fluxes cannot be accurately estimated without considering multi-scale effects. Our modeling captures the dominance of small-scale features such as bedforms that drive the majority of hyporheic flow, but it also captures how hyporheic flow is substantially modified by relatively small changes in streamflow or groundwater flow. The additional field measurements add sensitivity and power to whole stream tracer additions by improving resolution of the relative importance of storage at different scales (e.g. bar-scale versus bedform-scale). This information is critical in identifying hot spots where important biogeochemical reactions occur. In summary, interpreting multi-scale interactions in streams requires models that are physically based and that incorporate non-linear process dynamics. Such models can take advantage of increasingly comprehensive field data to integrate transport processes across spatially variable flow and geomorphic conditions. The most useful field and modeling approaches will be those that are simple enough to be easily implemented by users from various disciplines but comprehensive enough to produce meaningful predictions for a wide range of flow and geomorphic scenarios. This capability is needed to support improved strategies for protecting stream ecological health in the face of accelerating land use and climate change.
Bauerle, William L.; Bowden, Joseph D.
2011-01-01
A spatially explicit mechanistic model, MAESTRA, was used to separate key parameters affecting transpiration to provide insights into the most influential parameters for accurate predictions of within-crown and within-canopy transpiration. Once validated among Acer rubrum L. genotypes, model responses to different parameterization scenarios were scaled up to stand transpiration (expressed per unit leaf area) to assess how transpiration might be affected by the spatial distribution of foliage properties. For example, when physiological differences were accounted for, differences in leaf width among A. rubrum L. genotypes resulted in a 25% difference in transpiration. An in silico within-canopy sensitivity analysis was conducted over the range of genotype parameter variation observed and under different climate forcing conditions. The analysis revealed that seven of 16 leaf traits had a ≥5% impact on transpiration predictions. Under sparse foliage conditions, comparisons of the present findings with previous studies were in agreement that parameters such as the maximum Rubisco-limited rate of photosynthesis can explain ∼20% of the variability in predicted transpiration. However, the spatial analysis shows how such parameters can decrease or change in importance below the uppermost canopy layer. Alternatively, model sensitivity to leaf width and minimum stomatal conductance was continuous along a vertical canopy depth profile. Foremost, transpiration sensitivity to an observed range of morphological and physiological parameters is examined and the spatial sensitivity of transpiration model predictions to vertical variations in microclimate and foliage density is identified to reduce the uncertainty of current transpiration predictions. PMID:21617246
Field Scale Spatial Modelling of Surface Soil Quality Attributes in Controlled Traffic Farming
NASA Astrophysics Data System (ADS)
Guenette, Kris; Hernandez-Ramirez, Guillermo
2017-04-01
The employment of controlled traffic farming (CTF) can yield improvements to soil quality attributes through the confinement of equipment traffic to tramlines with the field. There is a need to quantify and explain the spatial heterogeneity of soil quality attributes affected by CTF to further improve our understanding and modelling ability of field scale soil dynamics. Soil properties such as available nitrogen (AN), pH, soil total nitrogen (STN), soil organic carbon (SOC), bulk density, macroporosity, soil quality S-Index, plant available water capacity (PAWC) and unsaturated hydraulic conductivity (Km) were analysed and compared among trafficked and un-trafficked areas. We contrasted standard geostatistical methods such as ordinary kriging (OK) and covariate kriging (COK) as well as the hybrid method of regression kriging (ROK) to predict the spatial distribution of soil properties across two annual cropland sites actively employing CTF in Alberta, Canada. Field scale variability was quantified more accurately through the inclusion of covariates; however, the use of ROK was shown to improve model accuracy despite the regression model composition limiting the robustness of the ROK method. The exclusion of traffic from the un-trafficked areas displayed significant improvements to bulk density, macroporosity and Km while subsequently enhancing AN, STN and SOC. The ability of the regression models and the ROK method to account for spatial trends led to the highest goodness-of-fit and lowest error achieved for the soil physical properties, as the rigid traffic regime of CTF altered their spatial distribution at the field scale. Conversely, the COK method produced the most optimal predictions for the soil nutrient properties and Km. The use of terrain covariates derived from light ranging and detection (LiDAR), such as of elevation and topographic position index (TPI), yielded the best models in the COK method at the field scale.
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.
Flux measurements in the surface Marine Atmospheric Boundary Layer over the Aegean Sea, Greece.
Kostopoulos, V E; Helmis, C G
2014-10-01
Micro-meteorological measurements within the surface Marine Atmospheric Boundary Layer took place at the shoreline of two islands at northern and south-eastern Aegean Sea of Greece. The primary goal of these experimental campaigns was to study the momentum, heat and humidity fluxes over this part of the north-eastern Mediterranean Sea, characterized by limited spatial and temporal scales which could affect these exchanges at the air-sea interface. The great majority of the obtained records from both sites gave higher values up to factor of two, compared with the estimations from the most widely used parametric formulas that came mostly from measurements over open seas and oceans. Friction velocity values from both campaigns varied within the same range and presented strong correlation with the wind speed at 10 m height while the calculated drag coefficient values at the same height for both sites were found to be constant in relation with the wind speed. Using eddy correlation analysis, the heat flux values were calculated (virtual heat fluxes varied from -60 to 40 W/m(2)) and it was found that they are affected by the limited spatial and temporal scales of the responding air-sea interaction mechanism. Similarly, the humidity fluxes appeared to be strongly influenced by the observed intense spatial heterogeneity of the sea surface temperature. Copyright © 2014 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Ye, Ran; Cai, Yanhong; Wei, Yongjie; Li, Xiaoming
2017-04-01
The spatial pattern of phytoplankton community can indicate potential environmental variation in different water bodies. In this context, spatial pattern of phytoplankton community and its response to environmental and spatial factors were studied in the coastal waters of northern Zhejiang, East China Sea using multivariate statistical techniques. Results showed that 94 species belonging to 40 genera, 5 phyla were recorded (the remaining 9 were identified to genus level) with diatoms being the most dominant followed by dinoflagellates. Hierarchical clustering analysis (HCA), nonmetric multidimentional scaling (NMDS), and analysis of similarity (ANOSIM) all demomstrated that the whole study area could be divided into 3 subareas with significant differences. Indicator species analysis (ISA) further confirmed that the indicator species of each subarea correlated significantly with specific environmental factors. Distance-based linear model (Distlm) and Mantel test revealed that silicate (SiO32-), phosphate (PO43-), pH, and dissolved oxygen (DO) were the most important environmental factors influencing phytoplankton community. Variation portioning (VP) finally concluded that the shared fractions of environmental and spatial factors were higher than either the pure environmental effects or the pure spatial effects, suggesting phytoplankton biogeography were mainly affected by both the environmental variability and dispersal limitation. Additionally, other factors (eg., trace metals, biological grazing, climate change, and time-scale variation) may also be the sources of the unexplained variation which need further study.
Recent variations in seasonality of temperature and precipitation in Canada, 1976-95
NASA Astrophysics Data System (ADS)
Whitfield, Paul H.; Bodtker, Karin; Cannon, Alex J.
2002-11-01
A previously reported analysis of rehabilitated monthly temperature and precipitation time series for several hundred stations across Canada showed generally spatially coherent patterns of variation between two decades (1976-85 and 1986-95). The present work expands that analysis to finer time scales and a greater number of stations. We demonstrate how the finer temporal resolution, at 5 day or 11 day intervals, increases the separation between clusters of recent variations in seasonal patterns of temperature and precipitation. We also expand the analysis by increasing the number of stations from only rehabilitated monthly data sets to rehabilitated daily sets, then to approximately 1500 daily observation stations. This increases the spatial density of data and allows a finer spatial resolution of patterns between the two decades. We also examine the success of clustering partial records, i.e. sites where the data record is incomplete. The intent of this study was to be consistent with previous work and explore how greater temporal and spatial detail in the climate data affects the resolution of patterns of recent climate variations. The variations we report for temperature and precipitation are taking place at different temporal and spatial scales. Further, the spatial patterns are much broader than local climate regions and ecozones, indicating that the differences observed may be the result of variations in atmospheric circulation.
Diversity in spatial scope of contrast adaptation among mouse retinal ganglion cells.
Khani, Mohammad Hossein; Gollisch, Tim
2017-12-01
Retinal ganglion cells adapt to changes in visual contrast by adjusting their response kinetics and sensitivity. While much work has focused on the time scales of these adaptation processes, less is known about the spatial scale of contrast adaptation. For example, do small, localized contrast changes affect a cell's signal processing across its entire receptive field? Previous investigations have provided conflicting evidence, suggesting that contrast adaptation occurs either locally within subregions of a ganglion cell's receptive field or globally over the receptive field in its entirety. Here, we investigated the spatial extent of contrast adaptation in ganglion cells of the isolated mouse retina through multielectrode-array recordings. We applied visual stimuli so that ganglion cell receptive fields contained regions where the average contrast level changed periodically as well as regions with constant average contrast level. This allowed us to analyze temporal stimulus integration and sensitivity separately for stimulus regions with and without contrast changes. We found that the spatial scope of contrast adaptation depends strongly on cell identity, with some ganglion cells displaying clear local adaptation, whereas others, in particular large transient ganglion cells, adapted globally to contrast changes. Thus, the spatial scope of contrast adaptation in mouse retinal ganglion cells appears to be cell-type specific. This could reflect differences in mechanisms of contrast adaptation and may contribute to the functional diversity of different ganglion cell types. NEW & NOTEWORTHY Understanding whether adaptation of a neuron in a sensory system can occur locally inside the receptive field or whether it always globally affects the entire receptive field is important for understanding how the neuron processes complex sensory stimuli. For mouse retinal ganglion cells, we here show that both local and global contrast adaptation exist and that this diversity in spatial scope can contribute to the functional diversity of retinal ganglion cell types. Copyright © 2017 the American Physiological Society.
Diversity in spatial scope of contrast adaptation among mouse retinal ganglion cells
Khani, Mohammad Hossein
2017-01-01
Retinal ganglion cells adapt to changes in visual contrast by adjusting their response kinetics and sensitivity. While much work has focused on the time scales of these adaptation processes, less is known about the spatial scale of contrast adaptation. For example, do small, localized contrast changes affect a cell’s signal processing across its entire receptive field? Previous investigations have provided conflicting evidence, suggesting that contrast adaptation occurs either locally within subregions of a ganglion cell’s receptive field or globally over the receptive field in its entirety. Here, we investigated the spatial extent of contrast adaptation in ganglion cells of the isolated mouse retina through multielectrode-array recordings. We applied visual stimuli so that ganglion cell receptive fields contained regions where the average contrast level changed periodically as well as regions with constant average contrast level. This allowed us to analyze temporal stimulus integration and sensitivity separately for stimulus regions with and without contrast changes. We found that the spatial scope of contrast adaptation depends strongly on cell identity, with some ganglion cells displaying clear local adaptation, whereas others, in particular large transient ganglion cells, adapted globally to contrast changes. Thus, the spatial scope of contrast adaptation in mouse retinal ganglion cells appears to be cell-type specific. This could reflect differences in mechanisms of contrast adaptation and may contribute to the functional diversity of different ganglion cell types. NEW & NOTEWORTHY Understanding whether adaptation of a neuron in a sensory system can occur locally inside the receptive field or whether it always globally affects the entire receptive field is important for understanding how the neuron processes complex sensory stimuli. For mouse retinal ganglion cells, we here show that both local and global contrast adaptation exist and that this diversity in spatial scope can contribute to the functional diversity of retinal ganglion cell types. PMID:28904106
[Response of fine roots to soil nutrient spatial heterogeneity].
Wang, Qingcheng; Cheng, Yunhuan
2004-06-01
The spatial heterogeneity is the complexity and variation of systems or their attributes, and the heterogeneity of soil nutrients is ubiquitous in all natural ecosystems. The scale of spatial heterogeneity varies considerably among different ecosystems, from tens of centimeters to hundred meters. Some of the scales can be detected by individual plant. Because the growth of individual plants can be strongly influenced by soil heterogeneity, it follows that the inter-specific competition should also be affected. During the long process of evolution, plants developed various plastic responses with their root system, including morphological, physiological and mycorrhizal plasticity, to maximize the nutrient acquisition from heterogeneous soil resources. Morphological plasticity, an adjustment in root system spatial allocation and architecture in response to spatial heterogeneous distribution of available soil resources, has been most intensively studied, and root proliferation in nutrient rich patches has been certified for many species. The species that do respond may have an increased rate of nutrient uptake, leading to a competitive advantage. Scale and precision are two important features employed in describing the size and foraging behavior of root system. It was hypothesized that scale and precision is negatively related, i. e., the species with high scale of root system tend to be a less precise forager. The outcomes of different research work have been diverse, far from reaching a consensus. Species with high scale are not necessarily less precise in fine root allocation, and vice versa. The proliferation of fine root in enriched micro-sites is species dependent, and also affected by other factors, such as patch attributes (size and nutrients concentration), nutrients, and overall soil fertility. Beside root proliferation in nutrient enriched patches, plants can also adapt themselves to the heterogeneous soil environment by altering other root characteristics such as fine root diameter, branch angle, length, and spatial architecture of root system. Physiological and mycorrhizal plasticity can add some influence on the morphological plasticity to some extent, but they are less studied. Roots located in different patches can quickly regulate their nutrient uptake kinetics within different nutrient patches, and increase overall nutrient uptake. Physiological response may, to certain extent, reduce morphological response, and is meaningful for plant growth on soils with frequently changing spatial and temporal heterogeneity. Mycorrhizal plasticity has been least studied so far. Some researches revealed that mycorrhiza, rather than fine root, proliferated in enriched patches. But, it is not the case with other studies. The proliferation of mycorrhiza within enriched patches is more profitable in term of carbon invest. The effect of fine root proliferation on nutrient uptake is complex, depending on ion mobility and whether or not neighboring plant exists. The influence of root plasticity on the growth of plants is species specific. Some species (sensitive species) gain growth benefit, while others don't. The ability of an individual plant to response to heterogeneous resources has significant effect on its competitive ability and its fate within the community, and eventually shapes the composition and structure of the community.
A nested observation and model approach to non linear groundwater surface water interactions.
NASA Astrophysics Data System (ADS)
van der Velde, Y.; Rozemeijer, J. C.; de Rooij, G. H.
2009-04-01
Surface water quality measurements in The Netherlands are scattered in time and space. Therefore, water quality status and its variations and trends are difficult to determine. In order to reach the water quality goals according to the European Water Framework Directive, we need to improve our understanding of the dynamics of surface water quality and the processes that affect it. In heavily drained lowland catchment groundwater influences the discharge towards the surface water network in many complex ways. Especially a strong seasonal contracting and expanding system of discharging ditches and streams affects discharge and solute transport. At a tube drained field site the tube drain flux and the combined flux of all other flow routes toward a stretch of 45 m of surface water have been measured for a year. Also the groundwater levels at various locations in the field and the discharge at two nested catchment scales have been monitored. The unique reaction of individual flow routes on rainfall events at the field site allowed us to separate the discharge at a 4 ha catchment and at a 6 km2 into flow route contributions. The results of this nested experimental setup combined with the results of a distributed hydrological model has lead to the formulation of a process model approach that focuses on the spatial variability of discharge generation driven by temporal and spatial variations in groundwater levels. The main idea of this approach is that discharge is not generated by catchment average storages or groundwater heads, but is mainly generated by points scale extremes i.e. extreme low permeability, extreme high groundwater heads or extreme low surface elevations, all leading to catchment discharge. We focused on describing the spatial extremes in point scale storages and this led to a simple and measurable expression that governs the non-linear groundwater surface water interaction. We will present the analysis of the field site data to demonstrate the potential of nested-scale, high frequency observations. The distributed hydrological model results will be used to show transient catchment scale relations between groundwater levels and discharges. These analyses lead to a simple expression that can describe catchment scale groundwater surface water interactions.
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
Wen, Lu; Dong, Shi Kui; Li, Yuan Yuan; Sherman, Ruth; Shi, Jian Jun; Liu, De Mei; Wang, Yan Long; Ma, Yu Shou; Zhu, Lei
2013-10-01
Understanding the complex effects of biotic and abiotic factors on the composition of vegetation is very important for developing and implementing strategies for promoting sustainable grassland development. The vegetation-disturbance-environment relationship was examined in degraded alpine grasslands in the headwater areas of three rivers on the Qinghai-Tibet Plateau in this study. The investigated hypotheses were that (1) the heterogeneity of the vegetation of the alpine grassland is due to a combination of biotic and abiotic factors and that (2) at a small scale, biotic factors are more important for the distribution of alpine vegetation. On this basis, four transects were set along altitudinal gradients from 3,770 to 3,890 m on a sunny slope, and four parallel transects were set along altitudinal gradients on a shady slope in alpine grasslands in Guoluo Prefecture of Qinghai Province, China. It was found that biological disturbances were the major forces driving the spatial heterogeneity of the alpine grassland vegetation and abiotic factors were of secondary importance. Heavy grazing and intensive rat activity resulted in increases in unpalatable and poisonous weeds and decreased fine forages in the form of sedges, forbs, and grasses in the vegetation composition. Habitat degradation associated with biological disturbances significantly affected the spatial variation of the alpine grassland vegetation, i.e., more pioneer plants of poisonous or unpalatable weed species, such as Ligularia virgaurea and Euphorbia fischeriana, were found in bare patches. Environmental/abiotic factors were less important than biological disturbances in affecting the spatial distribution of the alpine grassland vegetation at a small scale. It was concluded that rat control and light grazing should be applied first in implementing restoration strategies. The primary vegetation in lightly grazed and less rat-damaged sites should be regarded as a reference for devising vegetation restoration measures in alpine pastoral regions.
NASA Astrophysics Data System (ADS)
Mendoza, Pablo A.; Mizukami, Naoki; Ikeda, Kyoko; Clark, Martyn P.; Gutmann, Ethan D.; Arnold, Jeffrey R.; Brekke, Levi D.; Rajagopalan, Balaji
2016-10-01
We examine the effects of regional climate model (RCM) horizontal resolution and forcing scaling (i.e., spatial aggregation of meteorological datasets) on the portrayal of climate change impacts. Specifically, we assess how the above decisions affect: (i) historical simulation of signature measures of hydrologic behavior, and (ii) projected changes in terms of annual water balance and hydrologic signature measures. To this end, we conduct our study in three catchments located in the headwaters of the Colorado River basin. Meteorological forcings for current and a future climate projection are obtained at three spatial resolutions (4-, 12- and 36-km) from dynamical downscaling with the Weather Research and Forecasting (WRF) regional climate model, and hydrologic changes are computed using four different hydrologic model structures. These projected changes are compared to those obtained from running hydrologic simulations with current and future 4-km WRF climate outputs re-scaled to 12- and 36-km. The results show that the horizontal resolution of WRF simulations heavily affects basin-averaged precipitation amounts, propagating into large differences in simulated signature measures across model structures. The implications of re-scaled forcing datasets on historical performance were primarily observed on simulated runoff seasonality. We also found that the effects of WRF grid resolution on projected changes in mean annual runoff and evapotranspiration may be larger than the effects of hydrologic model choice, which surpasses the effects from re-scaled forcings. Scaling effects on projected variations in hydrologic signature measures were found to be generally smaller than those coming from WRF resolution; however, forcing aggregation in many cases reversed the direction of projected changes in hydrologic behavior.
NASA Astrophysics Data System (ADS)
Michael, Holly A.; Khan, Mahfuzur R.
2016-12-01
Aquifer heterogeneity presents a primary challenge in predicting the movement of solutes in groundwater systems. The problem is particularly difficult on very large scales, across which permeability, chemical properties, and pumping rates may vary by many orders of magnitude and data are often sparse. An example is the fluvio-deltaic aquifer system of Bangladesh, where naturally-occurring arsenic (As) exists over tens of thousands of square kilometers in shallow groundwater. Millions of people in As-affected regions rely on deep (≥150 m) groundwater as a safe source of drinking water. The sustainability of this resource has been evaluated with models using effective properties appropriate for a basin-scale contamination problem, but the extent to which preferential flow affects the timescale of downward migration of As-contaminated shallow groundwater is unknown. Here we embed detailed, heterogeneous representations of hydraulic conductivity (K), pumping rates, and sorptive properties (Kd) within a basin-scale numerical groundwater flow and solute transport model to evaluate their effects on vulnerability and deviations from simulations with homogeneous representations in two areas with different flow systems. Advective particle tracking shows that heterogeneity in K does not affect average travel times from shallow zones to 150 m depth, but the travel times of the fastest 10% of particles decreases by a factor of ∼2. Pumping distributions do not strongly affect travel times if irrigation remains shallow, but increases in the deep pumping rate substantially reduce travel times. Simulation of advective-dispersive transport with sorption shows that deep groundwater is protected from contamination over a sustainable timeframe (>1000 y) if the spatial distribution of Kd is uniform. However, if only low-K sediments sorb As, 30% of the aquifer is not protected. Results indicate that sustainable management strategies in the Bengal Basin should consider impacts of both physical and chemical heterogeneity, as well as their correlation. These insights from Bangladesh show that preferential flow strongly influences breakthrough of both conservative and reactive solutes even at large spatial scales, with implications for predicting water supply vulnerability in contaminated heterogeneous aquifers worldwide.
Brakebill, John W.; Wolock, David M.; Terziotti, Silvia
2011-01-01
Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based ⁄ statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling.
Landscape patterns and soil organic carbon stocks in agricultural bocage landscapes
NASA Astrophysics Data System (ADS)
Viaud, Valérie; Lacoste, Marine; Michot, Didier; Walter, Christian
2014-05-01
Soil organic carbon (SOC) has a crucial impact on global carbon storage at world scale. SOC spatial variability is controlled by the landscape patterns resulting from the continuous interactions between the physical environment and the society. Natural and anthropogenic processes occurring and interplaying at the landscape scale, such as soil redistribution in the lateral and vertical dimensions by tillage and water erosion processes or spatial differentiation of land-use and land-management practices, strongly affect SOC dynamics. Inventories of SOC stocks, reflecting their spatial distribution, are thus key elements to develop relevant management strategies to improving carbon sequestration and mitigating climate change and soil degradation. This study aims to quantify SOC stocks and their spatial distribution in a 1,000-ha agricultural bocage landscape with dairy production as dominant farming system (Zone Atelier Armorique, LTER Europe, NW France). The site is characterized by high heterogeneity on short distance due to a high diversity of soils with varying waterlogging, soil parent material, topography, land-use and hedgerow density. SOC content and stocks were measured up to 105-cm depth in 200 sampling locations selected using conditioned Latin hypercube sampling. Additive sampling was designed to specifically explore SOC distribution near to hedges: 112 points were sampled at fixed distance on 14 transects perpendicular from hedges. We illustrate the heterogeneity of spatial and vertical distribution of SOC stocks at landscape scale, and quantify SOC stocks in the various landscape components. Using multivariate statistics, we discuss the variability and co-variability of existing spatial organization of cropping systems, environmental factors, and SOM stocks, over landscape. Ultimately, our results may contribute to improving regional or national digital soil mapping approaches, by considering the distribution of SOC stocks within each modeling unit and by accounting for the impact of sensitive ecosystems.
Exploring Land Use and Land Cover Change and Feedbacks in the Global Change Assessment Model
NASA Astrophysics Data System (ADS)
Chen, M.; Vernon, C. R.; Huang, M.; Calvin, K. V.; Le Page, Y.; Kraucunas, I.
2017-12-01
Land Use and Land Cover Change (LULCC) is a major driver of global and regional environmental change. Projections of land use change are thus an essential component in Integrated Assessment Models (IAMs) to study feedbacks between transformation of energy systems and land productivity under the context of climate change. However, the spatial scale of IAMs, e.g., the Global Change Assessment Model (GCAM), is typically larger than the scale of terrestrial processes in the human-Earth system, LULCC downscaling therefore becomes a critical linkage among these multi-scale and multi-sector processes. Parametric uncertainties in LULCC downscaling algorithms, however, have been under explored, especially in the context of how such uncertainties could propagate to affect energy systems in a changing climate. In this study, we use a LULCC downscaling model, Demeter, to downscale GCAM-based future land use scenarios into fine spatial scales, and explore the sensitivity of downscaled land allocations to key parameters. Land productivity estimates (e.g., biomass production and crop yield) based on the downscaled LULCC scenarios are then fed to GCAM to evaluate how energy systems might change due to altered water and carbon cycle dynamics and their interactions with the human system, , which would in turn affect future land use projections. We demonstrate that uncertainties in LULCC downscaling can result in significant differences in simulated scenarios, indicating the importance of quantifying parametric uncertainties in LULCC downscaling models for integrated assessment studies.
Zoller, Thomas; Fèvre, Eric M; Welburn, Susan C; Odiit, Martin; Coleman, Paul G
2008-01-01
Background Sleeping sickness (HAT) caused by T.b. rhodesiense is a major veterinary and human public health problem in Uganda. Previous studies have investigated spatial risk factors for T.b. rhodesiense at large geographic scales, but none have properly investigated such risk factors at small scales, i.e. within affected villages. In the present work, we use a case-control methodology to analyse both behavioural and spatial risk factors for HAT in an endemic area. Methods The present study investigates behavioural and occupational risk factors for infection with HAT within villages using a questionnaire-based case-control study conducted in 17 villages endemic for HAT in SE Uganda, and spatial risk factors in 4 high risk villages. For the spatial analysis, the location of homesteads with one or more cases of HAT up to three years prior to the beginning of the study was compared to all non-case homesteads. Analysing spatial associations with respect to irregularly shaped geographical objects required the development of a new approach to geographical analysis in combination with a logistic regression model. Results The study was able to identify, among other behavioural risk factors, having a family member with a history of HAT (p = 0.001) as well as proximity of a homestead to a nearby wetland area (p < 0.001) as strong risk factors for infection. The novel method of analysing complex spatial interactions used in the study can be applied to a range of other diseases. Conclusion Spatial risk factors for HAT are maintained across geographical scales; this consistency is useful in the design of decision support tools for intervention and prevention of the disease. Familial aggregation of cases was confirmed for T. b. rhodesiense HAT in the study and probably results from shared behavioural and spatial risk factors amongmembers of a household. PMID:18590541
M. Concilio; J. Chen; S. Ma; M. North
2009-01-01
Predictions of future climate change rely on models of how both environmental conditions and disturbance impact carbon cycling at various temporal and spatial scales. Few multi-year studies, however, have examined how carbon efflux is affected by the interaction of disturbance and interannual climate variation. We measured daytime soil respiration (R...
William T. Peterjohn; Margaret A. Harlacher; Martin J. Christ; Mary Beth Adams
2015-01-01
In forest ecosystems there are numerous factors that influence nitrate (NO3) availability and retention in ways that can significantly affect receiving waters. Unfortunately these factors often co-exist and interact making it difficult to establish the importance of each individually. Three reference watersheds at the Fernow Experimental Forest (...
Monitoring tree secies diversity over large spatial and temporal scales
James F. Rosson; Clifford C. Amundsen
2004-01-01
The prospect of decline in biological diversity has become a central concern in the life sciences, both around the world and across the United States. Anthropogenic disturbance has been identified as a major factor affecting species diversity trends. An increase in the harvesting of naturally diverse timber stands in the South has become an important issue. The...
The role of remote sensing in process‐scaling studies of managed forest ecosystems
Jeffrey G. Masek; Daniel J. Hayes; M. Joseph Hughes; Sean P. Healey; David P. Turner
2015-01-01
Sustaining forest resources requires a better understanding of forest ecosystem processes, and how management decisions and climate change may affect these processes in the future. While plot and inventory data provide our most detailed information on forest carbon, energy, and water cycling, applying this understanding to broader spatial and temporal domains...
Spatial and temporal patterns in erosion from forest roads
Charles H. Luce; Thomas A. Black
2001-01-01
Erosion from forest roads is an important contribution to the sediment budget of many forested basins, particularly over short time scales. Sediment production from 74 road segments was measured over three years to examine how road slope, segment length, cutslope height, and soil texture affect sediment production and how these relationships change with time. In the...
Climate change and watershed mercury export in a Coastal Plain watershed
Heather Golden; Christopher D. Knightes; Paul A. Conrads; Toby D. Feaster; Gary M. Davis; Stephen T. Benedict; Paul M. Bradley
2016-01-01
Future changes in climatic conditions may affect variations in watershed processes (e.g., hydrological, biogeochemical) and surface water quality across a wide range of physiographic provinces, ecosystems, and spatial scales. How such climatic shifts will impact watershed mercury (Hg) dynamics and hydrologically-driven Hg transport is a significant concern.
Daniel J. Isaak; Seth J. Wenger; Michael K. Young
2017-01-01
Temperature profoundly affects ecology, a fact ever more evident as the ability to measure thermal environments increases and global changes alter these environments. The spatial structure of thermalscapes is especially relevant to the distribution and abundance of ectothermic organisms but the ability to describe biothermal relationships at extents and grains relevant...
Kivlin, Stephanie N; Hawkes, Christine V
2016-01-01
The high diversity of tree species has traditionally been considered an important controller of belowground processes in tropical rainforests. However, soil water availability and resources are also primary regulators of soil bacteria in many ecosystems. Separating the effects of these biotic and abiotic factors in the tropics is challenging because of their high spatial and temporal heterogeneity. To determine the drivers of tropical soil bacteria, we examined tree species effects using experimental tree monocultures and secondary forests at La Selva Biological Station in Costa Rica. A randomized block design captured spatial variation and we sampled at four dates across two years to assess temporal variation. We measured bacteria richness, phylogenetic diversity, community composition, biomass, and functional potential. All bacteria parameters varied significantly across dates. In addition, bacteria richness and phylogenetic diversity were affected by the interaction of vegetation type and date, whereas bacteria community composition was affected by the interaction of vegetation type and block. Shifts in bacteria community richness and composition were unrelated to shifts in enzyme function, suggesting physiological overlap among taxa. Based on the observed temporal and spatial heterogeneity, our understanding of tropical soil bacteria will benefit from additional work to determine the optimal temporal and spatial scales for sampling. Understanding spatial and temporal variation will facilitate prediction of how tropical soil microbes will respond to future environmental change. PMID:27391450
Kivlin, Stephanie N; Hawkes, Christine V
2016-01-01
The high diversity of tree species has traditionally been considered an important controller of belowground processes in tropical rainforests. However, soil water availability and resources are also primary regulators of soil bacteria in many ecosystems. Separating the effects of these biotic and abiotic factors in the tropics is challenging because of their high spatial and temporal heterogeneity. To determine the drivers of tropical soil bacteria, we examined tree species effects using experimental tree monocultures and secondary forests at La Selva Biological Station in Costa Rica. A randomized block design captured spatial variation and we sampled at four dates across two years to assess temporal variation. We measured bacteria richness, phylogenetic diversity, community composition, biomass, and functional potential. All bacteria parameters varied significantly across dates. In addition, bacteria richness and phylogenetic diversity were affected by the interaction of vegetation type and date, whereas bacteria community composition was affected by the interaction of vegetation type and block. Shifts in bacteria community richness and composition were unrelated to shifts in enzyme function, suggesting physiological overlap among taxa. Based on the observed temporal and spatial heterogeneity, our understanding of tropical soil bacteria will benefit from additional work to determine the optimal temporal and spatial scales for sampling. Understanding spatial and temporal variation will facilitate prediction of how tropical soil microbes will respond to future environmental change.
Westhoff, Jacob T.; Paukert, Craig P.
2014-01-01
Climate change is predicted to increase water temperatures in many lotic systems, but little is known about how changes in air temperature affect lotic systems heavily influenced by groundwater. Our objectives were to document spatial variation in temperature for spring-fed Ozark streams in Southern Missouri USA, create a spatially explicit model of mean daily water temperature, and use downscaled climate models to predict the number of days meeting suitable stream temperature for three aquatic species of concern to conservation and management. Longitudinal temperature transects and stationary temperature loggers were used in the Current and Jacks Fork Rivers during 2012 to determine spatial and temporal variability of water temperature. Groundwater spring influence affected river water temperatures in both winter and summer, but springs that contributed less than 5% of the main stem discharge did not affect river temperatures beyond a few hundred meters downstream. A multiple regression model using variables related to season, mean daily air temperature, and a spatial influence factor (metric to account for groundwater influence) was a strong predictor of mean daily water temperature (r2 = 0.98; RMSE = 0.82). Data from two downscaled climate simulations under the A2 emissions scenario were used to predict daily water temperatures for time steps of 1995, 2040, 2060, and 2080. By 2080, peak numbers of optimal growth temperature days for smallmouth bass are expected to shift to areas with more spring influence, largemouth bass are expected to experience more optimal growth days (21 – 317% increase) regardless of spring influence, and Ozark hellbenders may experience a reduction in the number of optimal growth days in areas with the highest spring influence. Our results provide a framework for assessing fine-scale (10 s m) thermal heterogeneity and predict shifts in thermal conditions at the watershed and reach scale. PMID:25356982
Direct and indirect genetic and fine-scale location effects on breeding date in song sparrows.
Germain, Ryan R; Wolak, Matthew E; Arcese, Peter; Losdat, Sylvain; Reid, Jane M
2016-11-01
Quantifying direct and indirect genetic effects of interacting females and males on variation in jointly expressed life-history traits is central to predicting microevolutionary dynamics. However, accurately estimating sex-specific additive genetic variances in such traits remains difficult in wild populations, especially if related individuals inhabit similar fine-scale environments. Breeding date is a key life-history trait that responds to environmental phenology and mediates individual and population responses to environmental change. However, no studies have estimated female (direct) and male (indirect) additive genetic and inbreeding effects on breeding date, and estimated the cross-sex genetic correlation, while simultaneously accounting for fine-scale environmental effects of breeding locations, impeding prediction of microevolutionary dynamics. We fitted animal models to 38 years of song sparrow (Melospiza melodia) phenology and pedigree data to estimate sex-specific additive genetic variances in breeding date, and the cross-sex genetic correlation, thereby estimating the total additive genetic variance while simultaneously estimating sex-specific inbreeding depression. We further fitted three forms of spatial animal model to explicitly estimate variance in breeding date attributable to breeding location, overlap among breeding locations and spatial autocorrelation. We thereby quantified fine-scale location variances in breeding date and quantified the degree to which estimating such variances affected the estimated additive genetic variances. The non-spatial animal model estimated nonzero female and male additive genetic variances in breeding date (sex-specific heritabilities: 0·07 and 0·02, respectively) and a strong, positive cross-sex genetic correlation (0·99), creating substantial total additive genetic variance (0·18). Breeding date varied with female, but not male inbreeding coefficient, revealing direct, but not indirect, inbreeding depression. All three spatial animal models estimated small location variance in breeding date, but because relatedness and breeding location were virtually uncorrelated, modelling location variance did not alter the estimated additive genetic variances. Our results show that sex-specific additive genetic effects on breeding date can be strongly positively correlated, which would affect any predicted rates of microevolutionary change in response to sexually antagonistic or congruent selection. Further, we show that inbreeding effects on breeding date can also be sex specific and that genetic effects can exceed phenotypic variation stemming from fine-scale location-based variation within a wild population. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.
Wakelin, Steven; Tillard, Guyléne; van Ham, Robert; Ballard, Ross; Farquharson, Elizabeth; Gerard, Emily; Geurts, Rene; Brown, Matthew; Ridgway, Hayley; O'Callaghan, Maureen
2018-01-01
Biological nitrogen fixation through the legume-rhizobia symbiosis is important for sustainable pastoral production. In New Zealand, the most widespread and valuable symbiosis occurs between white clover (Trifolium repens L.) and Rhizobium leguminosarum bv. trifolii (Rlt). As variation in the population size (determined by most probable number assays; MPN) and effectiveness of N-fixation (symbiotic potential; SP) of Rlt in soils may affect white clover performance, the extent in variation in these properties was examined at three different spatial scales: (1) From 26 sites across New Zealand, (2) at farm-wide scale, and (3) within single fields. Overall, Rlt populations ranged from 95 to >1 x 108 per g soil, with variation similar at the three spatial scales assessed. For almost all samples, there was no relationship between rhizobia population size and ability of the population to fix N during legume symbiosis (SP). When compared with the commercial inoculant strain, the SP of soils ranged between 14 to 143% efficacy. The N-fixing ability of rhizobia populations varied more between samples collected from within a single hill country field (0.8 ha) than between 26 samples collected from diverse locations across New Zealand. Correlations between SP and calcium and aluminium content were found in all sites, except within a dairy farm field. Given the general lack of association between SP and MPN, and high spatial variability of SP at single field scale, provision of advice for treating legume seed with rhizobia based on field-average MPN counts needs to be carefully considered.
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
Tillard, Guyléne; van Ham, Robert; Ballard, Ross; Farquharson, Elizabeth; Gerard, Emily; Geurts, Rene; Brown, Matthew; Ridgway, Hayley; O’Callaghan, Maureen
2018-01-01
Biological nitrogen fixation through the legume-rhizobia symbiosis is important for sustainable pastoral production. In New Zealand, the most widespread and valuable symbiosis occurs between white clover (Trifolium repens L.) and Rhizobium leguminosarum bv. trifolii (Rlt). As variation in the population size (determined by most probable number assays; MPN) and effectiveness of N-fixation (symbiotic potential; SP) of Rlt in soils may affect white clover performance, the extent in variation in these properties was examined at three different spatial scales: (1) From 26 sites across New Zealand, (2) at farm-wide scale, and (3) within single fields. Overall, Rlt populations ranged from 95 to >1 x 108 per g soil, with variation similar at the three spatial scales assessed. For almost all samples, there was no relationship between rhizobia population size and ability of the population to fix N during legume symbiosis (SP). When compared with the commercial inoculant strain, the SP of soils ranged between 14 to 143% efficacy. The N-fixing ability of rhizobia populations varied more between samples collected from within a single hill country field (0.8 ha) than between 26 samples collected from diverse locations across New Zealand. Correlations between SP and calcium and aluminium content were found in all sites, except within a dairy farm field. Given the general lack of association between SP and MPN, and high spatial variability of SP at single field scale, provision of advice for treating legume seed with rhizobia based on field-average MPN counts needs to be carefully considered. PMID:29489845
NASA Astrophysics Data System (ADS)
Tang, U. W.; Wang, Z. S.
2008-10-01
Each city has its unique urban form. The importance of urban form on sustainable development has been recognized in recent years. Traditionally, air quality modelling in a city is in a mesoscale with grid resolution of kilometers, regardless of its urban form. This paper introduces a GIS-based air quality and noise model system developed to study the built environment of highly compact urban forms. Compared with traditional mesoscale air quality model system, the present model system has a higher spatial resolution down to individual buildings along both sides of the street. Applying the developed model system in the Macao Peninsula with highly compact urban forms, the average spatial resolution of input and output data is as high as 174 receptor points per km2. Based on this input/output dataset with a high spatial resolution, this study shows that even the highly compact urban forms can be fragmented into a very small geographic scale of less than 3 km2. This is due to the significant temporal variation of urban development. The variation of urban form in each fragment in turn affects air dispersion, traffic condition, and thus air quality and noise in a measurable scale.
Upscaling and Downscaling of Land Surface Fluxes with Surface Temperature
NASA Astrophysics Data System (ADS)
Kustas, W. P.; Anderson, M. C.; Hain, C.; Albertson, J. D.; Gao, F.; Yang, Y.
2015-12-01
Land surface temperature (LST) is a key surface boundary condition that is significantly correlated to surface flux partitioning between latent and sensible heat. The spatial and temporal variation in LST is driven by radiation, wind, vegetation cover and roughness as well as soil moisture status in the surface and root zone. Data from airborne and satellite-based platforms provide LST from ~10 km to sub meter resolutions. A land surface scheme called the Two-Source Energy Balance (TSEB) model has been incorporated into a multi-scale regional modeling system ALEXI (Atmosphere Land Exchange Inverse) and a disaggregation scheme (DisALEXI) using higher resolution LST. Results with this modeling system indicates that it can be applied over heterogeneous land surfaces and estimate reliable surface fluxes with minimal in situ information. Consequently, this modeling system allows for scaling energy fluxes from subfield to regional scales in regions with little ground data. In addition, the TSEB scheme has been incorporated into a large Eddy Simulation (LES) model for investigating dynamic interactions between variations in the land surface state reflected in the spatial pattern in LST and the lower atmospheric air properties affecting energy exchange. An overview of research results on scaling of fluxes and interactions with the lower atmosphere from the subfield level to regional scales using the TSEB, ALEX/DisALEX and the LES-TSEB approaches will be presented. Some unresolved issues in the use of LST at different spatial resolutions for estimating surface energy balance and upscaling fluxes, particularly evapotranspiration, will be discussed.
Atuo, Fidelis Akunke; O'Connell, Timothy John
2017-08-01
Sympatric predators are predicted to partition resources, especially under conditions of food limitation. Spatial heterogeneity that influences prey availability might play an important role in the scales at which potential competitors select habitat. We assessed potential mechanisms for coexistence by examining the role of heterogeneity in resource partitioning between sympatric raptors overwintering in the southern Great Plains. We conducted surveys for wintering Red-tailed hawk ( Buteo jamaicensis ) and Northern Harrier ( Circus cyanea ) at two state wildlife management areas in Oklahoma, USA. We used information from repeated distance sampling to project use locations in a GIS. We applied resource selection functions to model habitat selection at three scales and analyzed for niche partitioning using the outlying mean index. Habitat selection of the two predators was mediated by spatial heterogeneity. The two predators demonstrated significant fine-scale discrimination in habitat selection in homogeneous landscapes, but were more sympatric in heterogeneous landscapes. Red-tailed hawk used a variety of cover types in heterogeneous landscapes but specialized on riparian forest in homogeneous landscapes. Northern Harrier specialized on upland grasslands in homogeneous landscapes but selected more cover types in heterogeneous landscapes. Our study supports the growing body of evidence that landscapes can affect animal behaviors. In the system we studied, larger patches of primary land cover types were associated with greater allopatry in habitat selection between two potentially competing predators. Heterogeneity within the scale of raptor home ranges was associated with greater sympatry in use and less specialization in land cover types selected.
Waibel, Michael S.; Gannett, Marshall W.; Chang, Heejun; Hulbe, Christina L.
2013-01-01
We examine the spatial variability of the response of aquifer systems to climate change in and adjacent to the Cascade Range volcanic arc in the Deschutes Basin, Oregon using downscaled global climate model projections to drive surface hydrologic process and groundwater flow models. Projected warming over the 21st century is anticipated to shift the phase of precipitation toward more rain and less snow in mountainous areas in the Pacific Northwest, resulting in smaller winter snowpack and in a shift in the timing of runoff to earlier in the year. This will be accompanied by spatially variable changes in the timing of groundwater recharge. Analysis of historic climate and hydrologic data and modeling studies show that groundwater plays a key role in determining the response of stream systems to climate change. The spatial variability in the response of groundwater systems to climate change, particularly with regard to flow-system scale, however, has generally not been addressed in the literature. Here we simulate the hydrologic response to projected future climate to show that the response of groundwater systems can vary depending on the location and spatial scale of the flow systems and their aquifer characteristics. Mean annual recharge averaged over the basin does not change significantly between the 1980s and 2080s climate periods given the ensemble of global climate models and emission scenarios evaluated. There are, however, changes in the seasonality of groundwater recharge within the basin. Simulation results show that short-flow-path groundwater systems, such as those providing baseflow to many headwater streams, will likely have substantial changes in the timing of discharge in response changes in seasonality of recharge. Regional-scale aquifer systems with flow paths on the order of many tens of kilometers, in contrast, are much less affected by changes in seasonality of recharge. Flow systems at all spatial scales, however, are likely to reflect interannual changes in total recharge. These results provide insights into the possible impacts of climate change to other regional aquifer systems, and the streams they support, where discharge points represent a range of flow system scales.
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;
2016-01-01
The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05*Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = -0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.
A framework for implementing biodiversity offsets: selecting sites and determining scale
Kiesecker, Joseph M.; Copeland, Holly; Pocewicz, Amy; Nibbelink, Nate; McKenney, Bruce; Dahlke, John; Holloran, Matthew J.; Stroud, Dan
2009-01-01
Biodiversity offsets provide a mechanism for maintaining or enhancing environmental values in situations where development is sought despite detrimental environmental impacts. They seek to ensure that unavoidable negative environmental impacts of development are balanced by environmental gains, with the overall aim of achieving a net neutral or positive outcome. Once the decision has been made to offset, multiple issues arise regarding how to do so in practice. A key concern is site selection. In light of the general aim to locate offsets close to the affected sites to ensure that benefits accrue in the same area, what is the appropriate spatial scale for identifying potential offset sites (e.g., local, ecoregional)? We use the Marxan site-selection algorithm to address conceptual and methodological challenges associated with identifying a set of potential offset sites and determining an appropriate spatial scale for them. To demonstrate this process, we examined the design of offsets for impacts from development on the Jonah natural gas field in Wyoming.
Land use, spatial scale, and stream systems: Lessons from an agricultural region
Vondracek, B.; Blann, K.L.; Cox, C.B.; Nerbonne, J.F.; Mumford, K.G.; Nerbonne, B.A.; Sovell, L.A.; Zimmerman, J.K.H.
2005-01-01
We synthesized nine studies that examined the influence of land use at different spatial scales in structuring biotic assemblages and stream channel characteristics in southeastern Minnesota streams. Recent studies have disagreed about the relative importance of catchment versus local characteristics in explaining variation in fish assemblages. Our synthesis indicates that both riparian- and catchment-scale land use explained significant variation in water quality, channel morphology, and fish distribution and density. Fish and macroinvertebrate assemblages can be positively affected by increasing the extent of perennial riparian and upland vegetation. Our synthesis is robust; more than 425 stream reaches were examined in an area that includes a portion of three ecoregions. Fishes ranged from coldwater to warmwater adapted. We suggest that efforts to rehabilitate stream system form and function over the long term should focus on increasing perennial vegetation in both riparian areas and uplands and on managing vegetation in large, contiguous blocks. ?? 2005 Springer Science+Business Media, Inc.
Scaling relations for watersheds
NASA Astrophysics Data System (ADS)
Fehr, E.; Kadau, D.; Araújo, N. A. M.; Andrade, J. S., Jr.; Herrmann, H. J.
2011-09-01
We study the morphology of watersheds in two and three dimensional systems subjected to different degrees of spatial correlations. The response of these objects to small, local perturbations is also investigated with extensive numerical simulations. We find the fractal dimension of the watersheds to generally decrease with the Hurst exponent, which quantifies the degree of spatial correlations. Moreover, in two dimensions, our results match the range of fractal dimensions 1.10≤df≤1.15 observed for natural landscapes. We report that the watershed is strongly affected by local perturbations. For perturbed two and three dimensional systems, we observe a power-law scaling behavior for the distribution of areas (volumes) enclosed by the original and the displaced watershed and for the distribution of distances between outlets. Finite-size effects are analyzed and the resulting scaling exponents are shown to depend significantly on the Hurst exponent. The intrinsic relation between watershed and invasion percolation, as well as relations between exponents conjectured in previous studies with two dimensional systems, are now confirmed by our results in three dimensions.
Multiresolution comparison of precipitation datasets for large-scale models
NASA Astrophysics Data System (ADS)
Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.
2014-12-01
Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.
City rats: insight from rat spatial behavior into human cognition in urban environments.
Yaski, Osnat; Portugali, Juval; Eilam, David
2011-09-01
The structure and shape of the urban environment influence our ability to find our way about in the city. Understanding how the physical properties of the environment affect spatial behavior and cognition is therefore a necessity. However, there are inherent difficulties in empirically studying complex and large-scale urban environments. These include the need to isolate the impact of specific urban features and to acquire data on the physical activity of individuals. In the present study, we attempted to overcome the above obstacles and examine the relation between urban environments and spatial cognition by testing the spatial behavior of rats. This idea originated from the resemblance in the operative brain functions and in the mechanisms and strategies employed by humans and other animals when acquiring spatial information and establishing an internal representation, as revealed in past studies. Accordingly, we tested rats in arenas that simulated a grid urban layout (e.g. Manhattan streets) and an irregular urban layout (e.g. Jerusalem streets). We found that in the grid layout, rat movement was more structured and extended over a greater area compared with their restricted movement in the irregular layout. These movement patterns recall those of humans in respective urban environments, illustrating that the structure and shape of the environment affect spatial behavior similarly in humans and rats. Overall, testing rats in environments that simulate facets of urban environments can provide new insights into human spatial cognition in urban environments.
Gidoin, Cynthia; Avelino, Jacques; Deheuvels, Olivier; Cilas, Christian; Bieng, Marie Ange Ngo
2014-03-01
Vegetation composition and plant spatial structure affect disease intensity through resource and microclimatic variation effects. The aim of this study was to evaluate the independent effect and relative importance of host composition and plant spatial structure variables in explaining disease intensity at the plot scale. For that purpose, frosty pod rot intensity, a disease caused by Moniliophthora roreri on cacao pods, was monitored in 36 cacao agroforests in Costa Rica in order to assess the vegetation composition and spatial structure variables conducive to the disease. Hierarchical partitioning was used to identify the most causal factors. Firstly, pod production, cacao tree density and shade tree spatial structure had significant independent effects on disease intensity. In our case study, the amount of susceptible tissue was the most relevant host composition variable for explaining disease intensity by resource dilution. Indeed, cacao tree density probably affected disease intensity more by the creation of self-shading rather than by host dilution. Lastly, only regularly distributed forest trees, and not aggregated or randomly distributed forest trees, reduced disease intensity in comparison to plots with a low forest tree density. A regular spatial structure is probably crucial to the creation of moderate and uniform shade as recommended for frosty pod rot management. As pod production is an important service expected from these agroforests, shade tree spatial structure may be a lever for integrated management of frosty pod rot in cacao agroforests.
NASA Astrophysics Data System (ADS)
Hu, Rongming; Wang, Shu; Guo, Jiao; Guo, Liankun
2018-04-01
Impervious surface area and vegetation coverage are important biophysical indicators of urban surface features which can be derived from medium-resolution images. However, remote sensing data obtained by a single sensor are easily affected by many factors such as weather conditions, and the spatial and temporal resolution can not meet the needs for soil erosion estimation. Therefore, the integrated multi-source remote sensing data are needed to carry out high spatio-temporal resolution vegetation coverage estimation. Two spatial and temporal vegetation coverage data and impervious data were obtained from MODIS and Landsat 8 remote sensing images. Based on the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), the vegetation coverage data of two scales were fused and the data of vegetation coverage fusion (ESTARFM FVC) and impervious layer with high spatiotemporal resolution (30 m, 8 day) were obtained. On this basis, the spatial variability of the seepage-free surface and the vegetation cover landscape in the study area was measured by means of statistics and spatial autocorrelation analysis. The results showed that: 1) ESTARFM FVC and impermeable surface have higher accuracy and can characterize the characteristics of the biophysical components covered by the earth's surface; 2) The average impervious surface proportion and the spatial configuration of each area are different, which are affected by natural conditions and urbanization. In the urban area of Xi'an, which has typical characteristics of spontaneous urbanization, landscapes are fragmented and have less spatial dependence.
NASA Astrophysics Data System (ADS)
Matsui, H.; Koike, M.; Kondo, Y.; Takegawa, N.; Kita, K.; Miyazaki, Y.; Hu, M.; Chang, S.; Blake, D. R.; Fast, J. D.; Zaveri, R. A.; Streets, D. G.; Zhang, Q.; Zhu, T.
2009-12-01
Regional aerosol model calculations were made using the WRF-CMAQ and WRF-chem models to study spatial and temporal variations of aerosols around Beijing, China, in the summer of 2006, when the CAREBEIJING-2006 intensive campaign was conducted. Model calculations captured temporal variations of primary (such as elemental carbon, EC) and secondary (such as sulfate) aerosols observed in and around Beijing. The spatial distributions of aerosol optical depth observed by the MODIS satellite sensors were also reproduced over northeast China. Model calculations showed distinct differences in spatial distributions between primary and secondary aerosols in association with synoptic-scale meteorology. Secondary aerosols increased in air around Beijing on a scale of about 1000 x 1000 km2 under an anticyclonic pressure system. This airmass was transported northward from the high anthropogenic emission area extending south of Beijing with continuous photochemical production. Subsequent cold front passage brought clean air from the north, and polluted air around Beijing was swept to the south of Beijing. This cycle was repeated about once a week and was found to be responsible for observed enhancements/reductions of aerosols at the intensive measurement sites. In contrast to secondary aerosols, the spatial distributions of primary aerosols (EC) reflected those of emissions, resulting in only slight variability despite the changes in synoptic-scale meteorology. In accordance with these results, source apportionment simulations revealed that primary aerosols around Beijing were controlled by emissions within 100 km around Beijing within the preceding 24 hours, while emissions as far as 500 km and within the preceding 3 days were found to affect secondary aerosols.
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
NASA Astrophysics Data System (ADS)
Caruso, Alice; Boano, Fulvio; Ridolfi, Luca
2015-04-01
Surface water bodies continuously interact with the subsurface and it is by now widely known that the hyporheic zone plays a key role in the mixing of river water with shallow groundwater. Hyporheic exchange occurs over a very wide range of spatial and temporal scales and the exchange processes at different scales interact and determine a complex system of nested flow cells. This intricacy results from the multiplicity of spatial scale that characterize landscape and river morphology. In the last years, many processes that regulate the surface-groundwater interactions have been elucidated and a more holistic view of groundwater and surface water has been adopted. However, despite several insights on the mechanisms of hyporheic exchange have been achieved, many important aspects remain to be clarified, i.e. how surface-groundwater interactions influence solute transport, microbial activity and biogeochemical transformations at the scale of entire watersheds. To date a deep knowledge of small-scale processes has been developed but what is lacking is a unifying overview of the role of surface water-groundwater exchange for the health of the whole water system at larger scales, i.e. the scale of the entire basin. In order to better understand the complex multiscale nature of spatial patterns of surface-subsurface exchange, we aim to assess the importance of the individual scales included in the range between watershed scale to stream reach scale. Hence, we study the large-scale subsurface flow field taking into account the surface-groundwater interactions induced by landscape topography from the basin scale to smaller scales ranging from tens of kilometers to tens of meters. The aim of this research is to analyze how individual topographic scales affect the flow field and to understand which ones are the most important and should be focused on. To study the impact of various scales of landscape topography we apply an analytical model that provides an exact solution of the underlying three dimensional groundwater flow and a numerical particle tracking routine that allows to obtain streamlines and residence time distributions from the flow field. Therefore, starting from a previously published mathematical tool we set the goal of investigating the interaction between the scales and clarifying their role. We consider real basin examples and describe subsurface flow at the landscape scale, identifying inflow patterns of groundwater to the river network, in order to obtain, in the near future, results to be used for conserving, managing and restoring of a riverine ecosystem.
Scale-dependent effects of nonnative plant invasion on host-seeking tick abundance
Adalsteinsson, Solny A.; D’Amico, Vincent; Shriver, W. Gregory; Brisson, Dustin; Buler, Jeffrey J.
2016-01-01
Nonnative, invasive shrubs can affect human disease risk through direct and indirect effects on vector populations. Multiflora rose (Rosa multiflora) is a common invader within eastern deciduous forests where tick-borne disease (e.g. Lyme disease) rates are high. We tested whether R. multiflora invasion affects blacklegged tick (Ixodes scapularis) abundance, and at what scale. We sampled host-seeking ticks at two spatial scales: fine-scale, within R. multiflora-invaded forest fragments; and patch scale, among R. multiflora-invaded and R. multiflora-free forest fragments. At a fine scale, we trapped 2.3 times more ticks under R. multiflora compared to paired traps 25 m away from R. multiflora. At the patch scale, we trapped 3.2 times as many ticks in R. multiflora-free forests compared to R. multiflora-invaded forests. Thus, ticks are concentrated beneath R. multiflora within invaded forests, but uninvaded forests support significantly more ticks. Among all covariates tested, leaf litter volume was the best predictor of tick abundance; at the patch scale, R. multiflora-invaded forests had less leaf litter than uninvaded forests. We suggest that leaf litter availability at the patch-scale plays a greater role in constraining tick abundance than the fine-scale, positive effect of invasive shrubs. PMID:27088044
On the Design of Wide-Field X-ray Telescopes
NASA Technical Reports Server (NTRS)
Elsner, Ronald F.; O'Dell, Stephen L.; Ramsey, Brian D.; Weiskopf, Martin C.
2009-01-01
X-ray telescopes having a relatively wide field-of-view and spatial resolution vs. polar off-axis angle curves much flatter than the parabolic dependence characteristic of Wolter I designs are of great interest for surveys of the X-ray sky and potentially for study of the Sun s X-ray emission. We discuss the various considerations affecting the design of such telescopes, including the possible use of polynomial mirror surface prescriptions, a method of optimizing the polynomial coefficients, scaling laws for mirror segment length vs. intersection radius, the loss of on-axis spatial resolution, and the positioning of focal plane detectors.
NASA Astrophysics Data System (ADS)
Virk, Ravinder
Areas with relatively high spatial heterogeneity generally have more biodiversity than spatially homogeneous areas due to increased potential habitat. Management practices such as controlled grazing also affect the biodiversity in grasslands, but the nature of this impact is not well understood. Therefore this thesis studies the impacts of variation in grazing on soil moisture and biomass heterogeneity. These are not only important in terms of management of protected grasslands, but also for designing an effective grazing system from a livestock management point of view. This research is a part of the cattle grazing experiment underway in Grasslands National Park (GNP) of Canada since 2006, as part of the adaptive management process for restoring ecological integrity of the northern mixed-grass prairie region. An experimental approach using field measurements and remote sensing (Landsat) was combined with modelling (CENTURY) to examine and predict the impacts of grazing intensity on the spatial heterogeneity and patterns of above-ground live plant biomass (ALB) in experimental pastures in a mixed grassland ecosystem. The field-based research quantified the temporal patterns and spatial variability in both soil moisture (SM) and ALB, and the influence of local intra-seasonal weather variability and slope location on the spatio-temporal variability of SM and ALB at field plot scales. Significant impacts of intra-seasonal weather variability, slope position and grazing pressure on SM and ALB across a range of scales (plot and local (within pasture)) were found. Grazing intensity significantly affected the ALB even after controlling for the effect of slope position. Satellite-based analysis extended the scale of interest to full pastures and the surrounding region to assess the effects of grazing intensity on the spatio-temporal pattern of ALB in mixed grasslands. Overall, low to moderate grazing intensity showed increase in ALB heterogeneity whereas no change in ALB heterogeneity over time was observed for heavy grazing intensity. All grazing intensities showed decrease in spatial range (patch size) over time indicating that grazing is a patchy process. The study demonstrates that cattle grazing with variable intensity can maintain and change the spatial patterns of vegetation in the studied region. Using a modelling approach, the relative degrees to which grazing intensity and soil properties affect grassland productivity and carbon dynamics at longer time-periods were investigated. Both grass productivity and carbon dynamics are sensitive to variability in soil texture and grazing intensity. Moderate grazing is predicted to be the best option in terms of maintaining sufficient heterogeneity to support species diversity, as well as for carbon management in the mixed grassland ecosystem.
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.
Submesoscale Sea Surface Temperature Variability from UAV and Satellite Measurements
NASA Astrophysics Data System (ADS)
Castro, S. L.; Emery, W. J.; Tandy, W., Jr.; Good, W. S.
2017-12-01
Technological advances in spatial resolution of observations have revealed the importance of short-lived ocean processes with scales of O(1km). These submesoscale processes play an important role for the transfer of energy from the meso- to small scales and for generating significant spatial and temporal intermittency in the upper ocean, critical for the mixing of the oceanic boundary layer. Submesoscales have been observed in sea surface temperatures (SST) from satellites. Satellite SST measurements are spatial averages over the footprint of the satellite. When the variance of the SST distribution within the footprint is small, the average value is representative of the SST over the whole pixel. If the variance is large, the spatial heterogeneity is a source of uncertainty in satellite derived SSTs. Here we show evidence that the submesoscale variability in SSTs at spatial scales of 1km is responsible for the spatial variability within satellite footprints. Previous studies of the spatial variability in SST, using ship-based radiometric data suggested that variability at scales smaller than 1 km is significant and affects the uncertainty of satellite-derived skin SSTs. We examine data collected by a calibrated thermal infrared radiometer, the Ball Experimental Sea Surface Temperature (BESST), flown on a UAV over the Arctic Ocean and compare them with coincident measurements from the MODIS spaceborne radiometer to assess the spatial variability of SST within 1 km pixels. By taking the standard deviation of all the BESST measurements within individual MODIS pixels we show that significant spatial variability exists within the footprints. The distribution of the surface variability measured by BESST shows a peak value of O(0.1K) with 95% of the pixels showing σ < 0.45K. More importantly, high-variability pixels are located at density fronts in the marginal ice zone, which are a primary source of submesoscale intermittency near the surface in the Arctic Ocean. Wavenumber spectra of the BESST SSTs indicate a spectral slope of -2, consistent with the presence of submesoscale processes. Furthermore, not only is the BESST wavenumber spectra able to match the MODIS SST spectra well, but also extends the spectral slope of -2 by 2 decades relative to MODIS, from wavelengths of 8km to 0.08km.
NASA Astrophysics Data System (ADS)
Caras, Tamir; Hedley, John; Karnieli, Arnon
2017-12-01
Remote sensing offers a potential tool for large scale environmental surveying and monitoring. However, remote observations of coral reefs are difficult especially due to the spatial and spectral complexity of the target compared to sensor specifications as well as the environmental implications of the water medium above. The development of sensors is driven by technological advances and the desired products. Currently, spaceborne systems are technologically limited to a choice between high spectral resolution and high spatial resolution, but not both. The current study explores the dilemma of whether future sensor design for marine monitoring should prioritise on improving their spatial or spectral resolution. To address this question, a spatially and spectrally resampled ground-level hyperspectral image was used to test two classification elements: (1) how the tradeoff between spatial and spectral resolutions affects classification; and (2) how a noise reduction by majority filter might improve classification accuracy. The studied reef, in the Gulf of Aqaba (Eilat), Israel, is heterogeneous and complex so the local substrate patches are generally finer than currently available imagery. Therefore, the tested spatial resolution was broadly divided into four scale categories from five millimeters to one meter. Spectral resolution resampling aimed to mimic currently available and forthcoming spaceborne sensors such as (1) Environmental Mapping and Analysis Program (EnMAP) that is characterized by 25 bands of 6.5 nm width; (2) VENμS with 12 narrow bands; and (3) the WorldView series with broadband multispectral resolution. Results suggest that spatial resolution should generally be prioritized for coral reef classification because the finer spatial scale tested (pixel size < 0.1 m) may compensate for some low spectral resolution drawbacks. In this regard, it is shown that the post-classification majority filtering substantially improves the accuracy of all pixel sizes up to the point where the kernel size reaches the average unit size (pixel < 0.25 m). However, careful investigation as to the effect of band distribution and choice could improve the sensor suitability for the marine environment task. This in mind, while the focus in this study was on the technologically limited spaceborne design, aerial sensors may presently provide an opportunity to implement the suggested setup.
[Scale effect of Nanjing urban green infrastructure network pattern and connectivity analysis.
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.
Cheek, Brandon D.; Grabowski, Timothy B.; Bean, Preston T.; Groeschel, Jillian R.; Magnelia, Stephan J.
2016-01-01
Habitat heterogeneity at multiple scales is a major factor affecting fish assemblage structure. However, assessments that examine these relationships at multiple scales concurrently are lacking. The lack of assessments at these scales is a critical gap in understanding as conservation and restoration efforts typically work at these levels.A combination of low-cost side-scan sonar surveys, aerial imagery using an unmanned aerial vehicle, and fish collections were used to evaluate the relationship between physicochemical and landscape variables at various spatial scales (e.g. micro-mesohabitat, mesohabitat, channel unit, stream reach) and stream–fish assemblage structure and habitat associations in the South Llano River, a spring-fed second-order stream on the Edwards Plateau in central Texas during 2012–2013.Low-cost side-scan sonar surveys have not typically been used to generate data for riverscape assessments of assemblage structure, thus the secondary objective was to assess the efficacy of this approach.The finest spatial scale (micro-mesohabitat) and the intermediate scale (channel unit) had the greatest explanatory power for variation in fish assemblage structure.Many of the fish endemic to the Edwards Plateau showed similar associations with physicochemical and landscape variables suggesting that conservation and restoration actions targeting a single endemic species may provide benefits to a large proportion of the endemic species in this system.Low-cost side-scan sonar proved to be a cost-effective means of acquiring information on the habitat availability of the entire river length and allowed the assessment of how a full suite of riverscape-level variables influenced local fish assemblage structure.
Tests of landscape influence: Nest predation and brood parasitism in fragmented ecosystems
Tewksbury, J.J.; Garner, L.; Garner, S.; Lloyd, J.D.; Saab, V.; Martin, T.E.
2006-01-01
The effects of landscape fragmentation on nest predation and brood parasitism, the two primary causes of avian reproductive failure, have been difficult to generalize across landscapes, yet few studies have clearly considered the context and spatial scale of fragmentation. Working in two river systems fragmented by agricultural and rural-housing development, we tracked nesting success and brood parasitism in >2500 bird nests in 38 patches of deciduous riparian woodland. Patches on both river systems were embedded in one of two local contexts (buffered from agriculture by coniferous forest, or adjacent to agriculture), but the abundance of agriculture and human habitation within 1 km of each patch was highly variable. We examined evidence for three models of landscape effects on nest predation based on (1) the relative importance of generalist agricultural nest predators, (2) predators associated with the natural habitats typically removed by agricultural development, or (3) an additive combination of these two predator communities. We found strong support for an additive predation model in which landscape features affect nest predation differently at different spatial scales. Riparian habitat with forest buffers had higher nest predation rates than sites adjacent to agriculture, but nest predation also increased with increasing agriculture in the larger landscape surrounding each site. These results suggest that predators living in remnant woodland buffers, as well as generalist nest predators associated with agriculture, affect nest predation rates, but they appear to respond at different spatial scales. Brood parasitism, in contrast, was unrelated to agricultural abundance on the landscape, but showed a strong nonlinear relationship with farm and house density, indicating a critical point at which increased human habitat causes increased brood parasitism. Accurate predictions regarding landscape effects on nest predation and brood parasitism will require an increased appreciation of the multiple scales at which landscape components influence predator and parasite behavior. ?? 2006 by the Ecological Society of America.
Fan, Chunyu; Tan, Lingzhao; Zhang, Chunyu; Zhao, Xiuhai; von Gadow, Klaus
2017-10-30
One of the core issues of forest community ecology is the exploration of how ecological processes affect community structure. The relative importance of different processes is still under debate. This study addresses four questions: (1) how is the taxonomic structure of a forest community affected by spatial scale? (2) does the taxonomic structure reveal effects of local processes such as environmental filtering, dispersal limitation or interspecific competition at a local scale? (3) does the effect of local processes on the taxonomic structure vary with the spatial scale? (4) does the analysis based on taxonomic structures provide similar insights when compared with the use of phylogenetic information? Based on the data collected in two large forest observational field studies, the taxonomic structures of the plant communities were analyzed at different sampling scales using taxonomic ratios (number of genera/number of species, number of families/number of species), and the relationship between the number of higher taxa and the number of species. Two random null models were used and the "standardized effect size" (SES) of taxonomic ratios was calculated, to assess possible differences between the observed and simulated taxonomic structures, which may be caused by specific ecological processes. We further applied a phylogeny-based method to compare results with those of the taxonomic approach. As expected, the taxonomic ratios decline with increasing grain size. The quantitative relationship between genera/families and species, described by a linearized power function, showed a good fit. With the exception of the family-species relationship in the Jiaohe study area, the exponents of the genus/family-species relationships did not show any scale dependent effects. The taxonomic ratios of the observed communities had significantly lower values than those of the simulated random community under the test of two null models at almost all scales. Null Model 2 which considered the spatial dispersion of species generated a taxonomic structure which proved to be more consistent with that in the observed community. As sampling sizes increased from 20 m × 20 m to 50 m × 50 m, the magnitudes of SESs of taxonomic ratios increased. Based on the phylogenetic analysis, we found that the Jiaohe plot was phylogenetically clustered at almost all scales. We detected significant phylogenetically overdispersion at the 20 m × 20 m and 30 m × 30 m scales in the Liangshui plot. The results suggest that the effect of abiotic filtering is greater than the effects of interspecific competition in shaping the local community at almost all scales. Local processes influence the taxonomic structures, but their combined effects vary with the spatial scale. The taxonomic approach provides similar insights as the phylogenetic approach, especially when we applied a more conservative null model. Analysing taxonomic structure may be a useful tool for communities where well-resolved phylogenetic data are not available.
NASA Astrophysics Data System (ADS)
Bond, B. J.; Peterson, K.; McKane, R.; Lajtha, K.; Quandt, D. J.; Allen, S. T.; Sell, S.; Daly, C.; Harmon, M. E.; Johnson, S. L.; Spies, T.; Sollins, P.; Abdelnour, A. G.; Stieglitz, M.
2010-12-01
We are pursuing the ambitious goal of understanding how complex terrain influences the responses of carbon and water cycle processes to climate variability and climate change. Our studies take place in H.J. Andrews Experimental Forest, an LTER (Long Term Ecological Research) site situated in Oregon’s central-western Cascade Range. Decades of long-term measurements and intensive research have revealed influences of topography on vegetation patterns, disturbance history, and hydrology. More recent research has shown surprising interactions between microclimates and synoptic weather patterns due to cold air drainage and pooling in mountain valleys. Using these data and insights, in addition to a recent LiDAR (Light Detection and Ranging) reconnaissance and a small sensor network, we are employing process-based models, including “SPA” (Soil-Plant-Atmosphere, developed by Mathew Williams of the University of Edinburgh), and “VELMA” (Visualizing Ecosystems for Land Management Alternatives, developed by Marc Stieglitz and colleagues of the Georgia Institute of Technology) to focus on two important features of mountainous landscapes: heterogeneity (both spatial and temporal) and connectivity (atmosphere-canopy-hillslope-stream). Our research questions include: 1) Do fine-scale spatial and temporal heterogeneity result in emergent properties at the basin scale, and if so, what are they? 2) How does connectivity across ecosystem components affect system responses to climate variability and change? Initial results show that for environmental drivers that elicit non-linear ecosystem responses on the plot scale, such as solar radiation, soil depth and soil water content, fine-scale spatial heterogeneity may produce unexpected emergent properties at larger scales. The results from such modeling experiments are necessarily a function of the supporting algorithms. However, comparisons based on models such as SPA and VELMA that operate at much different spatial scales (plots vs. hillslopes) and levels of biophysical organization (individual plants vs. aggregate plant biomass) can help us to understand how and why mountainous ecosystems may have distinctive responses to climate variability and climate change.
Spatiotemporal patterns of drought at various time scales in Shandong Province of Eastern China
NASA Astrophysics Data System (ADS)
Zuo, Depeng; Cai, Siyang; Xu, Zongxue; Li, Fulin; Sun, Wenchao; Yang, Xiaojing; Kan, Guangyuan; Liu, Pin
2018-01-01
The temporal variations and spatial patterns of drought in Shandong Province of Eastern China were investigated by calculating the standardized precipitation evapotranspiration index (SPEI) at 1-, 3-, 6-, 12-, and 24-month time scales. Monthly precipitation and air temperature time series during the period 1960-2012 were collected at 23 meteorological stations uniformly distributed over the region. The non-parametric Mann-Kendall test was used to explore the temporal trends of precipitation, air temperature, and the SPEI drought index. S-mode principal component analysis (PCA) was applied to identify the spatial patterns of drought. The results showed that an insignificant decreasing trend in annual total precipitation was detected at most stations, a significant increase of annual average air temperature occurred at all the 23 stations, and a significant decreasing trend in the SPEI was mainly detected at the coastal stations for all the time scales. The frequency of occurrence of extreme and severe drought at different time scales generally increased with decades; higher frequency and larger affected area of extreme and severe droughts occurred as the time scale increased, especially for the northwest of Shandong Province and Jiaodong peninsular. The spatial pattern of drought for SPEI-1 contains three regions: eastern Jiaodong Peninsular and northwestern and southern Shandong. As the time scale increased to 3, 6, and 12 months, the order of the three regions was transformed into another as northwestern Shandong, eastern Jiaodong Peninsular, and southern Shandong. For SPEI-24, the location identified by REOF1 was slightly shifted from northwestern Shandong to western Shandong, and REOF2 and REOF3 identified another two weak patterns in the south edge and north edge of Jiaodong Peninsular, respectively. The potential causes of drought and the impact of drought on agriculture in the study area have also been discussed. The temporal variations and spatial patterns of drought obtained in this study provide valuable information for water resources planning and drought disaster prevention and mitigation in Eastern China.
Local Geographic Variation of Public Services Inequality: Does the Neighborhood Scale Matter?
Wei, Chunzhu; Cabrera-Barona, Pablo; Blaschke, Thomas
2016-01-01
This study aims to explore the effect of the neighborhood scale when estimating public services inequality based on the aggregation of social, environmental, and health-related indicators. Inequality analyses were carried out at three neighborhood scales: the original census blocks and two aggregated neighborhood units generated by the spatial “k”luster analysis by the tree edge removal (SKATER) algorithm and the self-organizing map (SOM) algorithm. Then, we combined a set of health-related public services indicators with the geographically weighted principal components analyses (GWPCA) and the principal components analyses (PCA) to measure the public services inequality across all multi-scale neighborhood units. Finally, a statistical test was applied to evaluate the scale effects in inequality measurements by combining all available field survey data. We chose Quito as the case study area. All of the aggregated neighborhood units performed better than the original census blocks in terms of the social indicators extracted from a field survey. The SKATER and SOM algorithms can help to define the neighborhoods in inequality analyses. Moreover, GWPCA performs better than PCA in multivariate spatial inequality estimation. Understanding the scale effects is essential to sustain a social neighborhood organization, which, in turn, positively affects social determinants of public health and public quality of life. PMID:27706072
Moura, Mario R; Costa, Henrique C; Argôlo, Antônio J S; Jetz, Walter
2017-09-01
The ongoing biodiversity crisis increases the importance and urgency of studies addressing the role of environmental variation on the composition and evolutionary history of species assemblages, but especially the tropics and ectotherms remain understudied. In regions with rainy summers, coexistence of tropical ectothermic species may be determined by the partitioning of the climatic niche, as ectotherms can rely on water availability and thermoregulatory behaviour to buffer constraints along their climatic niche. Conversely, tropical ectotherms facing dry summers would have fewer opportunities to climatic niche partitioning and other processes rather than environmental filtering would mediate species coexistence. We used 218 snake assemblages to quantify the compositional (CBD) and phylogenetic (PBD) beta-diversity of snakes in the Atlantic Forest (AF) hotspot, South America. We identify two AF regions with distinct climatological regimes: dry summers in the northern-AF and rainy summers in the southern-AF. While accounting for the influence of multiscale spatial processes, we disentangle the relative contribution of thermal, water-related and topographic conditions in structuring the CBD and PBD of snake assemblages, and determine the extent in which snake assemblages under distinct climatological regimes are affected by environmental filtering. Thermal conditions best explain CBD and PBD of snakes for the whole AF, whereas water-related factors best explain the structure of snake assemblages within a same climatological regime. CBD and PBD patterns are similarly explained by spatial factors but snake assemblages facing dry summers are more affected by spatial processes operating at fine to intermediate spatial scale, whereas those assemblages in regions with rainy summers have a stronger signature of coarse-scale processes. As expected, environmental filtering plays a stronger role in southern-AF than northern-AF, and the synergism between thermal and water-related conditions is the key cause behind this difference. Differences in climatological regimes within the tropics affect processes mediating species coexistence. The influence of broad-scale gradients (e.g. temperature and precipitation) in structuring tropical ectothermic assemblages is greater in regions with rainy summers where climatic niche partitioning is more likely. Our findings highlight the potential stronger role of biotic interactions and neutral processes in structuring ectothermic assemblages facing changes towards warmer and dryer climates. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.
Janine Ruegg; Walter K. Dodds; Melinda D. Daniels; Ken R. Sheehan; Christina L. Baker; William B. Bowden; Kaitlin J. Farrell; Michael B. Flinn; Tamara K. Harms; Jeremy B. Jones; Lauren E. Koenig; John S. Kominoski; William H. McDowell; Samuel P. Parker; Amy D. Rosemond; Matt T. Trentman; Matt Whiles; Wilfred M. Wollheim
2016-01-01
ContextSpatial scaling of ecological processes is facilitated by quantifying underlying habitat attributes. Physical and ecological patterns are often measured at disparate spatial scales limiting our ability to quantify ecological processes at broader spatial scales using physical attributes.
Steven P. Norman; Danny C. Lee; Sandra Jacobson; Christine Damiani
2010-01-01
The tradeoffs that surround forest management are inherently complex, often involving multiple temporal and spatial scales. For example, conflicts may result when fuel treatments are designed to mediate long-term fuel hazards, but activities could impair sensitive aquatic habitat or degrade wildlife habitat in the short term. This complexity makes it hard for managers...
Sandra L. Haire; Carol Miller; Kevin McGarigal
2015-01-01
Management activities, applied over broad scales, can potentially affect attributes of fire regimes including fire severity. Wilderness landscapes provide a natural laboratory for exploring effects of management because in some federally designated wilderness areas the burning of naturally ignited fires is promoted. In order to better understand the contribution of...
R.W. Ruess; M.D. Anderson; J.W. McFarland; K. Kielland; K. Olson; D.L. Taylor
2013-01-01
In long-lived N-fixing plants, environmental conditions affecting plant growth and N demand vary at multiple temporal and spatial scales, and symbiont assemblages on a given host and patterns of allocation to nodule activities have been shown to vary according to environmental factors, suggesting that hosts may alter partner choice and manipulate symbiont assemblages...
USDA-ARS?s Scientific Manuscript database
Much of the central grasslands region (CGR) of North America experienced a multi-year extreme drought in the 1930s that combined with land management practices to result in broad-scale plant mortality, massive dust storms, and losses of soil and nutrients. All grassland types in the CGR were affecte...
Models for mapping potential habitat at landscape scales: an example using northern spotted owls.
William C. McComb; Michael T. McGrath; Thomas A. Spies; David Vesely
2002-01-01
We are assessing the potential for current and alternative policies in the Oregon Coast Range to affect habitat capability for a suite of forest resources. We provide an example of a spatially explicit habitat capability model for northern spotted owls (Strix occidentalis caurina)to illustrate the approach we are taking to assess potential changes...
Yun Yang; Martha C. Anderson; Feng Gao; Christopher R. Hain; Kathryn A. Semmens; William P. Kustas; Asko Noormets; Randolph H. Wynne; Valerie A. Thomas; Ge Sun
2017-01-01
As a primary flux in the global water cycle, evapotranspiration (ET) connects hydrologic and biological processes and is directly affected by water and land management, land use change and climate variability. Satellite remote sensing provides an effective means for diagnosing ET patterns over heterogeneous landscapes; however, limitations on the spatial and temporal...
Frate, Ludovico; Acosta, Alicia T R; Cabido, Marcelo; Hoyos, Laura; Carranza, Maria Laura
2015-01-01
The context in which a forest exists strongly influences its function and sustainability. Unveiling the multi-scale nature of forest fragmentation context is crucial to understand how human activities affect the spatial patterns of forests across a range of scales. However, this issue remains almost unexplored in subtropical ecosystems. In this study, we analyzed temporal changes (1979-2010) in forest contexts in the Argentinean dry Chaco at multiple extents. We classified forests over the last three decades based on forest context amount (Pf) and structural connectivity (Pff), which were measured using a moving window approach fixed at eight different extents (from local, ~ 6 ha, to regional, ~ 8300 ha). Specific multi-scale forest context profiles (for the years 1979 and 2010) were defined by projecting Pf vs. Pff mean values and were compared across spatial extents. The distributions of Pf across scales were described by scalograms and their shapes over time were compared. The amount of agricultural land and rangelands across the scales were also analyzed. The dry Chaco has undergone an intensive process of fragmentation, resulting in a shift from landscapes dominated by forests with gaps of rangelands to landscapes where small forest patches are embedded in agricultural lands. Multi-scale fragmentation analysis depicted landscapes in which local exploitation, which perforates forest cover, occurs alongside extensive forest clearings, reducing forests to small and isolated patches surrounded by agricultural lands. In addition, the temporal diminution of Pf's variability along with the increment of the mean slope of the Pf 's scalograms, indicate a simplification of the spatial pattern of forest over time. The observed changes have most likely been the result of the interplay between human activities and environmental constraints, which have shaped the spatial patterns of forests across scales. Based on our results, strategies for the conservation and sustainable management of the dry Chaco should take into account both the context of each habitat location and the scales over which a forest pattern might be preserved, altered or restored.
Frate, Ludovico; Acosta, Alicia T. R.; Cabido, Marcelo; Hoyos, Laura; Carranza, Maria Laura
2015-01-01
The context in which a forest exists strongly influences its function and sustainability. Unveiling the multi-scale nature of forest fragmentation context is crucial to understand how human activities affect the spatial patterns of forests across a range of scales. However, this issue remains almost unexplored in subtropical ecosystems. In this study, we analyzed temporal changes (1979–2010) in forest contexts in the Argentinean dry Chaco at multiple extents. We classified forests over the last three decades based on forest context amount (P f) and structural connectivity (P ff), which were measured using a moving window approach fixed at eight different extents (from local, ~ 6 ha, to regional, ~ 8300 ha). Specific multi-scale forest context profiles (for the years 1979 and 2010) were defined by projecting P f vs. P ff mean values and were compared across spatial extents. The distributions of P f across scales were described by scalograms and their shapes over time were compared. The amount of agricultural land and rangelands across the scales were also analyzed. The dry Chaco has undergone an intensive process of fragmentation, resulting in a shift from landscapes dominated by forests with gaps of rangelands to landscapes where small forest patches are embedded in agricultural lands. Multi-scale fragmentation analysis depicted landscapes in which local exploitation, which perforates forest cover, occurs alongside extensive forest clearings, reducing forests to small and isolated patches surrounded by agricultural lands. In addition, the temporal diminution of P f’s variability along with the increment of the mean slope of the P f ‘s scalograms, indicate a simplification of the spatial pattern of forest over time. The observed changes have most likely been the result of the interplay between human activities and environmental constraints, which have shaped the spatial patterns of forests across scales. Based on our results, strategies for the conservation and sustainable management of the dry Chaco should take into account both the context of each habitat location and the scales over which a forest pattern might be preserved, altered or restored. PMID:26630387
Layout-aware simulation of soft errors in sub-100 nm integrated circuits
NASA Astrophysics Data System (ADS)
Balbekov, A.; Gorbunov, M.; Bobkov, S.
2016-12-01
Single Event Transient (SET) caused by charged particle traveling through the sensitive volume of integral circuit (IC) may lead to different errors in digital circuits in some cases. In technologies below 180 nm, a single particle can affect multiple devices causing multiple SET. This fact adds the complexity to fault tolerant devices design, because the schematic design techniques become useless without their layout consideration. The most common layout mitigation technique is a spatial separation of sensitive nodes of hardened circuits. Spatial separation decreases the circuit performance and increases power consumption. Spacing should thus be reasonable and its scaling follows the device dimensions' scaling trend. This paper presents the development of the SET simulation approach comprised of SPICE simulation with "double exponent" current source as SET model. The technique uses layout in GDSII format to locate nearby devices that can be affected by a single particle and that can share the generated charge. The developed software tool automatizes multiple simulations and gathers the produced data to present it as the sensitivity map. The examples of conducted simulations of fault tolerant cells and their sensitivity maps are presented in this paper.
Explaining European fungal fruiting phenology with climate variability.
Andrew, Carrie; Heegaard, Einar; Høiland, Klaus; Senn-Irlet, Beatrice; Kuyper, Thomas W; Krisai-Greilhuber, Irmgard; Kirk, Paul M; Heilmann-Clausen, Jacob; Gange, Alan C; Egli, Simon; Bässler, Claus; Büntgen, Ulf; Boddy, Lynne; Kauserud, Håvard
2018-06-01
Here we assess the impact of geographically dependent (latitude, longitude, and altitude) changes in bioclimatic (temperature, precipitation, and primary productivity) variability on fungal fruiting phenology across Europe. Two main nutritional guilds of fungi, saprotrophic and ectomycorrhizal, were further separated into spring and autumn fruiters. We used a path analysis to investigate how biogeographic patterns in fungal fruiting phenology coincided with seasonal changes in climate and primary production. Across central to northern Europe, mean fruiting varied by approximately 25 d, primarily with latitude. Altitude affected fruiting by up to 30 d, with spring delays and autumnal accelerations. Fruiting was as much explained by the effects of bioclimatic variability as by their large-scale spatial patterns. Temperature drove fruiting of autumnal ectomycorrhizal and saprotrophic groups as well as spring saprotrophic groups, while primary production and precipitation were major drivers for spring-fruiting ectomycorrhizal fungi. Species-specific phenology predictors were not stable, instead deviating from the overall mean. There is significant likelihood that further climatic change, especially in temperature, will impact fungal phenology patterns at large spatial scales. The ecological implications are diverse, potentially affecting food webs (asynchrony), nutrient cycling and the timing of nutrient availability in ecosystems. © 2018 by the Ecological Society of America.
Hernández-Martínez, Jacqueline; Morales-Malacara, Juan B; Alvarez-Añorve, Mariana Yolotl; Amador-Hernández, Sergio; Oyama, Ken; Avila-Cabadilla, Luis Daniel
2018-05-21
The anthropogenic modification of natural landscapes, and the consequent changes in the environmental conditions and resources availability at multiple spatial scales can affect complex species interactions involving key-stone species such as bat-parasite interactions. In this study, we aimed to identify the drivers potentially influencing host-bat fly interactions at different spatial scales (at the host, vegetation stand and landscape level), in a tropical anthropogenic landscape. For this purpose, we mist-netted phyllostomid and moormopid bats and collected the bat flies (streblids) parasitizing them in 10 sites representing secondary and old growth forest. In general, the variation in fly communities largely mirrored the variation in bat communities as a result of the high level of specialization characterizing host-bat fly interaction networks. Nevertheless, we observed that: (1) bats roosting dynamics can shape bat-streblid interactions, modulating parasite prevalence and the intensity of infestation; (2) a degraded matrix could favor crowding and consequently the exchange of ectoparasites among bat species, lessening the level of specialization of the interaction networks and promoting novel interactions; and (3) bat-fly interaction can also be shaped by the dilution effect, as a decrease in bat diversity could be associated with a potential increase in the dissemination and prevalence of streblids.
Catchment-scale Validation of a Physically-based, Post-fire Runoff and Erosion Model
NASA Astrophysics Data System (ADS)
Quinn, D.; Brooks, E. S.; Robichaud, P. R.; Dobre, M.; Brown, R. E.; Wagenbrenner, J.
2017-12-01
The cascading consequences of fire-induced ecological changes have profound impacts on both natural and managed forest ecosystems. Forest managers tasked with implementing post-fire mitigation strategies need robust tools to evaluate the effectiveness of their decisions, particularly those affecting hydrological recovery. Various hillslope-scale interfaces of the physically-based Water Erosion Prediction Project (WEPP) model have been successfully validated for this purpose using fire-effected plot experiments, however these interfaces are explicitly designed to simulate single hillslopes. Spatially-distributed, catchment-scale WEPP interfaces have been developed over the past decade, however none have been validated for post-fire simulations, posing a barrier to adoption for forest managers. In this validation study, we compare WEPP simulations with pre- and post-fire hydrological records for three forested catchments (W. Willow, N. Thomas, and S. Thomas) that burned in the 2011 Wallow Fire in Northeastern Arizona, USA. Simulations were conducted using two approaches; the first using automatically created inputs from an online, spatial, post-fire WEPP interface, and the second using manually created inputs which incorporate the spatial variability of fire effects observed in the field. Both approaches were compared to five years of observed post-fire sediment and flow data to assess goodness of fit.
Bird diversity along a gradient of fragmented habitats of the Cerrado.
Jesus, Shayana DE; Pedro, Wagner A; Bispo, Arthur A
2018-01-01
Understanding the factors that affect biodiversity is of central interest to ecology, and essential to species conservation and ecosystems management. We sampled bird communities in 17 forest fragments in the Cerrado biome, the Central-West region of Brazil. We aimed to know the communities structure pattern and the influence of geographical distance and environmental variables on them, along a gradient of fragmented habitats at both local and landscape scales. Eight structural variables of the fragments served as an environmental distance measurement at the local scale while five metrics served as an environmental distance measurement at the landscape scale. Species presence-absence data were used to calculate the dissimilarity index. Beta diversity was calculated using three indices (βsim, βnes and βsor), representing the spatial species turnover, nestedness and total beta diversity, respectively. Spatial species turnover was the predominant pattern in the structure of the communities. Variations in beta diversity were explained only by the environmental variables of the landscape with spatial configuration being more important than the composition. This fact indicates that, in Cerrado of Goiás avian communities structure, deterministic ecological processes associated to differences in species responses to landscape fragmentation are more important than stochastic processes driven by species dispersal.
Reuter, Kim E; Wills, Abigail R; Lee, Raymond W; Cordes, Erik E; Sewall, Brent J
2016-01-01
Human-modified habitats are expanding rapidly; many tropical countries have highly fragmented and degraded forests. Preserving biodiversity in these areas involves protecting species-like frugivorous bats-that are important to forest regeneration. Fruit bats provide critical ecosystem services including seed dispersal, but studies of how their diets are affected by habitat change have often been rather localized. This study used stable isotope analyses (δ15N and δ13C measurement) to examine how two fruit bat species in Madagascar, Pteropus rufus (n = 138) and Eidolon dupreanum (n = 52) are impacted by habitat change across a large spatial scale. Limited data for Rousettus madagascariensis are also presented. Our results indicated that the three species had broadly overlapping diets. Differences in diet were nonetheless detectable between P. rufus and E. dupreanum, and these diets shifted when they co-occurred, suggesting resource partitioning across habitats and vertical strata within the canopy to avoid competition. Changes in diet were correlated with a decrease in forest cover, though at a larger spatial scale in P. rufus than in E. dupreanum. These results suggest fruit bat species exhibit differing responses to habitat change, highlight the threats fruit bats face from habitat change, and clarify the spatial scales at which conservation efforts could be implemented.
Forests synchronize their growth in contrasting Eurasian regions in response to climate warming.
Shestakova, Tatiana A; Gutiérrez, Emilia; Kirdyanov, Alexander V; Camarero, Jesús Julio; Génova, Mar; Knorre, Anastasia A; Linares, Juan Carlos; Resco de Dios, Víctor; Sánchez-Salguero, Raúl; Voltas, Jordi
2016-01-19
Forests play a key role in the carbon balance of terrestrial ecosystems. One of the main uncertainties in global change predictions lies in how the spatiotemporal dynamics of forest productivity will be affected by climate warming. Here we show an increasing influence of climate on the spatial variability of tree growth during the last 120 y, ultimately leading to unprecedented temporal coherence in ring-width records over wide geographical scales (spatial synchrony). Synchrony in growth patterns across cold-constrained (central Siberia) and drought-constrained (Spain) Eurasian conifer forests have peaked in the early 21st century at subcontinental scales (∼ 1,000 km). Such enhanced synchrony is similar to that observed in trees co-occurring within a stand. In boreal forests, the combined effects of recent warming and increasing intensity of climate extremes are enhancing synchrony through an earlier start of wood formation and a stronger impact of year-to-year fluctuations of growing-season temperatures on growth. In Mediterranean forests, the impact of warming on synchrony is related mainly to an advanced onset of growth and the strengthening of drought-induced growth limitations. Spatial patterns of enhanced synchrony represent early warning signals of climate change impacts on forest ecosystems at subcontinental scales.
Forests synchronize their growth in contrasting Eurasian regions in response to climate warming
Shestakova, Tatiana A.; Gutiérrez, Emilia; Kirdyanov, Alexander V.; Camarero, Jesús Julio; Génova, Mar; Knorre, Anastasia A.; Linares, Juan Carlos; Sánchez-Salguero, Raúl; Voltas, Jordi
2016-01-01
Forests play a key role in the carbon balance of terrestrial ecosystems. One of the main uncertainties in global change predictions lies in how the spatiotemporal dynamics of forest productivity will be affected by climate warming. Here we show an increasing influence of climate on the spatial variability of tree growth during the last 120 y, ultimately leading to unprecedented temporal coherence in ring-width records over wide geographical scales (spatial synchrony). Synchrony in growth patterns across cold-constrained (central Siberia) and drought-constrained (Spain) Eurasian conifer forests have peaked in the early 21st century at subcontinental scales (∼1,000 km). Such enhanced synchrony is similar to that observed in trees co-occurring within a stand. In boreal forests, the combined effects of recent warming and increasing intensity of climate extremes are enhancing synchrony through an earlier start of wood formation and a stronger impact of year-to-year fluctuations of growing-season temperatures on growth. In Mediterranean forests, the impact of warming on synchrony is related mainly to an advanced onset of growth and the strengthening of drought-induced growth limitations. Spatial patterns of enhanced synchrony represent early warning signals of climate change impacts on forest ecosystems at subcontinental scales. PMID:26729860
Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands
Baldwin, Robert F.; Leonard, Paul B.
2015-01-01
Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection. PMID:26465155
Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands.
Baldwin, Robert F; Leonard, Paul B
2015-01-01
Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection.
NASA Astrophysics Data System (ADS)
Liu, Q.; Chiu, L. S.; Hao, X.
2017-10-01
The abundance or lack of rainfall affects peoples' life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007), accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG). However, the models' resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling) procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA) at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days) and monthly resolutions. The probability distributions (PDF) and cumulative distribution functions(CDF) of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS) test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.
Grid scale drives the scale and long-term stability of place maps
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
Subjective scaling of spatial room acoustic parameters influenced by visual environmental cues
Valente, Daniel L.; Braasch, Jonas
2010-01-01
Although there have been numerous studies investigating subjective spatial impression in rooms, only a few of those studies have addressed the influence of visual cues on the judgment of auditory measures. In the psychophysical study presented here, video footage of five solo music∕speech performers was shown for four different listening positions within a general-purpose space. The videos were presented in addition to the acoustic signals, which were auralized using binaural room impulse responses (BRIR) that were recorded in the same general-purpose space. The participants were asked to adjust the direct-to-reverberant energy ratio (D∕R ratio) of the BRIR according to their expectation considering the visual cues. They were also directed to rate the apparent source width (ASW) and listener envelopment (LEV) for each condition. Visual cues generated by changing the sound-source position in the multi-purpose space, as well as the makeup of the sound stimuli affected the judgment of spatial impression. Participants also scaled the direct-to-reverberant energy ratio with greater direct sound energy than was measured in the acoustical environment. PMID:20968367
Scolozzi, Rocco; Geneletti, Davide
2011-03-01
In human dominated landscapes, ecosystems are under increasing pressures caused by urbanization and infrastructure development. In Alpine valleys remnant natural areas are increasingly affected by habitat fragmentation and loss. In these contexts, there is a growing risk of local extinction for wildlife populations; hence assessing the consequences on biodiversity of proposed land use changes is extremely important. The article presents a methodology to assess the impacts of land use changes on target species at a local scale. The approach relies on the application of ecological profiles of target species for habitat potential (HP) assessment, using high resolution GIS-data within a multiple level framework. The HP, in this framework, is based on a species-specific assessment of the suitability of a site, as well of surrounding areas. This assessment is performed through spatial rules, structured as sets of queries on landscape objects. We show that by considering spatial dependencies in habitat assessment it is possible to perform better quantification of impacts of local-level land use changes on habitats.
Yang, Ying; Wang, Zhi-Hao; Jin, Sen; Gao, Di; Liu, Nan; Chen, Shan-Ping; Zhang, Sinan; Liu, Qing; Liu, Enjie; Wang, Xin; Liang, Xiao; Wei, Pengfei; Li, Xiaoguang; Li, Yin; Yue, Chenyu; Li, Hong-lian; Wang, Ya-Li; Wang, Qun; Ke, Dan; Xie, Qingguo; Xu, Fuqiang; Wang, Liping; Wang, Jian-Zhi
2016-01-01
Different emotional states lead to distinct behavioural consequences even when faced with the same challenging events. Emotions affect learning and memory capacities, but the underlying neurobiological mechanisms remain elusive. Here we establish models of learned helplessness (LHL) and learned hopefulness (LHF) by exposing animals to inescapable foot shocks or with anticipated avoidance trainings. The LHF animals show spatial memory potentiation with excitatory monosynaptic upscaling between posterior basolateral amygdale (BLP) and ventral hippocampal CA1 (vCA1), whereas the LHL show memory deficits with an attenuated BLP–vCA1 connection. Optogenetic disruption of BLP–vCA1 inputs abolishes the effects of LHF and impairs synaptic plasticity. By contrast, targeted BLP–vCA1 stimulation rescues the LHL-induced memory deficits and mimics the effects of LHF. BLP–vCA1 stimulation increases synaptic transmission and dendritic plasticity with the upregulation of CREB and intrasynaptic AMPA receptors in CA1. These findings indicate that opposite excitatory monosynaptic scaling of BLP–vCA1 controls LHF- and LHL-modulated spatial memory, revealing circuit-specific mechanisms linking emotions to memory. PMID:27411738
Yang, Ying; Wang, Zhi-Hao; Jin, Sen; Gao, Di; Liu, Nan; Chen, Shan-Ping; Zhang, Sinan; Liu, Qing; Liu, Enjie; Wang, Xin; Liang, Xiao; Wei, Pengfei; Li, Xiaoguang; Li, Yin; Yue, Chenyu; Li, Hong-Lian; Wang, Ya-Li; Wang, Qun; Ke, Dan; Xie, Qingguo; Xu, Fuqiang; Wang, Liping; Wang, Jian-Zhi
2016-07-14
Different emotional states lead to distinct behavioural consequences even when faced with the same challenging events. Emotions affect learning and memory capacities, but the underlying neurobiological mechanisms remain elusive. Here we establish models of learned helplessness (LHL) and learned hopefulness (LHF) by exposing animals to inescapable foot shocks or with anticipated avoidance trainings. The LHF animals show spatial memory potentiation with excitatory monosynaptic upscaling between posterior basolateral amygdale (BLP) and ventral hippocampal CA1 (vCA1), whereas the LHL show memory deficits with an attenuated BLP-vCA1 connection. Optogenetic disruption of BLP-vCA1 inputs abolishes the effects of LHF and impairs synaptic plasticity. By contrast, targeted BLP-vCA1 stimulation rescues the LHL-induced memory deficits and mimics the effects of LHF. BLP-vCA1 stimulation increases synaptic transmission and dendritic plasticity with the upregulation of CREB and intrasynaptic AMPA receptors in CA1. These findings indicate that opposite excitatory monosynaptic scaling of BLP-vCA1 controls LHF- and LHL-modulated spatial memory, revealing circuit-specific mechanisms linking emotions to memory.
Species dispersal rates alter diversity and ecosystem stability in pond metacommunities.
Howeth, Jennifer G; Leibold, Mathew A
2010-09-01
Metacommunity theory suggests that relationships between diversity and ecosystem stability can be determined by the rate of species dispersal among local communities. The predicted relationships, however, may depend upon the relative strength of local environmental processes and disturbance. Here we evaluate the role of dispersal frequency and local predation perturbations in affecting patterns of diversity and stability in pond plankton metacommunities. Pond metacommunities were composed of three mesocosm communities: one of the three communities maintained constant "press" predation from a selective predator, bluegill sunfish (Lepomis macrochirus); the second community maintained "press" conditions without predation; and the third community experienced recurrent "pulsed" predation from bluegill sunfish. The triads of pond communities were connected at either no, low (0.7%/d), or high (20%/d) planktonic dispersal. Richness and composition of zooplankton and stability of plankton biomass and ecosystem productivity were measured at local and regional spatial scales. Dispersal significantly affected diversity such that local and regional biotas at the low dispersal rate maintained the greatest number of species. The unimodal local dispersal-diversity relationship was predator-dependent, however, as selective press predation excluded species regardless of dispersal. Further, there was no effect of dispersal on beta diversity because predation generated local conditions that selected for distinct community assemblages. Spatial and temporal ecosystem stability responded to dispersal frequency but not predation. Low dispersal destabilized the spatial stability of producer biomass but stabilized temporal ecosystem productivity. The results indicate that selective predation can prevent species augmentation from mass effects but has no apparent influence on stability. Dispersal rates, in contrast, can have significant effects on both species diversity and ecosystem stability at multiple spatial scales in metacommunities.
Saranya, K R L; Reddy, C Sudhakar; Rao, P V V Prasada; Jha, C S
2014-05-01
Analyzing the spatial extent and distribution of forest fires is essential for sustainable forest resource management. There is no comprehensive data existing on forest fires on a regular basis in Biosphere Reserves of India. The present work have been carried out to locate and estimate the spatial extent of forest burnt areas using Resourcesat-1 data and fire frequency covering decadal fire events (2004-2013) in Similipal Biosphere Reserve. The anomalous quantity of forest burnt area was recorded during 2009 as 1,014.7 km(2). There was inconsistency in the fire susceptibility across the different vegetation types. The spatial analysis of burnt area shows that an area of 34.2 % of dry deciduous forests, followed by tree savannah, shrub savannah, and grasslands affected by fires in 2013. The analysis based on decadal time scale satellite data reveals that an area of 2,175.9 km(2) (59.6 % of total vegetation cover) has been affected by varied rate of frequency of forest fires. Fire density pattern indicates low count of burnt area patches in 2013 estimated at 1,017 and high count at 1,916 in 2004. An estimate of fire risk area over a decade identifies 12.2 km(2) is experiencing an annual fire damage. Summing the fire frequency data across the grids (each 1 km(2)) indicates 1,211 (26 %) grids are having very high disturbance regimes due to repeated fires in all the 10 years, followed by 711 grids in 9 years and 418 in 8 years and 382 in 7 years. The spatial database offers excellent opportunities to understand the ecological impact of fires on biodiversity and is helpful in formulating conservation action plans.
Optimal configurations of spatial scale for grid cell firing under noise and uncertainty
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
The importance of spatial fishing behavior for coral reef resilience
NASA Astrophysics Data System (ADS)
Rassweiler, A.; Lauer, M.; Holbrook, S. J.
2016-02-01
Coral reefs are dynamic systems in which disturbances periodically reduce coral cover but are normally followed by recovery of the coral community. However, human activity may have reduced this resilience to disturbance in many coral reef systems, as an increasing number of reefs have undergone persistent transitions from coral-dominated to macroalgal-dominated community states. Fishing on herbivores may be one cause of reduced reef resilience, as lower herbivory can make it easier for macroalgae to become established after a disturbance. Despite the acknowledged importance of fishing, relatively little attention has been paid to the potential for feedbacks between ecosystem state and fisher behavior. Here we couple methods from environmental anthropology and ecology to explore these feedbacks between small-scale fisheries and coral reefs in Moorea, French Polynesia. We document how aspects of ecological state such as the abundance of macroalgae affect people's preference for fishing in particular lagoon habitats. We then incorporate biases towards fishing in certain ecological states into a spatially explicit bio-economic model of ecological dynamics and fishing in Moorea's lagoons. We find that feedbacks between spatial fishing behavior and ecological state can have critical effects on coral reefs. Presence of these spatial behaviors consistently leads to more coherence across the reef-scape. However, whether this coherence manifests as increased resilience or increased fragility depends on the spatial scales of fisher movement and the magnitudes of disturbance. These results emphasize the potential importance of spatially-explicit fishing behavior for reef resilience, but also the complexity of the feedbacks involved.
Climate warming, marine protected areas and the ocean-scale integrity of coral reef ecosystems.
Graham, Nicholas A J; McClanahan, Tim R; MacNeil, M Aaron; Wilson, Shaun K; Polunin, Nicholas V C; Jennings, Simon; Chabanet, Pascale; Clark, Susan; Spalding, Mark D; Letourneur, Yves; Bigot, Lionel; Galzin, René; Ohman, Marcus C; Garpe, Kajsa C; Edwards, Alasdair J; Sheppard, Charles R C
2008-08-27
Coral reefs have emerged as one of the ecosystems most vulnerable to climate variation and change. While the contribution of a warming climate to the loss of live coral cover has been well documented across large spatial and temporal scales, the associated effects on fish have not. Here, we respond to recent and repeated calls to assess the importance of local management in conserving coral reefs in the context of global climate change. Such information is important, as coral reef fish assemblages are the most species dense vertebrate communities on earth, contributing critical ecosystem functions and providing crucial ecosystem services to human societies in tropical countries. Our assessment of the impacts of the 1998 mass bleaching event on coral cover, reef structural complexity, and reef associated fishes spans 7 countries, 66 sites and 26 degrees of latitude in the Indian Ocean. Using Bayesian meta-analysis we show that changes in the size structure, diversity and trophic composition of the reef fish community have followed coral declines. Although the ocean scale integrity of these coral reef ecosystems has been lost, it is positive to see the effects are spatially variable at multiple scales, with impacts and vulnerability affected by geography but not management regime. Existing no-take marine protected areas still support high biomass of fish, however they had no positive affect on the ecosystem response to large-scale disturbance. This suggests a need for future conservation and management efforts to identify and protect regional refugia, which should be integrated into existing management frameworks and combined with policies to improve system-wide resilience to climate variation and change.
Wang, You-Qi; Bai, Yi-Ru; Wang, Jian-Yu
2014-07-01
Determining spatial distributions and analyses contamination condition of soil heavy metals play an important role in evaluation of the quality of agricultural ecological environment and the protection of food safety and human health. Topsoil samples (0-20 cm) from 223 sites in farmland were collected at two scales of sampling grid (1 m x 1 m, 10 m x 10 m) in the Yellow River irrigation area of Ningxia. The objectives of this study were to investigate the spatial variability of total copper (Cu), total zinc (Zn), total chrome (Cr), total cadmium (Cd) and total lead (Pb) on the two sampling scales by the classical and geostatistical analyses. The single pollution index (P(i)) and the Nemerow pollution index (P) were used to evaluate the soil heavy metal pollution. The classical statistical analyses showed that all soil heavy metals demonstrated moderate variability, the coefficient of variation (CV) changed in the following sequence: Cd > Pb > Cr > Zn > Cu. Geostatistical analyses showed that the nugget coefficient of Cd on the 10 m x 10 m scale and Pb on the 1 m x 1 m scale were 100% with pure nugget variograms, which showed weak variability affected by random factors. The nugget coefficient of the other indexes was less than 25%, which showed a strong variability affected by structural factors. The results combined with P(i) and P indicated that most soil heavy metals have slight pollution except total copper, and in general there were the trend of heavy metal accumulation in the study area.
Menke, S.B.; Holway, D.A.; Fisher, R.N.; Jetz, W.
2009-01-01
Aim: Species distribution models (SDMs) or, more specifically, ecological niche models (ENMs) are a useful and rapidly proliferating tool in ecology and global change biology. ENMs attempt to capture associations between a species and its environment and are often used to draw biological inferences, to predict potential occurrences in unoccupied regions and to forecast future distributions under environmental change. The accuracy of ENMs, however, hinges critically on the quality of occurrence data. ENMs often use haphazardly collected data rather than data collected across the full spectrum of existing environmental conditions. Moreover, it remains unclear how processes affecting ENM predictions operate at different spatial scales. The scale (i.e. grain size) of analysis may be dictated more by the sampling regime than by biologically meaningful processes. The aim of our study is to jointly quantify how issues relating to region and scale affect ENM predictions using an economically important and ecologically damaging invasive species, the Argentine ant (Linepithema humile). Location: California, USA. Methods: We analysed the relationship between sampling sufficiency, regional differences in environmental parameter space and cell size of analysis and resampling environmental layers using two independently collected sets of presence/absence data. Differences in variable importance were determined using model averaging and logistic regression. Model accuracy was measured with area under the curve (AUC) and Cohen's kappa. Results: We first demonstrate that insufficient sampling of environmental parameter space can cause large errors in predicted distributions and biological interpretation. Models performed best when they were parametrized with data that sufficiently sampled environmental parameter space. Second, we show that altering the spatial grain of analysis changes the relative importance of different environmental variables. These changes apparently result from how environmental constraints and the sampling distributions of environmental variables change with spatial grain. Conclusions: These findings have clear relevance for biological inference. Taken together, our results illustrate potentially general limitations for ENMs, especially when such models are used to predict species occurrences in novel environments. We offer basic methodological and conceptual guidelines for appropriate sampling and scale matching. ?? 2009 The Authors Journal compilation ?? 2009 Blackwell Publishing.
Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions
NASA Astrophysics Data System (ADS)
Hwang, S.; Graham, W. D.; Geurink, J.; Adams, A.; Martinez, C. J.
2010-12-01
Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the central Florida. The hydrologic response of two southwest Florida watersheds to the gridded observation data, the original bias corrected CMIP3 data, and the new spatiotemporally corrected CMIP3 predictions was compared using an integrated surface-subsurface hydrologic model developed by Tampa Bay Water.
Animal taxa contrast in their scale-dependent responses to land use change in rural Africa.
Foord, Stefan Hendrik; Swanepoel, Lourens Hendrik; Evans, Steven William; Schoeman, Colin Stefan; Erasmus, Barend Frederik N; Schoeman, M Corrie; Keith, Mark; Smith, Alain; Mauda, Evans Vusani; Maree, Naudene; Nembudani, Nkhumeleni; Dippenaar-Schoeman, Anna Sophia; Munyai, Thinandavha Caswell; Taylor, Peter John
2018-01-01
Human-dominated landscapes comprise the bulk of the world's terrestrial surface and Africa is predicted to experience the largest relative increase over the next century. A multi-scale approach is required to identify processes that maintain diversity in these landscapes. Here we identify scales at which animal diversity responds by partitioning regional diversity in a rural African agro-ecosystem between one temporal and four spatial scales. Human land use practices are the main driver of diversity in all seven animal assemblages considered, with medium sized mammals and birds most affected. Even the least affected taxa, bats and non-volant small mammals (rodents), responded with increased abundance in settlements and agricultural sites respectively. Regional turnover was important to invertebrate taxa and their response to human land use was intermediate between that of the vertebrate extremes. Local scale (< 300 m) heterogeneity was the next most important level for all taxa, highlighting the importance of fine scale processes for the maintenance of biodiversity. Identifying the triggers of these changes within the context of functional landscapes would provide the context for the long-term sustainability of these rapidly changing landscapes.
Animal taxa contrast in their scale-dependent responses to land use change in rural Africa
Swanepoel, Lourens Hendrik; Evans, Steven William; Schoeman, Colin Stefan; Erasmus, Barend Frederik N.; Schoeman, M. Corrie; Keith, Mark; Smith, Alain; Mauda, Evans Vusani; Maree, Naudene; Nembudani, Nkhumeleni; Dippenaar-Schoeman, Anna Sophia; Munyai, Thinandavha Caswell; Taylor, Peter John
2018-01-01
Human-dominated landscapes comprise the bulk of the world’s terrestrial surface and Africa is predicted to experience the largest relative increase over the next century. A multi-scale approach is required to identify processes that maintain diversity in these landscapes. Here we identify scales at which animal diversity responds by partitioning regional diversity in a rural African agro-ecosystem between one temporal and four spatial scales. Human land use practices are the main driver of diversity in all seven animal assemblages considered, with medium sized mammals and birds most affected. Even the least affected taxa, bats and non-volant small mammals (rodents), responded with increased abundance in settlements and agricultural sites respectively. Regional turnover was important to invertebrate taxa and their response to human land use was intermediate between that of the vertebrate extremes. Local scale (< 300 m) heterogeneity was the next most important level for all taxa, highlighting the importance of fine scale processes for the maintenance of biodiversity. Identifying the triggers of these changes within the context of functional landscapes would provide the context for the long-term sustainability of these rapidly changing landscapes. PMID:29738559
Schmidt, Tom L.; Barton, Nicholas H.; Rašić, Gordana; Turley, Andrew P.; Montgomery, Brian L.; Iturbe-Ormaetxe, Inaki; Cook, Peter E.; Ryan, Peter A.; Ritchie, Scott A.; Hoffmann, Ary A.; O’Neill, Scott L.
2017-01-01
Dengue-suppressing Wolbachia strains are promising tools for arbovirus control, particularly as they have the potential to self-spread following local introductions. To test this, we followed the frequency of the transinfected Wolbachia strain wMel through Ae. aegypti in Cairns, Australia, following releases at 3 nonisolated locations within the city in early 2013. Spatial spread was analysed graphically using interpolation and by fitting a statistical model describing the position and width of the wave. For the larger 2 of the 3 releases (covering 0.97 km2 and 0.52 km2), we observed slow but steady spatial spread, at about 100–200 m per year, roughly consistent with theoretical predictions. In contrast, the smallest release (0.11 km2) produced erratic temporal and spatial dynamics, with little evidence of spread after 2 years. This is consistent with the prediction concerning fitness-decreasing Wolbachia transinfections that a minimum release area is needed to achieve stable local establishment and spread in continuous habitats. Our graphical and likelihood analyses produced broadly consistent estimates of wave speed and wave width. Spread at all sites was spatially heterogeneous, suggesting that environmental heterogeneity will affect large-scale Wolbachia transformations of urban mosquito populations. The persistence and spread of Wolbachia in release areas meeting minimum area requirements indicates the promise of successful large-scale population transformation. PMID:28557993
Schmidt, Tom L; Barton, Nicholas H; Rašić, Gordana; Turley, Andrew P; Montgomery, Brian L; Iturbe-Ormaetxe, Inaki; Cook, Peter E; Ryan, Peter A; Ritchie, Scott A; Hoffmann, Ary A; O'Neill, Scott L; Turelli, Michael
2017-05-01
Dengue-suppressing Wolbachia strains are promising tools for arbovirus control, particularly as they have the potential to self-spread following local introductions. To test this, we followed the frequency of the transinfected Wolbachia strain wMel through Ae. aegypti in Cairns, Australia, following releases at 3 nonisolated locations within the city in early 2013. Spatial spread was analysed graphically using interpolation and by fitting a statistical model describing the position and width of the wave. For the larger 2 of the 3 releases (covering 0.97 km2 and 0.52 km2), we observed slow but steady spatial spread, at about 100-200 m per year, roughly consistent with theoretical predictions. In contrast, the smallest release (0.11 km2) produced erratic temporal and spatial dynamics, with little evidence of spread after 2 years. This is consistent with the prediction concerning fitness-decreasing Wolbachia transinfections that a minimum release area is needed to achieve stable local establishment and spread in continuous habitats. Our graphical and likelihood analyses produced broadly consistent estimates of wave speed and wave width. Spread at all sites was spatially heterogeneous, suggesting that environmental heterogeneity will affect large-scale Wolbachia transformations of urban mosquito populations. The persistence and spread of Wolbachia in release areas meeting minimum area requirements indicates the promise of successful large-scale population transformation.
Coupling of Water and Carbon Cycles in Boreal Ecosystems at Watershed and National Scales
NASA Astrophysics Data System (ADS)
Chen, J. M.; Ju, W.; Govind, A.; Sonnentag, O.
2009-05-01
The boreal landscapes is relatively flat giving the impression of spatial homogeneity. However, glacial activities have left distinct fingerprints on the vegetation distribution on moderately rolling terrains over the boreal landscape. Upland or lowland forests types or wetlands having various degrees of hydrological connectivitiy to the surrounding terrain are typical of the boreal landscape. The nature of the terrain creates unique hydrological conditions affecting the local-scale ecophysiological and biogeochemical processes. As part of the Canadian Carbon Program, we investigated the importance of lateral water redistribution through surface and subsurface flows in the spatial distribution of the vertical fluxes of water and carbon. A spatially explicit hydroecological model (BEPS-TerrainLab) has been developed and tested in forested and wetland watersheds . Remotely sensed vegetation parameters along with other spatial datasets are used to run this model, and tower flux data are used for partial validation. It is demonstrated in both forest and wetland watersheds that ignoring the lateral water redistribution over the landscape, commonly done in 1-dimensional bucket models, can cause considerable biases in the vertical carbon and water flux estimation, in addition to the distortion of the spatial patterns of these fluxes. The biases in the carbon flux are considerably larger than those in the water flux. The significance of these findings in national carbon budget estimation is demonstrated by separate modeling of 2015 watersheds over the Canadian landmass.
Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie
2015-01-01
Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.
Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie
2015-01-01
Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks. PMID:26496370
Dependence of Snowmelt Simulations on Scaling of the Forcing Processes (Invited)
NASA Astrophysics Data System (ADS)
Winstral, A. H.; Marks, D. G.; Gurney, R. J.
2009-12-01
The spatial organization and scaling relationships of snow distribution in mountain environs is ultimately dependent on the controlling processes. These processes include interactions between weather, topography, vegetation, snow state, and seasonally-dependent radiation inputs. In large scale snow modeling it is vital to know these dependencies to obtain accurate predictions while reducing computational costs. This study examined the scaling characteristics of the forcing processes and the dependency of distributed snowmelt simulations to their scaling. A base model simulation characterized these processes with 10m resolution over a 14.0 km2 basin with an elevation range of 1474 - 2244 masl. Each of the major processes affecting snow accumulation and melt - precipitation, wind speed, solar radiation, thermal radiation, temperature, and vapor pressure - were independently degraded to 1 km resolution. Seasonal and event-specific results were analyzed. Results indicated that scale effects on melt vary by process and weather conditions. The dependence of melt simulations on the scaling of solar radiation fluxes also had a seasonal component. These process-based scaling characteristics should remain static through time as they are based on physical considerations. As such, these results not only provide guidance for current modeling efforts, but are also well suited to predicting how potential climate changes will affect the heterogeneity of mountain snow distributions.
NASA Astrophysics Data System (ADS)
Hübner, R.; Heller, K.; Günther, T.; Kleber, A.
2015-01-01
Besides floodplains, hillslopes are basic units that mainly control water movement and flow pathways within catchments of subdued mountain ranges. The structure of their shallow subsurface affects water balance, e.g. infiltration, retention, and runoff. Nevertheless, there is still a gap in the knowledge of the hydrological dynamics on hillslopes, notably due to the lack of generalization and transferability. This study presents a robust multi-method framework of electrical resistivity tomography (ERT) in addition to hydrometric point measurements, transferring hydrometric data into higher spatial scales to obtain additional patterns of distribution and dynamics of soil moisture on a hillslope. A geoelectrical monitoring in a small catchment in the eastern Ore Mountains was carried out at weekly intervals from May to December 2008 to image seasonal moisture dynamics on the hillslope scale. To link water content and electrical resistivity, the parameters of Archie's law were determined using different core samples. To optimize inversion parameters and methods, the derived spatial and temporal water content distribution was compared to tensiometer data. The results from ERT measurements show a strong correlation with the hydrometric data. The response is congruent to the soil tension data. Water content calculated from the ERT profile shows similar variations as that of water content from soil moisture sensors. Consequently, soil moisture dynamics on the hillslope scale may be determined not only by expensive invasive punctual hydrometric measurements, but also by minimally invasive time-lapse ERT, provided that pedo-/petrophysical relationships are known. Since ERT integrates larger spatial scales, a combination with hydrometric point measurements improves the understanding of the ongoing hydrological processes and better suits identification of heterogeneities.
Urban dogs in rural areas: Human-mediated movement defines dog populations in southern Chile.
Villatoro, Federico J; Sepúlveda, Maximiliano A; Stowhas, Paulina; Silva-Rodríguez, Eduardo A
2016-12-01
Management strategies for dog populations and their diseases include reproductive control, euthanasia and vaccination, among others. However, the effectiveness of these strategies can be severely affected by human-mediated dog movement. If immigration is important, then the location of origin of dogs imported by humans will be fundamental to define the spatial scales over which population management and research should apply. In this context, the main objective of our study was to determine the spatial extent of dog demographic processes in rural areas and the proportion of dogs that could be labeled as immigrants at multiple spatial scales. To address our objective we conducted surveys in households located in a rural landscape in southern Chile. Interviews allowed us to obtain information on the demographic characteristics of dogs in these rural settings, human influence on dog mortality and births, the localities of origin of dogs living in rural areas, and the spatial extent of human-mediated dog movement. We found that most rural dogs (64.1%) were either urban dogs that had been brought to rural areas (40.0%), or adopted dogs that had been previously abandoned in rural roads (24.1%). Some dogs were brought from areas located as far as ∼700km away from the study area. Human-mediated movement of dogs, especially from urban areas, seems to play a fundamental role in the population dynamics of dogs in rural areas. Consequently, local scale efforts to manage dog populations or their diseases are unlikely to succeed if implemented in isolation, simply because dogs can be brought from surrounding urban areas or even distant locations. We suggest that efforts to manage or study dog populations and related diseases should be implemented using a multi-scale approach. Copyright © 2016 Elsevier B.V. All rights reserved.
On the Lamb vector divergence as a momentum field diagnostic employed in turbulent channel flow
NASA Astrophysics Data System (ADS)
Hamman, Curtis W.; Kirby, Robert M.; Klewicki, Joseph C.
2006-11-01
Vorticity, enstrophy, helicity, and other derived field variables provide invaluable information about the kinematics and dynamics of fluids. However, whether or not derived field variables exist that intrinsically identify spatially localized motions having a distinct capacity to affect a time rate of change of linear momentum is seldom addressed in the literature. The purpose of the present study is to illustrate the unique attributes of the divergence of the Lamb vector in order to qualify its potential for characterizing such spatially localized motions. Toward this aim, we describe the mathematical properties, near-wall behavior, and scaling characteristics of the divergence of the Lamb vector for turbulent channel flow. When scaled by inner variables, the mean divergence of the Lamb vector merges to a single curve in the inner layer, and the fluctuating quantities exhibit a strong correlation with the Bernoulli function throughout much of the inner layer.
NASA Technical Reports Server (NTRS)
Yurchak, Boris S.
2010-01-01
The study of the collective effects of radar scattering from an aggregation of discrete scatterers randomly distributed in a space is important for better understanding the origin of the backscatter from spatially extended geophysical targets (SEGT). We consider the microstructure irregularities of a SEGT as the essential factor that affect radar backscatter. To evaluate their contribution this study uses the "slice" approach: particles close to the front of incident radar wave are considered to reflect incident electromagnetic wave coherently. The radar equation for a SEGT is derived. The equation includes contributions to the total backscatter from correlated small-scale fluctuations of the slice's reflectivity. The correlation contribution changes in accordance with an earlier proposed idea by Smith (1964) based on physical consideration. The slice approach applied allows parameterizing the features of the SEGT's inhomogeneities.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dale, Virginia H; Kline, Keith L; Kaffka, Stephen R
Landscape sustainability of agricultural systems considers effects of farm activities on social, economic, and ecosystem services at local and regional scales. Sustainable agriculture entails: defining sustainability, developing easily measured indicators of sustainability, moving toward integrated agricultural systems, and offering incentives or imposing regulations to affect farmer behavior. A landscape perspective is useful because landscape ecology provides theory and methods for dealing with spatial heterogeneity, scaling, integration, and complexity. To implement agricultural sustainability, we propose adopting a systems perspective, recognizing spatial heterogeneity, addressing the influences of context, and integrating landscape-design principles. Topics that need further attention at local and regional scalesmore » include (1) protocols for quantifying material and energy flows; (2) effects of management practices; (3) incentives for enhancing social, economic, and ecosystem services; (4) integrated landscape planning and management; (5) monitoring and assessment; (6) effects of societal demand; and (7) consistent and holistic policies for promoting agricultural sustainability.« less
Prioritizing conservation investments for mammal species globally
Wilson, Kerrie A.; Evans, Megan C.; Di Marco, Moreno; Green, David C.; Boitani, Luigi; Possingham, Hugh P.; Chiozza, Federica; Rondinini, Carlo
2011-01-01
We need to set priorities for conservation because we cannot do everything, everywhere, at the same time. We determined priority areas for investment in threat abatement actions, in both a cost-effective and spatially and temporally explicit way, for the threatened mammals of the world. Our analysis presents the first fine-resolution prioritization analysis for mammals at a global scale that accounts for the risk of habitat loss, the actions required to abate this risk, the costs of these actions and the likelihood of investment success. We evaluated the likelihood of success of investments using information on the past frequency and duration of legislative effectiveness at a country scale. The establishment of new protected areas was the action receiving the greatest investment, while restoration was never chosen. The resolution of the analysis and the incorporation of likelihood of success made little difference to this result, but affected the spatial location of these investments. PMID:21844046
A task-irrelevant stimulus attribute affects perception and short-term memory
Huang, Jie; Kahana, Michael J.; Sekuler, Robert
2010-01-01
Selective attention protects cognition against intrusions of task-irrelevant stimulus attributes. This protective function was tested in coordinated psychophysical and memory experiments. Stimuli were superimposed, horizontally and vertically oriented gratings of varying spatial frequency; only one orientation was task relevant. Experiment 1 demonstrated that a task-irrelevant spatial frequency interfered with visual discrimination of the task-relevant spatial frequency. Experiment 2 adopted a two-item Sternberg task, using stimuli that had been scaled to neutralize interference at the level of vision. Despite being visually neutralized, the task-irrelevant attribute strongly influenced recognition accuracy and associated reaction times (RTs). This effect was sharply tuned, with the task-irrelevant spatial frequency having an impact only when the task-relevant spatial frequencies of the probe and study items were highly similar to one another. Model-based analyses of judgment accuracy and RT distributional properties converged on the point that the irrelevant orientation operates at an early stage in memory processing, not at a later one that supports decision making. PMID:19933454
Deciphering the Costs of Reproduction in Mango – Vegetative Growth Matters
Capelli, Mathilde; Lauri, Pierre-Éric; Normand, Frédéric
2016-01-01
Irregular fruit production across successive years is a major issue that limits the profitability of most temperate and tropical fruit crops. It is particularly affected by the reciprocal relationships between vegetative and reproductive growth. The concept of the costs of reproduction is defined in terms of losses in the potential future reproductive success caused by current investment in reproduction. This concept, developed in ecology and evolutionary biology, could provide a methodological framework to analyze irregular bearing in fruit crops, especially in relation to the spatial scale at which studies are done. The objective of this study was to investigate the direct effects of reproduction during a growing cycle on reproduction during the following growing cycle and the indirect effects through vegetative growth between these two reproductive events, for four mango cultivars and during two growing cycles. Two spatial scales were considered: the growth unit (GU) and the scaffold branch. Costs of reproduction were detected between two successive reproductive events and between reproduction and vegetative growth. These costs were scale-dependent, generally detected at the GU scale and infrequently at the scaffold branch scale, suggesting partial branch autonomy with respect to processes underlying the effects of reproduction on vegetative growth. In contrast, the relationships between vegetative growth and reproduction were positive at the GU scale and at the scaffold branch scale in most cases, suggesting branch autonomy for the processes, mainly local, underlying flowering and fruiting. The negative effect of reproduction on vegetative growth prevailed over the positive effect of vegetative growth on the subsequent reproduction. The costs of reproduction were also cultivar-dependent. Those revealed at the GU scale were related to the bearing behavior of each cultivar. Our results put forward the crucial role of vegetative growth occurring between two reproductive events. They are discussed in the context of irregular bearing considering both the spatial scale and the various bearing habits of the mango cultivars, in order to formulate new hypotheses about this issue. PMID:27818665
Brakebill, J.W.; Wolock, D.M.; Terziotti, S.E.
2011-01-01
Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based/statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.
NASA Astrophysics Data System (ADS)
Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.
2017-12-01
In the Brazilian rainforest-savanna transition zone, deforestation has the potential to significantly affect rainfall by disrupting rainfall recycling, the process by which regional evapotranspiration contributes to regional rainfall. Understanding rainfall recycling in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching, agriculture, hydropower generation, and drinking water management. Simulations in previous studies suggest complex, scale-dependent interactions between forest cover connectivity and rainfall. For example, the size and distribution of deforested patches has been found to affect rainfall quantity and spatial distribution. Here we take an empirical approach, using the spatial connectivity of rainfall as an indicator of rainfall recycling, to ask: as forest cover connectivity decreased from 1981 - 2015, how did the spatial connectivity of rainfall change in the Brazilian rainforest-savanna transition zone? We use satellite forest cover and rainfall data covering this period of intensive forest cover loss in the region (forest cover from the Hansen Global Forest Change dataset; rainfall from the Climate Hazards Infrared Precipitation with Stations dataset). Rainfall spatial connectivity is quantified using transfer entropy, a metric from information theory, and summarized using network statistics. Networks of connectivity are quantified for paired deforested and non-deforested regions before deforestation (1981-1995) and during/after deforestation (2001-2015). Analyses reveal a decline in spatial connectivity networks of rainfall following deforestation.
Accounting for Rainfall Spatial Variability in Prediction of Flash Floods
NASA Astrophysics Data System (ADS)
Saharia, M.; Kirstetter, P. E.; Gourley, J. J.; Hong, Y.; Vergara, H. J.
2016-12-01
Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 20,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. Next the model is used to predict flash flooding characteristics all over the continental U.S., specifically over regions poorly covered by hydrological observations. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).
Accounting for rainfall spatial variability in the prediction of flash floods
NASA Astrophysics Data System (ADS)
Saharia, Manabendra; Kirstetter, Pierre-Emmanuel; Gourley, Jonathan J.; Hong, Yang; Vergara, Humberto; Flamig, Zachary L.
2017-04-01
Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 15,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. The database has been subjected to rigorous quality control by accounting for radar beam height and percentage snow in basins. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a historical flood fatalities database. This analysis framework will serve as a baseline for evaluating distributed hydrologic model simulations such as the Flooded Locations And Simulated Hydrographs Project (FLASH) (http://flash.ou.edu).
Spatial heterogeneity study of vegetation coverage at Heihe River Basin
NASA Astrophysics Data System (ADS)
Wu, Lijuan; Zhong, Bo; Guo, Liyu; Zhao, Xiangwei
2014-11-01
Spatial heterogeneity of the animal-landscape system has three major components: heterogeneity of resource distributions in the physical environment, heterogeneity of plant tissue chemistry, heterogeneity of movement modes by the animal. Furthermore, all three different types of heterogeneity interact each other and can either reinforce or offset one another, thereby affecting system stability and dynamics. In previous studies, the study areas are investigated by field sampling, which costs a large amount of manpower. In addition, uncertain in sampling affects the quality of field data, which leads to unsatisfactory results during the entire study. In this study, remote sensing data is used to guide the sampling for research on heterogeneity of vegetation coverage to avoid errors caused by randomness of field sampling. Semi-variance and fractal dimension analysis are used to analyze the spatial heterogeneity of vegetation coverage at Heihe River Basin. The spherical model with nugget is used to fit the semivariogram of vegetation coverage. Based on the experiment above, it is found, (1)there is a strong correlation between vegetation coverage and distance of vegetation populations within the range of 0-28051.3188m at Heihe River Basin, but the correlation loses suddenly when the distance greater than 28051.3188m. (2)The degree of spatial heterogeneity of vegetation coverage at Heihe River Basin is medium. (3)Spatial distribution variability of vegetation occurs mainly on small scales. (4)The degree of spatial autocorrelation is 72.29% between 25% and 75%, which means that spatial correlation of vegetation coverage at Heihe River Basin is medium high.
NASA Astrophysics Data System (ADS)
Matsui, H.; Koike, M.; Kondo, Y.; Takegawa, N.; Kita, K.; Miyazaki, Y.; Hu, M.; Chang, S.-Y.; Blake, D. R.; Fast, J. D.; Zaveri, R. A.; Streets, D. G.; Zhang, Q.; Zhu, T.
2009-01-01
Regional aerosol model calculations were made using the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) and WRF-chem models to study spatial and temporal variations of aerosols around Beijing, China, in the summer of 2006, when the Campaigns of Air Quality Research in Beijing and Surrounding Region 2006 (CAREBeijing) intensive campaign was conducted. Model calculations captured temporal variations of primary (such as elemental carbon (EC)) and secondary (such as sulfate) aerosols observed in and around Beijing. The spatial distributions of aerosol optical depth observed by the MODIS satellite sensors were also reproduced over northeast China. Model calculations showed distinct differences in spatial distributions between primary and secondary aerosols in association with synoptic-scale meteorology. Secondary aerosols increased in air around Beijing on a scale of about 1000 × 1000 km2 under an anticyclonic pressure system. This air mass was transported northward from the high anthropogenic emission area extending south of Beijing with continuous photochemical production. Subsequent cold front passage brought clean air from the north, and polluted air around Beijing was swept to the south of Beijing. This cycle was repeated about once a week and was found to be responsible for observed enhancements/reductions of aerosols at the intensive measurement sites. In contrast to secondary aerosols, the spatial distributions of primary aerosols (EC) reflected those of emissions, resulting in only slight variability despite the changes in synoptic-scale meteorology. In accordance with these results, source apportionment simulations revealed that primary aerosols around Beijing were controlled by emissions within 100 km around Beijing within the preceding 24 h, while emissions as far as 500 km and within the preceding 3 days were found to affect secondary aerosols.
Forecasting of extreme events in Andes mountain basins using CFSv2
NASA Astrophysics Data System (ADS)
Castro, L.
2017-12-01
As has been shown in several recent studies related with climate change, there has been an increase in heavy daily precipitation events, and this is expected to continue in almost all areas of the globe. In central Chile, where the hydrological regime is influenced by snow accumulation, an increase in temperatures is expected due to CC, which in turn may cause an elevation of the freezing level. The impact on the freezing level increase is also significant because a larger area of the basin will be exposed to liquid precipitation rather than snow, and afterwards will have a strong impact on streamflow. The frequency of extreme precipitation events and freezing level increases have recently affected the north and central parts of Chile. In order to predict the severity of an extreme hydrometeorological event in a mountainous basin affected by rainfall and freezing level variations, this paper pose that it is necessary to know in advance the expected meteorology and the way it will affect the hydrological response of the basin. To achieve this purpose, it will be necessary to have meteorological forecasts of a numerical model for short-term prediction, corrected and disaggregated at local scale. The methodological process is as follows. First, we consider the generation of daily forecasts at local scale using statistical downscaling methods for the forecasts obtained from an NWP model. Second, we pose to improve our knowledge the spatial-temporal distribution of the meteorological forcings using a dense network of meteorological stations in a mountain basin. With the above, the statistical methods used to represent the spatial-temporal variability of the meteorological forcings at basin scale will be evaluated.
Forest gradient response in Sierran landscapes: the physical template
Urban, Dean L.; Miller, Carol; Halpin, Patrick N.; Stephenson, Nathan L.
2000-01-01
Vegetation pattern on landscapes is the manifestation of physical gradients, biotic response to these gradients, and disturbances. Here we focus on the physical template as it governs the distribution of mixed-conifer forests in California's Sierra Nevada. We extended a forest simulation model to examine montane environmental gradients, emphasizing factors affecting the water balance in these summer-dry landscapes. The model simulates the soil moisture regime in terms of the interaction of water supply and demand: supply depends on precipitation and water storage, while evapotranspirational demand varies with solar radiation and temperature. The forest cover itself can affect the water balance via canopy interception and evapotranspiration. We simulated Sierran forests as slope facets, defined as gridded stands of homogeneous topographic exposure, and verified simulated gradient response against sample quadrats distributed across Sequoia National Park. We then performed a modified sensitivity analysis of abiotic factors governing the physical gradient. Importantly, the model's sensitivity to temperature, precipitation, and soil depth varies considerably over the physical template, particularly relative to elevation. The physical drivers of the water balance have characteristic spatial scales that differ by orders of magnitude. Across large spatial extents, temperature and precipitation as defined by elevation primarily govern the location of the mixed conifer zone. If the analysis is constrained to elevations within the mixed-conifer zone, local topography comes into play as it influences drainage. Soil depth varies considerably at all measured scales, and is especially dominant at fine (within-stand) scales. Physical site variables can influence soil moisture deficit either by affecting water supply or water demand; these effects have qualitatively different implications for forest response. These results have clear implications about purely inferential approaches to gradient analysis, and bear strongly on our ability to use correlative approaches in assessing the potential responses of montane forests to anthropogenic climatic change.
Agent Based Modeling: Fine-Scale Spatio-Temporal Analysis of Pertussis
NASA Astrophysics Data System (ADS)
Mills, D. A.
2017-10-01
In epidemiology, spatial and temporal variables are used to compute vaccination efficacy and effectiveness. The chosen resolution and scale of a spatial or spatio-temporal analysis will affect the results. When calculating vaccination efficacy, for example, a simple environment that offers various ideal outcomes is often modeled using coarse scale data aggregated on an annual basis. In contrast to the inadequacy of this aggregated method, this research uses agent based modeling of fine-scale neighborhood data centered around the interactions of infants in daycare and their families to demonstrate an accurate reflection of vaccination capabilities. Despite being able to prevent major symptoms, recent studies suggest that acellular Pertussis does not prevent the colonization and transmission of Bordetella Pertussis bacteria. After vaccination, a treated individual becomes a potential asymptomatic carrier of the Pertussis bacteria, rather than an immune individual. Agent based modeling enables the measurable depiction of asymptomatic carriers that are otherwise unaccounted for when calculating vaccination efficacy and effectiveness. Using empirical data from a Florida Pertussis outbreak case study, the results of this model demonstrate that asymptomatic carriers bias the calculated vaccination efficacy and reveal a need for reconsidering current methods that are widely used for calculating vaccination efficacy and effectiveness.
Local loss and spatial homogenization of plant diversity reduce ecosystem multifunctionality.
Hautier, Yann; Isbell, Forest; Borer, Elizabeth T; Seabloom, Eric W; Harpole, W Stanley; Lind, Eric M; MacDougall, Andrew S; Stevens, Carly J; Adler, Peter B; Alberti, Juan; Bakker, Jonathan D; Brudvig, Lars A; Buckley, Yvonne M; Cadotte, Marc; Caldeira, Maria C; Chaneton, Enrique J; Chu, Chengjin; Daleo, Pedro; Dickman, Christopher R; Dwyer, John M; Eskelinen, Anu; Fay, Philip A; Firn, Jennifer; Hagenah, Nicole; Hillebrand, Helmut; Iribarne, Oscar; Kirkman, Kevin P; Knops, Johannes M H; La Pierre, Kimberly J; McCulley, Rebecca L; Morgan, John W; Pärtel, Meelis; Pascual, Jesus; Price, Jodi N; Prober, Suzanne M; Risch, Anita C; Sankaran, Mahesh; Schuetz, Martin; Standish, Rachel J; Virtanen, Risto; Wardle, Glenda M; Yahdjian, Laura; Hector, Andy
2018-01-01
Biodiversity is declining in many local communities while also becoming increasingly homogenized across space. Experiments show that local plant species loss reduces ecosystem functioning and services, but the role of spatial homogenization of community composition and the potential interaction between diversity at different scales in maintaining ecosystem functioning remains unclear, especially when many functions are considered (ecosystem multifunctionality). We present an analysis of eight ecosystem functions measured in 65 grasslands worldwide. We find that more diverse grasslands-those with both species-rich local communities (α-diversity) and large compositional differences among localities (β-diversity)-had higher levels of multifunctionality. Moreover, α- and β-diversity synergistically affected multifunctionality, with higher levels of diversity at one scale amplifying the contribution to ecological functions at the other scale. The identity of species influencing ecosystem functioning differed among functions and across local communities, explaining why more diverse grasslands maintained greater functionality when more functions and localities were considered. These results were robust to variation in environmental drivers. Our findings reveal that plant diversity, at both local and landscape scales, contributes to the maintenance of multiple ecosystem services provided by grasslands. Preserving ecosystem functioning therefore requires conservation of biodiversity both within and among ecological communities.
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.
Curvature constraints from large scale structure
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dio, Enea Di; Montanari, Francesco; Raccanelli, Alvise
We modified the CLASS code in order to include relativistic galaxy number counts in spatially curved geometries; we present the formalism and study the effect of relativistic corrections on spatial curvature. The new version of the code is now publicly available. Using a Fisher matrix analysis, we investigate how measurements of the spatial curvature parameter Ω {sub K} with future galaxy surveys are affected by relativistic effects, which influence observations of the large scale galaxy distribution. These effects include contributions from cosmic magnification, Doppler terms and terms involving the gravitational potential. As an application, we consider angle and redshift dependentmore » power spectra, which are especially well suited for model independent cosmological constraints. We compute our results for a representative deep, wide and spectroscopic survey, and our results show the impact of relativistic corrections on spatial curvature parameter estimation. We show that constraints on the curvature parameter may be strongly biased if, in particular, cosmic magnification is not included in the analysis. Other relativistic effects turn out to be subdominant in the studied configuration. We analyze how the shift in the estimated best-fit value for the curvature and other cosmological parameters depends on the magnification bias parameter, and find that significant biases are to be expected if this term is not properly considered in the analysis.« less
Optimal Scaling of Aftershock Zones using Ground Motion Forecasts
NASA Astrophysics Data System (ADS)
Wilson, John Max; Yoder, Mark R.; Rundle, John B.
2018-02-01
The spatial distribution of aftershocks following major earthquakes has received significant attention due to the shaking hazard these events pose for structures and populations in the affected region. Forecasting the spatial distribution of aftershock events is an important part of the estimation of future seismic hazard. A simple spatial shape for the zone of activity has often been assumed in the form of an ellipse having semimajor axis to semiminor axis ratio of 2.0. However, since an important application of these calculations is the estimation of ground shaking hazard, an effective criterion for forecasting future aftershock impacts is to use ground motion prediction equations (GMPEs) in addition to the more usual approach of using epicentral or hypocentral locations. Based on these ideas, we present an aftershock model that uses self-similarity and scaling relations to constrain parameters as an option for such hazard assessment. We fit the spatial aspect ratio to previous earthquake sequences in the studied regions, and demonstrate the effect of the fitting on the likelihood of post-disaster ground motion forecasts for eighteen recent large earthquakes. We find that the forecasts in most geographic regions studied benefit from this optimization technique, while some are better suited to the use of the a priori aspect ratio.
Mack, Keenan M L; Bever, James D
2014-09-01
1. Negative plant-soil feedback occurs when the presence of an individual of a particular species at a particular site decreases the relative success of individuals of the same species compared to those other species at that site. This effect favors heterospecifics thereby facilitating coexistence and maintaining diversity. Empirical work has demonstrated that the average strengths of these feedbacks correlate with the relative abundance of species within a community, suggesting that feedbacks are an important driver of plant community composition. Understanding what factors contribute to the generation of this relationship is necessary for diagnosing the dynamic forces that maintain diversity in plant communities. 2. We used a spatially explicit, individual-based computer simulation to test the effects of dispersal distance, the size of feedback neighbourhoods, the strength of pairwise feedbacks and community wide variation of feedbacks, community richness, as well as life-history differences on the dependence of relative abundance on strength of feedback. 3. We found a positive dependence of relative abundance of a species on its average feedback for local scale dispersal and feedback. However, we found that the strength of this dependence decreased as either the spatial scale of dispersal and/or the spatial scale of feedback increased. We also found that for spatially local (i.e. relatively small) scale interaction and dispersal, as the mean strength of feedbacks in the community becomes less negative, the greater the increase in abundance produced by a comparable increase in species-specific average feedback. We found that life-history differences such as mortality rate did not generate a pattern with abundance, nor did they affect the relationship between abundance and average feedback. 4. Synthesis . Our results support the claim that empirical observations of a positive correlation between relative abundance and strength of average feedback serves as evidence that local scale negative feedbacks play a prominent role in structuring plant communities. We also identify that this relationship depends upon local scale plant dispersal and feedback which generates clumping and magnifies the negative feedbacks.
“Modeling Trends in Air Pollutant Concentrations over the ...
Regional model calculations over annual cycles have pointed to the need for accurately representing impacts of long-range transport. Linking regional and global scale models have met with mixed success as biases in the global model can propagate and influence regional calculations and often confound interpretation of model results. Since transport is efficient in the free-troposphere and since simulations over Continental scales and annual cycles provide sufficient opportunity for “atmospheric turn-over”, i.e., exchange between the free-troposphere and the boundary-layer, a conceptual framework is needed wherein interactions between processes occurring at various spatial and temporal scales can be consistently examined. The coupled WRF-CMAQ model is expanded to hemispheric scales and model simulations over period spanning 1990-current are analyzed to examine changes in hemispheric air pollution resulting from changes in emissions over this period. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for pr
NASA Astrophysics Data System (ADS)
Hu, Z.
2017-12-01
Climate change is predicted to cause dramatic variability in precipitation regime, not only in terms of change in annual precipitation amount, but also in precipitation seasonal distribution and precipitation event characteristics (high frenquency extrem precipitation, larger but fewer precipitation events), which combined to influence productivity of grassland in arid and semiarid regions. In this study, combining remote sensing products with in-situ measurements of aboveground net primary productivity (ANPP) and gross primary productivity (GPP) data from eddy covariance system in grassland of northern China, we quantified the effects of spatio-temporal vairation in precipitation on productivity from local sites to region scale. We found that, for an individual precipitation event, the duration of GPP-response to the individual precipitation event and the maximum absolute GPP response induced by the individual precipitation event increased linearly with the size of precipitation events. Comparison of the productivity-precipitation relationships between multi-sites determined that the predominant characteristics of precipitation events (PEC) that affected GPP differed remarkably between the water-limited temperate steppe and the temperature-limited alpine meadow. The number of heavy precipitation events (>10 mm d-1) was the most important PEC to impact GPP in the temperate steppe through affecting soil moisture at different soil profiles, while precipitation interval was the factor that affected GPP most in the alpine meadow via its effects on temperature. At the region scale, shape of ANPP-precipitation relationship varies with distinct spatial scales, and besides annual precipitation, precipitation seasonal distribution also has comparable impacts on spatial variation in ANPP. Temporal variability in ANPP was lower at both the dry and wet end, and peaked at a precipitation of 243.1±3.5mm, which is the transition region between typical steppe and desert steppe. Our work has important implications to obtain an advanced understanding of productivity-response of grassland ecosystems to altered precipitation regimes.
NASA Astrophysics Data System (ADS)
Tzanis, Andreas
2013-02-01
The Ground Probing Radar (GPR) is a valuable tool for near surface geological, geotechnical, engineering, environmental, archaeological and other work. GPR images of the subsurface frequently contain geometric information (constant or variable-dip reflections) from various structures such as bedding, cracks, fractures, etc. Such features are frequently the target of the survey; however, they are usually not good reflectors and they are highly localized in time and in space. Their scale is therefore a factor significantly affecting their detectability. At the same time, the GPR method is very sensitive to broadband noise from buried small objects, electromagnetic anthropogenic activity and systemic factors, which frequently blurs the reflections from such targets. This paper introduces a method to de-noise GPR data and extract geometric information from scale-and-dip dependent structural features, based on one-dimensional B-Spline Wavelets, two-dimensional directional B-Spline Wavelet (BSW) Filters and two-dimensional Gabor Filters. A directional BSW Filter is built by sidewise arranging s identical one-dimensional wavelets of length L, tapering the s-parallel direction (span) with a suitable window function and rotating the resulting matrix to the desired orientation. The length L of the wavelet defines the temporal and spatial scale to be isolated and the span determines the length over which to smooth (spatial resolution). The Gabor Filter is generated by multiplying an elliptical Gaussian by a complex plane wave; at any orientation the temporal or spatial scale(s) to be isolated are determined by the wavelength. λ of the plane wave and the spatial resolution by the spatial aspect ratio γ, which specifies the ellipticity of the support of the Gabor function. At any orientation, both types of filter may be tuned at any frequency or spatial wavenumber by varying the length or the wavelength respectively. The filters can be applied directly to two-dimensional radargrams, in which case they abstract information about given scales at given orientations. Alternatively, they can be rotated to different orientations under adaptive control, so that they remain tuned at a given frequency or wavenumber and the resulting images can be stacked in the LS sense, so as to obtain a complete representation of the input data at a given temporal or spatial scale. In addition to isolating geometrical information for further scrutiny, the proposed filtering methods can be used to enhance the S/N ratio in a manner particularly suitable for GPR data, because the frequency response of the filters mimics the frequency characteristics of the source wavelet. Finally, signal attenuation and temporal localization are closely associated: low attenuation interfaces tend to produce reflections rich in high frequencies and fine-scale localization as a function of time. Conversely, high attenuation interfaces will produce reflections rich in low frequencies and broad localization. Accordingly, the temporal localization characteristics of the filters may be exploited to investigate the characteristics of signal propagation (hence material properties). The method is shown to be very effective in extracting fine to coarse scale information from noisy data and is demonstrated with applications to noisy GPR data from archaeometric and geotechnical surveys.
NASA Astrophysics Data System (ADS)
Mount, G. J.; Comas, X.; Wright, W. J.; McClellan, M. D.
2014-12-01
Hydrogeologic characterization of karst limestone aquifers is difficult due to the variability in the spatial distribution of porosity and dissolution features. Typical methods for aquifer investigation, such as drilling and pump testing, are limited by the scale or spatial extent of the measurement. Hydrogeophysical techniques such as ground penetrating radar (GPR) can provide indirect measurements of aquifer properties and be expanded spatially beyond typical point measures. This investigation used a multiscale approach to identify and quantify porosity distribution in the Miami Limestone, the lithostratigraphic unit that composes the uppermost portions of the Biscayne Aquifer in Miami Dade County, Florida. At the meter scale, laboratory measures of porosity and dielectric permittivity were made on blocks of Miami Limestone using zero offset GPR, laboratory and digital image techniques. Results show good correspondence between GPR and analytical porosity estimates and show variability between 22 and 66 %. GPR measurements at the field scale 10-1000 m investigated the bulk porosity of the limestone based on the assumption that a directly measured water table would remain at a consistent depth in the GPR reflection record. Porosity variability determined from the changes in the depth to water table resulted in porosity values that ranged from 33 to 61 %, with the greatest porosity variability being attributed to the presence of dissolution features. At the larger field scales, 100 - 1000 m, fitting of hyperbolic diffractions in GPR common offsets determined the vertical and horizontal variability of porosity in the saturated subsurface. Results indicate that porosity can vary between 23 and 41 %, and delineate potential areas of enhanced recharge or groundwater / surface water interactions. This study shows porosity variability in the Miami Limestone can range from 22 to 66 % within 1.5 m distances, with areas of high macroporosity or karst dissolution features occupying the higher end of the range. Spatial variability in porosity distribution may affect ground water recharge, allowing zones of high porosity and thus enhanced infiltration to concentrate contaminants into the aquifer and may play a role in small and regional scale aquifer models.
High resolution climate scenarios for snowmelt modelling in small alpine catchments
NASA Astrophysics Data System (ADS)
Schirmer, M.; Peleg, N.; Burlando, P.; Jonas, T.
2017-12-01
Snow in the Alps is affected by climate change with regard to duration, timing and amount. This has implications with respect to important societal issues as drinking water supply or hydropower generation. In Switzerland, the latter received a lot of attention following the political decision to phase out of nuclear electricity production. An increasing number of authorization requests for small hydropower plants located in small alpine catchments was observed in the recent years. This situation generates ecological conflicts, while the expected climate change poses a threat to water availability thus putting at risk investments in such hydropower plants. Reliable high-resolution climate scenarios are thus required, which account for small-scale processes to achieve realistic predictions of snowmelt runoff and its variability in small alpine catchments. We therefore used a novel model chain by coupling a stochastic 2-dimensional weather generator (AWE-GEN-2d) with a state-of-the-art energy balance snow cover model (FSM). AWE-GEN-2d was applied to generate ensembles of climate variables at very fine temporal and spatial resolution, thus providing all climatic input variables required for the energy balance modelling. The land-surface model FSM was used to describe spatially variable snow cover accumulation and melt processes. The FSM was refined to allow applications at very high spatial resolution by specifically accounting for small-scale processes, such as a subgrid-parametrization of snow covered area or an improved representation of forest-snow processes. For the present study, the model chain was tested for current climate conditions using extensive observational dataset of different spatial and temporal coverage. Small-scale spatial processes such as elevation gradients or aspect differences in the snow distribution were evaluated using airborne LiDAR data. 40-year of monitoring data for snow water equivalent, snowmelt and snow-covered area for entire Switzerland was used to verify snow distribution patterns at coarser spatial and temporal scale. The ability of the model chain to reproduce current climate conditions in small alpine catchments makes this model combination an outstanding candidate to produce high resolution climate scenarios of snowmelt in small alpine catchments.
Wang, Hongqing; Chen, Qin; Hu, Kelin; LaPeyre, Megan K.
2017-01-01
Freshwater and sediment management in estuaries affects water quality, particularly in deltaic estuaries. Furthermore, climate change-induced sea-level rise (SLR) and land subsidence also affect estuarine water quality by changing salinity, circulation, stratification, sedimentation, erosion, residence time, and other physical and ecological processes. However, little is known about how the magnitudes and spatial and temporal patterns in estuarine water quality variables will change in response to freshwater and sediment management in the context of future SLR. In this study, we applied the Delft3D model that couples hydrodynamics and water quality processes to examine the spatial and temporal variations of salinity, total suspended solids, and chlorophyll-α concentration in response to small (142 m3 s−1) and large (7080 m3 s−1) Mississippi River (MR) diversions under low (0.38 m) and high (1.44 m) relative SLR (RSLR = eustatic SLR + subsidence) scenarios in the Breton Sound Estuary, Louisiana, USA. The hydrodynamics and water quality model were calibrated and validated via field observations at multiple stations across the estuary. Model results indicate that the large MR diversion would significantly affect the magnitude and spatial and temporal patterns of the studied water quality variables across the entire estuary, whereas the small diversion tends to influence water quality only in small areas near the diversion. RSLR would also play a significant role on the spatial heterogeneity in estuary water quality by acting as an opposite force to river diversions; however, RSLR plays a greater role than the small-scale diversion on the magnitude and spatial pattern of the water quality parameters in this deltaic estuary.
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…
Xu, Zhijing; Zu, Zhenghu; Zheng, Tao; Zhang, Wendou; Xu, Qing; Liu, Jinjie
2014-01-01
The study analyses the role of long-distance travel behaviours on the large-scale spatial spreading of directly transmitted infectious diseases, focusing on two different travel types in terms of the travellers travelling to a specific group or not. For this purpose, we have formulated and analysed a metapopulation model in which the individuals in each subpopulation are organised into a scale-free contact network. The long-distance travellers between the subpopulations will temporarily change the network structure of the destination subpopulation through the "merging effects (MEs)," which indicates that the travellers will be regarded as either connected components or isolated nodes in the contact network. The results show that the presence of the MEs has constantly accelerated the transmission of the diseases and aggravated the outbreaks compared to the scenario in which the diversity of the long-distance travel types is arbitrarily discarded. Sensitivity analyses show that these results are relatively constant regarding a wide range variation of several model parameters. Our study has highlighted several important causes which could significantly affect the spatiotemporal disease dynamics neglected by the present studies.
Scale-free correlations in the geographical spreading of obesity
NASA Astrophysics Data System (ADS)
Gallos, Lazaros; Barttfeld, Pablo; Havlin, Shlomo; Sigman, Mariano; Makse, Hernan
2012-02-01
Obesity levels have been universally increasing. A crucial problem is to determine the influence of global and local drivers behind the obesity epidemic, to properly guide effective policies. Despite the numerous factors that affect the obesity evolution, we show a remarkable regularity expressed in a predictable pattern of spatial long-range correlations in the geographical spreading of obesity. We study the spatial clustering of obesity and a number of related health and economic indicators, and we use statistical physics methods to characterize the growth of the resulting clusters. The resulting scaling exponents allow us to broadly classify these indicators into two separate universality classes, weakly or strongly correlated. Weak correlations are found in generic human activity such as population distribution and the growth of the whole economy. Strong correlations are recovered, among others, for obesity, diabetes, and the food industry sectors associated with food consumption. Obesity turns out to be a global problem where local details are of little importance. The long-range correlations suggest influence that extends to large scales, hinting that the physical model of obesity clustering can be mapped to a long-range correlated percolation process.
NASA Astrophysics Data System (ADS)
Krell, N.; Evans, T. P.; Estes, L. D.; Caylor, K. K.
2017-12-01
While international metrics of food security and water availability are generated as spatial averages at the regional to national levels, climate variability impacts are differentially felt at the household level. This project investigated scales of variability of climate impacts on smallholder farmers using social and environmental data in central Kenya. Using sub-daily real-time environmental measurements to monitor smallholder agriculture, we investigated how changes in seasonal precipitation affected food security around Laikipia county from September 2015 to present. We also conducted SMS-based surveys of over 700 farmers to understand farmers' decision-making within the growing season. Our results highlight field-scale heterogeneity in biophysical and social factors governing crop yields using locally sensed real-time environmental data and weekly farmer-reported information about planting, harvesting, irrigation, and crop yields. Our preliminary results show relationships between changes in seasonal precipitation, NDVI, and soil moisture related to crop yields and decision-making at several scales. These datasets present a unique opportunity to collect highly spatially and temporally resolved information from data-poor regions at the household level.
Representation of vegetation by continental data sets derived from NOAA-AVHRR data
NASA Technical Reports Server (NTRS)
Justice, C. O.; Townshend, J. R. G.; Kalb, V. L.
1991-01-01
Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.
Effect of flow on bacterial transport and biofilm formation in saturated porous media
NASA Astrophysics Data System (ADS)
Rusconi, R.
2016-12-01
Understanding the transport of bacteria in saturated porous media is crucial for many applications ranging from the management of pumping wells subject to bio-clogging to the design of new bioremediation schemes for subsurface contamination. However, little is known about the spatial distribution of bacteria at the pore scale, particularly when small-scale heterogeneities - always present even in seemingly homogeneous aquifers - lead to preferential pathways for groundwater flow. In particular, the coupling of flow and motility has recently been shown to strongly affect bacterial transport1, and this leads us to predict that subsurface flow may strongly affect the dispersal of bacteria and the formation of biofilms in saturated aquifers. I present here microfluidic experiments combined with numerical simulations to show how the topological features of the flow correlate with bacterial concentration and promote the attachment of bacteria to specific regions of the pore network, which will ultimately influence the formations of biofilms. These results highlight the intimate link between small-scale biological processes and transport in porous media.
Guttery, Michael; Ribic, Christine; Sample, David W.; Paulios, Andy; Trosen, Chris; Dadisman, John D.; Schneider, Daniel; Horton, Josephine
2017-01-01
ContextBeyond the recognized importance of protecting large areas of contiguous habitat, conservation efforts for many species are complicated by the fact that patch suitability may also be affected by characteristics of the landscape within which the patch is located. Currently, little is known about the spatial scales at which species respond to different aspects of the landscape surrounding an occupied patch.ObjectivesUsing grassland bird point count data, we describe an approach to evaluating scale-specific effects of landscape composition on patch occupancy.MethodsWe used data from 793 point count surveys conducted in idle and grazed grasslands across Wisconsin, USA from 2012 to 2014 to evaluate scale-dependencies in the response of grassland birds to landscape composition. Patch occupancy models were used to evaluate the relationship between occupancy and landscape composition at scales from 100 to 3000 m.ResultsBobolink (Dolichonyx oryzivorus) exhibited a pattern indicating selection for grassland habitats in the surrounding landscape at all spatial scales while selecting against other habitats. Eastern Meadowlark (Sturnella magna) displayed evidence of scale sensitivity for all habitat types. Grasshopper Sparrow (Ammodramus savannarum) showed a strong positive response to pasture and idle grass at all scales and negatively to cropland at large scales. Unlike other species, patch occupancy by Henslow’s Sparrow (A. henslowii) was primarily influenced by patch area.ConclusionsOur results suggest that both working grasslands (pasture) and idle conservation grasslands can play an important role in grassland bird conservation but also highlight the importance of considering species-specific patch and landscape characteristics for effective conservation.
Beta-diversity of ectoparasites at two spatial scales: nested hierarchy, geography and habitat type.
Warburton, Elizabeth M; van der Mescht, Luther; Stanko, Michal; Vinarski, Maxim V; Korallo-Vinarskaya, Natalia P; Khokhlova, Irina S; Krasnov, Boris R
2017-06-01
Beta-diversity of biological communities can be decomposed into (a) dissimilarity of communities among units of finer scale within units of broader scale and (b) dissimilarity of communities among units of broader scale. We investigated compositional, phylogenetic/taxonomic and functional beta-diversity of compound communities of fleas and gamasid mites parasitic on small Palearctic mammals in a nested hierarchy at two spatial scales: (a) continental scale (across the Palearctic) and (b) regional scale (across sites within Slovakia). At each scale, we analyzed beta-diversity among smaller units within larger units and among larger units with partitioning based on either geography or ecology. We asked (a) whether compositional, phylogenetic/taxonomic and functional dissimilarities of flea and mite assemblages are scale dependent; (b) how geographical (partitioning of sites according to geographic position) or ecological (partitioning of sites according to habitat type) characteristics affect phylogenetic/taxonomic and functional components of dissimilarity of ectoparasite assemblages and (c) whether assemblages of fleas and gamasid mites differ in their degree of dissimilarity, all else being equal. We found that compositional, phylogenetic/taxonomic, or functional beta-diversity was greater on a continental rather than a regional scale. Compositional and phylogenetic/taxonomic components of beta-diversity were greater among larger units than among smaller units within larger units, whereas functional beta-diversity did not exhibit any consistent trend regarding site partitioning. Geographic partitioning resulted in higher values of beta-diversity of ectoparasites than ecological partitioning. Compositional and phylogenetic components of beta-diversity were higher in fleas than mites but the opposite was true for functional beta-diversity in some, but not all, traits.
Ferrer-Paris, José Rafael; Sánchez-Mercado, Ada; Rodríguez, Jon Paul
2013-03-01
The development of efficient sampling protocols is an essential prerequisite to evaluate and identify priority conservation areas. There are f ew protocols for fauna inventory and monitoring in wide geographical scales for the tropics, where the complexity of communities and high biodiversity levels, make the implementation of efficient protocols more difficult. We proposed here a simple strategy to optimize the capture of dung beetles, applied to sampling with baited traps and generalizable to other sampling methods. We analyzed data from eight transects sampled between 2006-2008 withthe aim to develop an uniform sampling design, that allows to confidently estimate species richness, abundance and composition at wide geographical scales. We examined four characteristics of any sampling design that affect the effectiveness of the sampling effort: the number of traps, sampling duration, type and proportion of bait, and spatial arrangement of the traps along transects. We used species accumulation curves, rank-abundance plots, indicator species analysis, and multivariate correlograms. We captured 40 337 individuals (115 species/morphospecies of 23 genera). Most species were attracted by both dung and carrion, but two thirds had greater relative abundance in traps baited with human dung. Different aspects of the sampling design influenced each diversity attribute in different ways. To obtain reliable richness estimates, the number of traps was the most important aspect. Accurate abundance estimates were obtained when the sampling period was increased, while the spatial arrangement of traps was determinant to capture the species composition pattern. An optimum sampling strategy for accurate estimates of richness, abundance and diversity should: (1) set 50-70 traps to maximize the number of species detected, (2) get samples during 48-72 hours and set trap groups along the transect to reliably estimate species abundance, (3) set traps in groups of at least 10 traps to suitably record the local species composition, and (4) separate trap groups by a distance greater than 5-10km to avoid spatial autocorrelation. For the evaluation of other sampling protocols we recommend to, first, identify the elements of sampling design that could affect the sampled effort (the number of traps, sampling duration, type and proportion of bait) and their spatial distribution (spatial arrangement of the traps) and then, to evaluate how they affect richness, abundance and species composition estimates.
Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models.
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.
Global Particle-in-Cell Simulations of Mercury's Magnetosphere
NASA Astrophysics Data System (ADS)
Schriver, D.; Travnicek, P. M.; Lapenta, G.; Amaya, J.; Gonzalez, D.; Richard, R. L.; Berchem, J.; Hellinger, P.
2017-12-01
Spacecraft observations of Mercury's magnetosphere have shown that kinetic ion and electron particle effects play a major role in the transport, acceleration, and loss of plasma within the magnetospheric system. Kinetic processes include reconnection, the breakdown of particle adiabaticity and wave-particle interactions. Because of the vast range in spatial scales involved in magnetospheric dynamics, from local electron Debye length scales ( meters) to solar wind/planetary magnetic scale lengths (tens to hundreds of planetary radii), fully self-consistent kinetic simulations of a global planetary magnetosphere remain challenging. Most global simulations of Earth's and other planet's magnetosphere are carried out using MHD, enhanced MHD (e.g., Hall MHD), hybrid, or a combination of MHD and particle in cell (PIC) simulations. Here, 3D kinetic self-consistent hybrid (ion particle, electron fluid) and full PIC (ion and electron particle) simulations of the solar wind interaction with Mercury's magnetosphere are carried out. Using the implicit PIC and hybrid simulations, Mercury's relatively small, but highly kinetic magnetosphere will be examined to determine how the self-consistent inclusion of electrons affects magnetic reconnection, particle transport and acceleration of plasma at Mercury. Also the spatial and energy profiles of precipitating magnetospheric ions and electrons onto Mercury's surface, which can strongly affect the regolith in terms of space weathering and particle outflow, will be examined with the PIC and hybrid codes. MESSENGER spacecraft observations are used both to initiate and validate the global kinetic simulations to achieve a deeper understanding of the role kinetic physics play in magnetospheric dynamics.
Structured decision making as a framework for large-scale wildlife harvest management decisions
Robinson, Kelly F.; Fuller, Angela K.; Hurst, Jeremy E.; Swift, Bryan L.; Kirsch, Arthur; Farquhar, James F.; Decker, Daniel J.; Siemer, William F.
2016-01-01
Fish and wildlife harvest management at large spatial scales often involves making complex decisions with multiple objectives and difficult tradeoffs, population demographics that vary spatially, competing stakeholder values, and uncertainties that might affect management decisions. Structured decision making (SDM) provides a formal decision analytic framework for evaluating difficult decisions by breaking decisions into component parts and separating the values of stakeholders from the scientific evaluation of management actions and uncertainty. The result is a rigorous, transparent, and values-driven process. This decision-aiding process provides the decision maker with a more complete understanding of the problem and the effects of potential management actions on stakeholder values, as well as how key uncertainties can affect the decision. We use a case study to illustrate how SDM can be used as a decision-aiding tool for management decision making at large scales. We evaluated alternative white-tailed deer (Odocoileus virginianus) buck-harvest regulations in New York designed to reduce harvest of yearling bucks, taking into consideration the values of the state wildlife agency responsible for managing deer, as well as deer hunters. We incorporated tradeoffs about social, ecological, and economic management concerns throughout the state. Based on the outcomes of predictive models, expert elicitation, and hunter surveys, the SDM process identified management alternatives that optimized competing objectives. The SDM process provided biologists and managers insight about aspects of the buck-harvest decision that helped them adopt a management strategy most compatible with diverse hunter values and management concerns.
The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields
NASA Astrophysics Data System (ADS)
Zhao, Y.; Estes, L. D.; Vergopolan, N.
2017-12-01
Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water stress. Understanding the relationships between soil moisture spatiotemporal variability and yields can help to improve agricultural drought risk assessment and seasonal crop yield forecasting as well as early season warning of potential famines.
Regional and local species richness in an insular environment: Serpentine plants in California
Harrison, S.; Safford, H.D.; Grace, J.B.; Viers, J.H.; Davies, K.F.
2006-01-01
We asked how the richness of the specialized (endemic) flora of serpentine rock outcrops in California varies at both the regional and local scales. Our study had two goals: first, to test whether endemic richness is affected by spatial habitat structure (e.g., regional serpentine area, local serpentine outcrop area, regional and local measures of outcrop isolation), and second, to conduct this test in the context of a broader assessment of environmental influences (e.g., climate, soils, vegetation, disturbance) and historical influences (e.g., geologic age, geographic province) on local and regional species richness. We measured endemic and total richness and environmental variables in 109 serpentine sites (1000-m2 paired plots) in 78 serpentine-containing regions of the state. We used structural equation modeling (SEM) to simultaneously relate regional richness to regionalscale predictors, and local richness to both local-scale and regional-scale predictors. Our model for serpentine endemics explained 66% of the variation in local endemic richness based on local environment (vegetation, soils, rock cover) and on regional endemic richness. It explained 73% of the variation in regional endemic richness based on regional environment (climate and productivity), historical factors (geologic age and geographic province), and spatial structure (regional total area of serpentine, the only significant spatial variable in our analysis). We did not find a strong influence of spatial structure on species richness. However, we were able to distinguish local vs. regional influences on species richness to a novel extent, despite the existence of correlations between local and regional conditions. ?? 2006 by the Ecological Society of America.
Yitbarek, Senay; Vandermeer, John H; Allen, David
2011-10-01
Spatial patterns observed in ecosystems have traditionally been attributed to exogenous processes. Recently, ecologists have found that endogenous processes also have the potential to create spatial patterns. Yet, relatively few studies have attempted to examine the combined effects of exogenous and endogenous processes on the distribution of organisms across spatial and temporal scales. Here we aim to do this, by investigating whether spatial patterns of under-story tree species at a large spatial scale (18 ha) influences the spatial patterns of ground foraging ant species at a much smaller spatial scale (20 m by 20 m). At the regional scale, exogenous processes (under-story tree community) had a strong effect on the spatial patterns in the ground-foraging ant community. We found significantly more Camponotus noveboracensis, Formica subsericae, and Lasius alienus species in black cherry (Prunis serotine Ehrh.) habitats. In witch-hazel (Hamamelis virginiana L.) habitats, we similarly found significantly more Myrmica americana, Formica fusca, and Formica subsericae. At smaller spatial scales, we observed the emergence of mosaic ant patches changing rapidly in space and time. Our study reveals that spatial patterns are the result of both exogenous and endogenous forces, operating at distinct scales.
A Review of Spatial Variation of Inorganic Nitrogen (N) Wet Deposition in China
Liu, Lei; Zhang, Xiuying; Wang, Shanqian; Lu, Xuehe; Ouyang, Xiaoying
2016-01-01
Atmospheric nitrogen (N) deposition (Ndep), an important component of the global N cycle, has increased sharply in recent decades in China. Although there were already some studies on Ndep on a national scale, there were some gaps on the magnitude and the spatial patterns of Ndep. In this study, a national-scale Ndep pattern was constructed based on 139 published papers from 2003 to 2014 and the effects of precipitation (P), energy consumption (E) and N fertilizer use (FN) on spatial patterns of Ndep were analyzed. The wet deposition flux of NH4+-N, NO3--N and total Ndep was 6.83, 5.35 and 12.18 kg ha-1 a-1, respectively. Ndep exhibited a decreasing gradient from southeast to northwest of China. Through accuracy assessment of the spatial Ndep distribution and comparisons with other studies, the spatial Ndep distribution by Lu and Tian and this study both gained high accuracy. A strong exponential function was found between P and Ndep, FN and Ndep and E and Ndep, and P and FN had higher contribution than E on the spatial variation of Ndep. Fossil fuel combustion was the main contributor for NO3--N (86.0%) and biomass burning contributed 5.4% on the deposition of NO3--N. The ion of NH4+ was mainly from agricultural activities (85.9%) and fossil fuel combustion (6.0%). Overall, Ndep in China might be considerably affected by the high emissions of NOx and NH3 from fossil fuel combustion and agricultural activities. PMID:26731264
Tack, Jason D.; Fedy, Bradley C.
2015-01-01
Proactive conservation planning for species requires the identification of important spatial attributes across ecologically relevant scales in a model-based framework. However, it is often difficult to develop predictive models, as the explanatory data required for model development across regional management scales is rarely available. Golden eagles are a large-ranging predator of conservation concern in the United States that may be negatively affected by wind energy development. Thus, identifying landscapes least likely to pose conflict between eagles and wind development via shared space prior to development will be critical for conserving populations in the face of imposing development. We used publically available data on golden eagle nests to generate predictive models of golden eagle nesting sites in Wyoming, USA, using a suite of environmental and anthropogenic variables. By overlaying predictive models of golden eagle nesting habitat with wind energy resource maps, we highlight areas of potential conflict among eagle nesting habitat and wind development. However, our results suggest that wind potential and the relative probability of golden eagle nesting are not necessarily spatially correlated. Indeed, the majority of our sample frame includes areas with disparate predictions between suitable nesting habitat and potential for developing wind energy resources. Map predictions cannot replace on-the-ground monitoring for potential risk of wind turbines on wildlife populations, though they provide industry and managers a useful framework to first assess potential development. PMID:26262876
Tack, Jason D.; Fedy, Bradley C.
2015-01-01
Proactive conservation planning for species requires the identification of important spatial attributes across ecologically relevant scales in a model-based framework. However, it is often difficult to develop predictive models, as the explanatory data required for model development across regional management scales is rarely available. Golden eagles are a large-ranging predator of conservation concern in the United States that may be negatively affected by wind energy development. Thus, identifying landscapes least likely to pose conflict between eagles and wind development via shared space prior to development will be critical for conserving populations in the face of imposing development. We used publically available data on golden eagle nests to generate predictive models of golden eagle nesting sites in Wyoming, USA, using a suite of environmental and anthropogenic variables. By overlaying predictive models of golden eagle nesting habitat with wind energy resource maps, we highlight areas of potential conflict among eagle nesting habitat and wind development. However, our results suggest that wind potential and the relative probability of golden eagle nesting are not necessarily spatially correlated. Indeed, the majority of our sample frame includes areas with disparate predictions between suitable nesting habitat and potential for developing wind energy resources. Map predictions cannot replace on-the-ground monitoring for potential risk of wind turbines on wildlife populations, though they provide industry and managers a useful framework to first assess potential development.
Reuter, Kim E.; Wills, Abigail R.; Lee, Raymond W.; Cordes, Erik E.; Sewall, Brent J.
2016-01-01
Human-modified habitats are expanding rapidly; many tropical countries have highly fragmented and degraded forests. Preserving biodiversity in these areas involves protecting species–like frugivorous bats–that are important to forest regeneration. Fruit bats provide critical ecosystem services including seed dispersal, but studies of how their diets are affected by habitat change have often been rather localized. This study used stable isotope analyses (δ15N and δ13C measurement) to examine how two fruit bat species in Madagascar, Pteropus rufus (n = 138) and Eidolon dupreanum (n = 52) are impacted by habitat change across a large spatial scale. Limited data for Rousettus madagascariensis are also presented. Our results indicated that the three species had broadly overlapping diets. Differences in diet were nonetheless detectable between P. rufus and E. dupreanum, and these diets shifted when they co-occurred, suggesting resource partitioning across habitats and vertical strata within the canopy to avoid competition. Changes in diet were correlated with a decrease in forest cover, though at a larger spatial scale in P. rufus than in E. dupreanum. These results suggest fruit bat species exhibit differing responses to habitat change, highlight the threats fruit bats face from habitat change, and clarify the spatial scales at which conservation efforts could be implemented. PMID:27097316
Hirota, Mitsuru; Zhang, Pengcheng; Gu, Song; Shen, Haihua; Kuriyama, Takeo; Li, Yingnian; Tang, Yanhong
2010-07-01
Characterizing the spatial variation in the CO2 flux at both large and small scales is essential for precise estimation of an ecosystem's CO2 sink strength. However, little is known about small-scale CO2 flux variations in an ecosystem. We explored these variations in a Kobresia meadow ecosystem on the Qinghai-Tibetan plateau in relation to spatial variability in species composition and biomass. We established 14 points and measured net ecosystem production (NEP), gross primary production (GPP), and ecosystem respiration (Re) in relation to vegetation biomass, species richness, and environmental variables at each point, using an automated chamber system during the 2005 growing season. Mean light-saturated NEP and GPP were 30.3 and 40.5 micromol CO2 m(-2) s(-1) [coefficient of variation (CV), 42.7 and 29.4], respectively. Mean Re at 20 degrees C soil temperature, Re(20), was -10.9 micromol CO2 m(-2) s(-1) (CV, 27.3). Re(20) was positively correlated with vegetation biomass. GPP(max) was positively correlated with species richness, but 2 of the 14 points were outliers. Vegetation biomass was the main determinant of spatial variation of Re, whereas species richness mainly affected that of GPP, probably reflecting the complexity of canopy structure and light partitioning in this small grassland patch.
Willatt, Stephanie E.; Cortese, Filomeno; Protzner, Andrea B.
2017-01-01
Increasing evidence suggests that brain signal variability is an important measure of brain function reflecting information processing capacity and functional integrity. In this study, we examined how maturation from childhood to adulthood affects the magnitude and spatial extent of state-to-state transitions in brain signal variability, and how this relates to cognitive performance. We looked at variability changes between resting-state and task (a symbol-matching task with three levels of difficulty), and within trial (fixation, post-stimulus, and post-response). We calculated variability with multiscale entropy (MSE), and additionally examined spectral power density (SPD) from electroencephalography (EEG) in children aged 8–14, and in adults aged 18–33. Our results suggest that maturation is characterized by increased local information processing (higher MSE at fine temporal scales) and decreased long-range interactions with other neural populations (lower MSE at coarse temporal scales). Children show MSE changes that are similar in magnitude, but greater in spatial extent when transitioning between internally- and externally-driven brain states. Additionally, we found that in children, greater changes in task difficulty were associated with greater magnitude of modulation in MSE. Our results suggest that the interplay between maturational and state-to-state changes in brain signal variability manifest across different spatial and temporal scales, and influence information processing capacity in the brain. PMID:28750035
Tack, Jason D; Fedy, Bradley C
2015-01-01
Proactive conservation planning for species requires the identification of important spatial attributes across ecologically relevant scales in a model-based framework. However, it is often difficult to develop predictive models, as the explanatory data required for model development across regional management scales is rarely available. Golden eagles are a large-ranging predator of conservation concern in the United States that may be negatively affected by wind energy development. Thus, identifying landscapes least likely to pose conflict between eagles and wind development via shared space prior to development will be critical for conserving populations in the face of imposing development. We used publically available data on golden eagle nests to generate predictive models of golden eagle nesting sites in Wyoming, USA, using a suite of environmental and anthropogenic variables. By overlaying predictive models of golden eagle nesting habitat with wind energy resource maps, we highlight areas of potential conflict among eagle nesting habitat and wind development. However, our results suggest that wind potential and the relative probability of golden eagle nesting are not necessarily spatially correlated. Indeed, the majority of our sample frame includes areas with disparate predictions between suitable nesting habitat and potential for developing wind energy resources. Map predictions cannot replace on-the-ground monitoring for potential risk of wind turbines on wildlife populations, though they provide industry and managers a useful framework to first assess potential development.
Crossover between two- and three-dimensional turbulence in spatial mixing layers
NASA Astrophysics Data System (ADS)
Biancofiore, Luca
2016-11-01
We investigate how the domain depth affects the turbulent behaviour in spatially developing mixing layers by means of large-eddy simulations (LES) based on a spectral vanishing viscosity technique. Analyses of spectra of the vertical velocity, of Lumley's diagrams, of the turbulent kinetic energy and of the vortex stretching show that a two-dimensional behaviour of the turbulence is promoted in spatial mixing layers by constricting the fluid motion in one direction. This finding is in agreement with previous works on turbulent systems constrained by a geometric anisotropy, pioneered by Smith, Chasnov & Waleffe. We observe that the growth of the momentum thickness along the streamwise direction is damped in a confined domain. A full two-dimensional turbulent behaviour is observed when the momentum thickness is of the same order of magnitude as the confining scale.
NASA Astrophysics Data System (ADS)
Wang, Qiufeng; Tian, Jing; Yu, Guirui
2014-05-01
Patterns in the spatial distribution of organisms provide important information about mechanisms that regulate the diversity and complexity of soil ecosystems. Therefore, information on spatial distribution of microbial community composition and functional diversity is urgently necessary. The spatial variability on a 26×36 m plot and vertical distribution (0-10 cm and 10-20 cm) of soil microbial community composition and functional diversity were studied in a natural broad-leaved Korean pine (Pinus koraiensis) mixed forest soil in Changbai Mountain. The phospholipid fatty acid (PLFA) pattern was used to characterize the soil microbial community composition and was compared with the community substrate utilization pattern using Biolog. Bacterial biomass dominated and showed higher variability than fungal biomass at all scales examined. The microbial biomass decreased with soil depths increased and showed less variability in lower 10-20 cm soil layer. The Shannon-Weaver index value for microbial functional diversity showed higher variability in upper 0-10 cm than lower 10-20 cm soil layer. Carbohydrates, carboxylic acids, polymers and amino acids are the main carbon sources possessing higher utilization efficiency or utilization intensity. At the same time, the four carbon source types contributed to the differentiation of soil microbial communities. This study suggests the higher diversity and complexity for this mix forest ecosystem. To determine the driving factors that affect this spatial variability of microorganism is the next step for our study.
Christina Lyons-Tinsley; David L. Peterson
2012-01-01
Previous studies have debated the flammability of young regenerating stands, especially those in a matrix of mature forest, and no consensus has emerged as to whether young stands are inherently prone to high-severity wildfire. This topic has recently been addressed using spatial imagery, and weak inferences were made given the scale mismatch between the coarse...
Density dependence, spatial scale and patterning in sessile biota.
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.
Chamizo, Sonia; Belnap, Jayne; Elridge, David J; Issa, Oumarou M
2016-01-01
Biocrusts exert a strong influence on hydrological processes in drylands by modifying numerous soil properties that affect water retention and movement in soils. Yet, their role in these processes is not clearly understood due to the large number of factors that act simultaneously and can mask the biocrust effect. The influence of biocrusts on soil hydrology depends on biocrust intrinsic characteristics such as cover, composition, and external morphology, which differ greatly among climate regimes, but also on external factors as soil type, topography and vegetation distribution patterns, as well as interactions among these factors. This chapter reviews the most recent literature published on the role of biocrusts in infiltration and runoff, soil moisture, evaporation and non-rainfall water inputs (fog, dew, water absorption), in an attempt to elucidate the key factors that explain how biocrusts affect land hydrology. In addition to the crust type and site characteristics, recent studies point to the crucial importance of the type of rainfall and the spatial scale at which biocrust effects are analyzed to understand their role in hydrological processes. Future studies need to consider the temporal and spatial scale investigated to obtain more accurate generalizations on the role of biocrusts in land hydrology.
Gothe, Emma; Sandin, Leonard; Allen, Craig R.; Angeler, David G.
2014-01-01
The distribution of functional traits within and across spatiotemporal scales has been used to quantify and infer the relative resilience across ecosystems. We use explicit spatial modeling to evaluate within- and cross-scale redundancy in headwater streams, an ecosystem type with a hierarchical and dendritic network structure. We assessed the cross-scale distribution of functional feeding groups of benthic invertebrates in Swedish headwater streams during two seasons. We evaluated functional metrics, i.e., Shannon diversity, richness, and evenness, and the degree of redundancy within and across modeled spatial scales for individual feeding groups. We also estimated the correlates of environmental versus spatial factors of both functional composition and the taxonomic composition of functional groups for each spatial scale identified. Measures of functional diversity and within-scale redundancy of functions were similar during both seasons, but both within- and cross-scale redundancy were low. This apparent low redundancy was partly attributable to a few dominant taxa explaining the spatial models. However, rare taxa with stochastic spatial distributions might provide additional information and should therefore be considered explicitly for complementing future resilience assessments. Otherwise, resilience may be underestimated. Finally, both environmental and spatial factors correlated with the scale-specific functional and taxonomic composition. This finding suggests that resilience in stream networks emerges as a function of not only local conditions but also regional factors such as habitat connectivity and invertebrate dispersal.
Muiruri, Evalyne W; Rainio, Kalle; Koricheva, Julia
2016-03-01
The enemies hypothesis states that reduced insect herbivory in mixed-species stands can be attributed to more effective top-down control by predators with increasing plant diversity. Although evidence for this mechanism exists for invertebrate predators, studies on avian predation are comparatively rare and have not explicitly tested the effects of diversity at different spatial scales, even though heterogeneity at macro- and micro-scales can influence bird foraging selection. We studied bird predation in an established forest diversity experiment in SW Finland, using artificial larvae installed on birch, alder and pine trees. Effects of tree species diversity and densities on bird predation were tested at two different scales: between plots and within the neighbourhood around focal trees. At the neighbourhood scale, birds preferentially foraged on focal trees surrounded by a higher diversity of neighbours. However, predation rates did not increase with tree species richness at the plot level and were instead negatively affected by tree height variation within the plot. The highest probability of predation was observed on pine, and rates of predation increased with the density of pine regardless of scale. Strong tree species preferences observed may be due to a combination of innate bird species preferences and opportunistic foraging on profitable-looking artificial prey. This study therefore finds partial support for the enemies hypothesis and highlights the importance of spatial scale and focal tree species in modifying trophic interactions between avian predators and insect herbivores in forest ecosystems.
A Spatial Framework to Map Heat Health Risks at Multiple Scales.
Ho, Hung Chak; Knudby, Anders; Huang, Wei
2015-12-18
In the last few decades extreme heat events have led to substantial excess mortality, most dramatically in Central Europe in 2003, in Russia in 2010, and even in typically cool locations such as Vancouver, Canada, in 2009. Heat-related morbidity and mortality is expected to increase over the coming centuries as the result of climate-driven global increases in the severity and frequency of extreme heat events. Spatial information on heat exposure and population vulnerability may be combined to map the areas of highest risk and focus mitigation efforts there. However, a mismatch in spatial resolution between heat exposure and vulnerability data can cause spatial scale issues such as the Modifiable Areal Unit Problem (MAUP). We used a raster-based model to integrate heat exposure and vulnerability data in a multi-criteria decision analysis, and compared it to the traditional vector-based model. We then used the Getis-Ord G(i) index to generate spatially smoothed heat risk hotspot maps from fine to coarse spatial scales. The raster-based model allowed production of maps at spatial resolution, more description of local-scale heat risk variability, and identification of heat-risk areas not identified with the vector-based approach. Spatial smoothing with the Getis-Ord G(i) index produced heat risk hotspots from local to regional spatial scale. The approach is a framework for reducing spatial scale issues in future heat risk mapping, and for identifying heat risk hotspots at spatial scales ranging from the block-level to the municipality level.
Importance of Local and Regional Scales in Shaping Mycobacterial Abundance in Freshwater Lakes.
Roguet, Adélaïde; Therial, Claire; Catherine, Arnaud; Bressy, Adèle; Varrault, Gilles; Bouhdamane, Lila; Tran, Viet; Lemaire, Bruno J; Vincon-Leite, Brigitte; Saad, Mohamed; Moulin, Laurent; Lucas, Françoise S
2018-05-01
Biogeographical studies considering the entire bacterial community may underestimate mechanisms of bacterial assemblages at lower taxonomic levels. In this context, the study aimed to identify factors affecting the spatial and temporal dynamic of the Mycobacterium, a genus widespread in aquatic ecosystems. Nontuberculous mycobacteria (NTM) density variations were quantified in the water column of freshwater lakes at the regional scale (annual monitoring of 49 lakes in the Paris area) and at the local scale (2-year monthly monitoring in Créteil Lake) by real-time quantitative PCR targeting the atpE gene. At the regional scale, mycobacteria densities in water samples ranged from 6.7 × 10 3 to 1.9 × 10 8 genome units per liter. Density variations were primarily explained by water pH, labile iron, and dispersal processes through the connection of the lakes to a river. In Créteil Lake, no spatial variation of mycobacterial densities was noticed over the 2-year monthly survey, except after large rainfall events. Indeed, storm sewer effluents locally and temporarily increased NTM densities in the water column. The temporal dynamic of the NTM densities in Créteil Lake was associated with suspended solid concentrations. No clear seasonal variation was noticed despite a shift in NTM densities observed over the 2012-2013 winter. Temporal NTM densities fluctuations were well predicted by the neutral community model, suggesting a random balance between loss and gain of mycobacterial taxa within Créteil Lake. This study highlights the importance of considering multiple spatial scales for understanding the spatio-temporal dynamic of bacterial populations in natural environments.
NASA Astrophysics Data System (ADS)
Luce, C. H.; Buffington, J. M.; Rieman, B. E.; Dunham, J. B.; McKean, J. A.; Thurow, R. F.; Gutierrez-Teira, B.; Rosenberger, A. E.
2005-05-01
Conservation and restoration of freshwater stream and river habitats are important goals for land management and natural resources research. Several examples of research have emerged showing that many species are adapted to temporary habitat disruptions, but that these adaptations are sensitive to the spatial grain and extent of disturbance as well as to its duration. When viewed from this perspective, questions of timing, spatial pattern, and relevant scales emerge as critical issues. In contrast, much regulation, management, and research remains tied to pollutant loading paradigms that are insensitive to either time or space scales. It is becoming clear that research is needed to examine questions and hypotheses about how physical processes affect ecological processes. Two overarching questions concisely frame the scientific issues: 1) How do we quantify physical watershed processes in a way that is meaningful to biological and ecological processes, and 2) how does the answer to that question vary with changing spatial and temporal scales? A joint understanding of scaling characteristics of physical process and the plasticity of aquatic species will be needed to accomplish this research; hence a strong need exists for integrative and collaborative development. Considering conservation biology problems in this fashion can lead to creative and non-obvious solutions because the integrated system has important non-linearities and feedbacks related to a biological system that has responded to substantial natural variability in the past. We propose that research beginning with ecological theories and principles followed with a structured examination of each physical process as related to the specific ecological theories is a strong approach to developing the necessary science, and such an approach may form a basis for development of scaling theories of hydrologic and geomorphic process. We illustrate the approach with several examples.
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.
NASA Astrophysics Data System (ADS)
Zhu, Wenjuan; Xiang, Wenhua; Pan, Qiong; Zeng, Yelin; Ouyang, Shuai; Lei, Pifeng; Deng, Xiangwen; Fang, Xi; Peng, Changhui
2016-07-01
Leaf area index (LAI) is an important parameter related to carbon, water, and energy exchange between canopy and atmosphere and is widely applied in process models that simulate production and hydrological cycles in forest ecosystems. However, fine-scale spatial heterogeneity of LAI and its controlling factors have yet to be fully understood in Chinese subtropical forests. We used hemispherical photography to measure LAI values in three subtropical forests (Pinus massoniana-Lithocarpus glaber coniferous and evergreen broadleaved mixed forests, Choerospondias axillaris deciduous broadleaved forests, and L. glaber-Cyclobalanopsis glauca evergreen broadleaved forests) from April 2014 to January 2015. Spatial heterogeneity of LAI and its controlling factors were analysed using geostatistical methods and the generalised additive models (GAMs) respectively. Our results showed that LAI values differed greatly in the three forests and their seasonal variations were consistent with plant phenology. LAI values exhibited strong spatial autocorrelation for the three forests measured in January and for the L. glaber-C. glauca forest in April, July, and October. Obvious patch distribution pattern of LAI values occurred in three forests during the non-growing period and this pattern gradually dwindled in the growing season. Stem number, crown coverage, proportion of evergreen conifer species on basal area basis, proportion of deciduous species on basal area basis, and forest types affected the spatial variations in LAI values in January, while stem number and proportion of deciduous species on basal area basis affected the spatial variations in LAI values in July. Floristic composition, spatial heterogeneity, and seasonal variations should be considered for sampling strategy in indirect LAI measurement and application of LAI to simulate functional processes in subtropical forests.
NASA Astrophysics Data System (ADS)
Nazarieh, F.; Ansari, H.; Ziaei, A. N.; Izady, A.; Davari, K.; Brunner, P.
2018-05-01
The time required for deep percolating water to reach the water table can be considerable in areas with a thick vadose zone. Sustainable groundwater management, therefore, has to consider the spatial and temporal dynamics of groundwater recharge. The key parameters that control the lag time have been widely examined in soil physics using small-scale lysimeters and modeling studies. However, only a small number of studies have analyzed how deep-percolation rates affect groundwater recharge dynamics over large spatial scales. This study examined how the parameters influencing lag time affect groundwater recharge in a semi-arid catchment under irrigation (in northeastern Iran) using a numerical modeling approach. Flow simulations were performed by the MODFLOW-NWT code with the Vadose-Zone Flow (UZF) Package. Calibration of the groundwater model was based on data from 48 observation wells. Flow simulations showed that lag times vary from 1 to more than 100 months. A sensitivity analysis demonstrated that during drought conditions, the lag time was highly sensitive to the rate of deep percolation. The study illustrated two critical points: (1) the importance of providing estimates of the lag time as a basis for sustainable groundwater management, and (2) lag time not only depends on factors such as soil hydraulic conductivity or vadose zone depth but also depends on the deep-percolation rates and the antecedent soil-moisture condition. Therefore, estimates of the lag time have to be associated with specific percolation rates, in addition to depth to groundwater and soil properties.
Using Mental Transformation Strategies for Spatial Scaling: Evidence from a Discrimination Task
ERIC Educational Resources Information Center
Möhring, Wenke; Newcombe, Nora S.; Frick, Andrea
2016-01-01
Spatial scaling, or an understanding of how distances in different-sized spaces relate to each other, is fundamental for many spatial tasks and relevant for success in numerous professions. Previous research has suggested that adults use mental transformation strategies to mentally scale spatial input, as indicated by linear increases in response…
Regional precipitation trend analysis at the Langat River Basin, Selangor, Malaysia
NASA Astrophysics Data System (ADS)
Palizdan, Narges; Falamarzi, Yashar; Huang, Yuk Feng; Lee, Teang Shui; Ghazali, Abdul Halim
2014-08-01
Various hydrological and meteorological variables such as rainfall and temperature have been affected by global climate change. Any change in the pattern of precipitation can have a significant impact on the availability of water resources, agriculture, and the ecosystem. Therefore, knowledge on rainfall trend is an important aspect of water resources management. In this study, the regional annual and seasonal precipitation trends at the Langat River Basin, Malaysia, for the period of 1982-2011 were examined at the 95 % level of significance using the regional average Mann-Kendall (RAMK) test and the regional average Mann-Kendall coupled with bootstrap (RAMK-bootstrap) method. In order to identify the homogeneous regions respectively for the annual and seasonal scales, firstly, at-site mean total annual and separately at-site mean total seasonal precipitation were spatialized into 5 km × 5 km grids using the inverse distance weighting (IDW) algorithm. Next, the optimum number of homogeneous regions (clusters) is computed using the silhouette coefficient approach. Next, the homogeneous regions were formed using the K-mean clustering method. From the annual scale perspective, all three regions showed positive trends. However, the application of two methods at this scale showed a significant trend only in the region AC1. The region AC2 experienced a significant positive trend using only the RAMK test. On a seasonal scale, all regions showed insignificant trends, except the regions I1C1 and I1C2 in the Inter-Monsoon 1 (INT1) season which experienced significant upward trends. In addition, it was proven that the significance of trends has been affected by the existence of serial and spatial correlations.
Numerical analysis of field-scale transport of bromacil
NASA Astrophysics Data System (ADS)
Russo, David; Tauber-Yasur, Inbar; Laufer, Asher; Yaron, Bruno
Field-scale transport of bromacil (5-bromo-3- sec-butyl-6-methyluracil) was analyzed using two different model processes for local description of the transport. The first was the classical, one-region convection dispersion equation (CDE) model while the second was the two-region, mobile-immobile (MIM) model. The analyses were performed by means of detailed three-dimensional, numerical simulations of the flow and the transport [Russo, D., Zaidel, J. and Laufer, A., Numerical analysis of flow and transport in a three-dimensional partially saturated heterogeneous soil. Water Resour. Res., 1998, in press], employing local soil hydraulic properties parameters from field measurements and local adsorption/desorption coefficients and the first-order degradation rate coefficient from laboratory measurements. Results of the analyses suggest that for a given flow regime, mass exchange between the mobile and the immobile regions retards the bromacil degradation, considerably affects the distribution of the bromacil resident concentration, c, at relatively large travel times, slightly affects the spatial moments of the distribution of c, and increases the skewing of the bromacil breakthrough and the uncertainty in its prediction, compared with the case in which the soil contained only a single (mobile) region. Mean and standard deviation of the simulated concentration profiles at various elapsed times were compared with measurements from a field-scale transport experiment [Tauber-Yasur, I., Hadas, A., Russo, D. and Yaron, B., Leaching of terbuthylazine and bromacil through field soils. Water, Air Soil Poln., 1998, in press] conducted at the Bet Dagan site. Given the limitations of the present study (e.g. the lack of detailed field data on the spatial variability of the soil chemical properties) the main conclusion of the present study is that the field-scale transport of bromacil at the Bet Dagan site is better quantified with the MIM model than the CDE model.
Plieninger, Tobias; Hui, Cang; Gaertner, Mirijam; Huntsinger, Lynn
2014-01-01
Land abandonment is common in the Mediterranean Basin, a global biodiversity hotspot, but little is known about its impacts on biodiversity. To upscale existing case-study insights to the Pan-Mediterranean level, we conducted a meta-analysis of the effects of land abandonment on plant and animal species richness and abundance in agroforestry, arable land, pastures, and permanent crops of the Mediterranean Basin. In particular, we investigated (1) which taxonomic groups (arthropods, birds, lichen, vascular plants) are more affected by land abandonment; (2) at which spatial and temporal scales the effect of land abandonment on species richness and abundance is pronounced; (3) whether previous land use and current protected area status affect the magnitude of changes in the number and abundance of species; and (4) how prevailing landforms and climate modify the impacts of land abandonment. After identifying 1240 potential studies, 154 cases from 51 studies that offered comparisons of species richness and abundance and had results relevant to our four areas of investigation were selected for meta-analysis. Results are that land abandonment showed slightly increased (effect size = 0.2109, P<0.0001) plant and animal species richness and abundance overall, though results were heterogeneous, with differences in effect size between taxa, spatial-temporal scales, land uses, landforms, and climate. In conclusion, there is no “one-size-fits-all” conservation approach that applies to the diverse contexts of land abandonment in the Mediterranean Basin. Instead, conservation policies should strive to increase awareness of this heterogeneity and the potential trade-offs after abandonment. The strong role of factors at the farm and landscape scales that was revealed by the analysis indicates that purposeful management at these scales can have a powerful impact on biodiversity. PMID:24865979
NASA Astrophysics Data System (ADS)
Coon, E.; Jan, A.; Painter, S. L.; Moulton, J. D.; Wilson, C. J.
2017-12-01
Many permafrost-affected regions in the Arctic manifest a polygonal patterned ground, which contains large carbon stores and is vulnerability to climate change as warming temperatures drive melting ice wedges, polygon degradation, and thawing of the underlying carbon-rich soils. Understanding the fate of this carbon is difficult. The system is controlled by complex, nonlinear physics coupling biogeochemistry, thermal-hydrology, and geomorphology, and there is a strong spatial scale separation between microtopograpy (at the scale of an individual polygon) and the scale of landscape change (at the scale of many thousands of polygons). Physics-based models have come a long way, and are now capable of representing the diverse set of processes, but only on individual polygons or a few polygons. Empirical models have been used to upscale across land types, including ecotypes evolving from low-centered (pristine) polygons to high-centered (degraded) polygon, and do so over large spatial extent, but are limited in their ability to discern causal process mechanisms. Here we present a novel strategy that looks to use physics-based models across scales, bringing together multiple capabilities to capture polygon degradation under a warming climate and its impacts on thermal-hydrology. We use fine-scale simulations on individual polygons to motivate a mixed-dimensional strategy that couples one-dimensional columns representing each individual polygon through two-dimensional surface flow. A subgrid model is used to incorporate the effects of surface microtopography on surface flow; this model is described and calibrated to fine-scale simulations. And critically, a subsidence model that tracks volume loss in bulk ice wedges is used to alter the subsurface structure and subgrid parameters, enabling the inclusion of the feedbacks associated with polygon degradation. This combined strategy results in a model that is able to capture the key features of polygon permafrost degradation, but in a simulation across a large spatial extent of polygonal tundra.
Cation export by overland flow in a recently burnt forest area in north-central Portugal.
Machado, A I; Serpa, D; Ferreira, R V; Rodríguez-Blanco, M L; Pinto, R; Nunes, M I; Cerqueira, M A; Keizer, J J
2015-08-15
The current fire regime in the Mediterranean Basin constitutes a serious threat to natural ecosystems because it drastically enhances surface runoff and soil erosion in the affected areas. Besides soil particles themselves, soil cations can be lost by fire-enhanced overland flow, increasing the risk of fertility loss of the typically shallow and nutrient poor Mediterranean soils. Although the importance of cations for land-use sustainability is widely recognized, cation losses by post-fire runoff have received little research attention. The present study aimed to address this research gap by assessing total exports of Na(+), K(+), Ca(2+) and Mg(2+) in a recently burnt forest area in north-central Portugal. These exports were compared for two types of planted forest (eucalypt vs. maritime pine plantations), two types of parent materials (schist vs. granite) and for two spatial scales (micro-plot vs. hill slope). The study sites were a eucalypt plantation on granite (BEG), a eucalypt plantation on schist (BES) and a maritime pine plantation on schist (BPS). Overland flow samples were collected during the first six months after the wildfire. Cation losses differed strikingly between the two forest types on schist, being higher at the eucalypt than pine site. This difference was evident at both spatial scales, and probably due to the extensive cover of a needle cast from the scorched pine crowns. The role of parent material in cation export was less straightforward as it varied with spatial scale. Cation losses were higher for the eucalypt plantation on schist than for that on granite at the micro-plot scale, whereas the reverse was observed at the hill slope scale. Finally, cation yields were higher at the micro-plot than slope scale, in agreement with the general notion of scaling-effect in runoff generation. Copyright © 2015 Elsevier B.V. All rights reserved.
Spatial Estimation of Populations at Risk from Radiological Dispersion Device Terrorism Incidents
DOE Office of Scientific and Technical Information (OSTI.GOV)
Regens, J.L.; Gunter, J.T.
2008-07-01
Delineation of the location and size of the population potentially at risk of exposure to ionizing radiation is one of the key analytical challenges in estimating accurately the severity of the potential health effects associated with a radiological terrorism incident. Regardless of spatial scale, the geographical units for which population data commonly are collected rarely coincide with the geographical scale necessary for effective incident management and medical response. This paper identifies major government and commercial open sources of U.S. population data and presents a GIS-based approach for allocating publicly available population data, including age distributions, to geographical units appropriate formore » planning and implementing incident management and medical response strategies. In summary: The gravity model offers a straight-forward, empirical tool for estimating population flows, especially when geographical areas are relatively well-defined in terms of accessibility and spatial separation. This is particularly important for several reasons. First, the spatial scale for the area impacted by a RDD terrorism event is unlikely to match fully the spatial scale of available population data. That is, the plume spread typically will not uniformly overlay the impacted area. Second, the number of people within the impacted area varies as a function whether an attack occurs during the day or night. For example, the population of a central business district or industrial area typically is larger during the day while predominately residential areas have larger night time populations. As a result, interpolation techniques that link population data to geographical units and allocate those data based on time-frame at a spatial scale that is relevant to enhancing preparedness and response. The gravity model's main advantage is that it efficiently allocates readily available, open source population data to geographical units appropriate for planning and implementing incident management and medical monitoring strategies. The importance of being able to link population estimates to geographic areas during the course of an RDD incident can be understood intuitively: - The spatial distribution of actual total dose equivalents of ionizing radiation is likely to vary due to changes in meteorological parameters as an event evolves over time; - The size of the geographical area affected also is likely to vary as a function of the actual release scenario; - The ability to identify the location and size of the populations that may be exposed to doses of ionizing radiation is critical to carrying out appropriate treatment and post-event medical monitoring; - Once a spatial interaction model has been validated for a city or a region, it can then be used for simulation and prediction purposes to assess the possible human health consequences of different release scenarios. (authors)« less
Liu, Xinchun; Zhang, Yuandong; Ren, Guangyao; Pan, Xiaoling; He, Qing
2004-07-01
The spatial pattern of ecological landscape during land utilization in Fukang is heavily influenced by natural difference and the scale of water and land resource development. Analyses on the spatial pattern based on different zones and indexes showed that from 1987 to 1998, the change of the spatial pattern of ecological landscape during land utilization in Fukang was mainly the increase of plantation area in pluvial fan and the decrease in alluvial plain. The case was on the contrary about badlands. The acreage of woodland decreased in lower mountains, uplands and alluvial plain, but no variety in alluvial plain. The acreage of grassland increased in lower mountains and uplands, while decreased in other fields. The acreage of town increased in each sample field, while that of water area remained uncharged. The landscape diversity and evenness was descending, the dominance was ascending in lower mountains and in pluvial fan, while it was reverse in alluvial plain. Accessorial fragmentation showed the increasing influence of human beings. The change of the spatial pattern of ecological landscape in Fukang focused on the acreage alteration of plantation and badlands in pluvial fan and alluvial plain. The key factor was the dynamic variation of water-salt in water and soil resource utilization. Terrain and land utilization were the key factors affecting water table, and the continuous changes of the water table worked on the spatial distribution of soil water-salt.
Non-Invasive Methods to Characterize Soil-Plant Interactions at Different Scales
NASA Astrophysics Data System (ADS)
Javaux, M.; Kemna, A.; Muench, M.; Oberdoerster, C.; Pohlmeier, A.; Vanderborght, J.; Vereecken, H.
2006-05-01
Root water uptake is a dynamic and non-linear process, which interacts with the soil natural variability and boundary conditions to generate heterogeneous spatial distributions of soil water. Soil-root fluxes are spatially variable due to heterogeneous gradients and hydraulic connections between soil and roots. While 1-D effective representation of the root water uptake has been successfully applied to predict transpiration and average water content profiles, finer spatial characterization of the water distribution may be needed when dealing with solute transport. Indeed, root water uptake affects the water velocity field, which has an effect on solute velocity and dispersion. Although this variability originates from small-scale processes, these may still play an important role at larger scales. Therefore, in addition to investigate the variability of the soil hydraulic properties, experimental and numerical tools for characterizing root water uptake (and its effects on soil water distribution) from the pore to the field scales are needed to predict in a proper way the solute transport. Obviously, non-invasive and modeling techniques which are helpful to achieve this objective will evolve with the scale of interest. At the pore scale, soil structure and root-soil interface phenomena have to be investigated to understand the interactions between soil and roots. Magnetic resonance imaging may help to monitor water gradients and water content changes around roots while spectral induced polarization techniques may be used to characterize the structure of the pore space. At the column scale, complete root architecture of small plants and water content depletion around roots can be imaged by magnetic resonance. At that scale, models should explicitly take into account the three-dimensional gradient dependency of the root water uptake, to be able to predict solute transport. At larger scales however, simplified models, which implicitly take into account the heterogeneous root water uptake along roots, should be preferred given the complexity of the system. At such scales, electrical resistance tomography or ground-penetrating radar can be used to map the water content changes and derive effective parameters for predicting solute transport.
Vieira, D C S; Serpa, D; Nunes, J P C; Prats, S A; Neves, R; Keizer, J J
2018-08-01
Wildfires have become a recurrent threat for many Mediterranean forest ecosystems. The characteristics of the Mediterranean climate, with its warm and dry summers and mild and wet winters, make this a region prone to wildfire occurrence as well as to post-fire soil erosion. This threat is expected to be aggravated in the future due to climate change and land management practices and planning. The wide recognition of wildfires as a driver for runoff and erosion in burnt forest areas has created a strong demand for model-based tools for predicting the post-fire hydrological and erosion response and, in particular, for predicting the effectiveness of post-fire management operations to mitigate these responses. In this study, the effectiveness of two post-fire treatments (hydromulch and natural pine needle mulch) in reducing post-fire runoff and soil erosion was evaluated against control conditions (i.e. untreated conditions), at different spatial scales. The main objective of this study was to use field data to evaluate the ability of different erosion models: (i) empirical (RUSLE), (ii) semi-empirical (MMF), and (iii) physically-based (PESERA), to predict the hydrological and erosive response as well as the effectiveness of different mulching techniques in fire-affected areas. The results of this study showed that all three models were reasonably able to reproduce the hydrological and erosive processes occurring in burned forest areas. In addition, it was demonstrated that the models can be calibrated at a small spatial scale (0.5 m 2 ) but provide accurate results at greater spatial scales (10 m 2 ). From this work, the RUSLE model seems to be ideal for fast and simple applications (i.e. prioritization of areas-at-risk) mainly due to its simplicity and reduced data requirements. On the other hand, the more complex MMF and PESERA models would be valuable as a base of a possible tool for assessing the risk of water contamination in fire-affected water bodies and for testing different land management scenarios. Copyright © 2018 Elsevier Inc. All rights reserved.
Across species-pool aggregation alters grassland productivity and diversity.
McKenna, Thomas P; Yurkonis, Kathryn A
2016-08-01
Plant performance is determined by the balance of intra- and interspecific neighbors within an individual's zone of influence. If individuals interact over smaller scales than the scales at which communities are measured, then altering neighborhood interactions may fundamentally affect community responses. These interactions can be altered by changing the number (species richness), abundances (species evenness), and positions (species pattern) of the resident plant species, and we aimed to test whether aggregating species at planting would alter effects of species richness and evenness on biomass production at a common scale of observation in grasslands. We varied plant species richness (2, 4, or 8 species and monocultures), evenness (0.64, 0.8, or 1.0), and pattern (planted randomly or aggregated in groups of four individuals) within 1 × 1 m plots established with transplants from a pool of 16 tallgrass prairie species and assessed plot-scale biomass production and diversity over the first three growing seasons. As expected, more species-rich plots produced more biomass by the end of the third growing season, an effect associated with a shift from selection to complementarity effects over time. Aggregating conspecifics at a 0.25-m scale marginally reduced biomass production across all treatments and increased diversity in the most even plots, but did not alter biodiversity effects or richness-productivity relationships. Results support the hypothesis that fine-scale species aggregation affects diversity by promoting species coexistence in this system. However, results indicate that inherent changes in species neighborhood relationships along grassland diversity gradients may only minimally affect community (meter) - scale responses among similarly designed biodiversity-ecosystem function studies. Given that species varied in their responses to local aggregation, it may be possible to use such species-specific results to spatially design larger-scale grassland communities to achieve desired diversity and productivity responses.
Determinants of pulmonary blood flow distribution.
Glenny, Robb W; Robertson, H Thomas
2011-01-01
The primary function of the pulmonary circulation is to deliver blood to the alveolar capillaries to exchange gases. Distributing blood over a vast surface area facilitates gas exchange, yet the pulmonary vascular tree must be constrained to fit within the thoracic cavity. In addition, pressures must remain low within the circulatory system to protect the thin alveolar capillary membranes that allow efficient gas exchange. The pulmonary circulation is engineered for these unique requirements and in turn these special attributes affect the spatial distribution of blood flow. As the largest organ in the body, the physical characteristics of the lung vary regionally, influencing the spatial distribution on large-, moderate-, and small-scale levels. © 2011 American Physiological Society.
Martinson, Holly M; Fagan, William F
2014-09-01
Habitat fragmentation is a complex process that affects ecological systems in diverse ways, altering everything from population persistence to ecosystem function. Despite widespread recognition that habitat fragmentation can influence food web interactions, consensus on the factors underlying variation in the impacts of fragmentation across systems remains elusive. In this study, we conduct a systematic review and meta-analysis to quantify the effects of habitat fragmentation and spatial habitat structure on resource consumption in terrestrial arthropod food webs. Across 419 studies, we found a negative overall effect of fragmentation on resource consumption. Variation in effect size was extensive but predictable. Specifically, resource consumption was reduced on small, isolated habitat fragments, higher at patch edges, and neutral with respect to landscape-scale spatial variables. In general, resource consumption increased in fragmented settings for habitat generalist consumers but decreased for specialist consumers. Our study demonstrates widespread disruption of trophic interactions in fragmented habitats and describes variation among studies that is largely predictable based on the ecological traits of the interacting species. We highlight future prospects for understanding how changes in spatial habitat structure may influence trophic modules and food webs. © 2014 John Wiley & Sons Ltd/CNRS.
A multiscale analysis of nest predation on Least Bell's Vireos (Vireo bellii pusillus)
Kus, Barbara E.; Peterson, Bonnie L.; Deutschman, Douglas H.
2008-01-01
We examined variables influencing nest predation on the endangered Least Bell's Vireo (Vireo bellii pusillus) at three spatial scales to determine what nest-site, habitat, or landscape characteristics affect the likelihood of nest predation and to determine the spatial distribution of predation risk and the variables influencing it. We used MARK to calculate daily survival rates of Least Bell's Vireo nests and applied an information-theoretic approach to evaluate support for logistic regression models of the effect of habitat variables on predation risk. Analysis of data for 195 nests collected during 1999 and 2000 at the San Luis Rey River and Pilgrim Creek in southern California revealed no effect of fine-scale factors, including nest height, supporting plant species, and three measures of nest concealment, on the likelihood of predation. At the intermediate scale, distances to the riparian-habitat edge and to internal gaps in the canopy were unrelated to nest survival. Surrounding land-use type was a poor predictor of predation risk, with the exception of proximity to golf course–park habitat and wetland. Nests within 400 m of golf course–park were only 20% as likely to avoid predation as nests >400 m from this habitat, and nests near wetland were more than twice as likely to survive as nests distant from wetland. Spatially, predation appeared to be random throughout the site, with localized clustering evident in the vicinity of golf course–park and wetland. Our results suggest that the landscape may be the most appropriate scale at which to manage nest predation in this system.
NASA Astrophysics Data System (ADS)
Maguire, A.; Boelman, N.; Griffin, K. L.; Jensen, J.; Hiers, E.; Johnson, D. M.; Vierling, L. A.; Eitel, J.
2017-12-01
The effect of climate change on treeline position at the latitudinal Forest-Tundra ecotone (FTE) is poorly understood. While the FTE is expansive (stretching 13,000 km acros the panarctic), understanding relationships between climate and tree function may depend on very fine scale processes. High resolution tools are therefore needed to appropriately characterize the leading (northernmost) edge of the FTE. We hypothesized that microstructural metrics obtainable from lidar remote sensing may explain variation in the physical growth environment that governs sapling establishment. To test our hypothesis, we used terrestrial laser scanning (TLS) to collect highly spatially resolved 3-D structural information of white spruce (Picea glauca) saplings and their aboveground growth environment at the leading edge of a FTE in northern Alaska and Northwest Territories, Canada. Coordinates of sapling locations were extracted from the 3-D TLS data. Within each sampling plot, 20 sets of coordinates were randomly selected from regions where no saplings were present. Ground roughness, canopy roughness, average aspect, average slope, average curvature, wind shelter index, and wetness indexwere extracted from point clouds within a variable radius from all coordinates. Generalized linear models (GLM) were fit to determine which microstructural metrics were most strongly associated with sapling establishment. Preliminary analyses of three plots suggest that vegetation roughness, wetness index, ground roughness, and slope were the most important terrain metrics governing sapling presence (Figure 1). Comprehensive analyses will include eight plots and GLMs optimized for scale at which structural parameters affect sapling establishment. Spatial autocorrelation of sample locations will be accounted for in models. Because these analyses address how the physical growth environment affects sapling establishment, model outputs will provide information for improving understanding of the ecological processes that regulate treeline dynamics. Moreover, establishing relationships between the remotely sensed structural growth environment and tree establishment provides new ways of spatially scaling across larger areas to study ecological change at the FTE.
Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China.
Yang, Haiou; Chen, Wenbo; Liang, Zhaofeng
2017-04-26
Fine particulate matter (PM 2.5 ) pollution has become one of the greatest urban issues in China. Studies have shown that PM 2.5 pollution is strongly related to the land use pattern at the micro-scale and optimizing the land use pattern has been suggested as an approach to mitigate PM 2.5 pollution. However, there are only a few researches analyzing the effect of land use on PM 2.5 pollution. This paper employed land use regression (LUR) models and statistical analysis to explore the effect of land use on PM 2.5 pollution in urban areas. Nanchang city, China, was taken as the study area. The LUR models were used to simulate the spatial variations of PM 2.5 concentrations. Analysis of variance and multiple comparisons were employed to study the PM 2.5 concentration variances among five different types of urban functional zones. Multiple linear regression was applied to explore the PM 2.5 concentration variances among the same type of urban functional zone. The results indicate that the dominant factor affecting PM 2.5 pollution in the Nanchang urban area was the traffic conditions. Significant variances of PM 2.5 concentrations among different urban functional zones throughout the year suggest that land use types generated a significant impact on PM 2.5 concentrations and the impact did not change as the seasons changed. Land use intensity indexes including the building volume rate, building density, and green coverage rate presented an insignificant or counter-intuitive impact on PM 2.5 concentrations when studied at the spatial scale of urban functional zones. Our study demonstrates that land use can greatly affect the PM 2.5 levels. Additionally, the urban functional zone was an appropriate spatial scale to investigate the impact of land use type on PM 2.5 pollution in urban areas.
Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China
Yang, Haiou; Chen, Wenbo; Liang, Zhaofeng
2017-01-01
Fine particulate matter (PM2.5) pollution has become one of the greatest urban issues in China. Studies have shown that PM2.5 pollution is strongly related to the land use pattern at the micro-scale and optimizing the land use pattern has been suggested as an approach to mitigate PM2.5 pollution. However, there are only a few researches analyzing the effect of land use on PM2.5 pollution. This paper employed land use regression (LUR) models and statistical analysis to explore the effect of land use on PM2.5 pollution in urban areas. Nanchang city, China, was taken as the study area. The LUR models were used to simulate the spatial variations of PM2.5 concentrations. Analysis of variance and multiple comparisons were employed to study the PM2.5 concentration variances among five different types of urban functional zones. Multiple linear regression was applied to explore the PM2.5 concentration variances among the same type of urban functional zone. The results indicate that the dominant factor affecting PM2.5 pollution in the Nanchang urban area was the traffic conditions. Significant variances of PM2.5 concentrations among different urban functional zones throughout the year suggest that land use types generated a significant impact on PM2.5 concentrations and the impact did not change as the seasons changed. Land use intensity indexes including the building volume rate, building density, and green coverage rate presented an insignificant or counter-intuitive impact on PM2.5 concentrations when studied at the spatial scale of urban functional zones. Our study demonstrates that land use can greatly affect the PM2.5 levels. Additionally, the urban functional zone was an appropriate spatial scale to investigate the impact of land use type on PM2.5 pollution in urban areas. PMID:28445430
NASA Astrophysics Data System (ADS)
Mendez-Barroso, L. A.; Vivoni, E.; Robles-Morua, A.; Yepez, E. A.; Rodriguez, J. C.; Watts, C.; Saiz-Hernandez, J.
2013-05-01
Seasonal vegetation changes highly affect the energy and hydrologic fluxes in semiarid regions around the world. Accounting for different water use strategies among drought-deciduous ecosystems is important for understanding how these exploit the temporally brief and localized rainfall pulses of the North American Monsoon (NAM). Furthermore, quantifying these plant-water relations can help elucidate the spatial patterns of ecohydrological processes at catchment scale in the NAM region. In this effort, we focus on the San Miguel river basin (~ 3500 km2) in Sonora, Mexico, which exhibits seasonal vegetation greening that varies across ecosystems organized along mountain fronts. To assess the spatial variability of ecohydrological conditions, we relied on diverse tools that included multi-temporal remote sensing observations, model-based meteorological forcing, ground-based water and energy flux measurements and hydrologic simulations carried out at multiple scales. We evaluated the impact of seasonal vegetation dynamics on evapotranspiration (ET), its partitioning into soil evaporation (E) and plant transpiration (T), as well as their spatiotemporal patterns over the course of the NAM season. We utilized ground observations of soil moisture and evapotranspiration estimated by the eddy covariance method at two sites, as well as inferences of ET partitioning from stable isotope measurements, to test the numerical simulations. We found that ecosystem phenological differences lead to variations in the time to peak in transpiration during a season and in the overall seasonal ratio of transpiration to evapotranspiration (T/ET). A sensitivity analysis of the numerical simulations revealed that vegetation cover and the soil moisure threshold at which stomata close exert strong controls on the seasonal dominance of transpiration or evaporation. The dynamics of ET and its partitioning are then mapped spatially revealing that mountain front ecosystems utilize water differently. The results of this study aid in understanding how variations in water use and phenological strategies affect how soil water is returned to the atmosphere with implications on the watershed runoff response.
Environmental controls on food web regimes: A fluvial perspective
NASA Astrophysics Data System (ADS)
Power, Mary E.
2006-02-01
Because food web regimes control the biomass of primary producers (e.g., plants or algae), intermediate consumers (e.g., invertebrates), and large top predators (tuna, killer whales), they are of societal as well as academic interest. Some controls over food web regimes may be internal, but many are mediated by conditions or fluxes over large spatial scales. To understand locally observed changes in food webs, we must learn more about how environmental gradients and boundaries affect the fluxes of energy, materials, or organisms through landscapes or seascapes that influence local species interactions. Marine biologists and oceanographers have overcome formidable challenges of fieldwork on the high seas to make remarkable progress towards this goal. In river drainage networks, we have opportunities to address similar questions at smaller spatial scales, in ecosystems with clear physical structure and organization. Despite these advantages, we still have much to learn about linkages between fluxes from watershed landscapes and local food webs in river networks. Longitudinal (downstream) gradients in productivity, disturbance regimes, and habitat structure exert strong effects on the organisms and energy sources of river food webs, but their effects on species interactions are just beginning to be explored. In fluid ecosystems with less obvious physical structure, like the open ocean, discerning features that control the movement of organisms and affect food web dynamics is even more challenging. In both habitats, new sensing, tracing and mapping technologies have revealed how landscape or seascape features (e.g., watershed divides, ocean fronts or circulation cells) channel, contain or concentrate organisms, energy and materials. Field experiments and direct in situ observations of basic natural history, however, remain as vital as ever in interpreting the responses of biota to these features. We need field data that quantify the many spatial and temporal scales of functional relationships that link environments, fluxes and food web interactions to understand how they will respond to intensifying anthropogenic forcing over the coming decades.
Tree-, stand- and site-specific controls on landscape-scale patterns of transpiration
NASA Astrophysics Data System (ADS)
Hassler, Sibylle; Markus, Weiler; Theresa, Blume
2017-04-01
Transpiration is a key process in the hydrological cycle and a sound understanding and quantification of transpiration and its spatial variability is essential for management decisions as well as for improving the parameterisation of hydrological and soil-vegetation-atmosphere transfer models. For individual trees, transpiration is commonly estimated by measuring sap flow. Besides evaporative demand and water availability, tree-specific characteristics such as species, size or social status control sap flow amounts of individual trees. Within forest stands, properties such as species composition, basal area or stand density additionally affect sap flow, for example via competition mechanisms. Finally, sap flow patterns might also be influenced by landscape-scale characteristics such as geology, slope position or aspect because they affect water and energy availability; however, little is known about the dynamic interplay of these controls. We studied the relative importance of various tree-, stand- and site-specific characteristics with multiple linear regression models to explain the variability of sap velocity measurements in 61 beech and oak trees, located at 24 sites spread over a 290 km2-catchment in Luxembourg. For each of 132 consecutive days of the growing season of 2014 we modelled the daily sap velocities of these 61 trees and determined the importance of the different predictors. Results indicate that a combination of tree-, stand- and site-specific factors controls sap velocity patterns in the landscape, namely tree species, tree diameter, the stand density, geology and aspect. Compared to these predictors, spatial variability of atmospheric demand and soil moisture explains only a small fraction of the variability in the daily datasets. However, the temporal dynamics of the explanatory power of the tree-specific characteristics, especially species, are correlated to the temporal dynamics of potential evaporation. Thus, transpiration estimates at the landscape scale would benefit from not only considering hydro-meteorological drivers, but also including tree, stand and site characteristics in order to improve the spatial representation of transpiration for hydrological and soil-vegetation-atmosphere transfer models.
Understanding the spatial complexity of surface hoar from slope to range scale
NASA Astrophysics Data System (ADS)
Hendrikx, J.
2015-12-01
Surface hoar, once buried, is a common weak layer type in avalanche accidents in continental and intermountain snowpacks around the World. Despite this, there is still limited understanding of the spatial variability in both the formation of, and eventual burial of, surface hoar at spatial scales which are of critical importance to avalanche forecasters. While it is relatively well understood that aspect plays an important role in the spatial location of the formation, and burial of these grain forms, due to the unequal distribution of incoming radiation, this factor alone does not explain the complex and often confusing spatial pattern of these grains forms throughout the landscape at different spatial scales. In this paper we present additional data from a unique data set including over two hundred days of manual observations of surface hoar at sixteen locations on Pioneer Mountain at the Yellowstone Club in southwestern Montana. Using this wealth of observational data located on different aspects, elevations and exposures, coupled with detailed meteorological observations, and detailed slope scale observation, we examine the spatial variability of surface hoar at this scale, and examine the factors that control its spatial distribution. Our results further supports our preliminary work, which shows that small-scale slope conditions, meteorological differences, and local scale lapse rates, can greatly influence the spatial variability of surface hoar, over and above that which aspect alone can explain. These results highlight our incomplete understanding of the processes at both the slope and range scale, and are likely to have implications for both regional and local scale avalanche forecasting in environments where surface hoar cause ongoing instabilities.
Abiotic and biotic controls of spatial pattern at alpine treeline
Malanson, George P.; Xiao, Ningchuan; Alftine, K.J.; Bekker, Mathew; Butler, David R.; Brown, Daniel G.; Cairns, David M.; Fagre, Daniel; Walsh, Stephen J.
2000-01-01
At alpine treeline, trees and krummholz forms affect the environment in ways that increase their growth and reproduction. We assess the way in which these positive feedbacks combine in spatial patterns to alter the environment in the neighborhood of existing plants. The research is significant because areas of alpine tundra are susceptible to encroachment by woody species as climate changes. Moreover, understanding the general processes of plant invasion is important. The importance of spatial pattern has been recognized, but the spatial pattern of positive feedbacks per se has not been explored in depth. We present a linked set of models of vegetation change at an alpine forest-tundra ecotone. Our aim is to create models that are as simple as possible in order to test specific hypotheses. We present results from a model of the resource averaging hypothesis and the positive feedback switch hypothesis of treelines. We compare the patterns generated by the models to patterns observed in fine scale remotely sensed data.
Chromosome territories reposition during DNA damage-repair response
2013-01-01
Background Local higher-order chromatin structure, dynamics and composition of the DNA are known to determine double-strand break frequencies and the efficiency of repair. However, how DNA damage response affects the spatial organization of chromosome territories is still unexplored. Results Our report investigates the effect of DNA damage on the spatial organization of chromosome territories within interphase nuclei of human cells. We show that DNA damage induces a large-scale spatial repositioning of chromosome territories that are relatively gene dense. This response is dose dependent, and involves territories moving from the nuclear interior to the periphery and vice versa. Furthermore, we have found that chromosome territory repositioning is contingent upon double-strand break recognition and damage sensing. Importantly, our results suggest that this is a reversible process where, following repair, chromosome territories re-occupy positions similar to those in undamaged control cells. Conclusions Thus, our report for the first time highlights DNA damage-dependent spatial reorganization of whole chromosomes, which might be an integral aspect of cellular damage response. PMID:24330859
Pernet, Fabrice; Lagarde, Franck; Jeannée, Nicolas; Daigle, Gaetan; Barret, Jean; Le Gall, Patrik; Quere, Claudie; D’orbcastel, Emmanuelle Roque
2014-01-01
Although spatial studies of diseases on land have a long history, far fewer have been made on aquatic diseases. Here, we present the first large-scale, high-resolution spatial and temporal representation of a mass mortality phenomenon cause by the Ostreid herpesvirus (OsHV-1) that has affected oysters (Crassostrea gigas) every year since 2008, in relation to their energetic reserves and the quality of their food. Disease mortality was investigated in healthy oysters deployed at 106 locations in the Thau Mediterranean lagoon before the start of the epizootic in spring 2011. We found that disease mortality of oysters showed strong spatial dependence clearly reflecting the epizootic process of local transmission. Disease initiated inside oyster farms spread rapidly beyond these areas. Local differences in energetic condition of oysters, partly driven by variation in food quality, played a significant role in the spatial and temporal dynamics of disease mortality. In particular, the relative contribution of diatoms to the diet of oysters was positively correlated with their energetic reserves, which in turn decreased the risk of disease mortality. PMID:24551106
Pernet, Fabrice; Lagarde, Franck; Jeannée, Nicolas; Daigle, Gaetan; Barret, Jean; Le Gall, Patrik; Quere, Claudie; D'orbcastel, Emmanuelle Roque
2014-01-01
Although spatial studies of diseases on land have a long history, far fewer have been made on aquatic diseases. Here, we present the first large-scale, high-resolution spatial and temporal representation of a mass mortality phenomenon cause by the Ostreid herpesvirus (OsHV-1) that has affected oysters (Crassostrea gigas) every year since 2008, in relation to their energetic reserves and the quality of their food. Disease mortality was investigated in healthy oysters deployed at 106 locations in the Thau Mediterranean lagoon before the start of the epizootic in spring 2011. We found that disease mortality of oysters showed strong spatial dependence clearly reflecting the epizootic process of local transmission. Disease initiated inside oyster farms spread rapidly beyond these areas. Local differences in energetic condition of oysters, partly driven by variation in food quality, played a significant role in the spatial and temporal dynamics of disease mortality. In particular, the relative contribution of diatoms to the diet of oysters was positively correlated with their energetic reserves, which in turn decreased the risk of disease mortality.
NASA Astrophysics Data System (ADS)
Kaiser, Christina; Evans, Sarah; Dieckmann, Ulf; Widder, Stefanie
2016-04-01
At the μm-scale, soil is a highly structured and complex environment, both in physical as well as in biological terms, characterized by non-linear interactions between microbes, substrates and minerals. As known from mathematics and theoretical ecology, spatial structure significantly affects the system's behaviour by enabling synergistic dynamics, facilitating diversity, and leading to emergent phenomena such as self-organisation and self-regulation. Such phenomena, however, are rarely considered when investigating mechanisms of microbial soil organic matter turnover. Soil organic matter is the largest terrestrial reservoir for organic carbon (C) and nitrogen (N) and plays a pivotal role in global biogeochemical cycles. Still, the underlying mechanisms of microbial soil organic matter buildup and turnover remain elusive. We explored mechanisms of microbial soil organic matter turnover using an individual-based, stoichiometrically and spatially explicit computer model, which simulates the microbial de-composer system at the soil microscale (i.e. on a grid of 100 x 100 soil microsites). Soil organic matter dynamics in our model emerge as the result of interactions among individual microbes with certain functional traits (f.e. enzyme production rates, growth rates, cell stoichiometry) at the microscale. By degrading complex substrates, and releasing labile substances microbes in our model continusly shape their environment, which in turn feeds back to spatiotemporal dynamics of the microbial community. In order to test the effect of microbial functional traits and organic matter input rate on soil organic matter turnover and C and N storage, we ran the model into steady state using continuous inputs of fresh organic material. Surprisingly, certain parameter settings that induce resource limitation of microbes lead to regular spatial pattern formation (f.e. moving spiral waves) of microbes and substrate at the μm-scale at steady-state. The occurrence of these pattern can be explained by the Turing mechanism. These pattern formation had strong consequences for process rates, as well as for C and N storage in the soil at the steady state: Scenarios that exhibited pattern formation were generally associated with higher C storage at steady state compared to those without pattern formation (i.e. at non-limiting conditions for microbes). Moreover, pattern formation lead to a spatial decoupling of C and N turnover processes, and to a spatial decoupling of microbial N mineralization and N immobilization. Taken together, our theoretical analysis shows that self-organisation may be a feature of the soil decomposer system, with consequences for process rates of microbial C and N turnover. Pattern formation through spatial self-organization, which has been observed on larger spatial scales in other resource-limited communities (e.g., vegetation patterns in arid or wetland eco-systems), may also occur at the soil microscale, leaving its mark on the soil's storage capacity for C and N.
Individual-Based Model of Microbial Life on Hydrated Rough Soil Surfaces
Kim, Minsu; Or, Dani
2016-01-01
Microbial life in soil is perceived as one of the most interesting ecological systems, with microbial communities exhibiting remarkable adaptability to vast dynamic environmental conditions. At the same time, it is a notoriously challenging system to understand due to its complexity including physical, chemical, and biological factors in synchrony. This study presents a spatially-resolved model of microbial dynamics on idealised rough soil surfaces represented as patches with different (roughness) properties that preserve the salient hydration physics of real surfaces. Cell level microbial interactions are considered within an individual-based formulation including dispersion and various forms of trophic dependencies (competition, mutualism). The model provides new insights into mechanisms affecting microbial community dynamics and gives rise to spontaneous formation of microbial community spatial patterns. The framework is capable of representing many interacting species and provides diversity metrics reflecting surface conditions and their evolution over time. A key feature of the model is its spatial scalability that permits representation of microbial processes from cell-level (micro-metric scales) to soil representative volumes at sub-metre scales. Several illustrative examples of microbial trophic interactions and population dynamics highlight the potential of the proposed modelling framework to quantitatively study soil microbial processes. The model is highly applicable in a wide range spanning from quantifying spatial organisation of multiple species under various hydration conditions to predicting microbial diversity residing in different soils. PMID:26807803
Kang, Jeon-Young; Aldstadt, Jared
2017-07-15
Dengue is a mosquito-borne infectious disease that is endemic in tropical and subtropical countries. Many individual-level simulation models have been developed to test hypotheses about dengue virus transmission. Often these efforts assume that human host and mosquito vector populations are randomly or uniformly distributed in the environment. Although, the movement of mosquitoes is affected by spatial configuration of buildings and mosquito populations are highly clustered in key buildings, little research has focused on the influence of the local built environment in dengue transmission models. We developed an agent-based model of dengue transmission in a village setting to test the importance of using realistic environments in individual-level models of dengue transmission. The results from one-way ANOVA analysis of simulations indicated that the differences between scenarios in terms of infection rates as well as serotype-specific dominance are statistically significant. Specifically, the infection rates in scenarios of a realistic environment are more variable than those of a synthetic spatial configuration. With respect to dengue serotype-specific cases, we found that a single dengue serotype is more often dominant in realistic environments than in synthetic environments. An agent-based approach allows a fine-scaled analysis of simulated dengue incidence patterns. The results provide a better understanding of the influence of spatial heterogeneity on dengue transmission at a local scale.
A variance-decomposition approach to investigating multiscale habitat associations
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
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 Bayesian method for assessing multiscalespecies-habitat relationships
Stuber, Erica F.; Gruber, Lutz F.; Fontaine, Joseph J.
2017-01-01
ContextScientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multi-scale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large.ObjectivesOur objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance.MethodsWe introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA.ResultsOur method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%.ConclusionsGiven the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships.
Coincident scales of forest feedback on climate and conservation in a diversity hot spot
Webb, Thomas J; Gaston, Kevin J; Hannah, Lee; Ian Woodward, F
2005-01-01
The dynamic relationship between vegetation and climate is now widely acknowledged. Climate influences the distribution of vegetation; and through a number of feedback mechanisms vegetation affects climate. This implies that land-use changes such as deforestation will have climatic consequences. However, the spatial scales at which such feedbacks occur remain largely unknown. Here, we use a large database of precipitation and tree cover records for an area of the biodiversity-rich Atlantic forest region in south eastern Brazil to investigate the forest–rainfall feedback at a range of spatial scales from ca 101–104 km2. We show that the strength of the feedback increases up to scales of at least 103 km2, with the climate at a particular locality influenced by the pattern of landcover extending over a large area. Thus, smaller forest fragments, even if well protected, may suffer degradation due to the climate responding to land-use change in the surrounding area. Atlantic forest vertebrate taxa also require large areas of forest to support viable populations. Areas of forest of ca 103 km2 would be large enough to support such populations at the same time as minimizing the risk of climatic feedbacks resulting from deforestation. PMID:16608697
Coincident scales of forest feedback on climate and conservation in a diversity hot spot.
Webb, Thomas J; Gaston, Kevin J; Hannah, Lee; Ian Woodward, F
2006-03-22
The dynamic relationship between vegetation and climate is now widely acknowledged. Climate influences the distribution of vegetation; and through a number of feedback mechanisms vegetation affects climate. This implies that land-use changes such as deforestation will have climatic consequences. However, the spatial scales at which such feedbacks occur remain largely unknown. Here, we use a large database of precipitation and tree cover records for an area of the biodiversity-rich Atlantic forest region in south eastern Brazil to investigate the forest-rainfall feedback at a range of spatial scales from ca 10(1)-10(4) km2. We show that the strength of the feedback increases up to scales of at least 10(3) km2, with the climate at a particular locality influenced by the pattern of landcover extending over a large area. Thus, smaller forest fragments, even if well protected, may suffer degradation due to the climate responding to land-use change in the surrounding area. Atlantic forest vertebrate taxa also require large areas of forest to support viable populations. Areas of forest of ca 10(3) km2 would be large enough to support such populations at the same time as minimizing the risk of climatic feedbacks resulting from deforestation.
Gurdak, Jason J.; Qi, Sharon L.
2012-01-01
Recently recharged water (defined here as <60 years old) is generally the most vulnerable part of a groundwater resource to nonpoint-source nitrate contamination. Understanding at the appropriate scale the interactions of natural and anthropogenic controlling factors that influence nitrate occurrence in recently recharged groundwater is critical to support best management and policy decisions that are often made at the aquifer to subaquifer scale. New logistic regression models were developed using data from the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program and National Water Information System for 17 principal aquifers of the U.S. to identify important source, transport, and attenuation factors that control nonpoint source nitrate concentrations greater than relative background levels in recently recharged groundwater and were used to predict the probability of detecting elevated nitrate in areas beyond the sampling network. Results indicate that dissolved oxygen, crops and irrigated cropland, fertilizer application, seasonally high water table, and soil properties that affect infiltration and denitrification are among the most important factors in predicting elevated nitrate concentrations. Important differences in controlling factors and spatial predictions were identified in the principal aquifer and national-scale models and support the conclusion that similar spatial scales are needed between informed groundwater management and model development.
Comparison of Spatial Correlation Parameters between Full and Model Scale Launch Vehicles
NASA Technical Reports Server (NTRS)
Kenny, Jeremy; Giacomoni, Clothilde
2016-01-01
The current vibro-acoustic analysis tools require specific spatial correlation parameters as input to define the liftoff acoustic environment experienced by the launch vehicle. Until recently these parameters have not been very well defined. A comprehensive set of spatial correlation data were obtained during a scale model acoustic test conducted in 2014. From these spatial correlation data, several parameters were calculated: the decay coefficient, the diffuse to propagating ratio, and the angle of incidence. Spatial correlation data were also collected on the EFT-1 flight of the Delta IV vehicle which launched on December 5th, 2014. A comparison of the spatial correlation parameters from full scale and model scale data will be presented.
Nonlinear plasma wave models in 3D fluid simulations of laser-plasma interaction
NASA Astrophysics Data System (ADS)
Chapman, Thomas; Berger, Richard; Arrighi, Bill; Langer, Steve; Banks, Jeffrey; Brunner, Stephan
2017-10-01
Simulations of laser-plasma interaction (LPI) in inertial confinement fusion (ICF) conditions require multi-mm spatial scales due to the typical laser beam size and durations of order 100 ps in order for numerical laser reflectivities to converge. To be computationally achievable, these scales necessitate a fluid-like treatment of light and plasma waves with a spatial grid size on the order of the light wave length. Plasma waves experience many nonlinear phenomena not naturally described by a fluid treatment, such as frequency shifts induced by trapping, a nonlinear (typically suppressed) Landau damping, and mode couplings leading to instabilities that can cause the plasma wave to decay rapidly. These processes affect the onset and saturation of stimulated Raman and Brillouin scattering, and are of direct interest to the modeling and prediction of deleterious LPI in ICF. It is not currently computationally feasible to simulate these Debye length-scale phenomena in 3D across experimental scales. Analytically-derived and/or numerically benchmarked models of processes occurring at scales finer than the fluid simulation grid offer a path forward. We demonstrate the impact of a range of kinetic processes on plasma reflectivity via models included in the LPI simulation code pF3D. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
Large-scale impacts of herbivores on the structural diversity of African savannas
Asner, Gregory P.; Levick, Shaun R.; Kennedy-Bowdoin, Ty; Knapp, David E.; Emerson, Ruth; Jacobson, James; Colgan, Matthew S.; Martin, Roberta E.
2009-01-01
African savannas are undergoing management intensification, and decision makers are increasingly challenged to balance the needs of large herbivore populations with the maintenance of vegetation and ecosystem diversity. Ensuring the sustainability of Africa's natural protected areas requires information on the efficacy of management decisions at large spatial scales, but often neither experimental treatments nor large-scale responses are available for analysis. Using a new airborne remote sensing system, we mapped the three-dimensional (3-D) structure of vegetation at a spatial resolution of 56 cm throughout 1640 ha of savanna after 6-, 22-, 35-, and 41-year exclusions of herbivores, as well as in unprotected areas, across Kruger National Park in South Africa. Areas in which herbivores were excluded over the short term (6 years) contained 38%–80% less bare ground compared with those that were exposed to mammalian herbivory. In the longer-term (> 22 years), the 3-D structure of woody vegetation differed significantly between protected and accessible landscapes, with up to 11-fold greater woody canopy cover in the areas without herbivores. Our maps revealed 2 scales of ecosystem response to herbivore consumption, one broadly mediated by geologic substrate and the other mediated by hillslope-scale variation in soil nutrient availability and moisture conditions. Our results are the first to quantitatively illustrate the extent to which herbivores can affect the 3-D structural diversity of vegetation across large savanna landscapes. PMID:19258457
On the nonlinearity of spatial scales in extreme weather attribution statements
NASA Astrophysics Data System (ADS)
Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah; Alexander, Lisa V.; Wehner, Michael; Shiogama, Hideo; Wolski, Piotr; Ciavarella, Andrew; Christidis, Nikolaos
2018-04-01
In the context of ongoing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporal scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.
On the nonlinearity of spatial scales in extreme weather attribution statements
DOE Office of Scientific and Technical Information (OSTI.GOV)
Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah
In the context of continuing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporalmore » scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.« less
On the nonlinearity of spatial scales in extreme weather attribution statements
Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah; ...
2017-06-17
In the context of continuing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporalmore » scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.« less
NASA Astrophysics Data System (ADS)
Xu, C.; Zhao, S.; Zhao, B.
2017-12-01
Spatial heterogeneity is scale-dependent, that is, the quantification and representation of spatial pattern vary with the resolution and extent. Overwhelming practices focused on scale effect of landscape metrics, and predicable scaling relationships found among some of them are thought to be the most effective and precise way to quantify multi-scale characteristics. However, previous studies tended to consider a narrow range of scales, and few focused on the critical threshold of scaling function. Here we examine the scalograms of 38 widely-used landscape-level metrics in a more integral spectrum of grain size among 96 landscapes with various extent (i.e. from 25km2 up towards to 221 km2), which sampled randomly from NLCD product. Our goal is to explore the existence of scaling domain and whether the response of metrics to changing resolution would be influenced by spatial extent. Results clearly show the existence of scaling domain for 13 of them (Type II), while the behaviors of other 13 (Type I) exhibit simple scaling functions and the rest (Type III) demonstrate various forms like no obvious change or fluctuation across the integral spectrum of grain size. In addition, an invariant power law scaling relationship was found between critical resolution and spatial extent for metrics falling into Type II, as the critical resolution is proportional to Eρ (ρ is a constant, and E is the extent). All the scaling exponents (ρ) are positive, suggesting that the critical resolutions for these characteristics of landscape structure can be relaxed as the spatial extent expands. This agrees well with empirical perception that coarser grain size might be allowed for spatial data with larger extent. Furthermore, the parameters of scaling functions for metrics falling into Type I and Type II vary with spatial extent, and power law or logarithmic relationships could be identified between them for some metrics. Our finding support the existence of self-organized criticality for a hierarchically-structured landscape. Although the underlying mechanism driving the scaling relationship remains unclear, it could provide guidance toward general principles in spatial pattern analysis and on selecting the proper resolution to avoid the misrepresentation of spatial pattern and profound biases in further ecological progress research.
Urban Resources Selection and Allocation for Emergency Shelters: In a Multi-Hazard Environment.
Chen, Wei; Zhai, Guofang; Ren, Chongqiang; Shi, Yijun; Zhang, Jianxin
2018-06-14
This study explores how emergency shelters can adapt to a multi-hazard environment by geographic information system (GIS) and takes Guangzhou as a case for analysis. The physical suitability of the overall urban resources was first assessed by aiming to select the suitable resources and safe locations for emergency shelters in the context of multiple disasters. Afterward, by analyzing the scale and spatial distribution of affected areas and populations under different types of disaster scenarios, the demand for different kinds of shelters were predicted. Lastly, taking into account the coverage of the affected people, shelters were allocated according to different conditions in the districts. This work will hopefully provide a reference for the construction of emergency shelters and help form emergency operations in order to mitigate the impact of hazards. The issues identified in the study need to be further studied in medium or small-scale cities.
Scaling properties of the Arctic sea ice Deformation from Buoy Dispersion Analysis
NASA Astrophysics Data System (ADS)
Weiss, J.; Rampal, P.; Marsan, D.; Lindsay, R.; Stern, H.
2007-12-01
A temporal and spatial scaling analysis of Arctic sea ice deformation is performed over time scales from 3 hours to 3 months and over spatial scales from 300 m to 300 km. The deformation is derived from the dispersion of pairs of drifting buoys, using the IABP (International Arctic Buoy Program) buoy data sets. This study characterizes the deformation of a very large solid plate -the Arctic sea ice cover- stressed by heterogeneous forcing terms like winds and ocean currents. It shows that the sea ice deformation rate depends on the scales of observation following specific space and time scaling laws. These scaling properties share similarities with those observed for turbulent fluids, especially for the ocean and the atmosphere. However, in our case, the time scaling exponent depends on the spatial scale, and the spatial exponent on the temporal scale, which implies a time/space coupling. An analysis of the exponent values shows that Arctic sea ice deformation is very heterogeneous and intermittent whatever the scales, i.e. it cannot be considered as viscous-like, even at very large time and/or spatial scales. Instead, it suggests a deformation accommodated by a multi-scale fracturing/faulting processes.
NASA Astrophysics Data System (ADS)
Hutter, Nils; Losch, Martin; Menemenlis, Dimitris
2017-04-01
Sea ice models with the traditional viscous-plastic (VP) rheology and very high grid resolution can resolve leads and deformation rates that are localised along Linear Kinematic Features (LKF). In a 1-km pan-Arctic sea ice-ocean simulation, the small scale sea-ice deformations in the Central Arctic are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS). A new coupled scaling analysis for data on Eulerian grids determines the spatial and the temporal scaling as well as the coupling between temporal and spatial scales. The spatial scaling of the modelled sea ice deformation implies multi-fractality. The spatial scaling is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling and its coupling to temporal scales with satellite observations and models with the modern elasto-brittle rheology challenges previous results with VP models at coarse resolution where no such scaling was found. The temporal scaling analysis, however, shows that the VP model does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.
Wu, Hao; Luo, Junjie; Yu, Huimin; Rattner, Amir; Mo, Alisa; Wang, Yanshu; Smallwood, Philip M; Erlanger, Bracha; Wheelan, Sarah J; Nathans, Jeremy
2014-01-08
Female eutherian mammals use X chromosome inactivation (XCI) to epigenetically regulate gene expression from ∼4% of the genome. To quantitatively map the topography of XCI for defined cell types at single cell resolution, we have generated female mice that carry X-linked, Cre-activated, and nuclear-localized fluorescent reporters--GFP on one X chromosome and tdTomato on the other. Using these reporters in combination with different Cre drivers, we have defined the topographies of XCI mosaicism for multiple CNS cell types and of retinal vascular dysfunction in a model of Norrie disease. Depending on cell type, fluctuations in the XCI mosaic are observed over a wide range of spatial scales, from neighboring cells to left versus right sides of the body. These data imply a major role for XCI in generating female-specific, genetically directed, stochastic diversity in eutherian mammals on spatial scales that would be predicted to affect CNS function within and between individuals. Copyright © 2014 Elsevier Inc. All rights reserved.
Copeland, Stella; Bradford, John B.; Duniway, Michael C.; Schuster, Rudy
2017-01-01
Climate and land-use interactions are likely to affect future environmental and socioeconomic conditions in drylands, which tend to be limited by water resources and prone to land degradation. We characterized the potential for interactions between land-use types and land-use and climate change in a model dryland system, the Colorado Plateau, a region with a history of climatic variability and land-use change. We analyzed the spatial and temporal trends in aridification, land-use, and recreation at the county and 10 km2 grid scales. Our results show that oil and gas development and recreation may interact due to increasing trends and overlapping areas of high intensity. Projections suggest that aridification will impact all vegetation classes, with some of the highest proportional change in the south-east. The results suggest that the rate of change and spatial pattern of land-use in the future may differ from past patterns in land-use scale and intensity.
Wu, Hao; Luo, Junjie; Yu, Huimin; Rattner, Amir; Mo, Alisa; Wang, Yanshu; Smallwood, Philip M.; Erlanger, Bracha; Wheelan, Sarah J.; Nathans, Jeremy
2014-01-01
Female eutherian mammals use X-chromosome inactivation (XCI) to epigenetically regulate gene expression from ~4% of genes. To quantitatively map the topography of XCI for defined cell types at single cell resolution, we have generated female mice that carry X-linked, Cre-activated, and nuclear-localized fluorescent reporters – GFP on one X-chromosome and tdTomato on the other. Using these reporters in combination with different Cre drivers we have defined the topographies of XCI mosaicism for multiple CNS cell types and of retinal vascular dysfunction in a model of Norrie Disease. Depending on cell type, fluctuations in the XCI mosaic are observed over a wide range of spatial scales, from neighboring cells to left vs. right sides of the body. These data imply a major role for XCI in generating female-specific, genetically directed, stochastic diversity in eutherian mammals on spatial scales that would be predicted to affect CNS function within and between individuals. PMID:24411735
NASA Astrophysics Data System (ADS)
Koenig, W.
2016-12-01
The ecological impacts of modern global climate change are detectable in a wide variety of phenomena ranging from shifts in species ranges to changes in community composition and human disease dynamics. Thus far, however, little attention has been given to temporal changes in environmental spatial synchrony-the coincident change in abundance or value across the landscape-or environmental variability, despite the importance of these factors as drivers of population rescue and extinction and reproductive dynamics of both animal and plant populations. We quantified spatial synchrony of widespread North American wintering birds species using Audubon Christmas Bird Counts over the past 50 years and seed set variability (mast fruiting) among trees over the past century and found that both spatial synchrony of the birds and seed set variability have significantly increased over these time periods. The first of these results was mirrored by significant increases in spatial synchrony of mean maximum air temperature across North America, primarily during the summer, while the second is consistent with the hypothesis that climate change is resulting in greater seed set variability. These findings suggest the potential for temporal changes in envioronmental synchrony and variability to be affecting a wide range of ecological phenomena by influencing the probability of population rescue and extinction and by affecting ecosystem processes that rely on the resource pulses provided by mast fruiting plants.
Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai
2016-08-24
This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.
NASA Astrophysics Data System (ADS)
Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai
2016-08-01
This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.
Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai
2016-01-01
This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302–480 km, while the annual precipitation showed smaller scales of 111–182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions. PMID:27553388
The luminosity function for the CfA redshift survey slices
NASA Technical Reports Server (NTRS)
De Lapparent, Valerie; Geller, Margaret J.; Huchra, John P.
1989-01-01
The luminosity function for two complete slices of the extension of the CfA redshift survey is calculated. The nonparametric technique of Lynden-Bell (1971) and Turner (1979) is used to determine the shape for the luminosity function of the 12 deg slice of the redshift survey. The amplitude of the luminosity function is determined, taking large-scale inhomogeneities into account. The effects of the Malmquist bias on a magnitude-limited redshift survey are examined, showing that the random errors in the magnitudes for the 12 deg slice affect both the determination of the luminosity function and the spatial density constrast of large scale structures.
Zhang, X.; McGuire, A.D.; Ruess, Roger W.
2006-01-01
A major challenge confronting the scientific community is to understand both patterns of and controls over spatial and temporal variability of carbon exchange between boreal forest ecosystems and the atmosphere. An understanding of the sources of variability of carbon processes at fine scales and how these contribute to uncertainties in estimating carbon fluxes is relevant to representing these processes at coarse scales. To explore some of the challenges and uncertainties in estimating carbon fluxes at fine to coarse scales, we conducted a modeling analysis of canopy foliar maintenance respiration for black spruce ecosystems of Alaska by scaling empirical hourly models of foliar maintenance respiration (Rm) to estimate canopy foliar Rm for individual stands. We used variation in foliar N concentration among stands to develop hourly stand-specific models and then developed an hourly pooled model. An uncertainty analysis identified that the most important parameter affecting estimates of canopy foliar Rm was one that describes R m at 0??C per g N, which explained more than 55% of variance in annual estimates of canopy foliar Rm. The comparison of simulated annual canopy foliar Rm identified significant differences between stand-specific and pooled models for each stand. This result indicates that control over foliar N concentration should be considered in models that estimate canopy foliar Rm of black spruce stands across the landscape. In this study, we also temporally scaled the hourly stand-level models to estimate canopy foliar Rm of black spruce stands using mean monthly temperature data. Comparisons of monthly Rm between the hourly and monthly versions of the models indicated that there was very little difference between the estimates of hourly and monthly models, suggesting that hourly models can be aggregated to use monthly input data with little loss of precision. We conclude that uncertainties in the use of a coarse-scale model for estimating canopy foliar Rm at regional scales depend on uncertainties in representing needle-level respiration and on uncertainties in representing the spatial variability of canopy foliar N across a region. The development of spatial data sets of canopy foliar N represents a major challenge in estimating canopy foliar maintenance respiration at regional scales. ?? Springer 2006.
Impact of scale on morphological spatial pattern of forest
Katarzyna Ostapowicz; Peter Vogt; Kurt H. Riitters; Jacek Kozak; Christine Estreguil
2008-01-01
Assessing and monitoring landscape pattern structure from multi-scale land-cover maps can utilize morphological spatial pattern analysis (MSPA), only if various influences of scale are known and taken into account. This paper lays part of the foundation for applying MSPA analysis in landscape monitoring by quantifying scale effects on six classes of spatial patterns...
Retention capacity of correlated surfaces.
Schrenk, K J; Araújo, N A M; Ziff, R M; Herrmann, H J
2014-06-01
We extend the water retention model [C. L. Knecht et al., Phys. Rev. Lett. 108, 045703 (2012)] to correlated random surfaces. We find that the retention capacity of discrete random landscapes is strongly affected by spatial correlations among the heights. This phenomenon is related to the emergence of power-law scaling in the lake volume distribution. We also solve the uncorrelated case exactly for a small lattice and present bounds on the retention of uncorrelated landscapes.
Ellipsoidal universe can solve the cosmic microwave background quadrupole problem.
Campanelli, L; Cea, P; Tedesco, L
2006-09-29
The recent 3 yr Wilkinson Microwave Anisotropy Probe data have confirmed the anomaly concerning the low quadrupole amplitude compared to the best-fit Lambda-cold dark matter prediction. We show that by allowing the large-scale spatial geometry of our universe to be plane symmetric with eccentricity at decoupling or order 10(-2), the quadrupole amplitude can be drastically reduced without affecting higher multipoles of the angular power spectrum of the temperature anisotropy.
Gonçalves-Souza, Thiago; Romero, Gustavo Q.; Cottenie, Karl
2014-01-01
Biogeography and metacommunity ecology provide two different perspectives on species diversity. Both are spatial in nature but their spatial scales do not necessarily match. With recent boom of metacommunity studies, we see an increasing need for clear discrimination of spatial scales relevant for both perspectives. This discrimination is a necessary prerequisite for improved understanding of ecological phenomena across scales. Here we provide a case study to illustrate some spatial scale-dependent concepts in recent metacommunity studies and identify potential pitfalls. We presented here the diversity patterns of Neotropical lepidopterans and spiders viewed both from metacommunity and biogeographical perspectives. Specifically, we investigated how the relative importance of niche- and dispersal-based processes for community assembly change at two spatial scales: metacommunity scale, i.e. within a locality, and biogeographical scale, i.e. among localities widely scattered along a macroclimatic gradient. As expected, niche-based processes dominated the community assembly at metacommunity scale, while dispersal-based processes played a major role at biogeographical scale for both taxonomical groups. However, we also observed small but significant spatial effects at metacommunity scale and environmental effects at biogeographical scale. We also observed differences in diversity patterns between the two taxonomical groups corresponding to differences in their dispersal modes. Our results thus support the idea of continuity of processes interactively shaping diversity patterns across scales and emphasize the necessity of integration of metacommunity and biogeographical perspectives. PMID:25549332
Land Cover and Topography Affect the Land Transformation Caused by Wind Facilities
Diffendorfer, Jay E.; Compton, Roger W.
2014-01-01
Land transformation (ha of surface disturbance/MW) associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only), sites (strings with roads connecting them, buried cables and other infrastructure), and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure). An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here. PMID:24558449
Land cover and topography affect the land transformation caused by wind facilities
Diffendorfer, Jay E.; Compton, Roger W.
2014-01-01
Land transformation (ha of surface disturbance/MW) associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only), sites (strings with roads connecting them, buried cables and other infrastructure), and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure). An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here.
The relationship between observational scale and explained variance in benthic communities
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
Impacts of beaver dams on hydrologic and temperature regimes in a mountain stream
NASA Astrophysics Data System (ADS)
Majerova, M.; Neilson, B. T.; Schmadel, N. M.; Wheaton, J. M.; Snow, C. J.
2015-01-01
Beaver dams affect hydrologic processes, channel complexity, and stream temperature by increasing inundated areas and influencing groundwater-surface water interactions. We explored the impacts of beaver dams on hydrologic and temperature regimes at different spatial and temporal scales within a mountain stream in northern Utah over a three-year period spanning pre- and post-beaver colonization. Using continuous stream discharge, stream temperature, synoptic tracer experiments, and groundwater elevation measurements we documented pre-beaver conditions in the first year of the study. In the second year, we captured the initial effects of three beaver dams, while the third year included the effects of ten dams. After beaver colonization, reach scale discharge observations showed a shift from slightly losing to gaining. However, at the smaller sub-reach scale, the discharge gains and losses increased in variability due to more complex flow pathways with beaver dams forcing overland flow and increasing surface and subsurface storage. At the reach scale, temperatures were found to increase by 0.38 °C (3.8%), which in part is explained by a 230% increase in mean reach residence time. At the smallest, beaver dam scale, there were notable increases in the thermal heterogeneity where warmer and cooler niches were created. Through the quantification of hydrologic and thermal changes at different spatial and temporal scales, we document increased variability during post-beaver colonization and highlight the need to understand the impacts of beaver dams on stream ecosystems and their potential role in stream restoration.
Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun
2014-01-01
Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.
Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun
2014-01-01
Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760
NASA Astrophysics Data System (ADS)
Bicalho, E. S.; Teixeira, D. B.; Panosso, A. R.; Perillo, L. I.; Iamaguti, J. L.; Pereira, G. T.; La Scala, N., Jr.
2012-04-01
Soil CO2 emission (FCO2) is influenced by chemical, physical and biological factors that affect the production of CO2 in the soil and its transport to the atmosphere, varying in time and space depending on environmental conditions, including the management of agricultural area. The aim of this study was to investigate the structure of spatial variability of FCO2 and soil properties by using fractal dimension (DF), derived from isotropic variograms at different scales, and construction of fractograms. The experimental area consisted of a regular grid of 60 × 60 m on sugarcane area under green management, containing 141 points spaced at minimum distances ranging from 0.5 to 10 m. Soil CO2 emission, soil temperature and soil moisture were evaluated over a period of 7 days, and soil chemical and physical properties were determined by sampling at a depth of 0.0 to 0.1 m. FCO2 showed an overall average of 1.51 µmol m-2 s-1, correlated significantly (p < 0.05) with soil physical factors such as soil bulk density, air-filled pore space, macroporosity and microporosity. Significant DF values were obtained in the characterization of FCO2 in medium and large scales (from 20 m). Variations in DF with the scale, which is the fractogram, indicate that the structure of FCO2 variability is similar to that observed for the soil temperature and total pore volume, and reverse for the other soil properties, except for macroporosity, sand content, soil organic matter, carbon stock, C/N ratio and CEC, which fractograms were not significantly correlated to the FCO2 fractogram. Thus, the structure of spatial variability for most soil properties, characterized by fractogram, presents a significant relationship with the structure of spatial variability of FCO2, generally with similar or dissimilar behavior, indicating the possibility of using the fractogram as tool to better observe the behavior of the spatial dependence of the variables along the scale.
Cohen, David; Martel, Claire; Wilson, Anna; Déchambre, Nicole; Amy, Céline; Duverger, Ludovic; Guile, Jean-Marc; Pipiras, Eva; Benzacken, Brigitte; Cavé, Hélène; Cohen, Laurent; Héron, Delphine; Plaza, Monique
2007-09-01
Duplications of chromosome 15 may be one of the most common single genetic causes of autism spectrum disorders (ASD), aside from fragile X. Most of the cases are associated with maternally derived interstitial duplication involving 15q11-13. This case report describes a female proband with a maternally derived interstitial duplication of proximal 15q. She did not exhibit any symptoms of ASD apart from some developmental delay. By adolescence, she showed mild dysmorphism, a discrepant profile on the Wechsler Intelligence Scale for Children (Verbal IQ = 87; Performance IQ = 65) and a major deficit in visual-spatial abilities affecting fine motor skills, mathematical reasoning, visual memory and some global reading tasks. This is one of the first reports of a child with a maternal duplication who exhibits a visual-spatial deficit without ASD.
Paparelli, Laura; Corthout, Nikky; Pavie, Benjamin; Annaert, Wim; Munck, Sebastian
2016-01-01
The spatial distribution of proteins within the cell affects their capability to interact with other molecules and directly influences cellular processes and signaling. At the plasma membrane, multiple factors drive protein compartmentalization into specialized functional domains, leading to the formation of clusters in which intermolecule interactions are facilitated. Therefore, quantifying protein distributions is a necessity for understanding their regulation and function. The recent advent of super-resolution microscopy has opened up the possibility of imaging protein distributions at the nanometer scale. In parallel, new spatial analysis methods have been developed to quantify distribution patterns in super-resolution images. In this chapter, we provide an overview of super-resolution microscopy and summarize the factors influencing protein arrangements on the plasma membrane. Finally, we highlight methods for analyzing clusterization of plasma membrane proteins, including examples of their applications.
Neuropsychologic assessment of long-term survivors of childhood leukemia.
Pfefferbaum-Levine, B; Copeland, D R; Fletcher, J M; Ried, H L; Jaffe, N; McKinnon, W R
1984-01-01
Thirty-two long-term survivors of childhood leukemia who were followed up at the University of Texas M. D. Anderson Hospital were evaluated with a battery of 17 neuropsychologic tests. These tests were selected to assess the development of cognitive skills and functions associated with brain impairment in children. Statistically significant differences were found between the group of children given CNS irradiation and the nonirradiated group on full-scale IQ and verbal IQ scores, mathematics skills, constructional skills, and memory for spatial material. Of particular interest was the absence of differences in language-based measures of verbal memory and the presence of group differences on measures of memory for spatial material. While the sample size was small, the findings delineate specific areas likely to be affected. These results indicate the need for caution when including cranial irradiation in CNS prophylaxis. When any CNS treatment is given, it seems appropriate that provisions be made for assessment and remediation of affected skills.
Climate limits across space and time on European forest structure
NASA Astrophysics Data System (ADS)
Moreno, A. L. S.; Neumann, M.; Hasenauer, H.
2017-12-01
The impact climate has on forests has been extensively studied. However, the large scale effect climate has on forest structures, such as average diameters, heights and basal area are understudied in a spatially explicit manner. The limits, tipping points and thresholds that climate places on forest structures dictate the services a forest may provide, the vulnerability of a forest to mortality and the potential value of the timber there within. The majority of current research either investigates climate impacts on forest pools and fluxes, on a tree physiological scale or on case studies that are used to extrapolate results and potential impacts. A spatially explicit study on how climate affects forest structure over a large region would give valuable information to stakeholders who are more concerned with ecosystem services that cannot be described by pools and fluxes but require spatially explicit information - such as biodiversity, habitat suitability, and market values. In this study, we quantified the limits that climate (maximum, minimum temperature and precipitation) places on 3 forest structures, diameter at breast height, height, and basal area throughout Europe. Our results show clear climatic zones of high and low upper limits for each forest structure variable studied. We also spatially analyzed how climate restricts the potential bio-physical upper limits and creates tipping points of each forest structure variable and which climate factors are most limiting. Further, we demonstrated how the climate change has affected 8 individual forests across Europe and then the continent as a whole. We find that diameter, height and basal area are limited by climate in different ways and that areas may have high upper limits in one structure and low upper limits in another limitted by different climate variables. We also found that even though individual forests may have increased their potential upper limit forest structure values, European forests as a whole have lost, on average, 5.0%, 1.7% and 6.5% in potential mean forest diameter, height and basal area, respectively.
An invariability-area relationship sheds new light on the spatial scaling of ecological stability.
Wang, Shaopeng; Loreau, Michel; Arnoldi, Jean-Francois; Fang, Jingyun; Rahman, K Abd; Tao, Shengli; de Mazancourt, Claire
2017-05-19
The spatial scaling of stability is key to understanding ecological sustainability across scales and the sensitivity of ecosystems to habitat destruction. Here we propose the invariability-area relationship (IAR) as a novel approach to investigate the spatial scaling of stability. The shape and slope of IAR are largely determined by patterns of spatial synchrony across scales. When synchrony decays exponentially with distance, IARs exhibit three phases, characterized by steeper increases in invariability at both small and large scales. Such triphasic IARs are observed for primary productivity from plot to continental scales. When synchrony decays as a power law with distance, IARs are quasilinear on a log-log scale. Such quasilinear IARs are observed for North American bird biomass at both species and community levels. The IAR provides a quantitative tool to predict the effects of habitat loss on population and ecosystem stability and to detect regime shifts in spatial ecological systems, which are goals of relevance to conservation and policy.