How is a stream impacted by burial? Examining the spatial variation within urban buried streams in Cincinnati, OH

EPA Science Inventory

While the effects of urbanization on stream ecosystems have been well-documented, little is known regarding the impact of burying streams within culverts. Our project aims to explore the ecological impacts of stream burial at a fine spatial scale. Two culverted urban streams in C...

Fine-scale spatial genetic dynamics over the life cycle of the tropical tree Prunus africana.

PubMed

Berens, D G; Braun, C; González-Martínez, S C; Griebeler, E M; Nathan, R; Böhning-Gaese, K

2014-11-01

Studying fine-scale spatial genetic patterns across life stages is a powerful approach to identify ecological processes acting within tree populations. We investigated spatial genetic dynamics across five life stages in the insect-pollinated and vertebrate-dispersed tropical tree Prunus africana in Kakamega Forest, Kenya. Using six highly polymorphic microsatellite loci, we assessed genetic diversity and spatial genetic structure (SGS) from seed rain and seedlings, and different sapling stages to adult trees. We found significant SGS in all stages, potentially caused by limited seed dispersal and high recruitment rates in areas with high light availability. SGS decreased from seed and early seedling stages to older juvenile stages. Interestingly, SGS was stronger in adults than in late juveniles. The initial decrease in SGS was probably driven by both random and non-random thinning of offspring clusters during recruitment. Intergenerational variation in SGS could have been driven by variation in gene flow processes, overlapping generations in the adult stage or local selection. Our study shows that complex sequential processes during recruitment contribute to SGS of tree populations.

Quantifying the imprint of mesoscale and synoptic-scale atmospheric transport on total column carbon dioxide measurements

NASA Astrophysics Data System (ADS)

Torres, A. D.; Keppel-Aleks, G.; Doney, S. C.; Feng, S.; Lauvaux, T.; Fendrock, M. A.; Rheuben, J.

2017-12-01

Remote sensing instruments provide an unprecedented density of observations of the atmospheric CO2 column average mole fraction (denoted as XCO2), which can be used to constrain regional scale carbon fluxes. Inferring fluxes from XCO2 observations is challenging, as measurements and inversion methods are sensitive to not only the imprint local and large-scale fluxes, but also mesoscale and synoptic-scale atmospheric transport. Quantifying the fine-scale variability in XCO2 from mesoscale and synoptic-scale atmospheric transport will likely improve overall error estimates from flux inversions by improving estimates of representation errors that occur when XCO2 observations are compared to modeled XCO2 in relatively coarse transport models. Here, we utilize various statistical methods to quantify the imprint of atmospheric transport on XCO2 observations. We compare spatial variations along Orbiting Carbon Observatory (OCO-2) satellite tracks to temporal variations observed by the Total Column Carbon Observing Network (TCCON). We observe a coherent seasonal cycle of both within-day temporal and fine-scale spatial variability (of order 10 km) of XCO2 from these two datasets, suggestive of the imprint of mesoscale systems. To account for other potential sources of error in XCO2 retrieval, we compare observed temporal and spatial variations of XCO2 to high-resolution output from the Weather Research and Forecasting (WRF) model run at 9 km resolution. In both simulations and observations, the Northern hemisphere mid-latitude XCO2 showed peak variability during the growing season when atmospheric gradients are largest. These results are qualitatively consistent with our expectations of seasonal variations of the imprint of synoptic and mesoscale atmospheric transport on XCO2 observations; suggesting that these statistical methods could be sensitive to the imprint of atmospheric transport on XCO2 observations.

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

PubMed Central

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

2011-01-01

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

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

PubMed

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

2011-01-01

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

Reproductive phenology of coastal plain Atlantic forest vegetation: comparisons from seashore to foothills.

PubMed

Staggemeier, Vanessa Graziele; Morellato, Leonor Patrícia Cerdeira

2011-11-01

The diversity of tropical forest plant phenology has called the attention of researchers for a long time. We continue investigating the factors that drive phenological diversity on a wide scale, but we are unaware of the variation of plant reproductive phenology at a fine spatial scale despite the high spatial variation in species composition and abundance in tropical rainforests. We addressed fine scale variability by investigating the reproductive phenology of three contiguous vegetations across the Atlantic rainforest coastal plain in Southeastern Brazil. We asked whether the vegetations differed in composition and abundance of species, the microenvironmental conditions and the reproductive phenology, and how their phenology is related to regional and local microenvironmental factors. The study was conducted from September 2007 to August 2009 at three contiguous sites: (1) seashore dominated by scrub vegetation, (2) intermediary covered by restinga forest and (3) foothills covered by restinga pre-montane transitional forest. We conducted the microenvironmental, plant and phenological survey within 30 transects of 25 m × 4 m (10 per site). We detected significant differences in floristic, microenvironment and reproductive phenology among the three vegetations. The microenvironment determines the spatial diversity observed in the structure and composition of the flora, which in turn determines the distinctive flowering and fruiting peaks of each vegetation (phenological diversity). There was an exchange of species providing flowers and fruits across the vegetation complex. We conclude that plant reproductive patterns as described in most phenological studies (without concern about the microenvironmental variation) may conceal the fine scale temporal phenological diversity of highly diverse tropical vegetation. This phenological diversity should be taken into account when generating sensor-derived phenologies and when trying to understand tropical vegetation responses to environmental changes.

Spectral characteristics of background error covariance and multiscale data assimilation

DOE PAGES

Li, Zhijin; Cheng, Xiaoping; Gustafson, Jr., William I.; ...

2016-05-17

The steady increase of the spatial resolutions of numerical atmospheric and oceanic circulation models has occurred over the past decades. Horizontal grid spacing down to the order of 1 km is now often used to resolve cloud systems in the atmosphere and sub-mesoscale circulation systems in the ocean. These fine resolution models encompass a wide range of temporal and spatial scales, across which dynamical and statistical properties vary. In particular, dynamic flow systems at small scales can be spatially localized and temporarily intermittent. Difficulties of current data assimilation algorithms for such fine resolution models are numerically and theoretically examined. Ourmore » analysis shows that the background error correlation length scale is larger than 75 km for streamfunctions and is larger than 25 km for water vapor mixing ratios, even for a 2-km resolution model. A theoretical analysis suggests that such correlation length scales prevent the currently used data assimilation schemes from constraining spatial scales smaller than 150 km for streamfunctions and 50 km for water vapor mixing ratios. Moreover, our results highlight the need to fundamentally modify currently used data assimilation algorithms for assimilating high-resolution observations into the aforementioned fine resolution models. Lastly, within the framework of four-dimensional variational data assimilation, a multiscale methodology based on scale decomposition is suggested and challenges are discussed.« less

The complex roles of space and environment in structuring functional, taxonomic and phylogenetic beta diversity of frogs in the Atlantic Forest

PubMed Central

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

Determinants of the Spatial Distributions of Elemental Carbon and Particulate Matter in Eight Southern Californian Communities

PubMed Central

Urman, Robert; Gauderman, James; Fruin, Scott; Lurmann, Fred; Liu, Feifei; Hosseini, Reza; Franklin, Meredith; Avol, Edward; Penfold, Bryan; Gilliland, Frank; Brunekreef, Bert; McConnell, Rob

2014-01-01

Emerging evidence indicates that near-roadway pollution (NRP) in ambient air has adverse health effects. However, specific components of the NRP mixture responsible for these effects have not been established. A major limitation for health studies is the lack of exposure models that estimate NRP components observed in epidemiological studies over fine spatial scale of tens to hundreds of meters. In this study, exposure models were developed for fine-scale variation in biologically relevant elemental carbon (EC). Measurements of particulate matter (PM) and EC less than 2.5 μm in aerodynamic diameter (EC2.5) and of PM and EC of nanoscale size less than 0.2 μm were made at up to 29 locations in each of eight Southern California Children's Health Study communities. Regression-based prediction models were developed using a guided forward selection process to identify traffic variables and other pollutant sources, community physical characteristics and land use as predictors of PM and EC variation in each community. A combined eight-community model including only CALINE4 near-roadway dispersion-estimated vehicular emissions accounting for distance, distance-weighted traffic volume, and meteorology, explained 51% of the EC0.2 variability. Community-specific models identified additional predictors in some communities; however, in most communities the correlation between predicted concentrations from the eight-community model and observed concentrations stratified by community were similar to those for the community-specific models. EC2.5 could be predicted as well as EC0.2. EC2.5 estimated from CALINE4 and population density explained 53% of the within-community variation. Exposure prediction was further improved after accounting for between-community heterogeneity of CALINE4 effects associated with average distance to Pacific Ocean shoreline (to 61% for EC0.2) and for regional NOx pollution (to 57% for EC2.5). PM fine spatial scale variation was poorly predicted in both size fractions. In conclusion, models of exposure that include traffic measures such as CALINE4 can provide useful estimates for EC0.2 and EC2.5 on a spatial scale appropriate for health studies of NRP in selected Southern California communities. PMID:25313293

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

PubMed

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

2016-07-01

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

Merging fine and coarse resolution remotely sensed data with household-level survey data to evaluate small-scale vulnerability to climate change in West Africa

NASA Astrophysics Data System (ADS)

Grace, K.; Husak, G. J.

2016-12-01

Climate change, in the form of increasingly variable temperatures and rainfall, is anticipated to have potentially dramatic impacts on subsistence agricultural communities throughout the world. Poor people who depend on rainfall to produce food or to produce products to sell to buy food are expected to be particularly vulnerable to the negative impacts associated with climate change. Poor people have extremely limited resources that can be used to cope with weather events and these resources are even more strained when the individuals live in poor countries. While poor and rural producers are most likely to face high levels of vulnerability to food insecurity due to their dependence on rainfall for their agricultural production, annual agricultural censuses are virtually non-existent. Surveying all of the producers in a country each year is extremely costly owing to difficulties in accessing farmers and the costs associated with extensive surveys. The result, however, is very limited information on the spatial and temporal variation in production and the resulting impacts on micro-scale food insecurity and livelihood stability. In this project we use a combination of fine and coarse resolution remotely sensed data ( 1m data, 250m NDVI data and 10km rainfall data, and others) and recently collected survey data from the World Bank to estimate agricultural and land use characteristics at a fine spatial scale in Burkina Faso, Mali and Niger. The analysis will produce estimates of cultivated area that incorporate spatially dynamic climate and vegetation data but that also account for the variation in agricultural practices associated with the different ethnic and religious groups within each country. The survey data will help to calibrate the models and will also serve as a way to validate the statistical models used to estimate on the ground agricultural practices. The models will then be used to evaluate fine-scale agricultural response to climate change in the form of drying and warming.

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

NASA Technical Reports Server (NTRS)

Meng, Ran; Wu, Jin; Schwager, Kathy L.; Zhao, Feng; Dennison, Philip E.; Cook, Bruce D.; Brewster, Kristen; Green, Timothy M.; Serbin, Shawn P.

2017-01-01

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

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

Meng, Ran; Wu, Jin; Schwager, Kathy L.

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

DOE PAGES

Meng, Ran; Wu, Jin; Schwager, Kathy L.; ...

2017-01-21

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Fine-scale structure in the far-infrared Milky-Way

NASA Technical Reports Server (NTRS)

Waller, William H.; Wall, William F.; Reach, William T.; Varosi, Frank; Ebert, Rick; Laughlin, Gaylin; Boulanger, Francois

1995-01-01

This final report summarizes the work performed and which falls into five broad categories: (1) generation of a new data product (mosaics of the far-infrared emission in the Milky Way); (2) acquisition of associated data products at other wavelengths; (3) spatial filtering of the far-infrared mosaics and resulting images of the FIR fine-scale structure; (4) evaluation of the spatially filtered data; (5) characterization of the FIR fine-scale structure in terms of its spatial statistics; and (6) identification of interstellar counterparts to the FIR fine-scale structure.

Separating the effects of environment and space on tree species distribution: from population to community.

PubMed

Lin, Guojun; Stralberg, Diana; Gong, Guiquan; Huang, Zhongliang; Ye, Wanhui; Wu, Linfang

2013-01-01

Quantifying the relative contributions of environmental conditions and spatial factors to species distribution can help improve our understanding of the processes that drive diversity patterns. In this study, based on tree inventory, topography and soil data from a 20-ha stem-mapped permanent forest plot in Guangdong Province, China, we evaluated the influence of different ecological processes at different spatial scales using canonical redundancy analysis (RDA) at the community level and multiple linear regression at the species level. At the community level, the proportion of explained variation in species distribution increased with grid-cell sizes, primarily due to a monotonic increase in the explanatory power of environmental variables. At the species level, neither environmental nor spatial factors were important determinants of overstory species' distributions at small cell sizes. However, purely spatial variables explained most of the variation in the distributions of understory species at fine and intermediate cell sizes. Midstory species showed patterns that were intermediate between those of overstory and understory species. At the 20-m cell size, the influence of spatial factors was stronger for more dispersal-limited species, suggesting that much of the spatial structuring in this community can be explained by dispersal limitation. Comparing environmental factors, soil variables had higher explanatory power than did topography for species distribution. However, both topographic and edaphic variables were highly spatial structured. Our results suggested that dispersal limitation has an important influence on fine-intermediate scale (from several to tens of meters) species distribution, while environmental variability facilitates species distribution at intermediate (from ten to tens of meters) and broad (from tens to hundreds of meters) scales.

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

PubMed

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

2017-09-11

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

Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and direction.

PubMed

Yonehara, Yoshinari; Goto, Yusuke; Yoda, Ken; Watanuki, Yutaka; Young, Lindsay C; Weimerskirch, Henri; Bost, Charles-André; Sato, Katsufumi

2016-08-09

Ocean surface winds are an essential factor in understanding the physical interactions between the atmosphere and the ocean. Surface winds measured by satellite scatterometers and buoys cover most of the global ocean; however, there are still spatial and temporal gaps and finer-scale variations of wind that may be overlooked, particularly in coastal areas. Here, we show that flight paths of soaring seabirds can be used to estimate fine-scale (every 5 min, ∼5 km) ocean surface winds. Fine-scale global positioning system (GPS) positional data revealed that soaring seabirds flew tortuously and ground speed fluctuated presumably due to tail winds and head winds. Taking advantage of the ground speed difference in relation to flight direction, we reliably estimated wind speed and direction experienced by the birds. These bird-based wind velocities were significantly correlated with wind velocities estimated by satellite-borne scatterometers. Furthermore, extensive travel distances and flight duration of the seabirds enabled a wide range of high-resolution wind observations, especially in coastal areas. Our study suggests that seabirds provide a platform from which to measure ocean surface winds, potentially complementing conventional wind measurements by covering spatial and temporal measurement gaps.

Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and direction

PubMed Central

Yonehara, Yoshinari; Goto, Yusuke; Yoda, Ken; Watanuki, Yutaka; Young, Lindsay C.; Weimerskirch, Henri; Bost, Charles-André; Sato, Katsufumi

2016-01-01

Ocean surface winds are an essential factor in understanding the physical interactions between the atmosphere and the ocean. Surface winds measured by satellite scatterometers and buoys cover most of the global ocean; however, there are still spatial and temporal gaps and finer-scale variations of wind that may be overlooked, particularly in coastal areas. Here, we show that flight paths of soaring seabirds can be used to estimate fine-scale (every 5 min, ∼5 km) ocean surface winds. Fine-scale global positioning system (GPS) positional data revealed that soaring seabirds flew tortuously and ground speed fluctuated presumably due to tail winds and head winds. Taking advantage of the ground speed difference in relation to flight direction, we reliably estimated wind speed and direction experienced by the birds. These bird-based wind velocities were significantly correlated with wind velocities estimated by satellite-borne scatterometers. Furthermore, extensive travel distances and flight duration of the seabirds enabled a wide range of high-resolution wind observations, especially in coastal areas. Our study suggests that seabirds provide a platform from which to measure ocean surface winds, potentially complementing conventional wind measurements by covering spatial and temporal measurement gaps. PMID:27457932

Selecting habitat to survive: the impact of road density on survival in a large carnivore.

PubMed

Basille, Mathieu; Van Moorter, Bram; Herfindal, Ivar; Martin, Jodie; Linnell, John D C; Odden, John; Andersen, Reidar; Gaillard, Jean-Michel

2013-01-01

Habitat selection studies generally assume that animals select habitat and food resources at multiple scales to maximise their fitness. However, animals sometimes prefer habitats of apparently low quality, especially when considering the costs associated with spatially heterogeneous human disturbance. We used spatial variation in human disturbance, and its consequences on lynx survival, a direct fitness component, to test the Hierarchical Habitat Selection hypothesis from a population of Eurasian lynx Lynx lynx in southern Norway. Data from 46 lynx monitored with telemetry indicated that a high proportion of forest strongly reduced the risk of mortality from legal hunting at the home range scale, while increasing road density strongly increased such risk at the finer scale within the home range. We found hierarchical effects of the impact of human disturbance, with a higher road density at a large scale reinforcing its negative impact at a fine scale. Conversely, we demonstrated that lynx shifted their habitat selection to avoid areas with the highest road densities within their home ranges, thus supporting a compensatory mechanism at fine scale enabling lynx to mitigate the impact of large-scale disturbance. Human impact, positively associated with high road accessibility, was thus a stronger driver of lynx space use at a finer scale, with home range characteristics nevertheless constraining habitat selection. Our study demonstrates the truly hierarchical nature of habitat selection, which aims at maximising fitness by selecting against limiting factors at multiple spatial scales, and indicates that scale-specific heterogeneity of the environment is driving individual spatial behaviour, by means of trade-offs across spatial scales.

Assessment of fine-scale resource selection and spatially explicit habitat suitability modelling for a re-introduced tiger (Panthera tigris) population in central India

PubMed Central

Sarkar, Mriganka Shekhar; Johnson, Jeyaraj A.; Sen, Subharanjan

2017-01-01

Background Large carnivores influence ecosystem functions at various scales. Thus, their local extinction is not only a species-specific conservation concern, but also reflects on the overall habitat quality and ecosystem value. Species-habitat relationships at fine scale reflect the individuals’ ability to procure resources and negotiate intraspecific competition. Such fine scale habitat choices are more pronounced in large carnivores such as tiger (Panthera tigris), which exhibits competitive exclusion in habitat and mate selection strategies. Although landscape level policies and conservation strategies are increasingly promoted for tiger conservation, specific management interventions require knowledge of the habitat correlates at fine scale. Methods We studied nine radio-collared individuals of a successfully reintroduced tiger population in Panna Tiger Reserve, central India, focussing on the species-habitat relationship at fine scales. With 16 eco-geographical variables, we performed Manly’s selection ratio and K-select analyses to define population-level and individual-level variation in resource selection, respectively. We analysed the data obtained during the exploratory period of six tigers and during the settled period of eight tigers separately, and compared the consequent results. We further used the settled period characteristics to model and map habitat suitability based on the Mahalanobis D2 method and the Boyce index. Results There was a clear difference in habitat selection by tigers between the exploratory and the settled period. During the exploratory period, tigers selected dense canopy and bamboo forests, but also spent time near villages and relocated village sites. However, settled tigers predominantly selected bamboo forests in complex terrain, riverine forests and teak-mixed forest, and totally avoided human settlements and agriculture areas. There were individual variations in habitat selection between exploratory and settled periods. Based on threshold limits of habitat selection by the Boyce Index, we established that 83% of core and 47% of buffer areas are now suitable habitats for tiger in this reserve. Discussion Tiger management often focuses on large-scale measures, but this study for the first time highlights the behaviour and fine-scale individual-specific habitat selection strategies. Such knowledge is vital for management of critical tiger habitats and specifically for the success of reintroduction programs. Our spatially explicit habitat suitability map provides a baseline for conservation planning and optimizing carrying capacity of the tiger population in this reserve. PMID:29114438

Assessment of fine-scale resource selection and spatially explicit habitat suitability modelling for a re-introduced tiger (Panthera tigris) population in central India.

PubMed

Sarkar, Mriganka Shekhar; Krishnamurthy, Ramesh; Johnson, Jeyaraj A; Sen, Subharanjan; Saha, Goutam Kumar

2017-01-01

Large carnivores influence ecosystem functions at various scales. Thus, their local extinction is not only a species-specific conservation concern, but also reflects on the overall habitat quality and ecosystem value. Species-habitat relationships at fine scale reflect the individuals' ability to procure resources and negotiate intraspecific competition. Such fine scale habitat choices are more pronounced in large carnivores such as tiger ( Panthera tigris ), which exhibits competitive exclusion in habitat and mate selection strategies. Although landscape level policies and conservation strategies are increasingly promoted for tiger conservation, specific management interventions require knowledge of the habitat correlates at fine scale. We studied nine radio-collared individuals of a successfully reintroduced tiger population in Panna Tiger Reserve, central India, focussing on the species-habitat relationship at fine scales. With 16 eco-geographical variables, we performed Manly's selection ratio and K-select analyses to define population-level and individual-level variation in resource selection, respectively. We analysed the data obtained during the exploratory period of six tigers and during the settled period of eight tigers separately, and compared the consequent results. We further used the settled period characteristics to model and map habitat suitability based on the Mahalanobis D 2 method and the Boyce index. There was a clear difference in habitat selection by tigers between the exploratory and the settled period. During the exploratory period, tigers selected dense canopy and bamboo forests, but also spent time near villages and relocated village sites. However, settled tigers predominantly selected bamboo forests in complex terrain, riverine forests and teak-mixed forest, and totally avoided human settlements and agriculture areas. There were individual variations in habitat selection between exploratory and settled periods. Based on threshold limits of habitat selection by the Boyce Index, we established that 83% of core and 47% of buffer areas are now suitable habitats for tiger in this reserve. Tiger management often focuses on large-scale measures, but this study for the first time highlights the behaviour and fine-scale individual-specific habitat selection strategies. Such knowledge is vital for management of critical tiger habitats and specifically for the success of reintroduction programs. Our spatially explicit habitat suitability map provides a baseline for conservation planning and optimizing carrying capacity of the tiger population in this reserve.

Coupling fine-scale root and canopy structure using ground-based remote sensing

DOE PAGES

Hardiman, Brady S.; Gough, Christopher M.; Butnor, John R.; ...

2017-02-21

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation) at multiple spatialmore » scales 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5–4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Lastly, our study highlights the potential, and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure.« less

Coupling fine-scale root and canopy structure using ground-based remote sensing

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

Hardiman, Brady S.; Gough, Christopher M.; Butnor, John R.

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation) at multiple spatialmore » scales 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5–4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Lastly, our study highlights the potential, and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure.« less

The impact of mating systems and dispersal on fine-scale genetic structure at maternally, paternally and biparentally inherited markers.

PubMed

Shaw, Robyn E; Banks, Sam C; Peakall, Rod

2018-01-01

For decades, studies have focused on how dispersal and mating systems influence genetic structure across populations or social groups. However, we still lack a thorough understanding of how these processes and their interaction shape spatial genetic patterns over a finer scale (tens-hundreds of metres). Using uniparentally inherited markers may help answer these questions, yet their potential has not been fully explored. Here, we use individual-level simulations to investigate the effects of dispersal and mating system on fine-scale genetic structure at autosomal, mitochondrial and Y chromosome markers. Using genetic spatial autocorrelation analysis, we found that dispersal was the major driver of fine-scale genetic structure across maternally, paternally and biparentally inherited markers. However, when dispersal was restricted (mean distance = 100 m), variation in mating behaviour created strong differences in the comparative level of structure detected at maternally and paternally inherited markers. Promiscuity reduced spatial genetic structure at Y chromosome loci (relative to monogamy), whereas structure increased under polygyny. In contrast, mitochondrial and autosomal markers were robust to differences in the specific mating system, although genetic structure increased across all markers when reproductive success was skewed towards fewer individuals. Comparing males and females at Y chromosome vs. mitochondrial markers, respectively, revealed that some mating systems can generate similar patterns to those expected under sex-biased dispersal. This demonstrates the need for caution when inferring ecological and behavioural processes from genetic results. Comparing patterns between the sexes, across a range of marker types, may help us tease apart the processes shaping fine-scale genetic structure. © 2017 John Wiley & Sons Ltd.

A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2017-07-01

Use of General Circulation Model (GCM) precipitation and evapotranspiration sequences for hydrologic modelling can result in unrealistic simulations due to the coarse scales at which GCMs operate and the systematic biases they contain. The Bias Correction Spatial Disaggregation (BCSD) method is a popular statistical downscaling and bias correction method developed to address this issue. The advantage of BCSD is its ability to reduce biases in the distribution of precipitation totals at the GCM scale and then introduce more realistic variability at finer scales than simpler spatial interpolation schemes. Although BCSD corrects biases at the GCM scale before disaggregation; at finer spatial scales biases are re-introduced by the assumptions made in the spatial disaggregation process. Our study focuses on this limitation of BCSD and proposes a rank-based approach that aims to reduce the spatial disaggregation bias especially for both low and high precipitation extremes. BCSD requires the specification of a multiplicative bias correction anomaly field that represents the ratio of the fine scale precipitation to the disaggregated precipitation. It is shown that there is significant temporal variation in the anomalies, which is masked when a mean anomaly field is used. This can be improved by modelling the anomalies in rank-space. Results from the application of the rank-BCSD procedure improve the match between the distributions of observed and downscaled precipitation at the fine scale compared to the original BCSD approach. Further improvements in the distribution are identified when a scaling correction to preserve mass in the disaggregation process is implemented. An assessment of the approach using a single GCM over Australia shows clear advantages especially in the simulation of particularly low and high downscaled precipitation amounts.

Genetic structuring of northern myotis (Myotis septentrionalis) at multiple spatial scales

USGS Publications Warehouse

Johnson, Joshua B.; Roberts, James H.; King, Timothy L.; Edwards, John W.; Ford, W. Mark; Ray, David A.

2014-01-01

Although groups of bats may be genetically distinguishable at large spatial scales, the effects of forest disturbances, particularly permanent land use conversions on fine-scale population structure and gene flow of summer aggregations of philopatric bat species are less clear. We genotyped and analyzed variation at 10 nuclear DNA microsatellite markers in 182 individuals of the forest-dwelling northern myotis (Myotis septentrionalis) at multiple spatial scales, from within first-order watersheds scaling up to larger regional areas in West Virginia and New York. Our results indicate that groups of northern myotis were genetically indistinguishable at any spatial scale we considered, and the collective population maintained high genetic diversity. It is likely that the ability to migrate, exploit small forest patches, and use networks of mating sites located throughout the Appalachian Mountains, Interior Highlands, and elsewhere in the hibernation range have allowed northern myotis to maintain high genetic diversity and gene flow regardless of forest disturbances at local and regional spatial scales. A consequence of maintaining high gene flow might be the potential to minimize genetic founder effects following population declines caused currently by the enzootic White-nose Syndrome.

Fine-scale spatial climate variation and drought mediate the likelihood of reburning

Treesearch

Sean A. Parks; Marc‐Andre Parisien; Carol Miller; Lisa M. Holsinger; Larry Scott Baggett

2018-01-01

In many forested ecosystems, it is increasingly recognized that the probability of burning is substantially reduced within the footprint of previously burned areas. This self‐limiting effect of wildland fire is considered a fundamental emergent property of ecosystems and is partly responsible for structuring landscape heterogeneity (i.e., mosaics of different age...

Untangling the contribution of aspect, drainage position and elevation to the spatial variability of fine surface fuels in south east Australian forests

NASA Astrophysics Data System (ADS)

Sheridan, Gary; nyman, petter; Duff, Tom; Baillie, Craig; Bovill, William; Lane, Patrick; Tolhurst, Kevin

2015-04-01

The prediction of fuel moisture content is important for estimating the rate of spread of wildfires, the ignition probability of firebrands, and for the efficient scheduling of prescribed fire. The moisture content of fine surface fuels varies spatially at large scales (10's to 100's km) due to variation in meteorological variables (eg. temperature, relative humidity, precipitation). At smaller scales (100's of metres) in steep topography spatial variability is attributed to topographic influences that include differences in radiation due to aspect and slope, differences in precipitation, temperature and relative humidity due to elevation, and differences in soil moisture due to hillslope drainage position. Variable forest structure and canopy shading adds further to the spatial variability in surface fuel moisture. In this study we aim to combine daily 5km resolution gridded weather data with 20m resolution DEM and vegetation structure data to predict the spatial variability of fine surface fuels in steep topography. Microclimate stations were established in south east Australia to monitor surface fine fuel moisture continuously (every 15 minutes) using newly developed instrumented litter packs, in addition to temperature and relative humidity measurements inside the litter pack, and measurement of precipitation and energy inputs above and below the forest canopy. Microclimate stations were established across a gradient of aspect (5 stations), drainage position (7 stations), elevation (15 stations), and canopy cover conditions (6 stations). The data from this extensive network of microclimate stations across a broad spectrum of topographic conditions is being analysed to enable the downscaling of gridded weather data to spatial scales that are relevant to the connectivity of wildfire fuels and to the scheduling and outcome of prescribed fires. The initial results from the first year of this study are presented here.

Coexistence between wildlife and humans at fine spatial scales.

PubMed

Carter, Neil H; Shrestha, Binoj K; Karki, Jhamak B; Pradhan, Narendra Man Babu; Liu, Jianguo

2012-09-18

Many wildlife species face imminent extinction because of human impacts, and therefore, a prevailing belief is that some wildlife species, particularly large carnivores and ungulates, cannot coexist with people at fine spatial scales (i.e., cannot regularly use the exact same point locations). This belief provides rationale for various conservation programs, such as resettling human communities outside protected areas. However, quantitative information on the capacity and mechanisms for wildlife to coexist with humans at fine spatial scales is scarce. Such information is vital, because the world is becoming increasingly crowded. Here, we provide empirical information about the capacity and mechanisms for tigers (a globally endangered species) to coexist with humans at fine spatial scales inside and outside Nepal's Chitwan National Park, a flagship protected area for imperiled wildlife. Information obtained from field cameras in 2010 and 2011 indicated that human presence (i.e., people on foot and vehicles) was ubiquitous and abundant throughout the study site; however, tiger density was also high. Surprisingly, even at a fine spatial scale (i.e., camera locations), tigers spatially overlapped with people on foot and vehicles in both years. However, in both years, tigers offset their temporal activity patterns to be much less active during the day when human activity peaked. In addition to temporal displacement, tiger-human coexistence was likely enhanced by abundant tiger prey and low levels of tiger poaching. Incorporating fine-scale spatial and temporal activity patterns into conservation plans can help address a major global challenge-meeting human needs while sustaining wildlife.

Fine-grained sediment spatial distribution on the basis of a geostatistical analysis: Example of the eastern Bay of the Seine (France)

NASA Astrophysics Data System (ADS)

Méar, Y.; Poizot, E.; Murat, A.; Lesueur, P.; Thomas, M.

2006-12-01

The eastern Bay of the Seine (English Channel) was the subject in 1991 of a sampling survey of superficial sediments. Geostatistic tools were used to examine the complexity of the spatial distribution of the fine-grained fraction (<50 μm). A central depocentre of fine sediments (i.e. content up to 50%) oriented in a NW-SE direction in a muddy coastal strip, in a very high energy hydrodynamical situation due to storm swells and its megatidal setting, is for the first time recognised and discussed. Within this sedimentary unit, the distribution of the fine fraction is very heterogeneous, with mud patches of less than 4000 m diameter; the boundary between these mud patches and their substratum is very sharp. The distribution of this fine fraction appears to be controlled by an anticyclonic eddy located off the Pays de Caux. Under the influence of this, the suspended material expelled from the Seine estuary moves along the coast and swings off Antifer harbour, towards the NW. It is trapped within this eddy because of the settling of suspended particulate matter. Both at a general scale and a local scale the morphology (whether inherited or due to modern processes) has a strong influence on the spatial distribution of the fine fraction. At the general scale, the basin-like shape of the area facilitates the silting, and the presence of the submarine dunes, called "Ridins d'Antifer", clearly determines the northern limit of the muddy zone. At a local scale, the same influence is obvious: paleovalleys trap the fine sediments, whereas isolated sand dunes and ripples limit the silting. This duality of role of the morphology is therefore one of the reasons why the muddy surface is extremely heterogeneous spatially. The presence of an important population of suspension feeding echinoderm, the brittle-star Ophiothrix fragilis Abildgaard, has led to a local increase in the silting, and to the modification of the physicochemical and sedimentological parameters. A complex relationship is shown to occur between the amount of fine fraction and the number of brittle-stars (ind. m -2). Classical statistical methods are not appropriate to study the spatial distribution of the mud fraction, because the spatial component of the percentage of the distribution is not integrated in the analysis. On the other hand, this is the main property of the geostatistic concepts. The use of geostatistic tools within a strict and clearly identified procedure enables the proposal of an accurate cartography. Further application of the proposed protocol (based on a semivariographic study and a conditional simulation interpolation) for surficial sediments mapping will help explain spatial and temporal variations of fine-grained fraction. Then assessments of sedimentation and erosion stages allow highlighting signature of environmental processes.

Spatial adaptive sampling in multiscale simulation

NASA Astrophysics Data System (ADS)

Rouet-Leduc, Bertrand; Barros, Kipton; Cieren, Emmanuel; Elango, Venmugil; Junghans, Christoph; Lookman, Turab; Mohd-Yusof, Jamaludin; Pavel, Robert S.; Rivera, Axel Y.; Roehm, Dominic; McPherson, Allen L.; Germann, Timothy C.

2014-07-01

In a common approach to multiscale simulation, an incomplete set of macroscale equations must be supplemented with constitutive data provided by fine-scale simulation. Collecting statistics from these fine-scale simulations is typically the overwhelming computational cost. We reduce this cost by interpolating the results of fine-scale simulation over the spatial domain of the macro-solver. Unlike previous adaptive sampling strategies, we do not interpolate on the potentially very high dimensional space of inputs to the fine-scale simulation. Our approach is local in space and time, avoids the need for a central database, and is designed to parallelize well on large computer clusters. To demonstrate our method, we simulate one-dimensional elastodynamic shock propagation using the Heterogeneous Multiscale Method (HMM); we find that spatial adaptive sampling requires only ≈ 50 ×N0.14 fine-scale simulations to reconstruct the stress field at all N grid points. Related multiscale approaches, such as Equation Free methods, may also benefit from spatial adaptive sampling.

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

PubMed Central

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

2016-01-01

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

Regulation of the demographic structure in isomorphic biphasic life cycles at the spatial fine scale.

PubMed

Vieira, Vasco Manuel Nobre de Carvalho da Silva; Mateus, Marcos Duarte

2014-01-01

Isomorphic biphasic algal life cycles often occur in the environment at ploidy abundance ratios (Haploid:Diploid) different from 1. Its spatial variability occurs within populations related to intertidal height and hydrodynamic stress, possibly reflecting the niche partitioning driven by their diverging adaptation to the environment argued necessary for their prevalence (evolutionary stability). Demographic models based in matrix algebra were developed to investigate which vital rates may efficiently generate an H:D variability at a fine spatial resolution. It was also taken into account time variation and type of life strategy. Ploidy dissimilarities in fecundity rates set an H:D spatial structure miss-fitting the ploidy fitness ratio. The same happened with ploidy dissimilarities in ramet growth whenever reproductive output dominated the population demography. Only through ploidy dissimilarities in looping rates (stasis, breakage and clonal growth) did the life cycle respond to a spatially heterogeneous environment efficiently creating a niche partition. Marginal locations were more sensitive than central locations. Related results have been obtained experimentally and numerically for widely different life cycles from the plant and animal kingdoms. Spore dispersal smoothed the effects of ploidy dissimilarities in fertility and enhanced the effects of ploidy dissimilarities looping rates. Ploidy dissimilarities in spore dispersal could also create the necessary niche partition, both over the space and time dimensions, even in spatial homogeneous environments and without the need for conditional differentiation of the ramets. Fine scale spatial variability may be the key for the prevalence of isomorphic biphasic life cycles, which has been neglected so far.

Regulation of the Demographic Structure in Isomorphic Biphasic Life Cycles at the Spatial Fine Scale

PubMed Central

Vieira, Vasco Manuel Nobre de Carvalho da Silva; Mateus, Marcos Duarte

2014-01-01

Isomorphic biphasic algal life cycles often occur in the environment at ploidy abundance ratios (Haploid:Diploid) different from 1. Its spatial variability occurs within populations related to intertidal height and hydrodynamic stress, possibly reflecting the niche partitioning driven by their diverging adaptation to the environment argued necessary for their prevalence (evolutionary stability). Demographic models based in matrix algebra were developed to investigate which vital rates may efficiently generate an H:D variability at a fine spatial resolution. It was also taken into account time variation and type of life strategy. Ploidy dissimilarities in fecundity rates set an H:D spatial structure miss-fitting the ploidy fitness ratio. The same happened with ploidy dissimilarities in ramet growth whenever reproductive output dominated the population demography. Only through ploidy dissimilarities in looping rates (stasis, breakage and clonal growth) did the life cycle respond to a spatially heterogeneous environment efficiently creating a niche partition. Marginal locations were more sensitive than central locations. Related results have been obtained experimentally and numerically for widely different life cycles from the plant and animal kingdoms. Spore dispersal smoothed the effects of ploidy dissimilarities in fertility and enhanced the effects of ploidy dissimilarities looping rates. Ploidy dissimilarities in spore dispersal could also create the necessary niche partition, both over the space and time dimensions, even in spatial homogeneous environments and without the need for conditional differentiation of the ramets. Fine scale spatial variability may be the key for the prevalence of isomorphic biphasic life cycles, which has been neglected so far. PMID:24658603

Spatial consistency of chinook salmon redd distribution within and among years in the Cowlitz River, Washington

USGS Publications Warehouse

Klett, Katherine J.C.; Torgersen, Christian E.; Henning, Julie A.; Murray, Christopher J.

2013-01-01

We investigated the spawning patterns of Chinook Salmon Oncorhynchus tshawytscha on the lower Cowlitz River, Washington, using a unique set of fine- and coarse-scale temporal and spatial data collected during biweekly aerial surveys conducted in 1991–2009 (500 m to 28 km resolution) and 2008–2009 (100–500 m resolution). Redd locations were mapped from a helicopter during 2008 and 2009 with a hand-held GPS synchronized with in-flight audio recordings. We examined spatial patterns of Chinook Salmon redd reoccupation among and within years in relation to segment-scale geomorphic features. Chinook Salmon spawned in the same sections each year with little variation among years. On a coarse scale, 5 years (1993, 1998, 2000, 2002, and 2009) were compared for reoccupation. Redd locations were highly correlated among years. Comparisons on a fine scale (500 m) between 2008 and 2009 also revealed a high degree of consistency among redd locations. On a finer temporal scale, we observed that Chinook Salmon spawned in the same sections during the first and last week. Redds were clustered in both 2008 and 2009. Regression analysis with a generalized linear model at the 500-m scale indicated that river kilometer and channel bifurcation were positively associated with redd density, whereas sinuosity was negatively associated with redd density. Collecting data on specific redd locations with a GPS during aerial surveys was logistically feasible and cost effective and greatly enhanced the spatial precision of Chinook Salmon spawning surveys.

Interactions of multi-scale heterogeneity in the lithosphere: Australia

NASA Astrophysics Data System (ADS)

Kennett, B. L. N.; Yoshizawa, K.; Furumura, T.

2017-10-01

Understanding the complex heterogeneity of the continental lithosphere involves a wide variety of spatial scales and the synthesis of multiple classes of information. Seismic surface waves and multiply reflected body waves provide the main constraints on broad-scale structure, and bounds on the extent of the lithosphere-asthenosphere transition (LAT) can be found from the vertical gradients of S wavespeed. Information on finer-scale structures comes through body wave studies, including detailed seismic tomography and P-wave reflectivity extracted from stacked autocorrelograms of continuous component records. With the inclusion of deterministic large-scale structure and realistic medium-scale stochastic features fine-scale variations are subdued. The resulting multi-scale heterogeneity model for the Australian region gives a good representation of the character of observed seismograms and their geographic variations and matches the observations of P-wave reflectivity. P reflections in the 0.5-3.0 Hz band in the uppermost mantle suggest variations on vertical scales of a few hundred metres with amplitudes of the order of 1%. Interference of waves reflected or converted at sequences of such modest variations in physical properties produce relatively simple behaviour for lower frequencies, which can suggest simpler structures than are actually present. Vertical changes in the character of fine-scale heterogeneity can produce apparent discontinuities. In Central Australia a 'mid-lithospheric discontinuity' can be tracked via changes in frequency content of station reflectivity, with links to the broad-scale pattern of wavespeed gradients and, in particular, the gradients of radial anisotropy. Comparisons with xenolith results from southeastern Australia indicate a strong tie between geochemical stratification and P-wave reflectivity.

Coexistence between wildlife and humans at fine spatial scales

PubMed Central

Carter, Neil H.; Shrestha, Binoj K.; Karki, Jhamak B.; Pradhan, Narendra Man Babu; Liu, Jianguo

2012-01-01

Many wildlife species face imminent extinction because of human impacts, and therefore, a prevailing belief is that some wildlife species, particularly large carnivores and ungulates, cannot coexist with people at fine spatial scales (i.e., cannot regularly use the exact same point locations). This belief provides rationale for various conservation programs, such as resettling human communities outside protected areas. However, quantitative information on the capacity and mechanisms for wildlife to coexist with humans at fine spatial scales is scarce. Such information is vital, because the world is becoming increasingly crowded. Here, we provide empirical information about the capacity and mechanisms for tigers (a globally endangered species) to coexist with humans at fine spatial scales inside and outside Nepal’s Chitwan National Park, a flagship protected area for imperiled wildlife. Information obtained from field cameras in 2010 and 2011 indicated that human presence (i.e., people on foot and vehicles) was ubiquitous and abundant throughout the study site; however, tiger density was also high. Surprisingly, even at a fine spatial scale (i.e., camera locations), tigers spatially overlapped with people on foot and vehicles in both years. However, in both years, tigers offset their temporal activity patterns to be much less active during the day when human activity peaked. In addition to temporal displacement, tiger–human coexistence was likely enhanced by abundant tiger prey and low levels of tiger poaching. Incorporating fine-scale spatial and temporal activity patterns into conservation plans can help address a major global challenge—meeting human needs while sustaining wildlife. PMID:22949642

Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland

NASA Astrophysics Data System (ADS)

Lu, Bing; He, Yuhong

2017-06-01

Investigating spatio-temporal variations of species composition in grassland is an essential step in evaluating grassland health conditions, understanding the evolutionary processes of the local ecosystem, and developing grassland management strategies. Space-borne remote sensing images (e.g., MODIS, Landsat, and Quickbird) with spatial resolutions varying from less than 1 m to 500 m have been widely applied for vegetation species classification at spatial scales from community to regional levels. However, the spatial resolutions of these images are not fine enough to investigate grassland species composition, since grass species are generally small in size and highly mixed, and vegetation cover is greatly heterogeneous. Unmanned Aerial Vehicle (UAV) as an emerging remote sensing platform offers a unique ability to acquire imagery at very high spatial resolution (centimetres). Compared to satellites or airplanes, UAVs can be deployed quickly and repeatedly, and are less limited by weather conditions, facilitating advantageous temporal studies. In this study, we utilize an octocopter, on which we mounted a modified digital camera (with near-infrared (NIR), green, and blue bands), to investigate species composition in a tall grassland in Ontario, Canada. Seven flight missions were conducted during the growing season (April to December) in 2015 to detect seasonal variations, and four of them were selected in this study to investigate the spatio-temporal variations of species composition. To quantitatively compare images acquired at different times, we establish a processing flow of UAV-acquired imagery, focusing on imagery quality evaluation and radiometric correction. The corrected imagery is then applied to an object-based species classification. Maps of species distribution are subsequently used for a spatio-temporal change analysis. Results indicate that UAV-acquired imagery is an incomparable data source for studying fine-scale grassland species composition, owing to its high spatial resolution. The overall accuracy is around 85% for images acquired at different times. Species composition is spatially attributed by topographical features and soil moisture conditions. Spatio-temporal variation of species composition implies the growing process and succession of different species, which is critical for understanding the evolutionary features of grassland ecosystems. Strengths and challenges of applying UAV-acquired imagery for vegetation studies are summarized at the end.

Spatial and Temporal Patterns of Suspended Sediment Yields in Nested Urban Catchments

NASA Astrophysics Data System (ADS)

Kemper, J. T.; Miller, A. J.; Welty, C.

2017-12-01

In a highly regulated area such as the Chesapeake Bay watershed, suspended sediment is a matter of primary concern. Near real-time turbidity and discharge data have been collected continuously for more than four years at five stream gages representing three nested watershed scales (1-2 sq km, 5-6 sq km, 14 sq km) in the highly impervious Dead Run watershed, located in Baltimore County, MD. Using turbidity-concentration relationships based on sample analyses at the gage site, sediment yields for each station can be quantified for a variety of temporal scales. Sediment yields have been calculated for 60+ different storms across four years. Yields show significant spatial variation, both at equivalent sub-watershed scales and from headwaters to mouth. Yields are higher at the headwater station with older development and virtually no stormwater management (DR5) than at the station with more recent development and more extensive stormwater management (DR2). However, this pattern is reversed for the stations at the next larger scale: yields are lower at DR4, downstream of DR5, than at DR3, downstream of DR2. This suggests spatial variation in the dominant sediment sources within each subwatershed. Additionally, C-Q hysteresis curves display consistent counterclockwise behavior at the DR4 station, in contrast to the consistent clockwise behavior displayed at the DR3 station. This further suggests variation in dominant sediment sources (perhaps distal vs local, respectively). We observe consistent seasonal trends in the relative magnitudes of sediment yield for different subwatersheds (e.g. DR3>DR4 in summer, DR5>DR2 in spring). We also observe significant year-to-year variation in sediment yield at the headwater and intermediate scales, whereas yields at the 14 sq km scale are largely similar across the monitored years. This observation would be consistent with the possibility that internal storage and remobilization tend to modulate downstream yields even with spatial and temporal variation in upstream sources. The fine-scale design of this study represents a unique opportunity to compare and contrast sediment yields across a variety of spatial and temporal scales, and provide insight into sediment transport dynamics within an urbanized watershed.

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

NASA Technical Reports Server (NTRS)

Levin, Simon A.; Pacala, Stephen W.

1997-01-01

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

Water availability drives signatures of local adaptation in whitebark pine (Pinus albicaulis Engelm.) across fine spatial scales of the Lake Tahoe Basin, USA

Treesearch

Brandon M. Lind; Christopher J. Friedline; Jill L. Wegrzyn; Patricia E. Maloney; Detlev R. Vogler; David B. Neale; Andrew J. Eckert

2017-01-01

Patterns of local adaptation at fine spatial scales are central to understanding how evolution proceeds, and are essential to the effective management of economically and ecologically important forest tree species. Here, we employ single and multilocus analyses of genetic data (n = 116 231 SNPs) to describe signatures of fine-scale...

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

PubMed

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

2011-12-01

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

Development of high-resolution (250 m) historical daily gridded air temperature data using reanalysis and distributed sensor networks for the US northern Rocky Mountains

Treesearch

Zachary A. Holden; Alan Swanson; Anna E. Klene; John T. Abatzoglou; Solomon Z. Dobrowski; Samuel A. Cushman; John Squires; Gretchen G. Moisen; Jared W. Oyler

2016-01-01

Gridded temperature data sets are typically produced at spatial resolutions that cannot fully resolve fine-scale variation in surface air temperature in regions of complex topography. These data limitations have become increasingly important as scientists and managers attempt to understand and plan for potential climate change impacts. Here, we describe the...

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Gradients, vegetation and climate: spatial and temporal dynamics in the Olympic Mountains, USA

USGS Publications Warehouse

Peterson, David L.; Schreiner, Edward G.; Buckingham, Nelsa M.

1997-01-01

The steep environmental gradients of mountains result in the juxtaposition of diverse vegetation associations with narrow ecotones because life zones are compressed. Variation in geologic substrate, landforms, and soils, in combination with steep environmental gradients, create habitat diversity across spatial scales from 106 ha to <10 m2. This leads to higher biodiversity in a smaller space than in landscapes with less topographic variation. Mountains are often considered to be refuges for biological diversity at the regional scale, although variation in landscape features creates refuges at a fine scale as well. Mountains should also be considered a source of biological diversity, because they provide the germplasm for migration into lowland areas following glacial recession. Many taxa are distributed over a broad range of elevations and habitats, which maximizes the potential to respond to environmental perturbations. Reorganization of species distribution and abundance as a result of climatic change may be impacted considerably by human-caused fragmentation of landscape features, especially at lower elevations. This paper uses palaeoecological and biogeographical data to investigate the spatial and temporal vegetation dynamics of a steep maritime range, the Olympic Mountains (USA). The role of resource management in protecting vegetation in a fragmented landscape is discussed, with emphasis on how to address uncertainties such as climatic change.

Effects of topoclimatic complexity on the composition of woody plant communities.

PubMed

Oldfather, Meagan F; Britton, Matthew N; Papper, Prahlad D; Koontz, Michael J; Halbur, Michelle M; Dodge, Celeste; Flint, Alan L; Flint, Lorriane E; Ackerly, David D

2016-01-01

Topography can create substantial environmental variation at fine spatial scales. Shaped by slope, aspect, hill-position and elevation, topoclimate heterogeneity may increase ecological diversity, and act as a spatial buffer for vegetation responding to climate change. Strong links have been observed between climate heterogeneity and species diversity at broader scales, but the importance of topoclimate for woody vegetation across small spatial extents merits closer examination. We established woody vegetation monitoring plots in mixed evergreen-deciduous woodlands that spanned topoclimate gradients of a topographically heterogeneous landscape in northern California. We investigated the association between the structure of adult and regenerating size classes of woody vegetation and multidimensional topoclimate at a fine scale. We found a significant effect of topoclimate on both single-species distributions and community composition. Effects of topoclimate were evident in the regenerating size class for all dominant species (four Quercus spp., Umbellularia californica and Pseudotsuga menziesii) but only in two dominant species (Quercus agrifolia and Quercus garryana) for the adult size class. Adult abundance was correlated with water balance parameters (e.g. climatic water deficit) and recruit abundance was correlated with an interaction between the topoclimate parameters and conspecific adult abundance (likely reflecting local seed dispersal). However, in all cases, the topoclimate signal was weak. The magnitude of environmental variation across our study site may be small relative to the tolerance of long-lived woody species. Dispersal limitations, management practices and patchy disturbance regimes also may interact with topoclimate, weakening its influence on woody vegetation distributions. Our study supports the biological relevance of multidimensional topoclimate for mixed woodland communities, but highlights that this relationship might be mediated by interacting factors at local scales. Published by Oxford University Press on behalf of the Annals of Botany Company.

Effects of topoclimatic complexity on the composition of woody plant communities

PubMed Central

Oldfather, Meagan F.; Britton, Matthew N.; Papper, Prahlad D.; Koontz, Michael J.; Halbur, Michelle M.; Dodge, Celeste; Flint, Alan L.; Flint, Lorriane E.; Ackerly, David D.

2016-01-01

Topography can create substantial environmental variation at fine spatial scales. Shaped by slope, aspect, hill-position and elevation, topoclimate heterogeneity may increase ecological diversity, and act as a spatial buffer for vegetation responding to climate change. Strong links have been observed between climate heterogeneity and species diversity at broader scales, but the importance of topoclimate for woody vegetation across small spatial extents merits closer examination. We established woody vegetation monitoring plots in mixed evergreen-deciduous woodlands that spanned topoclimate gradients of a topographically heterogeneous landscape in northern California. We investigated the association between the structure of adult and regenerating size classes of woody vegetation and multidimensional topoclimate at a fine scale. We found a significant effect of topoclimate on both single-species distributions and community composition. Effects of topoclimate were evident in the regenerating size class for all dominant species (four Quercus spp., Umbellularia californica and Pseudotsuga menziesii) but only in two dominant species (Quercus agrifolia and Quercus garryana) for the adult size class. Adult abundance was correlated with water balance parameters (e.g. climatic water deficit) and recruit abundance was correlated with an interaction between the topoclimate parameters and conspecific adult abundance (likely reflecting local seed dispersal). However, in all cases, the topoclimate signal was weak. The magnitude of environmental variation across our study site may be small relative to the tolerance of long-lived woody species. Dispersal limitations, management practices and patchy disturbance regimes also may interact with topoclimate, weakening its influence on woody vegetation distributions. Our study supports the biological relevance of multidimensional topoclimate for mixed woodland communities, but highlights that this relationship might be mediated by interacting factors at local scales. PMID:27339048

Saturation sampling for spatial variation in multiple air pollutants across an inversion-prone metropolitan area of complex terrain

PubMed Central

2014-01-01

Background Characterizing intra-urban variation in air quality is important for epidemiological investigation of health outcomes and disparities. To date, however, few studies have been designed to capture spatial variation during select hours of the day, or to examine the roles of meteorology and complex terrain in shaping intra-urban exposure gradients. Methods We designed a spatial saturation monitoring study to target local air pollution sources, and to understand the role of topography and temperature inversions on fine-scale pollution variation by systematically allocating sampling locations across gradients in key local emissions sources (vehicle traffic, industrial facilities) and topography (elevation) in the Pittsburgh area. Street-level integrated samples of fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) were collected during morning rush and probable inversion hours (6-11 AM), during summer and winter. We hypothesized that pollution concentrations would be: 1) higher under inversion conditions, 2) exacerbated in lower-elevation areas, and 3) vary by season. Results During July - August 2011 and January - March 2012, we observed wide spatial and seasonal variability in pollution concentrations, exceeding the range measured at regulatory monitors. We identified elevated concentrations of multiple pollutants at lower-elevation sites, and a positive association between inversion frequency and NO2 concentration. We examined temporal adjustment methods for deriving seasonal concentration estimates, and found that the appropriate reference temporal trend differs between pollutants. Conclusions Our time-stratified spatial saturation approach found some evidence for modification of inversion-concentration relationships by topography, and provided useful insights for refining and interpreting GIS-based pollution source indicators for Land Use Regression modeling. PMID:24735818

Saturation sampling for spatial variation in multiple air pollutants across an inversion-prone metropolitan area of complex terrain.

PubMed

Shmool, Jessie Lc; Michanowicz, Drew R; Cambal, Leah; Tunno, Brett; Howell, Jeffery; Gillooly, Sara; Roper, Courtney; Tripathy, Sheila; Chubb, Lauren G; Eisl, Holger M; Gorczynski, John E; Holguin, Fernando E; Shields, Kyra Naumoff; Clougherty, Jane E

2014-04-16

Characterizing intra-urban variation in air quality is important for epidemiological investigation of health outcomes and disparities. To date, however, few studies have been designed to capture spatial variation during select hours of the day, or to examine the roles of meteorology and complex terrain in shaping intra-urban exposure gradients. We designed a spatial saturation monitoring study to target local air pollution sources, and to understand the role of topography and temperature inversions on fine-scale pollution variation by systematically allocating sampling locations across gradients in key local emissions sources (vehicle traffic, industrial facilities) and topography (elevation) in the Pittsburgh area. Street-level integrated samples of fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) were collected during morning rush and probable inversion hours (6-11 AM), during summer and winter. We hypothesized that pollution concentrations would be: 1) higher under inversion conditions, 2) exacerbated in lower-elevation areas, and 3) vary by season. During July - August 2011 and January - March 2012, we observed wide spatial and seasonal variability in pollution concentrations, exceeding the range measured at regulatory monitors. We identified elevated concentrations of multiple pollutants at lower-elevation sites, and a positive association between inversion frequency and NO2 concentration. We examined temporal adjustment methods for deriving seasonal concentration estimates, and found that the appropriate reference temporal trend differs between pollutants. Our time-stratified spatial saturation approach found some evidence for modification of inversion-concentration relationships by topography, and provided useful insights for refining and interpreting GIS-based pollution source indicators for Land Use Regression modeling.

Restricted cross-scale habitat selection by American beavers.

PubMed

Francis, Robert A; Taylor, Jimmy D; Dibble, Eric; Strickland, Bronson; Petro, Vanessa M; Easterwood, Christine; Wang, Guiming

2017-12-01

Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis (hereafter, beaver) has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining habitat selection are consistent between landscape and fine spatial scales. We built maximum entropy (MaxEnt) models to relate landscape-scale presence-only data to landscape variables, and used generalized linear mixed models to evaluate fine spatial scale habitat selection using global positioning system (GPS) relocation data. Explanatory variables between the landscape and fine spatial scale were compared for consistency. Our findings suggested that beaver habitat selection at coarse (study area) and fine (within home range) scales was congruent, and was influenced by increasing amounts of woody wetland edge density and shrub edge density, and decreasing amounts of open water edge density. Habitat suitability at the landscape scale also increased with decreasing amounts of grass frequency. As territorial, central-place foragers, beavers likely trade-off open water edge density (i.e., smaller non-forested wetlands or lodges closer to banks) for defense and shorter distances to forage and obtain construction material. Woody plants along edges and expanses of open water for predator avoidance may limit beaver fitness and subsequently determine beaver habitat selection.

Restricted cross-scale habitat selection by American beavers

PubMed Central

Taylor, Jimmy D; Dibble, Eric; Strickland, Bronson; Petro, Vanessa M; Easterwood, Christine; Wang, Guiming

2017-01-01

Abstract Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis (hereafter, beaver) has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining habitat selection are consistent between landscape and fine spatial scales. We built maximum entropy (MaxEnt) models to relate landscape-scale presence-only data to landscape variables, and used generalized linear mixed models to evaluate fine spatial scale habitat selection using global positioning system (GPS) relocation data. Explanatory variables between the landscape and fine spatial scale were compared for consistency. Our findings suggested that beaver habitat selection at coarse (study area) and fine (within home range) scales was congruent, and was influenced by increasing amounts of woody wetland edge density and shrub edge density, and decreasing amounts of open water edge density. Habitat suitability at the landscape scale also increased with decreasing amounts of grass frequency. As territorial, central-place foragers, beavers likely trade-off open water edge density (i.e., smaller non-forested wetlands or lodges closer to banks) for defense and shorter distances to forage and obtain construction material. Woody plants along edges and expanses of open water for predator avoidance may limit beaver fitness and subsequently determine beaver habitat selection. PMID:29492032

[Response of fine roots to soil nutrient spatial heterogeneity].

PubMed

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.

Regional-scale drivers of marine nematode distribution in Southern Ocean continental shelf sediments

NASA Astrophysics Data System (ADS)

Hauquier, Freija; Verleyen, Elie; Tytgat, Bjorn; Vanreusel, Ann

2018-07-01

Many marine meiofauna taxa seem to possess cosmopolitan species distributions, despite their endobenthic lifestyle and restricted long-distance dispersal capacities. In light of this paradox we used a metacommunity framework to study spatial turnover in free-living nematode distribution and assess the importance of local environmental conditions in explaining differences between communities in surface and subsurface sediments of the Southern Ocean continental shelf. We analysed nematode community structure in two sediment layers (0-3 cm and 3-5 cm) of locations maximum 2400 km apart. We first focused on a subset of locations to evaluate whether the genus level is sufficiently taxonomically fine-grained to study large-scale patterns in nematode community structure. We subsequently used redundancy and variation partitioning analyses to quantify the unique and combined effects of local environmental conditions and spatial descriptors on genus-level community composition. Macroecological patterns in community structure were highly congruent at the genus and species level. Nematode community composition was highly divergent between both depth strata, likely as a result of local abiotic conditions. Variation in community structure between the different regions largely stemmed from turnover (i.e. genus/species replacement) rather than nestedness (i.e. genus/species loss). The level of turnover among communities increased with geographic distance and was more pronounced in subsurface layers compared to surface sediments. Variation partitioning analysis revealed that both environmental and spatial predictors significantly explained variation in community structure. Moreover, the shared fraction of both sets of variables was high, which suggested a substantial amount of spatially structured environmental variation. Additionally, the effect of space independent of environment was much higher than the effect of environment independent of space, which shows the importance of including spatial descriptors in meiofauna and nematode community ecology. Large-scale assessment of free-living nematode diversity and abundance in the Southern Ocean shelf zone revealed strong horizontal and vertical spatial structuring in response to local environmental conditions, in combination with (most likely) dispersal limitation.

The Recombination Landscape in Wild House Mice Inferred Using Population Genomic Data.

PubMed

Booker, Tom R; Ness, Rob W; Keightley, Peter D

2017-09-01

Characterizing variation in the rate of recombination across the genome is important for understanding several evolutionary processes. Previous analysis of the recombination landscape in laboratory mice has revealed that the different subspecies have different suites of recombination hotspots. It is unknown, however, whether hotspots identified in laboratory strains reflect the hotspot diversity of natural populations or whether broad-scale variation in the rate of recombination is conserved between subspecies. In this study, we constructed fine-scale recombination rate maps for a natural population of the Eastern house mouse, Mus musculus castaneus We performed simulations to assess the accuracy of recombination rate inference in the presence of phase errors, and we used a novel approach to quantify phase error. The spatial distribution of recombination events is strongly positively correlated between our castaneus map, and a map constructed using inbred lines derived predominantly from M. m. domesticus Recombination hotspots in wild castaneus show little overlap, however, with the locations of double-strand breaks in wild-derived house mouse strains. Finally, we also find that genetic diversity in M. m. castaneus is positively correlated with the rate of recombination, consistent with pervasive natural selection operating in the genome. Our study suggests that recombination rate variation is conserved at broad scales between house mouse subspecies, but it is not strongly conserved at fine scales. Copyright © 2017 by the Genetics Society of America.

Spatial consistency of Chinook salmon redd distribution within and among years in the Cowlitz River, Washington

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

Klett, Katherine J.; Torgersen, Christian; Henning, Julie

2013-04-28

We investigated the spawning patterns of Chinook salmon Oncorhynchus tshawytscha on the lower Cowlitz River, Washington (USA) using a unique set of fine- and coarse-scale 35 temporal and spatial data collected during bi-weekly aerial surveys conducted in 1991-2009 (500 m to 28 km resolution) and 2008-2009 (100-500 m resolution). Redd locations were mapped from a helicopter during 2008 and 2009 with a hand-held global positioning system (GPS) synchronized with in-flight audio recordings. We examined spatial patterns of Chinook salmon redd reoccupation among and within years in relation to segment-scale geomorphic features. Chinook salmon spawned in the same sections each yearmore » with little variation among years. On a coarse scale, five years (1993, 1998, 2000, 2002, and 2009) were compared for reoccupation. Redd locations were highly correlated among years resulting in a minimum correlation coefficient of 0.90 (adjusted P = 0.002). Comparisons on a fine scale (500 m) between 2008 and 2009 also revealed a high degree of consistency among redd locations (P < 0.001). On a finer temporal scale, we observed that salmon spawned in the same sections during the first and last week (2008: P < 0.02; and 2009: P < 0.001). Redds were clustered in both 2008 and 2009 (P < 0.001). Regression analysis with a generalized linear model at the 500-m scale indicated that river kilometer and channel bifurcation were positively associated with redd density, whereas sinuosity was negatively associated with redd density. Collecting data on specific redd locations with a GPS during aerial surveys was logistically feasible and cost effective and greatly enhanced the spatial precision of Chinook salmon spawning surveys.« less

Matching Deep Tow Camera study and Sea Floor geochemical characterization of gas migration at the Tainan Ridge, South China Sea

NASA Astrophysics Data System (ADS)

Fan, L. F.; Lien, K. L.; Hsieh, I. C.; Lin, S.

2017-12-01

Methane seep in deep sea environment could lead to build up of chemosynthesis communities, and a number of geological and biological anomalies as compare to the surrounding area. In order to examine the linkage between seep anomalies and those at the vicinity background area, and to detail mapping those spatial variations, we used a deep towed camera system (TowCam) to survey seafloor on the Tainan Ridge, Northeastern South China Sea (SCS). The underwater sea floor pictures could provide better spatial variations to demonstrate impact of methane seep on the sea floor. Water column variations of salinity, temperature, dissolved oxygen were applied to delineate fine scale variations at the study area. In addition, sediment cores were collected for chemical analyses to confirm the existence of local spatial variations. Our results show large spatial variations existed as a result of differences in methane flux. In fact, methane is the driving force for the observed biogeochemical variations in the water column, on the sea floor, and in the sediment. Of the area we have surveyed, there are approximately 7% of total towcam survey data showing abnormal water properties. Corresponding to the water column anomalies, underwater sea floor pictures taken from those places showed that chemosynthetic clams and muscles could be identified, together with authigenic carbonate buildups, and bacterial mats. Moreover, sediment cores with chemical anomalies also matched those in the water column and on the sea floor. These anomalies, however, represent only a small portion of the area surveyed and could not be identified with typical (random) coring method. Methane seep, therefore, require tedious and multiple types of surveys to better understand the scale and magnitude of seep and biogeochemical anomalies those were driven by gas migrations.

Identification of fine scale and landscape scale drivers of urban aboveground carbon stocks using high-resolution modeling and mapping.

PubMed

Mitchell, Matthew G E; Johansen, Kasper; Maron, Martine; McAlpine, Clive A; Wu, Dan; Rhodes, Jonathan R

2018-05-01

Urban areas are sources of land use change and CO 2 emissions that contribute to global climate change. Despite this, assessments of urban vegetation carbon stocks often fail to identify important landscape-scale drivers of variation in urban carbon, especially the potential effects of landscape structure variables at different spatial scales. We combined field measurements with Light Detection And Ranging (LiDAR) data to build high-resolution models of woody plant aboveground carbon across the urban portion of Brisbane, Australia, and then identified landscape scale drivers of these carbon stocks. First, we used LiDAR data to quantify the extent and vertical structure of vegetation across the city at high resolution (5×5m). Next, we paired this data with aboveground carbon measurements at 219 sites to create boosted regression tree models and map aboveground carbon across the city. We then used these maps to determine how spatial variation in land cover/land use and landscape structure affects these carbon stocks. Foliage densities above 5m height, tree canopy height, and the presence of ground openings had the strongest relationships with aboveground carbon. Using these fine-scale relationships, we estimate that 2.2±0.4 TgC are stored aboveground in the urban portion of Brisbane, with mean densities of 32.6±5.8MgCha -1 calculated across the entire urban land area, and 110.9±19.7MgCha -1 calculated within treed areas. Predicted carbon densities within treed areas showed strong positive relationships with the proportion of surrounding tree cover and how clumped that tree cover was at both 1km 2 and 1ha resolutions. Our models predict that even dense urban areas with low tree cover can have high carbon densities at fine scales. We conclude that actions and policies aimed at increasing urban carbon should focus on those areas where urban tree cover is most fragmented. Copyright © 2017 Elsevier B.V. All rights reserved.

Predictors of malaria infection in a wild bird population: landscape-level analyses reveal climatic and anthropogenic factors.

PubMed

Gonzalez-Quevedo, Catalina; Davies, Richard G; Richardson, David S

2014-09-01

How the environment influences the transmission and prevalence of disease in a population of hosts is a key aspect of disease ecology. The role that environmental factors play in host-pathogen systems has been well studied at large scales, that is, differences in pathogen pressures among separate populations of hosts or across land masses. However, despite considerable understanding of how environmental conditions vary at fine spatial scales, the effect of these parameters on host-pathogen dynamics at such scales has been largely overlooked. Here, we used a combination of molecular screening and GIS-based analysis to investigate how environmental factors determine the distribution of malaria across the landscape in a population of Berthelot's pipit (Anthus berthelotii, Bolle 1862) on the island of Tenerife (Canary Islands, Spain) using spatially explicit models that account for spatial autocorrelation. Minimum temperature of the coldest month was found to be the most important predictor of malaria infection at the landscape scale across this population. Additionally, anthropogenic factors such as distance to artificial water reservoirs and distance to poultry farms were important predictors of malaria. A model including these factors, and the interaction between distance to artificial water reservoirs and minimum temperature, best explained the distribution of malaria infection in this system. These results suggest that levels of malaria infection in this endemic species may be artificially elevated by the impact of humans. Studies such as the one described here improve our understanding of how environmental factors, and their heterogeneity, affect the distribution of pathogens within wild populations. The results demonstrate the importance of measuring fine-scale variation - and not just regional effects - to understand how environmental variation can influence wildlife diseases. Such understanding is important for predicting the future spread and impact of disease and may help inform disease management programmes as well as the conservation of specific host species. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Partitioning the factors of spatial variation in regeneration density of shade-tolerant tree species.

PubMed

Gravel, Dominique; Beaudet, Marilou; Messier, Christian

2008-10-01

Understanding coexistence of highly shade-tolerant tree species is a longstanding challenge for forest ecologists. A conceptual model for the coexistence of sugar maple (Acer saccharum) and American beech (Fagus grandibfolia) has been proposed, based on a low-light survival/high-light growth trade-off, which interacts with soil fertility and small-scale spatiotemporal variation in the environment. In this study, we first tested whether the spatial distribution of seedlings and saplings can be predicted by the spatiotemporal variability of light availability and soil fertility, and second, the manner in which the process of environmental filtering changes with regeneration size. We evaluate the support for this hypothesis relative to the one for a neutral model, i.e., for seed rain density predicted from the distribution of adult trees. To do so, we performed intensive sampling over 86 quadrats (5 x 5 m) in a 0.24-ha plot in a mature maple-beech community in Quebec, Canada. Maple and beech abundance, soil characteristics, light availability, and growth history (used as a proxy for spatiotemporal variation in light availability) were finely measured to model variation in sapling composition across different size classes. Results indicate that the variables selected to model species distribution do effectively change with size, but not as predicted by the conceptual model. Our results show that variability in the environment is not sufficient to differentiate these species' distributions in space. Although species differ in their spatial distribution in the small size classes, they tend to correlate at the larger size class in which recruitment occurs. Overall, the results are not supportive of a model of coexistence based on small-scale variations in the environment. We propose that, at the scale of a local stand, the lack of fit of the model could result from the high similarity of species in the range of environmental conditions encountered, and we suggest that coexistence would be stable only at larger spatial scales at which variability in the environment is greater.

Magnetic contributions in Bekenstein type models

NASA Astrophysics Data System (ADS)

Kraiselburd, Lucila; Castillo, Florencia L.; Mosquera, Mercedes E.; Vucetich, Héctor

2018-02-01

In this work, we analyze the spatial and time variation of the fine structure constant (α ) upon the theoretical framework developed by Bekenstein (Phys. Rev. D 66, 123514 (2002), 10.1103/PhysRevD.66.123514). We have computed the field ψ related to α at first order of the weak-field approximation and have also improved the estimation of the nuclear magnetic energy and, therefore, their contributions to the source term in the equation of motion of ψ . We obtained that the results are similar to the ones published in L. Kraiselburd and H. Vucetich, Int. J. Mod. Phys. E 20, 101 (2011) which were computed using the zero order of the approximation, showing that one can neglect the first order contribution to the variation of the fine structure constant. Through the comparison between our theoretical results and the observational data of the Eötvös-type experiments or the time variation of α over the cosmological time scale, we set constraints on the free parameter of the Bekenstein model, namely the Bekenstein length.

Partitioning sources of variation in vertebrate species richness

USGS Publications Warehouse

Boone, R.B.; Krohn, W.B.

2000-01-01

Aim: To explore biogeographic patterns of terrestrial vertebrates in Maine, USA using techniques that would describe local and spatial correlations with the environment. Location: Maine, USA. Methods: We delineated the ranges within Maine (86,156 km2) of 275 species using literature and expert review. Ranges were combined into species richness maps, and compared to geomorphology, climate, and woody plant distributions. Methods were adapted that compared richness of all vertebrate classes to each environmental correlate, rather than assessing a single explanatory theory. We partitioned variation in species richness into components using tree and multiple linear regression. Methods were used that allowed for useful comparisons between tree and linear regression results. For both methods we partitioned variation into broad-scale (spatially autocorrelated) and fine-scale (spatially uncorrelated) explained and unexplained components. By partitioning variance, and using both tree and linear regression in analyses, we explored the degree of variation in species richness for each vertebrate group that Could be explained by the relative contribution of each environmental variable. Results: In tree regression, climate variation explained richness better (92% of mean deviance explained for all species) than woody plant variation (87%) and geomorphology (86%). Reptiles were highly correlated with environmental variation (93%), followed by mammals, amphibians, and birds (each with 84-82% deviance explained). In multiple linear regression, climate was most closely associated with total vertebrate richness (78%), followed by woody plants (67%) and geomorphology (56%). Again, reptiles were closely correlated with the environment (95%), followed by mammals (73%), amphibians (63%) and birds (57%). Main conclusions: Comparing variation explained using tree and multiple linear regression quantified the importance of nonlinear relationships and local interactions between species richness and environmental variation, identifying the importance of linear relationships between reptiles and the environment, and nonlinear relationships between birds and woody plants, for example. Conservation planners should capture climatic variation in broad-scale designs; temperatures may shift during climate change, but the underlying correlations between the environment and species richness will presumably remain.

Regional Scale High Resolution δ18O Prediction in Precipitation Using MODIS EVI

PubMed Central

Huang, Cho-Ying; Wang, Chung-Ho; Lin, Shou-De; Lo, Yi-Chen; Huang, Bo-Wen; Hatch, Kent A.; Shiu, Hau-Jie; You, Cheng-Feng; Chang, Yuan-Mou; Shen, Sheng-Feng

2012-01-01

The natural variation in stable water isotope ratio data, also known as water isoscape, is a spatiotemporal fingerprint and a powerful natural tracer that has been widely applied in disciplines as diverse as hydrology, paleoclimatology, ecology and forensic investigation. Although much effort has been devoted to developing a predictive water isoscape model, it remains a central challenge for scientists to generate high accuracy, fine scale spatiotemporal water isoscape prediction. Here we develop a novel approach of using the MODIS-EVI (the Moderate Resolution Imagining Spectroradiometer-Enhanced Vegetation Index), to predict δ18O in precipitation at the regional scale. Using a structural equation model, we show that the EVI and precipitated δ18O are highly correlated and thus the EVI is a good predictor of precipitated δ18O. We then test the predictability of our EVI-δ18O model and demonstrate that our approach can provide high accuracy with fine spatial (250×250 m) and temporal (16 days) scale δ18O predictions (annual and monthly predictabilities [r] are 0.96 and 0.80, respectively). We conclude the merging of the EVI and δ18O in precipitation can greatly extend the spatial and temporal data availability and thus enhance the applicability for both the EVI and water isoscape. PMID:23029053

Multiscale 3-D shape representation and segmentation using spherical wavelets.

PubMed

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2007-04-01

This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of our multiscale prior and 2) a segmentation task. In the reconstruction task, our results show that for a given training set size, our algorithm significantly improves the approximation of shapes in a testing set over the Point Distribution Model, which tends to oversmooth data. In the segmentation task, our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm, by capturing finer shape details.

Multiscale 3-D Shape Representation and Segmentation Using Spherical Wavelets

PubMed Central

Nain, Delphine; Haker, Steven; Bobick, Aaron

2013-01-01

This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of our multiscale prior and 2) a segmentation task. In the reconstruction task, our results show that for a given training set size, our algorithm significantly improves the approximation of shapes in a testing set over the Point Distribution Model, which tends to oversmooth data. In the segmentation task, our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm, by capturing finer shape details. PMID:17427745

Fine-scale climate change: modelling spatial variation in biologically meaningful rates of warming.

PubMed

Maclean, Ilya M D; Suggitt, Andrew J; Wilson, Robert J; Duffy, James P; Bennie, Jonathan J

2017-01-01

The existence of fine-grain climate heterogeneity has prompted suggestions that species may be able to survive future climate change in pockets of suitable microclimate, termed 'microrefugia'. However, evidence for microrefugia is hindered by lack of understanding of how rates of warming vary across a landscape. Here, we present a model that is applied to provide fine-grained, multidecadal estimates of temperature change based on the underlying physical processes that influence microclimate. Weather station and remotely derived environmental data were used to construct physical variables that capture the effects of terrain, sea surface temperatures, altitude and surface albedo on local temperatures, which were then calibrated statistically to derive gridded estimates of temperature. We apply the model to the Lizard Peninsula, United Kingdom, to provide accurate (mean error = 1.21 °C; RMS error = 1.63 °C) hourly estimates of temperature at a resolution of 100 m for the period 1977-2014. We show that rates of warming vary across a landscape primarily due to long-term trends in weather conditions. Total warming varied from 0.87 to 1.16 °C, with the slowest rates of warming evident on north-east-facing slopes. This variation contributed to substantial spatial heterogeneity in trends in bioclimatic variables: for example, the change in the length of the frost-free season varied from +11 to -54 days and the increase in annual growing degree-days from 51 to 267 °C days. Spatial variation in warming was caused primarily by a decrease in daytime cloud cover with a resulting increase in received solar radiation, and secondarily by a decrease in the strength of westerly winds, which has amplified the effects on temperature of solar radiation on west-facing slopes. We emphasize the importance of multidecadal trends in weather conditions in determining spatial variation in rates of warming, suggesting that locations experiencing least warming may not remain consistent under future climate change. © 2016 John Wiley & Sons Ltd.

Fine Spatial Scale Variation of Soil Microbial Communities under European Beech and Norway Spruce

PubMed Central

Nacke, Heiko; Goldmann, Kezia; Schöning, Ingo; Pfeiffer, Birgit; Kaiser, Kristin; Castillo-Villamizar, Genis A.; Schrumpf, Marion; Buscot, François; Daniel, Rolf; Wubet, Tesfaye

2016-01-01

The complex interactions between trees and soil microbes in forests as well as their inherent seasonal and spatial variations are poorly understood. In this study, we analyzed the effects of major European tree species (Fagus sylvatica L. and Picea abies (L.) Karst) on soil bacterial and fungal communities. Mineral soil samples were collected from different depths (0–10, 10–20 cm) and at different horizontal distances from beech or spruce trunks (0.5, 1.5, 2.5, 3.5 m) in early summer and autumn. We assessed the composition of soil bacterial and fungal communities based on 16S rRNA gene and ITS DNA sequences. Community composition of bacteria and fungi was most strongly affected by soil pH and tree species. Different ectomycorrhizal fungi (e.g., Tylospora) known to establish mutualistic associations with plant roots showed a tree species preference. Moreover, bacterial and fungal community composition showed spatial and seasonal shifts in soil surrounding beech and spruce. The relative abundance of saprotrophic fungi was higher at a depth of 0–10 vs. 10–20 cm depth. This was presumably a result of changes in nutrient availability, as litter input and organic carbon content decreased with soil depth. Overall bacterial community composition showed strong variations under spruce with increasing distance from the tree trunks, which might be attributed in part to higher fine root biomass near spruce trunks. Furthermore, overall bacterial community composition was strongly affected by season under deciduous trees. PMID:28066384

Fine Spatial Scale Variation of Soil Microbial Communities under European Beech and Norway Spruce.

PubMed

Nacke, Heiko; Goldmann, Kezia; Schöning, Ingo; Pfeiffer, Birgit; Kaiser, Kristin; Castillo-Villamizar, Genis A; Schrumpf, Marion; Buscot, François; Daniel, Rolf; Wubet, Tesfaye

2016-01-01

The complex interactions between trees and soil microbes in forests as well as their inherent seasonal and spatial variations are poorly understood. In this study, we analyzed the effects of major European tree species ( Fagus sylvatica L. and Picea abies (L.) Karst) on soil bacterial and fungal communities. Mineral soil samples were collected from different depths (0-10, 10-20 cm) and at different horizontal distances from beech or spruce trunks (0.5, 1.5, 2.5, 3.5 m) in early summer and autumn. We assessed the composition of soil bacterial and fungal communities based on 16S rRNA gene and ITS DNA sequences. Community composition of bacteria and fungi was most strongly affected by soil pH and tree species. Different ectomycorrhizal fungi (e.g., Tylospora ) known to establish mutualistic associations with plant roots showed a tree species preference. Moreover, bacterial and fungal community composition showed spatial and seasonal shifts in soil surrounding beech and spruce. The relative abundance of saprotrophic fungi was higher at a depth of 0-10 vs. 10-20 cm depth. This was presumably a result of changes in nutrient availability, as litter input and organic carbon content decreased with soil depth. Overall bacterial community composition showed strong variations under spruce with increasing distance from the tree trunks, which might be attributed in part to higher fine root biomass near spruce trunks. Furthermore, overall bacterial community composition was strongly affected by season under deciduous trees.

Seasonal variation in coastal marine habitat use by the European shag: Insights from fine scale habitat selection modeling and diet

NASA Astrophysics Data System (ADS)

Michelot, Candice; Pinaud, David; Fortin, Matthieu; Maes, Philippe; Callard, Benjamin; Leicher, Marine; Barbraud, Christophe

2017-07-01

Studies of habitat selection by higher trophic level species are necessary for using top predator species as indicators of ecosystem functioning. However, contrary to terrestrial ecosystems, few habitat selection studies have been conducted at a fine scale for coastal marine top predator species, and fewer have coupled diet data with habitat selection modeling to highlight a link between prey selection and habitat use. The aim of this study was to characterize spatially and oceanographically, at a fine scale, the habitats used by the European Shag Phalacrocorax aristotelis in the Special Protection Area (SPA) of Houat-Hœdic in the Mor Braz Bay during its foraging activity. Habitat selection models were built using in situ observation data of foraging shags (transect sampling) and spatially explicit environmental data to characterize marine benthic habitats. Observations were first adjusted for detectability biases and shag abundance was subsequently spatialized. The influence of habitat variables on shag abundance was tested using Generalized Linear Models (GLMs). Diet data were finally confronted to habitat selection models. Results showed that European shags breeding in the Mor Braz Bay changed foraging habitats according to the season and to the different environmental and energetic constraints. The proportion of the main preys also varied seasonally. Rocky and coarse sand habitats were clearly preferred compared to fine or muddy sand habitats. Shags appeared to be more selective in their foraging habitats during the breeding period and the rearing of chicks, using essentially rocky areas close to the colony and consuming preferentially fish from the Labridae family and three other fish families in lower proportions. During the post-breeding period shags used a broader range of habitats and mainly consumed Gadidae. Thus, European shags seem to adjust their feeding strategy to minimize energetic costs, to avoid intra-specific competition and to maximize access to suitable habitats and preys.

Mobile monitoring of particle number concentration and other traffic-related air pollutants in a near-highway neighborhood over the course of a year

PubMed Central

Padró-Martínez, Luz T.; Patton, Allison P.; Trull, Jeffrey B.; Zamore, Wig; Brugge, Doug; Durant, John L.

2012-01-01

Accurate quantification of exposures to traffic-related air pollution in near-highway neighborhoods is challenging due to the high degree of spatial and temporal variation of pollutant levels. The objective of this study was to measure air pollutant levels in a near-highway urban area over a wide range of traffic and meteorological conditions using a mobile monitoring platform. The study was performed in a 2.3-km2 area in Somerville, Massachusetts (USA), near Interstate I-93, a highway that carries 150,000 vehicles per day. The mobile platform was equipped with rapid-response instruments and was driven repeatedly along a 15.4-km route on 55 days between September 2009 and August 2010. Monitoring was performed in 4–6-hour shifts in the morning, afternoon and evening on both weekdays and weekends in winter, spring, summer and fall. Measurements were made of particle number concentration (PNC; 4–3,000 nm), particle size distribution, fine particle mass (PM2.5), particle-bound polycyclic aromatic hydrocarbons (pPAH), black carbon (BC), carbon monoxide (CO), and nitrogen oxides (NO and NOx). The highest pollutant concentrations were measured within 0–50 m of I-93 with distance-decay gradients varying depending on traffic and meteorology. The most pronounced variations were observed for PNC. Annual median PNC 0–50 m from I-93 was two-fold higher compared to the background area (>1 km from I-93). In general, PNC levels were highest in winter and lowest in summer and fall, higher on weekdays and Saturdays compared to Sundays, and higher during morning rush hour compared to later in the day. Similar spatial and temporal trends were observed for NO, CO and BC, but not for PM2.5. Spatial variations in PNC distance-decay gradients were non-uniform largely due to contributions from local street traffic. Hour-to-hour, day-to-day and season-to-season variations in PNC were of the same magnitude as spatial variations. Datasets containing fine-scale temporal and spatial variation of air pollution levels near highways may help to inform exposure assessment efforts. PMID:23144586

Impacts of geochemical and environmental factors on seasonal variation of heavy metals in a coastal lagoon Yucatan, Mexico.

PubMed

Arcega-Cabrera, F; Garza-Pérez, R; Noreña-Barroso, E; Oceguera-Vargas, I

2015-01-01

This study investigated the influence of geochemical and environmental factors on seasonal variation in metals in Yucatan's Chelem lagoon. Anthropogenic activities discharge non-treated wastewater directly into it with detrimental environmental consequences. Accordingly, this study established the spatial and temporal patterns of fine grain sediments and concentrations of heavy metals. Multivariate analyses showed fine grain facies deposition, transition sites dominated by fine grain transport, and fine grain erosion sites. Spatial and temporal variations of heavy metals concentration were significant for Cd, Cu, Cr, and Pb. As, Cd, and Sn were as much as 12 times higher than SQuiRTs standards (Buchman 2008). The results indicate that aquifer water is bringing metals from relatively far inland and releasing them into the lagoon. Thus, it appears that the contamination of this lagoon is highly complex and must take into account systemic connections with inland anthropogenic activates and pollution, as well as local factors.

Estimating resource acquisition and at-sea body condition of a marine predator

PubMed Central

Schick, Robert S; New, Leslie F; Thomas, Len; Costa, Daniel P; Hindell, Mark A; McMahon, Clive R; Robinson, Patrick W; Simmons, Samantha E; Thums, Michele; Harwood, John; Clark, James S

2013-01-01

Body condition plays a fundamental role in many ecological and evolutionary processes at a variety of scales and across a broad range of animal taxa. An understanding of how body condition changes at fine spatial and temporal scales as a result of interaction with the environment provides necessary information about how animals acquire resources. However, comparatively little is known about intra- and interindividual variation of condition in marine systems. Where condition has been studied, changes typically are recorded at relatively coarse time-scales. By quantifying how fine-scale interaction with the environment influences condition, we can broaden our understanding of how animals acquire resources and allocate them to body stores. Here we used a hierarchical Bayesian state-space model to estimate the body condition as measured by the size of an animal's lipid store in two closely related species of marine predator that occupy different hemispheres: northern elephant seals (Mirounga angustirostris) and southern elephant seals (Mirounga leonina). The observation model linked drift dives to lipid stores. The process model quantified daily changes in lipid stores as a function of the physiological condition of the seal (lipid:lean tissue ratio, departure lipid and departure mass), its foraging location, two measures of behaviour and environmental covariates. We found that physiological condition significantly impacted lipid gain at two time-scales – daily and at departure from the colony – that foraging location was significantly associated with lipid gain in both species of elephant seals and that long-term behavioural phase was associated with positive lipid gain in northern and southern elephant seals. In northern elephant seals, the occurrence of short-term behavioural states assumed to represent foraging were correlated with lipid gain. Lipid gain was a function of covariates in both species. Southern elephant seals performed fewer drift dives than northern elephant seals and gained lipids at a lower rate. We have demonstrated a new way to obtain time series of body condition estimates for a marine predator at fine spatial and temporal scales. This modelling approach accounts for uncertainty at many levels and has the potential to integrate physiological and movement ecology of top predators. The observation model we used was specific to elephant seals, but the process model can readily be applied to other species, providing an opportunity to understand how animals respond to their environment at a fine spatial scale. PMID:23869551

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Genetics of Central Valley O. mykiss populations: drainage and watershed scale analyses

USGS Publications Warehouse

Nielsen, Jennifer L.; Pavey, Scott A.; Wiacek, Talia; Williams, Ian S.

2005-01-01

Genetic variation at 11 microsatellite loci described population genetic structure for Oncorhynchus mykiss in the Central Valley, California. Spatial and temporal variation was examined as well as relationships between hatchery and putative natural spawning anadromous stocks. Genetic diversity was analyzed at two distinct spatial scales: fine-scale within drainage for five populations on Clear Creek; between and among drainage diversity for 23 populations. Significant regional spatial structure was apparent, both within Clear Creek and among rainbow trout populations throughout the Central Valley. Significant differences in allelic frequencies were found among most river or drainage systems. Less than 1% of the molecular variance could be attributed to differences found between drainages. Hatchery populations were shown to carry similar genetic diversity to geographically proximate wild populations. Central Valley M = 0.626 (below the M < 0.68 threshold) supported recent population reductions within the Central Valley. However, average estimated effective population size was relatively high (Ne = 5066). Significant allelic differences were found in rainbow trout collected above and below impassable dams on the American, Yuba, Stanislaus and Tuolumne rivers. Rainbow trout sampled in Spring Creek were extremely bottlenecked with allelic variation at only two loci and an estimated effective population size of 62, suggesting some local freshwater O. mykiss stocks may be declining rapidly. These data support significant genetic population structure for steelhead and rainbow trout populations within the Central Valley across multiple scales. Careful consideration of this genetic diversity and its distribution across the landscape should be part of future conservation and restoration efforts. 

Are patterns of fine-scale spatial genetic structure consistent between sites within tropical tree species?

PubMed Central

Smith, James R.; Ghazoul, Jaboury; Burslem, David F. R. P.; Itoh, Akira; Khoo, Eyen; Lee, Soon Leong; Maycock, Colin R.; Nanami, Satoshi; Ng, Kevin Kit Siong; Kettle, Chris J.

2018-01-01

Documenting the scale and intensity of fine-scale spatial genetic structure (FSGS), and the processes that shape it, is relevant to the sustainable management of genetic resources in timber tree species, particularly where logging or fragmentation might disrupt gene flow. In this study we assessed patterns of FSGS in three species of Dipterocarpaceae (Parashorea tomentella, Shorea leprosula and Shorea parvifolia) across four different tropical rain forests in Malaysia using nuclear microsatellite markers. Topographic heterogeneity varied across the sites. We hypothesised that forests with high topographic heterogeneity would display increased FSGS among the adult populations driven by habitat associations. This hypothesis was not supported for S. leprosula and S. parvifolia which displayed little variation in the intensity and scale of FSGS between sites despite substantial variation in topographic heterogeneity. Conversely, the intensity of FSGS for P. tomentella was greater at a more topographically heterogeneous than a homogeneous site, and a significant difference in the overall pattern of FSGS was detected between sites for this species. These results suggest that local patterns of FSGS may in some species be shaped by habitat heterogeneity in addition to limited gene flow by pollen and seed dispersal. Site factors can therefore contribute to the development of FSGS. Confirming consistency in species’ FSGS amongst sites is an important step in managing timber tree genetic diversity as it provides confidence that species specific management recommendations based on species reproductive traits can be applied across a species’ range. Forest managers should take into account the interaction between reproductive traits and site characteristics, its consequences for maintaining forest genetic resources and how this might influence natural regeneration across species if management is to be sustainable. PMID:29547644

Using spatio-temporal modeling to predict long-term exposure to black smoke at fine spatial and temporal scale

NASA Astrophysics Data System (ADS)

Dadvand, Payam; Rushton, Stephen; Diggle, Peter J.; Goffe, Louis; Rankin, Judith; Pless-Mulloli, Tanja

2011-01-01

Whilst exposure to air pollution is linked to a wide range of adverse health outcomes, assessing levels of this exposure has remained a challenge. This study reports a modeling approach for the estimation of weekly levels of ambient black smoke (BS) at residential postcodes across Northeast England (2055 km 2) over a 12 year period (1985-1996). A two-stage modeling strategy was developed using monitoring data on BS together with a range of covariates including data on traffic, population density, industrial activity, land cover (remote sensing), and meteorology. The first stage separates the temporal trend in BS for the region as a whole from within-region spatial variation and the second stage is a linear model which predicts BS levels at all locations in the region using spatially referenced covariate data as predictors and the regional predicted temporal trend as an offset. Traffic and land cover predictors were included in the final model, which predicted 70% of the spatio-temporal variation in BS across the study region over the study period. This modeling approach appears to provide a robust way of estimating exposure to BS at an inter-urban scale.

Data, data everywhere: detecting spatial patterns in fine-scale ecological information collected across a continent

Treesearch

Kevin M. Potter; Frank H. Koch; Christopher M. Oswalt; Basil V. Iannone

2016-01-01

Context Fine-scale ecological data collected across broad regions are becoming increasingly available. Appropriate geographic analyses of these data can help identify locations of ecological concern. Objectives We present one such approach, spatial association of scalable hexagons (SASH), whichidentifies locations where ecological phenomena occur at greater...

Spatial distribution of end-stage renal disease (ESRD) and social inequalities in mixed urban and rural areas: a study in the Bretagne administrative region of France.

PubMed

Kihal-Talantikite, Wahida; Deguen, Séverine; Padilla, Cindy; Siebert, Muriel; Couchoud, Cécile; Vigneau, Cécile; Bayat, Sahar

2015-02-01

Several studies have investigated the implication of biological and environmental factors on geographic variations of end-stage renal disease (ESRD) incidence at large area scales, but none of them assessed the implication of neighbourhood characteristics (healthcare supply, socio-economic level and urbanization degree) on spatial repartition of ESRD. We evaluated the spatial implications of adjustment for neighbourhood characteristics on the spatial distribution of ESRD incidence at the smallest geographic unit in France. All adult patients living in Bretagne and beginning renal replacement therapy during the 2004-09 period were included. Their residential address was geocoded at the census block level. Each census block was characterized by socio-economic deprivation index, healthcare supply and rural/urban typology. Using a spatial scan statistic, we examined whether there were significant clusters of high risk of ESRD incidence. The ESRD incidence was non-randomly spatially distributed, with a cluster of high risk in the western Bretagne region (relative risk, RR = 1.28, P-value = 0.0003). Adjustment for sex, age and neighbourhood characteristics induced cluster shifts. After these adjustments, a significant cluster (P = 0.013) persisted. Our spatial analysis of ESRD incidence at a fine scale, across a mixed rural/urban area, indicated that, beyond age and sex, neighbourhood characteristics explained a great part of spatial distribution of ESRD incidence. However, to better understand spatial variation of ESRD incidence, it would be necessary to research and adjust for other determinants of ESRD.

Genome-Wide Fine-Scale Recombination Rate Variation in Drosophila melanogaster

PubMed Central

Song, Yun S.

2012-01-01

Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA) and the other from Africa (Gikongoro, Rwanda). It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features—including recombination rates, diversity, divergence, GC content, gene content, and sequence quality—is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between recombination and diversity. PMID:23284288

Decomposing risk: landscape structure and wolf behavior generate different predation patterns in two sympatric ungulates.

PubMed

Gervasi, Vincenzo; Sand, Hakan; Zimmermann, Barbara; Mattisson, Jenny; Wabakken, Petter; Linnell, John D C

2013-10-01

Recolonizing carnivores can have a large impact on the status of wild ungulates, which have often modified their behavior in the absence of predation. Therefore, understanding the dynamics of reestablished predator-prey systems is crucial to predict their potential ecosystem effects. We decomposed the spatial structure of predation by recolonizing wolves (Canis lupus) on two sympatric ungulates, moose (Alces alces) and roe deer (Capreolus capreolus), in Scandinavia during a 10-year study. We monitored 18 wolves with GPS collars, distributed over 12 territories, and collected records from predation events. By using conditional logistic regression, we assessed the contributions of three main factors, the utilization patterns of each wolf territory, the spatial distribution of both prey species, and fine-scale landscape structure, in determining the spatial structure of moose and roe deer predation risk. The reestablished predator-prey system showed a remarkable spatial variation in kill occurrence at the intra-territorial level, with kill probabilities varying by several orders of magnitude inside the same territory. Variation in predation risk was evident also when a spatially homogeneous probability for a wolf to encounter a prey was simulated. Even inside the same territory, with the same landscape structure, and when exposed to predation by the same wolves, the two prey species experienced an opposite spatial distribution of predation risk. In particular, increased predation risk for moose was associated with open areas, especially clearcuts and young forest stands, whereas risk was lowered for roe deer in the same habitat types. Thus, fine-scale landscape structure can generate contrasting predation risk patterns in sympatric ungulates, so that they can experience large differences in the spatial distribution of risk and refuge areas when exposed to predation by a recolonizing predator. Territories with an earlier recolonization were not associated with a lower hunting success for wolves. Such constant efficiency in wolf predation during the recolonization process is in line with previous findings about the naive nature of Scandinavian moose to wolf predation. This, together with the human-dominated nature of the Scandinavian ecosystem, seems to limit the possibility for wolves to have large ecosystem effects and to establish a behaviorally mediated trophic cascade in Scandinavia.

Fine-scale natal homing and localized movement as shaped by sex and spawning habitat in chinook salmon

USGS Publications Warehouse

Neville, Helen; Isaak, Daniel; Dunham, J.B.; Thurow, Russel; Rieman, B.

2006-01-01

Natal homing is a hallmark of the life history of salmonid fishes, but the spatial scale of homing within local, naturally reproducing salmon populations is still poorly understood. Accurate homing (paired with restricted movement) should lead to the existence of fine-scale genetic structuring due to the spatial clustering of related individuals on spawning grounds. Thus, we explored the spatial resolution of natal homing using genetic associations among individual Chinook salmon (Oncorhynchus tshawytscha) in an interconnected stream network. We also investigated the relationship between genetic patterns and two factors hypothesized to influence natal homing and localized movements at finer scales in this species, localized patterns in the distribution of spawning gravels and sex. Spatial autocorrelation analyses showed that spawning locations in both sub-basins of our study site were spatially clumped, but the upper sub-basin generally had a larger spatial extent and continuity of redd locations than the lower sub-basin, where the distribution of redds and associated habitat conditions were more patchy. Male genotypes were not autocorrelated at any spatial scale in either sub-basin. Female genotypes showed significant spatial autocorrelation and genetic patterns for females varied in the direction predicted between the two sub-basins, with much stronger autocorrelation in the sub-basin with less continuity in spawning gravels. The patterns observed here support predictions about differential constraints and breeding tactics between the two sexes and the potential for fine-scale habitat structure to influence the precision of natal homing and localized movements of individual Chinook salmon on their breeding grounds.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-03-15

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

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

PubMed

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

2018-03-01

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

Using fine-scale fuel measurements to assess wildland fuels, potential fire behavior and hazard mitigation treatments in the southeastern USA

Treesearch

Roger D. Ottmar; John I. Blake; William T. Crolly

2012-01-01

The inherent spatial and temporal heterogeneity of fuel beds in forests of the southeastern United States may require fine scale fuel measurements for providing reliable fire hazard and fuel treatment effectiveness estimates. In a series of five papers, an intensive, fine scale fuel inventory from the Savanna River Site in the southeastern United States is used for...

Fine-Scale Habitat Segregation between Two Ecologically Similar Top Predators.

PubMed

Palomares, Francisco; Fernández, Néstor; Roques, Severine; Chávez, Cuauhtemoc; Silveira, Leandro; Keller, Claudia; Adrados, Begoña

2016-01-01

Similar, coexisting species often segregate along the spatial ecological axis. Here, we examine if two top predators (jaguars and pumas) present different fine-scale habitat use in areas of coexistence, and discuss if the observed pattern can be explained by the risk of interference competition between them. Interference competition theory predicts that pumas should avoid habitats or areas used by jaguars (the dominant species), and as a consequence should present more variability of niche parameters across study areas. We used non-invasive genetic sampling of faeces in 12 different areas and sensor satellite fine-scale habitat indices to answer these questions. Meta-analysis confirmed differences in fine-scale habitat use between jaguars and pumas. Furthermore, average marginality of the realized niches of pumas was more variable than those of jaguars, and tolerance (a measure of niche breadth) was on average 2.2 times higher in pumas than in jaguars, as expected under the interference competition risk hypothesis. The use of sensor satellite fine-scale habitat indices allowed the detection of subtle differences in the environmental characteristics of the habitats used by these two similar top predators, which, as a rule, until now were recorded using the same general habitat types. The detection of fine spatial segregation between these two top predators was scale-dependent.

Inferring landscape-scale land-use impacts on rivers using data from mesocosm experiments and artificial neural networks.

PubMed

Magierowski, Regina H; Read, Steve M; Carter, Steven J B; Warfe, Danielle M; Cook, Laurie S; Lefroy, Edward C; Davies, Peter E

2015-01-01

Identifying land-use drivers of changes in river condition is complicated by spatial scale, geomorphological context, land management, and correlations among responding variables such as nutrients and sediments. Furthermore, variations in standard metrics, such as substratum composition, do not necessarily relate causally to ecological impacts. Consequently, the absence of a significant relationship between a hypothesised driver and a dependent variable does not necessarily indicate the absence of a causal relationship. We conducted a gradient survey to identify impacts of catchment-scale grazing by domestic livestock on river macroinvertebrate communities. A standard correlative approach showed that community structure was strongly related to the upstream catchment area under grazing. We then used data from a stream mesocosm experiment that independently quantified the impacts of nutrients and fine sediments on macroinvertebrate communities to train artificial neural networks (ANNs) to assess the relative influence of nutrients and fine sediments on the survey sites from their community composition. The ANNs developed to predict nutrient impacts did not find a relationship between nutrients and catchment area under grazing, suggesting that nutrients were not an important factor mediating grazing impacts on community composition, or that these ANNs had no generality or insufficient power at the landscape-scale. In contrast, ANNs trained to predict the impacts of fine sediments indicated a significant relationship between fine sediments and catchment area under grazing. Macroinvertebrate communities at sites with a high proportion of land under grazing were thus more similar to those resulting from high fine sediments in a mesocosm experiment than to those resulting from high nutrients. Our study confirms that 1) fine sediment is an important mediator of land-use impacts on river macroinvertebrate communities, 2) ANNs can successfully identify subtle effects and separate the effects of correlated variables, and 3) data from small-scale experiments can generate relationships that help explain landscape-scale patterns.

Inferring Landscape-Scale Land-Use Impacts on Rivers Using Data from Mesocosm Experiments and Artificial Neural Networks

PubMed Central

Magierowski, Regina H.; Read, Steve M.; Carter, Steven J. B.; Warfe, Danielle M.; Cook, Laurie S.; Lefroy, Edward C.; Davies, Peter E.

2015-01-01

Identifying land-use drivers of changes in river condition is complicated by spatial scale, geomorphological context, land management, and correlations among responding variables such as nutrients and sediments. Furthermore, variations in standard metrics, such as substratum composition, do not necessarily relate causally to ecological impacts. Consequently, the absence of a significant relationship between a hypothesised driver and a dependent variable does not necessarily indicate the absence of a causal relationship. We conducted a gradient survey to identify impacts of catchment-scale grazing by domestic livestock on river macroinvertebrate communities. A standard correlative approach showed that community structure was strongly related to the upstream catchment area under grazing. We then used data from a stream mesocosm experiment that independently quantified the impacts of nutrients and fine sediments on macroinvertebrate communities to train artificial neural networks (ANNs) to assess the relative influence of nutrients and fine sediments on the survey sites from their community composition. The ANNs developed to predict nutrient impacts did not find a relationship between nutrients and catchment area under grazing, suggesting that nutrients were not an important factor mediating grazing impacts on community composition, or that these ANNs had no generality or insufficient power at the landscape-scale. In contrast, ANNs trained to predict the impacts of fine sediments indicated a significant relationship between fine sediments and catchment area under grazing. Macroinvertebrate communities at sites with a high proportion of land under grazing were thus more similar to those resulting from high fine sediments in a mesocosm experiment than to those resulting from high nutrients. Our study confirms that 1) fine sediment is an important mediator of land-use impacts on river macroinvertebrate communities, 2) ANNs can successfully identify subtle effects and separate the effects of correlated variables, and 3) data from small-scale experiments can generate relationships that help explain landscape-scale patterns. PMID:25775245

Spatial and seasonal variations of leaf area index (LAI) in subtropical secondary forests related to floristic composition and stand characters

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.

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

PubMed

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

2017-09-22

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

The Relationship Between Fusion, Suppression, and Diplopia in Normal and Amblyopic Vision.

PubMed

Spiegel, Daniel P; Baldwin, Alex S; Hess, Robert F

2016-10-01

Single vision occurs through a combination of fusion and suppression. When neither mechanism takes place, we experience diplopia. Under normal viewing conditions, the perceptual state depends on the spatial scale and interocular disparity. The purpose of this study was to examine the three perceptual states in human participants with normal and amblyopic vision. Participants viewed two dichoptically separated horizontal blurred edges with an opposite tilt (2.35°) and indicated their binocular percept: "one flat edge," "one tilted edge," or "two edges." The edges varied with scale (fine 4 min arc and coarse 32 min arc), disparity, and interocular contrast. We investigated how the binocular interactions vary in amblyopic (visual acuity [VA] > 0.2 logMAR, n = 4) and normal vision (VA ≤ 0 logMAR, n = 4) under interocular variations in stimulus contrast and luminance. In amblyopia, despite the established sensory dominance of the fellow eye, fusion prevails at the coarse scale and small disparities (75%). We also show that increasing the relative contrast to the amblyopic eye enhances the probability of fusion at the fine scale (from 18% to 38%), and leads to a reversal of the sensory dominance at coarse scale. In normal vision we found that interocular luminance imbalances disturbed binocular combination only at the fine scale in a way similar to that seen in amblyopia. Our results build upon the growing evidence that the amblyopic visual system is binocular and further show that the suppressive mechanisms rendering the amblyopic system functionally monocular are scale dependent.

Determinants of fish assemblage structure in Northwestern Great Plains streams

USGS Publications Warehouse

Mullen, J.A.; Bramblett, R.G.; Guy, C.S.; Zale, A.V.; Roberts, D.W.

2011-01-01

Prairie streams are known for their harsh and stochastic physical conditions, and the fish assemblages therein have been shown to be temporally variable. We assessed the spatial and temporal variation in fish assemblage structure in five intermittent, adventitious northwestern Great Plains streams representing a gradient of watershed areas. Fish assemblages and abiotic conditions varied more spatially than temporally. The most important variables explaining fish assemblage structure were longitudinal position and the proportion of fine substrates. The proportion of fine substrates increased proceeding upstream, approaching 100% in all five streams, and species richness declined upstream with increasing fine substrates. High levels of fine substrate in the upper reaches appeared to limit the distribution of obligate lithophilic fish species to reaches further downstream. Species richness and substrates were similar among all five streams at the lowermost and uppermost sites. However, in the middle reaches, species richness increased, the amount of fine substrate decreased, and connectivity increased as watershed area increased. Season and some dimensions of habitat (including thalweg depth, absolute distance to the main-stem river, and watershed size) were not essential in explaining the variation in fish assemblages. Fish species richness varied more temporally than overall fish assemblage structure did because common species were consistently abundant across seasons, whereas rare species were sometimes absent or perhaps not detected by sampling. The similarity in our results among five streams varying in watershed size and those from other studies supports the generalization that spatial variation exceeds temporal variation in the fish assemblages of prairie and warmwater streams. Furthermore, given longitudinal position, substrate, and stream size, general predictions regarding fish assemblage structure and function in prairie streams are possible. ?? American Fisheries Society 2011.

Coupling fine-scale root and canopy structure using ground-based remote sensing

Treesearch

Brady Hardiman; Christopher Gough; John Butnor; Gil Bohrer; Matteo Detto; Peter Curtis

2017-01-01

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in...

Lack of sex-biased dispersal promotes fine-scale genetic structure in alpine ungulates

Treesearch

Gretchen H. Roffler; Sandra L. Talbot; Gordon Luikart; George K. Sage; Kristy L. Pilgrim; Layne G. Adams; Michael K. Schwartz

2014-01-01

Identifying patterns of fine-scale genetic structure in natural populations can advance understanding of critical ecological processes such as dispersal and gene flow across heterogeneous landscapes. Alpine ungulates generally exhibit high levels of genetic structure due to female philopatry and patchy configuration of mountain habitats. We assessed the spatial scale...

Modelling Soil-Landscapes in Coastal California Hills Using Fine Scale Terrestrial Lidar

NASA Astrophysics Data System (ADS)

Prentice, S.; Bookhagen, B.; Kyriakidis, P. C.; Chadwick, O.

2013-12-01

Digital elevation models (DEMs) are the dominant input to spatially explicit digital soil mapping (DSM) efforts due to their increasing availability and the tight coupling between topography and soil variability. Accurate characterization of this coupling is dependent on DEM spatial resolution and soil sampling density, both of which may limit analyses. For example, DEM resolution may be too coarse to accurately reflect scale-dependent soil properties yet downscaling introduces artifactual uncertainty unrelated to deterministic or stochastic soil processes. We tackle these limitations through a DSM effort that couples moderately high density soil sampling with a very fine scale terrestrial lidar dataset (20 cm) implemented in a semiarid rolling hillslope domain where terrain variables change rapidly but smoothly over short distances. Our guiding hypothesis is that in this diffusion-dominated landscape, soil thickness is readily predicted by continuous terrain attributes coupled with catenary hillslope segmentation. We choose soil thickness as our keystone dependent variable for its geomorphic and hydrologic significance, and its tendency to be a primary input to synthetic ecosystem models. In defining catenary hillslope position we adapt a logical rule-set approach that parses common terrain derivatives of curvature and specific catchment area into discrete landform elements (LE). Variograms and curvature-area plots are used to distill domain-scale terrain thresholds from short range order noise characteristic of very fine-scale spatial data. The revealed spatial thresholds are used to condition LE rule-set inputs, rendering a catenary LE map that leverages the robustness of fine-scale terrain data to create a generalized interpretation of soil geomorphic domains. Preliminary regressions show that continuous terrain variables alone (curvature, specific catchment area) only partially explain soil thickness, and only in a subset of soils. For example, at spatial scales up 20, curvature explains 40% of soil thickness variance among soils <3 m deep, while soils >3 m deep show no clear relation to curvature. To further demonstration our geomorphic segmentation approach, we apply it to DEM domains where diffusion processes are less dominant than in our primary study area. Classified landform map derived from fine scale terrestrial lidar. Color classes depict hydrogeomorphic process domains in zero order watersheds.

A fast solver for the Helmholtz equation based on the generalized multiscale finite-element method

NASA Astrophysics Data System (ADS)

Fu, Shubin; Gao, Kai

2017-11-01

Conventional finite-element methods for solving the acoustic-wave Helmholtz equation in highly heterogeneous media usually require finely discretized mesh to represent the medium property variations with sufficient accuracy. Computational costs for solving the Helmholtz equation can therefore be considerably expensive for complicated and large geological models. Based on the generalized multiscale finite-element theory, we develop a novel continuous Galerkin method to solve the Helmholtz equation in acoustic media with spatially variable velocity and mass density. Instead of using conventional polynomial basis functions, we use multiscale basis functions to form the approximation space on the coarse mesh. The multiscale basis functions are obtained from multiplying the eigenfunctions of a carefully designed local spectral problem with an appropriate multiscale partition of unity. These multiscale basis functions can effectively incorporate the characteristics of heterogeneous media's fine-scale variations, thus enable us to obtain accurate solution to the Helmholtz equation without directly solving the large discrete system formed on the fine mesh. Numerical results show that our new solver can significantly reduce the dimension of the discrete Helmholtz equation system, and can also obviously reduce the computational time.

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

PubMed

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

2016-04-01

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

The wildland fuel cell concept: an approach to characterize fine-scale variation in fuels and fire in frequently burned longleaf pine forests

Treesearch

J. Kevin Hiers; Joseph J. O’Brien; R. J. Mitchell; John M. Grego; E. Louise Loudermilk

2009-01-01

In ecosystems with frequent surface fire regimes, fire and fuel heterogeneity has been largely overlookedowing to the lack of unburned patches and the difficulty in measuring fire behavior at fine scales (0.1–10 m). The diversevegetation in these ecosystems varies at these fine scales. This diversity could be...

Ultra-Fine Scale Spatially-Integrated Mapping of Habitat and Occupancy Using Structure-From-Motion.

PubMed

McDowall, Philip; Lynch, Heather J

2017-01-01

Organisms respond to and often simultaneously modify their environment. While these interactions are apparent at the landscape extent, the driving mechanisms often occur at very fine spatial scales. Structure-from-Motion (SfM), a computer vision technique, allows the simultaneous mapping of organisms and fine scale habitat, and will greatly improve our understanding of habitat suitability, ecophysiology, and the bi-directional relationship between geomorphology and habitat use. SfM can be used to create high-resolution (centimeter-scale) three-dimensional (3D) habitat models at low cost. These models can capture the abiotic conditions formed by terrain and simultaneously record the position of individual organisms within that terrain. While coloniality is common in seabird species, we have a poor understanding of the extent to which dense breeding aggregations are driven by fine-scale active aggregation or limited suitable habitat. We demonstrate the use of SfM for fine-scale habitat suitability by reconstructing the locations of nests in a gentoo penguin colony and fitting models that explicitly account for conspecific attraction. The resulting digital elevation models (DEMs) are used as covariates in an inhomogeneous hybrid point process model. We find that gentoo penguin nest site selection is a function of the topography of the landscape, but that nests are far more aggregated than would be expected based on terrain alone, suggesting a strong role of behavioral aggregation in driving coloniality in this species. This integrated mapping of organisms and fine scale habitat will greatly improve our understanding of fine-scale habitat suitability, ecophysiology, and the complex bi-directional relationship between geomorphology and habitat use.

Breed locally, disperse globally: Fine-scale genetic structure despite landscape-scale panmixia in a fire-specialist

Treesearch

Jennifer C. Pierson; Fred W. Allendorf; Pierre Drapeau; Michael K. Schwartz

2013-01-01

An exciting advance in the understanding of metapopulation dynamics has been the investigation of how populations respond to ephemeral patches that go 'extinct' during the lifetime of an individual. Previous research has shown that this scenario leads to genetic homogenization across large spatial scales. However, little is known about fine-scale genetic...

Fine-scale spatial genetic structure of common and declining bumble bees across an agricultural landscape.

PubMed

Dreier, Stephanie; Redhead, John W; Warren, Ian A; Bourke, Andrew F G; Heard, Matthew S; Jordan, William C; Sumner, Seirian; Wang, Jinliang; Carvell, Claire

2014-07-01

Land-use changes have threatened populations of many insect pollinators, including bumble bees. Patterns of dispersal and gene flow are key determinants of species' ability to respond to land-use change, but have been little investigated at a fine scale (<10 km) in bumble bees. Using microsatellite markers, we determined the fine-scale spatial genetic structure of populations of four common Bombus species (B. terrestris, B. lapidarius, B. pascuorum and B. hortorum) and one declining species (B. ruderatus) in an agricultural landscape in Southern England, UK. The study landscape contained sown flower patches representing agri-environment options for pollinators. We found that, as expected, the B. ruderatus population was characterized by relatively low heterozygosity, number of alleles and colony density. Across all species, inbreeding was absent or present but weak (FIS  = 0.01-0.02). Using queen genotypes reconstructed from worker sibships and colony locations estimated from the positions of workers within these sibships, we found that significant isolation by distance was absent in B. lapidarius, B. hortorum and B. ruderatus. In B. terrestris and B. pascuorum, it was present but weak; for example, in these two species, expected relatedness of queens founding colonies 1 m apart was 0.02. These results show that bumble bee populations exhibit low levels of spatial genetic structure at fine spatial scales, most likely because of ongoing gene flow via widespread queen dispersal. In addition, the results demonstrate the potential for agri-environment scheme conservation measures to facilitate fine-scale gene flow by creating a more even distribution of suitable habitats across landscapes. © 2014 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Spatial patterning in PM2.5 constituents under an inversion-focused sampling design across an urban area of complex terrain

PubMed Central

Tunno, Brett J; Dalton, Rebecca; Michanowicz, Drew R; Shmool, Jessie L C; Kinnee, Ellen; Tripathy, Sheila; Cambal, Leah; Clougherty, Jane E

2016-01-01

Health effects of fine particulate matter (PM2.5) vary by chemical composition, and composition can help to identify key PM2.5 sources across urban areas. Further, this intra-urban spatial variation in concentrations and composition may vary with meteorological conditions (e.g., mixing height). Accordingly, we hypothesized that spatial sampling during atmospheric inversions would help to better identify localized source effects, and reveal more distinct spatial patterns in key constituents. We designed a 2-year monitoring campaign to capture fine-scale intra-urban variability in PM2.5 composition across Pittsburgh, PA, and compared both spatial patterns and source effects during “frequent inversion” hours vs 24-h weeklong averages. Using spatially distributed programmable monitors, and a geographic information systems (GIS)-based design, we collected PM2.5 samples across 37 sampling locations per year to capture variation in local pollution sources (e.g., proximity to industry, traffic density) and terrain (e.g., elevation). We used inductively coupled plasma mass spectrometry (ICP-MS) to determine elemental composition, and unconstrained factor analysis to identify source suites by sampling scheme and season. We examined spatial patterning in source factors using land use regression (LUR), wherein GIS-based source indicators served to corroborate factor interpretations. Under both summer sampling regimes, and for winter inversion-focused sampling, we identified six source factors, characterized by tracers associated with brake and tire wear, steel-making, soil and road dust, coal, diesel exhaust, and vehicular emissions. For winter 24-h samples, four factors suggested traffic/fuel oil, traffic emissions, coal/industry, and steel-making sources. In LURs, as hypothesized, GIS-based source terms better explained spatial variability in inversion-focused samples, including a greater contribution from roadway, steel, and coal-related sources. Factor analysis produced source-related constituent suites under both sampling designs, though factors were more distinct under inversion-focused sampling. PMID:26507005

Influences of space, soil, nematodes and plants on microbial community composition of chalk grassland soils.

PubMed

Yergeau, Etienne; Bezemer, T Martijn; Hedlund, Katarina; Mortimer, Simon R; Kowalchuk, George A; Van Der Putten, Wim H

2010-08-01

Microbial communities respond to a variety of environmental factors related to resources (e.g. plant and soil organic matter), habitat (e.g. soil characteristics) and predation (e.g. nematodes, protozoa and viruses). However, the relative contribution of these factors on microbial community composition is poorly understood. Here, we sampled soils from 30 chalk grassland fields located in three different chalk hill ridges of Southern England, using a spatially explicit sampling scheme. We assessed microbial communities via phospholipid fatty acid (PLFA) analyses and PCR-denaturing gradient gel electrophoresis (DGGE) and measured soil characteristics, as well as nematode and plant community composition. The relative influences of space, soil, vegetation and nematodes on soil microorganisms were contrasted using variation partitioning and path analysis. Results indicate that soil characteristics and plant community composition, representing habitat and resources, shape soil microbial community composition, whereas the influence of nematodes, a potential predation factor, appears to be relatively small. Spatial variation in microbial community structure was detected at broad (between fields) and fine (within fields) scales, suggesting that microbial communities exhibit biogeographic patterns at different scales. Although our analysis included several relevant explanatory data sets, a large part of the variation in microbial communities remained unexplained (up to 92% in some analyses). However, in several analyses, significant parts of the variation in microbial community structure could be explained. The results of this study contribute to our understanding of the relative importance of different environmental and spatial factors in driving the composition of soil-borne microbial communities. © 2009 Society for Applied Microbiology and Blackwell Publishing Ltd.

Mapping and predictive variations of soil bacterial richness across France

PubMed Central

Dequietd, Samuel; Saby, Nicolas P. A.; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2017-01-01

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition. PMID:29059218

Mapping and predictive variations of soil bacterial richness across France.

PubMed

Terrat, Sébastien; Horrigue, Walid; Dequiedt, Samuel; Saby, Nicolas P A; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2017-01-01

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition.

Application and theoretical analysis of the flamelet model for supersonic turbulent combustion flows in the scramjet engine

NASA Astrophysics Data System (ADS)

Gao, Zhenxun; Wang, Jingying; Jiang, Chongwen; Lee, Chunhian

2014-11-01

In the framework of Reynolds-averaged Navier-Stokes simulation, supersonic turbulent combustion flows at the German Aerospace Centre (DLR) combustor and Japan Aerospace Exploration Agency (JAXA) integrated scramjet engine are numerically simulated using the flamelet model. Based on the DLR combustor case, theoretical analysis and numerical experiments conclude that: the finite rate model only implicitly considers the large-scale turbulent effect and, due to the lack of the small-scale non-equilibrium effect, it would overshoot the peak temperature compared to the flamelet model in general. Furthermore, high-Mach-number compressibility affects the flamelet model mainly through two ways: the spatial pressure variation and the static enthalpy variation due to the kinetic energy. In the flamelet library, the mass fractions of the intermediate species, e.g. OH, are more sensible to the above two effects than the main species such as H2O. Additionally, in the combustion flowfield where the pressure is larger than the value adopted in the generation of the flamelet library or the conversion from the static enthalpy to the kinetic energy occurs, the temperature obtained by the flamelet model without taking compressibility effects into account would be undershot, and vice versa. The static enthalpy variation effect has only little influence on the temperature simulation of the flamelet model, while the effect of the spatial pressure variation may cause relatively large errors. From the JAXA case, it is found that the flamelet model cannot in general be used for an integrated scramjet engine. The existence of the inlet together with the transverse injection scheme could cause large spatial variations of pressure, so the pressure value adopted for the generation of a flamelet library should be fine-tuned according to a pre-simulation of pure mixing.

Fine scale climatic and soil variability effects on plant species cover along the Front Range of Colorado, USA

NASA Astrophysics Data System (ADS)

Cumming, William Frank Preston

Fine scale studies are rarely performed to address landscape level responses to microclimatic variability. Is it the timing, distribution, and magnitude of soil temperature and moisture that affects what species emerge each season and, in turn, their resilience to fluctuations in microclimate. For this dissertation research, I evaluated the response of vegetation change to microclimatic variability within two communities over a three year period (2009-2012) utilizing 25 meter transects at two locations along the Front Range of Colorado near Boulder, CO and Golden, CO respectively. To assess microclimatic variability, spatial and temporal autocorrelation analyses were performed with soil temperature and moisture. Species cover was assessed along several line transects and correlated with microclimatic variability. Spatial and temporal autocorrelograms are useful tools in identifying the degree of dependency of soil temperature and moisture on the distance and time between pairs of measurements. With this analysis I found that a meter spatial resolution and two-hour measurements are sufficient to capture the fine scale variability in soil properties throughout the year. By comparing this to in situ measurements of soil properties and species percent cover I found that there are several plant functional types and/or species origin in particular that are more sensitive to variations in temperature and moisture than others. When all seasons, locations, correlations, and regional climate are looked at, it is the month of March that stands out in terms of significance. Additionally, of all of the vegetation types represented at these two sites C4, C3, native, non-native, and forb species seem to be the most sensitive to fluctuations in soil temperature, moisture, and regional climate in the spring season. The steady decline in percent species cover the study period and subsequent decrease in percent species cover and size at both locations may indicate that certain are unable to respond to continually higher temperatures and lower moisture availability that is inevitable with future climatic variability.

Fine-scale analysis of genetic structure in the brooding coral Seriatopora hystrix from the Red Sea

NASA Astrophysics Data System (ADS)

Maier, E.; Tollrian, R.; Nürnberger, B.

2009-09-01

The dispersal of gametes and larvae plays a key role in the population dynamics of sessile marine invertebrates. Species with internal fertilisation are often associated with very localised larval dispersal, which may cause small-scale patterns of neutral genetic variation. This study on the brooding coral Seriatopora hystrix from the Red Sea focused on the smallest possible scale: Two S. hystrix stands (~100 colonies each) near Dahab were completely sampled, mapped and analysed at five microsatellite markers. The sexual mode of reproduction, the likely occurrence of selfing and the level of immigration were in agreement with previous studies on this species. Contrary to previous findings, both stands were in Hardy-Weinberg proportions. Also, no evidence for spatially restricted larval dispersal within the sampled areas was found. Differences between this and previous studies on S. hystrix could reflect variation in life history or varying environmental conditions, which opens intriguing questions for future research.

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

PubMed

Ripoche, Marion; Lindsay, Leslie Robbin; Ludwig, Antoinette; Ogden, Nicholas H; Thivierge, Karine; Leighton, Patrick A

2018-03-27

Since its detection in Canada in the early 1990s, Ixodes scapularis , the primary tick vector of Lyme disease in eastern North America, has continued to expand northward. Estimates of the tick's broad-scale distribution are useful for tracking the extent of the Lyme disease risk zone; however, tick distribution may vary widely within this zone. Here, we investigated I. scapularis nymph distribution at three spatial scales across the Lyme disease emergence zone in southern Quebec, Canada. We collected ticks and compared the nymph densities among different woodlands and different plots and transects within the same woodland. Hot spot analysis highlighted significant nymph clustering at each spatial scale. In regression models, nymph abundance was associated with litter depth, humidity, and elevation, which contribute to a suitable habitat for ticks, but also with the distance from the trail and the type of trail, which could be linked to host distribution and human disturbance. Accounting for this heterogeneous nymph distribution at a fine spatial scale could help improve Lyme disease management strategies but also help people to understand the risk variation around them and to adopt appropriate behaviors, such as staying on the trail in infested parks to limit their exposure to the vector and associated pathogens.

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

PubMed Central

Lindsay, Leslie Robbin; Ludwig, Antoinette; Ogden, Nicholas H.; Thivierge, Karine; Leighton, Patrick A.

2018-01-01

Since its detection in Canada in the early 1990s, Ixodes scapularis, the primary tick vector of Lyme disease in eastern North America, has continued to expand northward. Estimates of the tick’s broad-scale distribution are useful for tracking the extent of the Lyme disease risk zone; however, tick distribution may vary widely within this zone. Here, we investigated I. scapularis nymph distribution at three spatial scales across the Lyme disease emergence zone in southern Quebec, Canada. We collected ticks and compared the nymph densities among different woodlands and different plots and transects within the same woodland. Hot spot analysis highlighted significant nymph clustering at each spatial scale. In regression models, nymph abundance was associated with litter depth, humidity, and elevation, which contribute to a suitable habitat for ticks, but also with the distance from the trail and the type of trail, which could be linked to host distribution and human disturbance. Accounting for this heterogeneous nymph distribution at a fine spatial scale could help improve Lyme disease management strategies but also help people to understand the risk variation around them and to adopt appropriate behaviors, such as staying on the trail in infested parks to limit their exposure to the vector and associated pathogens. PMID:29584627

Fine-Scale Mapping by Spatial Risk Distribution Modeling for Regional Malaria Endemicity and Its Implications under the Low-to-Moderate Transmission Setting in Western Cambodia

PubMed Central

Okami, Suguru; Kohtake, Naohiko

2016-01-01

The disease burden of malaria has decreased as malaria elimination efforts progress. The mapping approach that uses spatial risk distribution modeling needs some adjustment and reinvestigation in accordance with situational changes. Here we applied a mathematical modeling approach for standardized morbidity ratio (SMR) calculated by annual parasite incidence using routinely aggregated surveillance reports, environmental data such as remote sensing data, and non-environmental anthropogenic data to create fine-scale spatial risk distribution maps of western Cambodia. Furthermore, we incorporated a combination of containment status indicators into the model to demonstrate spatial heterogeneities of the relationship between containment status and risks. The explanatory model was fitted to estimate the SMR of each area (adjusted Pearson correlation coefficient R2 = 0.774; Akaike information criterion AIC = 149.423). A Bayesian modeling framework was applied to estimate the uncertainty of the model and cross-scale predictions. Fine-scale maps were created by the spatial interpolation of estimated SMRs at each village. Compared with geocoded case data, corresponding predicted values showed conformity [Spearman’s rank correlation r = 0.662 in the inverse distance weighed interpolation and 0.645 in ordinal kriging (95% confidence intervals of 0.414–0.827 and 0.368–0.813, respectively), Welch’s t-test; Not significant]. The proposed approach successfully explained regional malaria risks and fine-scale risk maps were created under low-to-moderate malaria transmission settings where reinvestigations of existing risk modeling approaches were needed. Moreover, different representations of simulated outcomes of containment status indicators for respective areas provided useful insights for tailored interventional planning, considering regional malaria endemicity. PMID:27415623

Disentangling how landscape spatial and temporal heterogeneity affects Savanna birds.

PubMed

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

2013-01-01

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

Disentangling How Landscape Spatial and Temporal Heterogeneity Affects Savanna Birds

PubMed Central

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

2013-01-01

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

Climate, soil and plant functional types as drivers of global fine-root trait variation

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

Freschet, Grégoire T.; Valverde-Barrantes, Oscar J.; Tucker, Caroline M.

Ecosystem functioning relies heavily on below-ground processes, which are largely regulated by plant fine-roots and their functional traits. However, our knowledge of fine-root trait distribution relies to date on local- and regional-scale studies with limited numbers of species, growth forms and environmental variation. We compiled a world-wide fine-root trait dataset, featuring 1115 species from contrasting climatic areas, phylogeny and growth forms to test a series of hypotheses pertaining to the influence of plant functional types, soil and climate variables, and the degree of manipulation of plant growing conditions on species fine-root trait variation. Most particularly, we tested the competing hypothesesmore » that fine-root traits typical of faster return on investment would be most strongly associated with conditions of limiting versus favourable soil resource availability. We accounted for both data source and species phylogenetic relatedness. We demonstrate that: (i) Climate conditions promoting soil fertility relate negatively to fine-root traits favouring fast soil resource acquisition, with a particularly strong positive effect of temperature on fine-root diameter and negative effect on specific root length (SRL), and a negative effect of rainfall on root nitrogen concentration; (ii) Soil bulk density strongly influences species fine-root morphology, by favouring thicker, denser fine-roots; (iii) Fine-roots from herbaceous species are on average finer and have higher SRL than those of woody species, and N 2-fixing capacity positively relates to root nitrogen; and (iv) Plants growing in pots have higher SRL than those grown in the field. Synthesis. This study reveals both the large variation in fine-root traits encountered globally and the relevance of several key plant functional types and soil and climate variables for explaining a substantial part of this variation. Climate, particularly temperature, and plant functional types were the two strongest predictors of fine-root trait variation. High trait variation occurred at local scales, suggesting that wide-ranging below-ground resource economics strategies are viable within most climatic areas and soil conditions.« less

Climate, soil and plant functional types as drivers of global fine-root trait variation

DOE PAGES

Freschet, Grégoire T.; Valverde-Barrantes, Oscar J.; Tucker, Caroline M.; ...

2017-03-08

Ecosystem functioning relies heavily on below-ground processes, which are largely regulated by plant fine-roots and their functional traits. However, our knowledge of fine-root trait distribution relies to date on local- and regional-scale studies with limited numbers of species, growth forms and environmental variation. We compiled a world-wide fine-root trait dataset, featuring 1115 species from contrasting climatic areas, phylogeny and growth forms to test a series of hypotheses pertaining to the influence of plant functional types, soil and climate variables, and the degree of manipulation of plant growing conditions on species fine-root trait variation. Most particularly, we tested the competing hypothesesmore » that fine-root traits typical of faster return on investment would be most strongly associated with conditions of limiting versus favourable soil resource availability. We accounted for both data source and species phylogenetic relatedness. We demonstrate that: (i) Climate conditions promoting soil fertility relate negatively to fine-root traits favouring fast soil resource acquisition, with a particularly strong positive effect of temperature on fine-root diameter and negative effect on specific root length (SRL), and a negative effect of rainfall on root nitrogen concentration; (ii) Soil bulk density strongly influences species fine-root morphology, by favouring thicker, denser fine-roots; (iii) Fine-roots from herbaceous species are on average finer and have higher SRL than those of woody species, and N 2-fixing capacity positively relates to root nitrogen; and (iv) Plants growing in pots have higher SRL than those grown in the field. Synthesis. This study reveals both the large variation in fine-root traits encountered globally and the relevance of several key plant functional types and soil and climate variables for explaining a substantial part of this variation. Climate, particularly temperature, and plant functional types were the two strongest predictors of fine-root trait variation. High trait variation occurred at local scales, suggesting that wide-ranging below-ground resource economics strategies are viable within most climatic areas and soil conditions.« less

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir.

PubMed

Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-09-23

The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies.

Spatial structure of morphological and neutral genetic variation in Brook Trout

USGS Publications Warehouse

Kazyak, David C.; Hilderbrand, Robert H.; Keller, Stephen R.; Colaw, Mark C.; Holloway, Amanda E.; Morgan, Raymond P.; King, Timothy L.

2015-01-01

Brook Trout Salvelinus fontinalis exhibit exceptional levels of life history variation, remarkable genetic variability, and fine-scale population structure. In many cases, neighboring populations may be highly differentiated from one another to an extent that is comparable with species-level distinctions in other taxa. Although genetic samples have been collected from hundreds of populations and tens of thousands of individuals, little is known about whether differentiation at neutral markers reflects phenotypic differences among Brook Trout populations. We compared differentiation in morphology and neutral molecular markers among populations from four geographically proximate locations (all within 24 km) to examine how genetic diversity covaries with morphology. We found significant differences among and/or within streams for all three morphological axes examined and identified the source stream of many individuals based on morphology (52.3% classification efficiency). Although molecular and morphological differentiation among streams ranged considerably (mean pairwise FST: 0.023–0.264; pairwise PST: 0.000–0.339), the two measures were not significantly correlated. While in some cases morphological characters appear to have diverged to a greater extent than expected by neutral genetic drift, many traits were conserved to a greater extent than were neutral genetic markers. Thus, while Brook Trout exhibit fine-scale spatial patterns in both morphology and neutral genetic diversity, these types of biological variabilities are being structured by different ecological and evolutionary processes. The relative influences of genetic drift versus selection and phenotypic plasticity in shaping morphology appear to vary among populations occupying nearby streams.

Scale-dependent complementarity of climatic velocity and environmental diversity for identifying priority areas for conservation under climate change.

PubMed

Carroll, Carlos; Roberts, David R; Michalak, Julia L; Lawler, Joshua J; Nielsen, Scott E; Stralberg, Diana; Hamann, Andreas; Mcrae, Brad H; Wang, Tongli

2017-11-01

As most regions of the earth transition to altered climatic conditions, new methods are needed to identify refugia and other areas whose conservation would facilitate persistence of biodiversity under climate change. We compared several common approaches to conservation planning focused on climate resilience over a broad range of ecological settings across North America and evaluated how commonalities in the priority areas identified by different methods varied with regional context and spatial scale. Our results indicate that priority areas based on different environmental diversity metrics differed substantially from each other and from priorities based on spatiotemporal metrics such as climatic velocity. Refugia identified by diversity or velocity metrics were not strongly associated with the current protected area system, suggesting the need for additional conservation measures including protection of refugia. Despite the inherent uncertainties in predicting future climate, we found that variation among climatic velocities derived from different general circulation models and emissions pathways was less than the variation among the suite of environmental diversity metrics. To address uncertainty created by this variation, planners can combine priorities identified by alternative metrics at a single resolution and downweight areas of high variation between metrics. Alternately, coarse-resolution velocity metrics can be combined with fine-resolution diversity metrics in order to leverage the respective strengths of the two groups of metrics as tools for identification of potential macro- and microrefugia that in combination maximize both transient and long-term resilience to climate change. Planners should compare and integrate approaches that span a range of model complexity and spatial scale to match the range of ecological and physical processes influencing persistence of biodiversity and identify a conservation network resilient to threats operating at multiple scales. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

FINE SCALE AIR QUALITY MODELING USING DISPERSION AND CMAQ MODELING APPROACHES: AN EXAMPLE APPLICATION IN WILMINGTON, DE

EPA Science Inventory

Characterization of spatial variability of air pollutants in an urban setting at fine scales is critical for improved air toxics exposure assessments, for model evaluation studies and also for air quality regulatory applications. For this study, we investigate an approach that su...

Multi-scale interactions between local hydrography, seabed topography, and community assembly on cold-water coral reefs

NASA Astrophysics Data System (ADS)

Henry, L.-A.; Moreno Navas, J.; Roberts, J. M.

2013-04-01

We investigated how interactions between hydrography, topography and species ecology influence the assembly of species and functional traits across multiple spatial scales of a cold-water coral reef seascape. In a novel approach for these ecosystems, we used a spatially resolved complex three-dimensional flow model of hydrography to help explain assembly patterns. Forward-selection of distance-based Moran's eigenvector mapping (dbMEM) variables identified two submodels of spatial scales at which communities change: broad-scale (across reef) and fine-scale (within reef). Variance partitioning identified bathymetric and hydrographic gradients important in creating broad-scale assembly of species and traits. In contrast, fine-scale assembly was related more to processes that created spatially autocorrelated patches of fauna, such as philopatric recruitment in sessile fauna, and social interactions and food supply in scavenging detritivores and mobile predators. Our study shows how habitat modification of reef connectivity and hydrography by bottom fishing and renewable energy installations could alter the structure and function of an entire cold-water coral reef seascape.

Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics

NASA Astrophysics Data System (ADS)

Xu, Y.; Wang, L.

2017-12-01

Soil moisture is important for agricultural and hydrological studies. However, ground truth soil moisture data for wide area is difficult to achieve. Microwave remote sensing such as Soil Moisture Active Passive (SMAP) can offer a solution for wide coverage. However, existing global soil moisture products only provide observations at coarse spatial resolutions, which often limit their applications in regional agricultural and hydrological studies. This paper therefore aims to generate fine scale soil moisture information and extend soil moisture spatial availability. A statistical downscaling scheme is presented that incorporates multiple fine scale geoinformation data into the downscaling of coarse scale SMAP data in the absence of ground measurement data. Geoinformation data related to soil moisture patterns including digital elevation model (DEM), land surface temperature (LST), land use and normalized difference vegetation index (NDVI) at a fine scale are used as auxiliary environmental variables for downscaling SMAP data. Generalized additive model (GAM) and regression tree are first conducted to derive statistical relationships between SMAP data and auxiliary geoinformation data at an original coarse scale, and residuals are then downscaled to a finer scale via area-to-point kriging (ATPK) by accounting for the spatial correlation information of the input residuals. The results from standard validation scores as well as the triple collocation (TC) method against soil moisture in-situ measurements show that the downscaling method can significantly improve the spatial details of SMAP soil moisture while maintain the accuracy.

Using dynamic Brownian bridge movement modelling to measure temporal patterns of habitat selection.

PubMed

Byrne, Michael E; Clint McCoy, J; Hinton, Joseph W; Chamberlain, Michael J; Collier, Bret A

2014-09-01

Accurately describing animal space use is vital to understanding how wildlife use habitat. Improvements in GPS technology continue to facilitate collection of telemetry data at high spatial and temporal resolutions. Application of the recently introduced dynamic Brownian bridge movement model (dBBMM) to such data is promising as the method explicitly incorporates the behavioural heterogeneity of a movement path into the estimated utilization distribution (UD). Utilization distributions defining space use are normally estimated for time-scales ranging from weeks to months, obscuring much of the fine-scale information available from high-volume GPS data sets. By accounting for movement heterogeneity, the dBBMM provides a rigorous, behaviourally based estimate of space use between each set of relocations. Focusing on UDs generated between individual sets of locations allows us to quantify fine-scale circadian variation in habitat use. We used the dBBMM to estimate UDs bounding individual time steps for three terrestrial species with different life histories to illustrate how the method can be used to identify fine-scale variations in habitat use. We also demonstrate how dBBMMs can be used to characterize circadian patterns of habitat selection and link fine-scale patterns of habitat use to behaviour. We observed circadian patterns of habitat use that varied seasonally for a white-tailed deer (Odocoileus virginianus) and coyote (Canis latrans). We found seasonal patterns in selection by the white-tailed deer and were able to link use of conifer forests and agricultural fields to behavioural state of the coyote. Additionally, we were able to quantify the date in which a Rio Grande wild turkey (Meleagris gallopavo intermedia) initiated laying as well as when during the day, she was most likely to visit the nest site to deposit eggs. The ability to quantify circadian patterns of habitat use may have important implications for research and management of wildlife. Additionally, the ability to link such patterns to behaviour may aid in the development of mechanistic models of habitat selection. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Quantifying climatic variability in monsoonal northern China over the last 2200 years and its role in driving Chinese dynastic changes

NASA Astrophysics Data System (ADS)

Li, Jianyong; Dodson, John; Yan, Hong; Zhang, David D.; Zhang, Xiaojian; Xu, Qinghai; Lee, Harry F.; Pei, Qing; Cheng, Bo; Li, Chunhai; Ni, Jian; Sun, Aizhi; Lu, Fengyan; Zong, Yongqiang

2017-03-01

Our understanding on the spatial-temporal patterns of climatic variability over the last few millennia in the East Asian monsoon-dominated northern China (NC), and its role at a macro-scale in affecting the prosperity and depression of Chinese dynasties is limited. Quantitative high-resolution, regionally-synthesized palaeoclimatic reconstructions as well as simulations, and numerical analyses of their relationships with various fine-scale, numerical agro-ecological, social-economic, and geo-political historical records during the period of China's history, are presented here for NC. We utilize pollen data together with climate modeling to reconstruct and simulate decadal- to centennial-scale variations in precipitation or temperature for NC during the last 2200 years (-200-2000 AD). We find an overall cyclic-pattern (wet/warm or dry/cold) in the precipitation and temperature anomalies on centennial- to millennial-scale that can be likely considered as a representative for the entire NC by comparison with other related climatic records. We suggest that solar activity may play a key role in driving the climatic fluctuations in NC during the last 22 centuries, with its quasi ∼100, 50, 23, or 22-year periodicity clearly identified in our climatic reconstructions. We employ variation partitioning and redundancy analysis to quantify the independent effects of climatic factors on accounting for the total variation of 17 fine-grained numerical Chinese historical records. We quantitatively illustrate that precipitation (67.4%) may have been more important than temperature (32.5%) in causing the overall agro-ecological and macro-geopolitical shifts in imperial China with NC as the central ruling region and an agricultural heartland over the last 2200 years.

Ultra-Fine Scale Spatially-Integrated Mapping of Habitat and Occupancy Using Structure-From-Motion

PubMed Central

McDowall, Philip; Lynch, Heather J.

2017-01-01

Organisms respond to and often simultaneously modify their environment. While these interactions are apparent at the landscape extent, the driving mechanisms often occur at very fine spatial scales. Structure-from-Motion (SfM), a computer vision technique, allows the simultaneous mapping of organisms and fine scale habitat, and will greatly improve our understanding of habitat suitability, ecophysiology, and the bi-directional relationship between geomorphology and habitat use. SfM can be used to create high-resolution (centimeter-scale) three-dimensional (3D) habitat models at low cost. These models can capture the abiotic conditions formed by terrain and simultaneously record the position of individual organisms within that terrain. While coloniality is common in seabird species, we have a poor understanding of the extent to which dense breeding aggregations are driven by fine-scale active aggregation or limited suitable habitat. We demonstrate the use of SfM for fine-scale habitat suitability by reconstructing the locations of nests in a gentoo penguin colony and fitting models that explicitly account for conspecific attraction. The resulting digital elevation models (DEMs) are used as covariates in an inhomogeneous hybrid point process model. We find that gentoo penguin nest site selection is a function of the topography of the landscape, but that nests are far more aggregated than would be expected based on terrain alone, suggesting a strong role of behavioral aggregation in driving coloniality in this species. This integrated mapping of organisms and fine scale habitat will greatly improve our understanding of fine-scale habitat suitability, ecophysiology, and the complex bi-directional relationship between geomorphology and habitat use. PMID:28076351

Measured and calculated acoustic attenuation rates of tuned resonator arrays for two surface impedance distribution models with flow

NASA Technical Reports Server (NTRS)

Parrott, Tony L.; Abrahamson, A. Louis; Jones, Michael G.

1988-01-01

An experiment was performed to validate two analytical models for predicting low frequency attenuation of duct liner configurations built from an array of seven resonators that could be individually tuned via adjustable cavity depths. These analytical models had previously been developed for high frequency aero-engine inlet duct liner design. In the low frequency application, the liner surface impedance distribution is unavoidably spatially varying by virtue of available fabrication techniques. The characteristic length of this spatial variation may be a significant fraction of the acoustic wavelength. Comparison of measured and predicted attenuation rates and transmission losses for both modal decomposition and finite element propagation models were in good to excellent agreement for a test frequency range that included the first and second cavity resonance frequencies. This was true for either of two surface impedance distribution modeling procedures used to simplify the impedance boundary conditions. In the presence of mean flow, measurements revealed a fine scale structure of acoustic hot spots in the attenuation and phase profiles. These details were accurately predicted by the finite element model. Since no impedance changes due to mean flow were assumed, it is concluded that this fine scale structure was due to convective effects of the mean flow interacting with the surface impedance nonuniformities.

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.

Estimation of fine-scale recombination intensity variation in the white-echinus interval of D. melanogaster

PubMed Central

Singh, Nadia D.; Aquadro, Charles F.; Clark, Andrew G.

2009-01-01

Accurate assessment of local recombination rate variation is crucial for understanding the recombination process and for determining the impact of natural selection on linked sites. In Drosophila, local recombination intensity has been estimated primarily by statistical approaches, estimating the local slope of the relationship between the physical and genetic maps. However, these estimates are limited in resolution, and as a result, the physical scale at which recombination intensity varies in Drosophila is largely unknown. While there is some evidence suggesting as much as a 40-fold variation in crossover rate at a local scale in D. pseudoobscura, little is known about the fine-scale structure of recombination rate variation in D. melanogaster. Here, we experimentally examine the fine-scale distribution of crossover events in a 1.2 Mb region on the D. melanogaster X chromosome using a classic genetic mapping approach. Our results show that crossover frequency is significantly heterogeneous within this region, varying ~ 3.5 fold. Simulations suggest that this degree of heterogeneity is sufficient to affect levels of standing nucleotide diversity, although the magnitude of this effect is small. We recover no statistical association between empirical estimates of nucleotide diversity and recombination intensity, which is likely due to the limited number of loci sampled in our population genetic dataset. However, codon bias is significantly negatively correlated with fine-scale recombination intensity estimates, as expected. Our results shed light on the relevant physical scale to consider in evolutionary analyses relating to recombination rate, and highlight the motivations to increase the resolution of the recombination map in Drosophila. PMID:19504037

How big should a mammal be? A macroecological look at mammalian body size over space and time

PubMed Central

Smith, Felisa A.; Lyons, S. Kathleen

2011-01-01

Macroecology was developed as a big picture statistical approach to the study of ecology and evolution. By focusing on broadly occurring patterns and processes operating at large spatial and temporal scales rather than on localized and/or fine-scaled details, macroecology aims to uncover general mechanisms operating at organism, population, and ecosystem levels of organization. Macroecological studies typically involve the statistical analysis of fundamental species-level traits, such as body size, area of geographical range, and average density and/or abundance. Here, we briefly review the history of macroecology and use the body size of mammals as a case study to highlight current developments in the field, including the increasing linkage with biogeography and other disciplines. Characterizing the factors underlying the spatial and temporal patterns of body size variation in mammals is a daunting task and moreover, one not readily amenable to traditional statistical analyses. Our results clearly illustrate remarkable regularities in the distribution and variation of mammalian body size across both geographical space and evolutionary time that are related to ecology and trophic dynamics and that would not be apparent without a broader perspective. PMID:21768152

CMAQ MODELING FOR AIR TOXICS AT FINE SCALES: A PROTOTYPE STUDY

EPA Science Inventory

Toxic air pollutants (TAPs) or hazardous air pollutants (HAPs) exhibit considerable spatial and temporal variability across urban areas. Therefore, the ability of chemical transport models (CTMs), e.g. Community Multi-scale Air Quality (CMAQ), to reproduce the spatial and tempor...

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

PubMed Central

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

2014-01-01

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

Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration

USGS Publications Warehouse

Shryock, Daniel F.; Havrilla, Caroline A.; DeFalco, Lesley; Esque, Todd C.; Custer, Nathan; Wood, Troy E.

2015-01-01

Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua, an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.

Terrestrial habitat selection and strong density-dependent mortality in recently metamorphosed amphibians.

PubMed

Patrick, David A; Harper, Elizabeth B; Hunter, Malcolm L; Calhoun, Aram J K

2008-09-01

To predict the effects of terrestrial habitat change on amphibian populations, we need to know how amphibians respond to habitat heterogeneity, and whether habitat choice remains consistent throughout the life-history cycle. We conducted four experiments to evaluate how the spatial distribution of juvenile wood frogs, Rana sylvatica (including both overall abundance and localized density), was influenced by habitat choice and habitat structure, and how this relationship changed with spatial scale and behavioral phase. The four experiments included (1) habitat manipulation on replicated 10-ha landscapes surrounding breeding pools; (2) short-term experiments with individual frogs emigrating through a manipulated landscape of 1 m wide hexagonal patches; and habitat manipulations in (3) small (4-m2); and (4) large (100-m2) enclosures with multiple individuals to compare behavior both during and following emigration. The spatial distribution of juvenile wood frogs following emigration resulted from differences in the scale at which juvenile amphibians responded to habitat heterogeneity during active vs. settled behavioral phases. During emigration, juvenile wood frogs responded to coarse-scale variation in habitat (selection between 2.2-ha forest treatments) but not to fine-scale variation. After settling, however, animals showed habitat selection at much smaller scales (2-4 m2). This resulted in high densities of animals in small patches of suitable habitat where they experienced rapid mortality. No evidence of density-dependent habitat selection was seen, with juveniles typically choosing to remain at extremely high densities in high-quality habitat, rather than occupying low-quality habitat. These experiments demonstrate how prediction of the terrestrial distribution of juvenile amphibians requires understanding of the complex behavioral responses to habitat heterogeneity. Understanding these patterns is important, given that human alterations to amphibian habitats may generate extremely high densities of animals, resulting in high density-dependent mortality.

Multiscale spatial and small-scale temporal variation in the composition of Riverine fish communities.

PubMed

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.

Relaxation of the single-slip condition in strain-gradient plasticity

PubMed Central

Anguige, Keith; Dondl, Patrick W.

2014-01-01

We consider the variational formulation of both geometrically linear and geometrically nonlinear elasto-plasticity subject to a class of hard single-slip conditions. Such side conditions typically render the associated boundary-value problems non-convex. We show that, for a large class of non-smooth plastic distortions, a given single-slip condition (specification of Burgers vectors) can be relaxed by introducing a microstructure through a two-stage process of mollification and lamination. The relaxed model can be thought of as an aid to simulating macroscopic plastic behaviour without the need to resolve arbitrarily fine spatial scales. PMID:25197243

Relaxation of the single-slip condition in strain-gradient plasticity.

PubMed

Anguige, Keith; Dondl, Patrick W

2014-09-08

We consider the variational formulation of both geometrically linear and geometrically nonlinear elasto-plasticity subject to a class of hard single-slip conditions. Such side conditions typically render the associated boundary-value problems non-convex. We show that, for a large class of non-smooth plastic distortions, a given single-slip condition (specification of Burgers vectors) can be relaxed by introducing a microstructure through a two-stage process of mollification and lamination. The relaxed model can be thought of as an aid to simulating macroscopic plastic behaviour without the need to resolve arbitrarily fine spatial scales.

Applying narrowband remote-sensing reflectance models to wideband data.

PubMed

Lee, Zhongping

2009-06-10

Remote sensing of coastal and inland waters requires sensors to have a high spatial resolution to cover the spatial variation of biogeochemical properties in fine scales. High spatial-resolution sensors, however, are usually equipped with spectral bands that are wide in bandwidth (50 nm or wider). In this study, based on numerical simulations of hyperspectral remote-sensing reflectance of optically-deep waters, and using Landsat band specifics as an example, the impact of a wide spectral channel on remote sensing is analyzed. It is found that simple adoption of a narrowband model may result in >20% underestimation in calculated remote-sensing reflectance, and inversely may result in >20% overestimation in inverted absorption coefficients even under perfect conditions, although smaller (approximately 5%) uncertainties are found for higher absorbing waters. These results provide a cautious note, but also a justification for turbid coastal waters, on applying narrowband models to wideband data.

Effects of population succession on demographic and genetic processes: predictions and tests in the daylily Hemerocallis thunbergii (Liliaceae).

PubMed

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

2007-07-01

Spatial genetic structure within plant populations is influenced by variation in demographic processes through space and time, including a population's successional status. To determine how demographic structure and fine-scale genetic structure (FSGS) change with stages in a population's successional history, we studied Hemerocallis thunbergii (Liliaceae), a nocturnal flowering and hawkmoth-pollinated herbaceous perennial with rapid population turnover dynamics. We examined nine populations assigned to three successive stages of population succession: expansion, maturation, and senescence. We developed stage-specific expectations for within-population demographic and genetic structure, and then for each population quantified the spatial aggregation of individuals and genotypes using spatial autocorrelation methods (nonaccumulative O-ring and kinship statistics, respectively), and at the landscape level measured inbreeding and genetic structure using Wright's F-statistics. Analyses using the O-ring statistic revealed significant aggregation of individuals at short spatial scales in expanding and senescing populations, in particular, which may reflect restricted seed dispersal around maternal individuals combined with relatively low local population densities at these stages. Significant FSGS was found for three of four expanding, no mature, and only one senescing population, a pattern generally consistent with expectations of successional processes. Although allozyme genetic diversity was high within populations (mean %P = 78.9 and H(E) = 0.281), landscape-level differentiation among sites was also high (F(ST) = 0.166) and all populations exhibited a significant deficit of heterozygotes relative to Hardy-Weinberg expectations (range F = 0.201-0.424, mean F(IS) = 0.321). Within populations, F was not correlated with the degree of FSGS, thus suggesting inbreeding due primarily to selfing as opposed to mating among close relatives in spatially structured populations. Our results demonstrate considerable variation in the spatial distribution of individuals and patterns and magnitude of FSGS in H. thunbergii populations across the landscape. This variation is generally consistent with succession-stage-specific differences in ecological processes operating within these populations.

Propagule Limitation, Disparate Habitat Quality, and Variation in Phenotypic Selection at a Local Species Range Boundary

PubMed Central

Moore, Kara A.; Stanton, Maureen L.

2014-01-01

Adaptation to novel conditions beyond current range boundaries requires the presence of suitable sites within dispersal range, but may be impeded when emigrants encounter poor habitat and sharply different selection pressures. We investigated fine-scale spatial heterogeneity in ecological dynamics and selection at a local population boundary of the annual plant Gilia tricolor. In two years, we planted G. tricolor seeds in core habitat, margin habitat at the edge of the local range, and exterior habitat in order to measure spatial and temporal variation in habitat quality, opportunity for selection, and selection on phenotypic traits. We found a striking decline in average habitat quality with distance from the population core, yet some migrant seeds were successful in suitable, unoccupied microsites at and beyond the range boundary. Total and direct selection on four out of five measured phenotypic traits varied across habitat zones, as well as between years. Moreover, the margin habitat often exerted unique selection pressures that were not intermediate between core and exterior habitats. This study reveals that a combination of ecological and evolutionary forces, including propagule limitation, variation in habitat quality and spatial heterogeneity in phenotypic selection may reduce opportunities for adaptive range expansion, even across a very local population boundary. PMID:24717472

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

PubMed Central

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

2016-01-01

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

Rooting strategies in a subtropical savanna: a landscape-scale three-dimensional assessment.

PubMed

Zhou, Yong; Boutton, Thomas W; Wu, X Ben; Wright, Cynthia L; Dion, Anais L

2018-04-01

In resource-limited savannas, the distribution and abundance of fine roots play an important role in acquiring essential resources and structuring vegetation patterns and dynamics. However, little is known regarding the three-dimensional distribution of fine roots in savanna ecosystems at the landscape scale. We quantified spatial patterns of fine root density to a depth of 1.2 m in a subtropical savanna landscape using spatially specific sampling. Kriged maps revealed that fine root density was highest at the centers of woody patches, decreased towards the canopy edges, and reached lowest values within the grassland matrix throughout the entire soil profile. Lacunarity analyses indicated that spatial heterogeneities of fine root density decreased continuously to a depth of 50 cm and then increased in deeper portions of the soil profile across this landscape. This vertical pattern might be related to inherent differences in root distribution between trees/shrubs and herbaceous species, and the presence/absence of an argillic horizon across this landscape. The greater density of fine roots beneath woody patches in both upper and lower portions of the soil profile suggests an ability to acquire disproportionately more resources than herbaceous species, which may facilitate the development and persistence of woody patches across this landscape.

Scaling uncertainties in estimating canopy foliar maintenance respiration for black spruce ecosystems in Alaska

USGS Publications Warehouse

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.

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir

PubMed Central

Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-01-01

Background: The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Methods: Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Results: Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. Conclusion: This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies. PMID:26404350

Rare variation facilitates inferences of fine-scale population structure in humans.

PubMed

O'Connor, Timothy D; Fu, Wenqing; Mychaleckyj, Josyf C; Logsdon, Benjamin; Auer, Paul; Carlson, Christopher S; Leal, Suzanne M; Smith, Joshua D; Rieder, Mark J; Bamshad, Michael J; Nickerson, Deborah A; Akey, Joshua M

2015-03-01

Understanding the genetic structure of human populations has important implications for the design and interpretation of disease mapping studies and reconstructing human evolutionary history. To date, inferences of human population structure have primarily been made with common variants. However, recent large-scale resequencing studies have shown an abundance of rare variation in humans, which may be particularly useful for making inferences of fine-scale population structure. To this end, we used an information theory framework and extensive coalescent simulations to rigorously quantify the informativeness of rare and common variation to detect signatures of fine-scale population structure. We show that rare variation affords unique insights into patterns of recent population structure. Furthermore, to empirically assess our theoretical findings, we analyzed high-coverage exome sequences in 6,515 European and African American individuals. As predicted, rare variants are more informative than common polymorphisms in revealing a distinct cluster of European-American individuals, and subsequent analyses demonstrate that these individuals are likely of Ashkenazi Jewish ancestry. Our results provide new insights into the population structure using rare variation, which will be an important factor to account for in rare variant association studies. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Exploring the small-scale spatial distribution of hypertension and its association to area deprivation based on health insurance claims in Northeastern Germany.

PubMed

Kauhl, B; Maier, W; Schweikart, J; Keste, A; Moskwyn, M

2018-01-10

Hypertension is one of the most frequently diagnosed chronic conditions in Germany. Targeted prevention strategies and allocation of general practitioners where they are needed most are necessary to prevent severe complications arising from high blood pressure. However, data on chronic diseases in Germany are mostly available through survey data, which do not only underestimate the actual prevalence but are also only available on coarse spatial scales. The discussion of including area deprivation for planning of healthcare is still relatively young in Germany, although previous studies have shown that area deprivation is associated with adverse health outcomes, irrespective of individual characteristics. The aim of this study is therefore to analyze the spatial distribution of hypertension at very fine geographic scales and to assess location-specific associations between hypertension, socio-demographic population characteristics and area deprivation based on health insurance claims of the AOK Nordost. To visualize the spatial distribution of hypertension prevalence at very fine geographic scales, we used the conditional autoregressive Besag-York-Mollié (BYM) model. Geographically weighted regression modelling (GWR) was applied to analyze the location-specific association of hypertension to area deprivation and further socio-demographic population characteristics. The sex- and age-adjusted prevalence of hypertension was 33.1% in 2012 and varied widely across northeastern Germany. The main risk factors for hypertension were proportions of insurants aged 45-64, 65 and older, area deprivation and proportion of persons commuting to work outside their residential municipality. The GWR model revealed important regional variations in the strength of the examined associations. Area deprivation has only a significant and therefore direct influence in large parts of Mecklenburg-West Pomerania. However, the spatially varying strength of the association between demographic variables and hypertension indicates that there also exists an indirect effect of area deprivation on the prevalence of hypertension. It can therefore be expected that persons ageing in deprived areas will be at greater risk of hypertension, irrespective of their individual characteristics. The future planning and allocation of primary healthcare in northeastern Germany would therefore greatly benefit from considering the effect of area deprivation.

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

PubMed

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

2011-07-01

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

Towards a More Biologically-meaningful Climate Characterization: Variability in Space and Time at Multiple Scales

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.

Modeling habitat for Marbled Murrelets on the Siuslaw National Forest, Oregon, using lidar data

USGS Publications Warehouse

Hagar, Joan C.; Aragon, Ramiro; Haggerty, Patricia; Hollenbeck, Jeff P.

2018-03-28

Habitat models using lidar-derived variables that quantify fine-scale variation in vegetation structure can improve the accuracy of occupancy estimates for canopy-dwelling species over models that use variables derived from other remote sensing techniques. However, the ability of models developed at such a fine spatial scale to maintain accuracy at regional or larger spatial scales has not been tested. We tested the transferability of a lidar-based habitat model for the threatened Marbled Murrelet (Brachyramphus marmoratus) between two management districts within a larger regional conservation zone in coastal western Oregon. We compared the performance of the transferred model against models developed with data from the application location. The transferred model had good discrimination (AUC = 0.73) at the application location, and model performance was further improved by fitting the original model with coefficients from the application location dataset (AUC = 0.79). However, the model selection procedure indicated that neither of these transferred models were considered competitive with a model trained on local data. The new model trained on data from the application location resulted in the selection of a slightly different set of lidar metrics from the original model, but both transferred and locally trained models consistently indicated positive relationships between the probability of occupancy and lidar measures of canopy structural complexity. We conclude that while the locally trained model had superior performance for local application, the transferred model could reasonably be applied to the entire conservation zone.

System and method for the detection of anomalies in an image

DOEpatents

Prasad, Lakshman; Swaminarayan, Sriram

2013-09-03

Preferred aspects of the present invention can include receiving a digital image at a processor; segmenting the digital image into a hierarchy of feature layers comprising one or more fine-scale features defining a foreground object embedded in one or more coarser-scale features defining a background to the one or more fine-scale features in the segmentation hierarchy; detecting a first fine-scale foreground feature as an anomaly with respect to a first background feature within which it is embedded; and constructing an anomalous feature layer by synthesizing spatially contiguous anomalous fine-scale features. Additional preferred aspects of the present invention can include detecting non-pervasive changes between sets of images in response at least in part to one or more difference images between the sets of images.

The relationship between observational scale and explained variance in benthic communities

PubMed Central

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

2018-01-01

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

Clonal growth and fine-scale genetic structure in tanoak (Notholithocarpus densiflorus: Fagaceae)

Treesearch

Richard S. Dodd; Wasima Mayer; Alejandro Nettel; Zara Afzal-Rafii

2013-01-01

The combination of sprouting and reproduction by seed can have important consequences on fine-scale spatial distribution of genetic structure (SGS). SGS is an important consideration for species’ restoration because it determines the minimum distance among seed trees to maximize genetic diversity while not prejudicing locally adapted genotypes. Local environmental...

Deriving spatial trends of air pollution at a neighborhood-scale through mobile monitoring

EPA Science Inventory

Abstract: Measuring air pollution in real-time using an instrumented vehicle platform has been an emerging strategy to resolve air pollution trends at a very fine spatial scale (10s of meters). Achieving second-by-second data representative of urban air quality trends requires a...

Geochemical signature of land-based activities in Caribbean coral surface samples

USGS Publications Warehouse

Prouty, N.G.; Hughen, K.A.; Carilli, J.

2008-01-01

Anthropogenic threats, such as increased sedimentation, agrochemical run-off, coastal development, tourism, and overfishing, are of great concern to the Mesoamerican Caribbean Reef System (MACR). Trace metals in corals can be used to quantify and monitor the impact of these land-based activities. Surface coral samples from the MACR were investigated for trace metal signatures resulting from relative differences in water quality. Samples were analyzed at three spatial scales (colony, reef, and regional) as part of a hierarchical multi-scale survey. A primary goal of the paper is to elucidate the extrapolation of information between fine-scale variation at the colony or reef scale and broad-scale patterns at the regional scale. Of the 18 metals measured, five yielded statistical differences at the colony and/or reef scale, suggesting fine-scale spatial heterogeneity not conducive to regional interpretation. Five metals yielded a statistical difference at the regional scale with an absence of a statistical difference at either the colony or reef scale. These metals are barium (Ba), manganese (Mn), chromium (Cr), copper (Cu), and antimony (Sb). The most robust geochemical indicators of land-based activities are coral Ba and Mn concentrations, which are elevated in samples from the southern region of the Gulf of Honduras relative to those from the Turneffe Islands. These findings are consistent with the occurrence of the most significant watersheds in the MACR from southern Belize to Honduras, which contribute sediment-laden freshwater to the coastal zone primarily as a result of human alteration to the landscape (e.g., deforestation and agricultural practices). Elevated levels of Cu and Sb were found in samples from Honduras and may be linked to industrial shipping activities where copper-antimony additives are commonly used in antifouling paints. Results from this study strongly demonstrate the impact of terrestrial runoff and anthropogenic activities on coastal water quality in the MACR. ?? 2008 Springer-Verlag.

DNA Barcoding Reveals Hidden Diversity of Sand Flies (Diptera: Psychodidae) at Fine and Broad Spatial Scales in Brazilian Endemic Regions for Leishmaniasis.

PubMed

Rodrigues, Bruno Leite; Carvalho-Costa, Luís Fernando; Pinto, Israel de Souza; Rebêlo, José Manuel Macário

2018-03-17

Sand fly (Diptera: Psychodidae) taxonomy is complex and time-consuming, which hampers epidemiological efforts directed toward controlling leishmaniasis in endemic regions such as northeastern Brazil. Here, we used a fragment of the mitochondrial cytochrome c oxidase I (COI) gene to identify sand fly species in Maranhão State (northeastern Brazil) and to assess cryptic diversity occurring at different spatial scales. For this, we obtained 148 COI sequences of 15 sand fly species (10 genera) from Maranhão (fine spatial scale), and joined them to COI sequences from other Brazilian localities (distant about 2,000 km from Maranhão, broad spatial scale) available in GenBank. We revealed cases of cryptic diversity in sand flies both at fine (Lutzomyia longipalpis (Lutz and Neiva) and Evandromyia termitophila (Martins, Falcão and Silva)) and broad spatial scales (Migonemyia migonei (França), Pressatia choti (Floch and Abonnenc), Psychodopygus davisi (Root), Sciopemyia sordellii (Shannon and Del Ponte), and Bichromomyia flaviscutellata (Mangabeira)). We argue that in the case of Bi. flaviscutellata, the cryptic diversity is associated with a putative new species. Cases in which DNA taxonomy was not as effective as morphological identification possibly involved recent speciation and/or introgressive hybridization, highlighting the need for integrative approaches to identify some sand fly species. Finally, we provide the first barcode sequences for four species (Brumptomyia avellari (Costa Lima), Evandromyia infraspinosa (Mangabeira), Evandromyia evandroi (Costa Lima and Antunes), and Psychodopygus complexus (Mangabeira)), which will be useful for further molecular identification of neotropical species.

Spatial variation in diesel-related elemental and organic PM2.5 components during workweek hours across a downtown core.

PubMed

Tunno, Brett J; Shmool, Jessie L C; Michanowicz, Drew R; Tripathy, Sheila; Chubb, Lauren G; Kinnee, Ellen; Cambal, Leah; Roper, Courtney; Clougherty, Jane E

2016-12-15

Capturing intra-urban variation in diesel-related pollution exposures remains a challenge, given its complex chemical mix, and relatively few well-characterized ambient-air tracers for the multiple diesel sources in densely-populated urban areas. To capture fine-scale spatial resolution (50×50m grid cells) in diesel-related pollution, we used geographic information systems (GIS) to systematically allocate 36 sampling sites across downtown Pittsburgh, PA, USA (2.8km 2 ), cross-stratifying to disentangle source impacts (i.e., truck density, bus route frequency, total traffic density). For buses, outbound and inbound trips per week were summed by route and a kernel density was calculated across sites. Programmable monitors collected fine particulate matter (PM 2.5 ) samples specific to workweek hours (Monday-Friday, 7 am-7 pm), summer and winter 2013. Integrated filters were analyzed for black carbon (BC), elemental carbon (EC), organic carbon (OC), elemental constituents, and diesel-related organic compounds [i.e., polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes]. To our knowledge, no studies have collected this suite of pollutants with such high sampling density, with the ability to capture spatial patterns during specific hours of interest. We hypothesized that we would find substantial spatial variation for each pollutant and significant associations with key sources (e.g. diesel and gasoline vehicles), with higher concentrations near the center of this small downtown core. Using a forward stepwise approach, we developed seasonal land use regression (LUR) models for PM 2.5 , BC, total EC, OC, PAHs, hopanes, steranes, aluminum (Al), calcium (Ca), and iron (Fe). Within this small domain, greater concentration differences were observed in most pollutants across sites, on average, than between seasons. Higher PM 2.5 and BC concentrations were found in the downtown core compared to the boundaries. PAHs, hopanes, and steranes displayed different spatial patterning across the study area by constituent. Most LUR models suggested a strong influence of bus-related emissions on pollution gradients. Buses were more dominant predictors compared to truck and vehicular traffic for several pollutants. Overall, we found substantial variation in diesel-related concentrations in a very small downtown area, which varied across elemental and organic components. Copyright © 2016. Published by Elsevier B.V.

Spatial Modeling and Uncertainty Assessment of Fine Scale Surface Processes Based on Coarse Terrain Elevation Data

NASA Astrophysics Data System (ADS)

Rasera, L. G.; Mariethoz, G.; Lane, S. N.

2017-12-01

Frequent acquisition of high-resolution digital elevation models (HR-DEMs) over large areas is expensive and difficult. Satellite-derived low-resolution digital elevation models (LR-DEMs) provide extensive coverage of Earth's surface but at coarser spatial and temporal resolutions. Although useful for large scale problems, LR-DEMs are not suitable for modeling hydrologic and geomorphic processes at scales smaller than their spatial resolution. In this work, we present a multiple-point geostatistical approach for downscaling a target LR-DEM based on available high-resolution training data and recurrent high-resolution remote sensing images. The method aims at generating several equiprobable HR-DEMs conditioned to a given target LR-DEM by borrowing small scale topographic patterns from an analogue containing data at both coarse and fine scales. An application of the methodology is demonstrated by using an ensemble of simulated HR-DEMs as input to a flow-routing algorithm. The proposed framework enables a probabilistic assessment of the spatial structures generated by natural phenomena operating at scales finer than the available terrain elevation measurements. A case study in the Swiss Alps is provided to illustrate the methodology.

Spatial variations of the Sr I 4607 Å scattering polarization peak

NASA Astrophysics Data System (ADS)

Bianda, M.; Berdyugina, S.; Gisler, D.; Ramelli, R.; Belluzzi, L.; Carlin, E. S.; Stenflo, J. O.; Berkefeld, T.

2018-06-01

Context. The scattering polarization signal observed in the photospheric Sr I 4607 Å line is expected to vary at granular spatial scales. This variation can be due to changes in the magnetic field intensity and orientation (Hanle effect), but also to spatial and temporal variations in the plasma properties. Measuring the spatial variation of such polarization signal would allow us to study the properties of the magnetic fields at subgranular scales, but observations are challenging since both high spatial resolution and high spectropolarimetric sensitivity are required. Aims: We aim to provide observational evidence of the polarization peak spatial variations, and to analyze the correlation they might have with granulation. Methods: Observations conjugating high spatial resolution and high spectropolarimetric precision were performed with the Zurich IMaging POLarimeter, ZIMPOL, at the GREGOR solar telescope, taking advantage of the adaptive optics system and the newly installed image derotator. Results: Spatial variations of the scattering polarization in the Sr I 4607 Å line are clearly observed. The spatial scale of these variations is comparable with the granular size. Small correlations between the polarization signal amplitude and the continuum intensity indicate that the polarization is higher at the center of granules than in the intergranular lanes.

Resolving uncertainties in the urban air quality, climate, and vegetation nexus through citizen science, satellite imagery, and atmospheric modeling

NASA Astrophysics Data System (ADS)

Jenerette, D.; Wang, J.; Chandler, M.; Ripplinger, J.; Koutzoukis, S.; Ge, C.; Castro Garcia, L.; Kucera, D.; Liu, X.

2017-12-01

Large uncertainties remain in identifying the distribution of urban air quality and temperature risks across neighborhood to regional scales. Nevertheless, many cities are actively expanding vegetation with an expectation to moderate both climate and air quality risks. We address these uncertainties through an integrated analysis of satellite data, atmospheric modeling, and in-situ environmental sensor networks maintained by citizen scientists. During the summer of 2017 we deployed neighborhood-scale networks of air temperature and ozone sensors through three campaigns across urbanized southern California. During each five-week campaign we deployed six sensor nodes that included an EPA federal equivalent method ozone sensor and a suite of meteorological sensors. Each node was further embedded in a network of 100 air temperature sensors that combined a randomized design developed by the research team and a design co-created by citizen scientists. Between 20 and 60 citizen scientists were recruited for each campaign, with local partners supporting outreach and training to ensure consistent deployment and data gathering. We observed substantial variation in both temperature and ozone concentrations at scales less than 4km, whole city, and the broader southern California region. At the whole city scale the average spatial variation with our ozone sensor network just for city of Long Beach was 26% of the mean, while corresponding variation in air temperature was only 7% of the mean. These findings contrast with atmospheric model estimates of variation at the regional scale of 11% and 1%. Our results show the magnitude of fine-scale variation underestimated by current models and may also suggest scaling functions that can connect neighborhood and regional variation in both ozone and temperature risks in southern California. By engaging citizen science with high quality sensors, satellite data, and real-time forecasting, our results help identify magnitudes of climate and air quality risk variation across scales and can guide individual decisions and urban policies surrounding vegetation to moderate these risks.

Doubly stochastic Poisson process models for precipitation at fine time-scales

NASA Astrophysics Data System (ADS)

Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao

2012-09-01

This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.

Empirical modeling of spatial and temporal variation in warm season nocturnal air temperatures in two North Idaho mountain ranges, USA

Treesearch

Zachery A. Holden; Michael A. Crimmins; Samuel A. Cushman; Jeremy S. Littell

2010-01-01

Accurate, fine spatial resolution predictions of surface air temperatures are critical for understanding many hydrologic and ecological processes. This study examines the spatial and temporal variability in nocturnal air temperatures across a mountainous region of Northern Idaho. Principal components analysis (PCA) was applied to a network of 70 Hobo temperature...

Spatial Variability of Sources and Mixing State of Atmospheric Particles in a Metropolitan Area.

PubMed

Ye, Qing; Gu, Peishi; Li, Hugh Z; Robinson, Ellis S; Lipsky, Eric; Kaltsonoudis, Christos; Lee, Alex K Y; Apte, Joshua S; Robinson, Allen L; Sullivan, Ryan C; Presto, Albert A; Donahue, Neil M

2018-05-30

Characterizing intracity variations of atmospheric particulate matter has mostly relied on fixed-site monitoring and quantifying variability in terms of different bulk aerosol species. In this study, we performed ground-based mobile measurements using a single-particle mass spectrometer to study spatial patterns of source-specific particles and the evolution of particle mixing state in 21 areas in the metropolitan area of Pittsburgh, PA. We selected sampling areas based on traffic density and restaurant density with each area ranging from 0.2 to 2 km 2 . Organics dominate particle composition in all of the areas we sampled while the sources of organics differ. The contribution of particles from traffic and restaurant cooking varies greatly on the neighborhood scale. We also investigate how primary and aged components in particles mix across the urban scale. Lastly we quantify and map the particle mixing state for all areas we sampled and discuss the overall pattern of mixing state evolution and its implications. We find that in the upwind and downwind of the urban areas, particles are more internally mixed while in the city center, particle mixing state shows large spatial heterogeneity that is mostly driven by emissions. This study is to our knowledge, the first study to perform fine spatial scale mapping of particle mixing state using ground-based mobile measurement and single-particle mass spectrometry.

Three-dimensional spatial patterns of soil carbon storage are altered by woody encroachment into grasslands

NASA Astrophysics Data System (ADS)

Zhou, Y.; Boutton, T. W.; Wu, X. B.

2016-12-01

Recent global trends of increasing woody plant abundance in grass-dominated ecosystems may substantially enhance soil organic carbon (SOC) storage and could represent an important carbon (C) sink in the terrestrial environment. However, most studies assessing SOC response to woody encroachment only consider surface soils, and have not explicitly assessed the extent to which deeper portions of the profile may be affected by this phenomenon. Consequently, little is known about the direction, magnitude, and spatial heterogeneity of SOC throughout the soil profile following woody encroachment. These factors were quantified via spatially-specific intensive soil sampling to a depth 1.2 m across a subtropical savanna landscape that has undergone woody proliferation during the past century in southern Texas, USA. Increased SOC sequestration following woody encroachment was observed throughout the profile, albeit at reduced magnitudes at deeper depths. Overall, soils beneath small woody clusters and larger groves accumulated 12.87 and 18.67 Mg C ha-1 more SOC, respectively, to a depth of 1. 2 m compared to grasslands. Recent woody encroachment during the past 100 y significantly altered the spatial pattern and amplified the spatial heterogeneity of SOC at the 0-5 cm depth, with marginal effects at 5-15 cm and no distinct impact on soils below 15 cm. Fine root density explained much of the variation in SOC in the upper 15 cm, while a combination of fine root density and soil clay content accounted for more of the variation in SOC in soils below 15 cm. These findings emphasize the existence of substantial SOC sequestration in deeper portions of the soil profile following woody encroachment. Given the geographical extent of woody encroachment on a global scale, this largely undocumented deep soil C sequestration suggests woody encroachment may play a more significant role in regional and global C sequestration than previously thought.

A three-dimensional spatial mapping approach to quantify fine-scale heterogeneity among leaves within canopies1

PubMed Central

Wingfield, Jenna L.; Ruane, Lauren G.; Patterson, Joshua D.

2017-01-01

Premise of the study: The three-dimensional structure of tree canopies creates environmental heterogeneity, which can differentially influence the chemistry, morphology, physiology, and/or phenology of leaves. Previous studies that subdivide canopy leaves into broad categories (i.e., “upper/lower”) fail to capture the differences in microenvironments experienced by leaves throughout the three-dimensional space of a canopy. Methods: We use a three-dimensional spatial mapping approach based on spherical polar coordinates to examine the fine-scale spatial distributions of photosynthetically active radiation (PAR) and the concentration of ultraviolet (UV)-absorbing compounds (A300) among leaves within the canopies of black mangroves (Avicennia germinans). Results: Linear regressions revealed that interior leaves received less PAR and produced fewer UV-absorbing compounds than leaves on the exterior of the canopy. By allocating more UV-absorbing compounds to the leaves on the exterior of the canopy, black mangroves may be maximizing UV-protection while minimizing biosynthesis of UV-absorbing compounds. Discussion: Three-dimensional spatial mapping provides an inexpensive and portable method to detect fine-scale differences in environmental and biological traits within canopies. We used it to understand the relationship between PAR and A300, but the same approach can also be used to identify traits associated with the spatial distribution of herbivores, pollinators, and pathogens. PMID:29188145

Spatial Patterns of Soil Respiration Links Above and Belowground Processes along a Boreal Aspen Fire Chronosequence

PubMed Central

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

Spatial Patterns of Soil Respiration Links Above and Belowground Processes along a Boreal Aspen Fire Chronosequence.

PubMed

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).

Network analysis reveals multiscale controls on streamwater chemistry

USGS Publications Warehouse

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

2014-01-01

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

Network analysis reveals multiscale controls on streamwater chemistry

PubMed Central

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

2014-01-01

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

Network analysis reveals multiscale controls on streamwater chemistry.

PubMed

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

2014-05-13

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

Variations in Grain-Scale Sediment Structure in a Gravel-Bed Channel as a Function of Fine Sediment Content and Morphological Location

NASA Astrophysics Data System (ADS)

Voepel, H.; Ahmed, S. I.; Hodge, R. A.; Leyland, J.; Sear, D. A.

2016-12-01

One of the major causes of uncertainty in estimates of bedload transport rates in gravel bed rivers is a lack of understanding of grain-scale sediment structure, and the impact that this structure has on bed stability. Furthermore, grain-scale structure varies throughout a channel and over time in ways that have not been fully quantified. Our research aims to quantify variations in sediment structure caused by two key variables; morphological location within a riffle-pool sequence (reflecting variation in hydraulic conditions), and the fine sediment content of the gravel bed (sand and clay). We report results from a series of flume experiments in which we water-worked a gravel bed with a riffle-pool morphology. The fine sediment content of the bed was incrementally increased over a series of runs from gravel only, to coarse sand, fine sand and two concentrations of clay. After each experimental run intact samples of the bed at different locations were extracted and the internal structure of the bed was measured using non-destructive, micro-focus X-ray computed tomography (CT) imaging. The CT images were processed to measure the properties of individual grains, including volume, center of mass, dimension, and contact points. From these data we were able to quantify the sediment structure through metrics including measurement of grain pivot angles, grain exposure and protrusion, and vertical variation in bed porosity and fine sediment content. Metrics derived from the CT data were verified using data from grain counts and tilt-table measurements on co-located samples. Comparison of the metrics across different morphological locations and fine sediment content demonstrates how these factors affect the bed structure. These results have implications for the development of sediment entrainment models for gravel bed rivers.

Demeter-W

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

2017-09-27

Demeter-W, an open-access software written in Python, consists of extensible module packages. It is developed with statistical downscaling algorithms, to spatially and temporally downscale water demand data into finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. For better understanding of the driving forces and patterns for global water withdrawal, the researchers is able to utilize Demeter-W to reconstruct the data sets to examine the issues related to water withdrawals at fine spatial and temporal scales.

Variations in grain-scale sediment structure and entrainment force in a gravel-bed channel as a function of fine sediment content and morphological location

NASA Astrophysics Data System (ADS)

Voepel, Hal; Ahmed, Sharif; Hodge, Rebecca; Leyland, Julian; Sear, David

2017-04-01

One of the major causes of uncertainty in estimates of bedload transport rates in gravel-bed rivers is a lack of understanding of grain-scale sediment structure, and the impact that this structure has on the force required to entrain sediment. There are at least two factors that standard entrainment models do not consider. The first is the way in which the spatial arrangement and orientation of grains and the resultant forces varies throughout a channel and over time, ways that have yet to be fully quantified. The second is that sediment entrainment is a 3D process, yet calculations of entrainment thresholds for sediment grains are typically based on 2D diagrams where we calculate static moments of force vectors about a pivot angle, represented as a single point rather than as a more realistic axis of rotation. Our research addresses these limitations by quantifying variations in 3D sediment structure and entrainment force requirements across two key parameters: morphological location within a riffle-pool sequence (reflecting variation in hydraulic conditions), and the fine sediment content of the gravel-bed (sand and clay). We report results from a series of flume experiments in which we water-worked a gravel-bed with a riffle-pool morphology containing varying amounts of fine sediment. After each experimental run intact samples of the bed at different locations were extracted and the internal structure of the bed was measured using non-destructive, micro-focus X-ray computed tomography (CT) imaging. The CT images were processed to measure the properties of individual grains, including volume, center of mass, dimension, and contact points. From these data we were able to quantify the sediment structure and entrainment force requirements through measurement of 3D metrics including grain pivot angles, grain exposure and protrusion. Comparison of the metrics across different morphological locations and fine sediment content demonstrates how these factors affect the bed structure and entrainment force requirement. These results have implications for the development of sediment entrainment models for gravel-bed rivers. Keywords: fluvial sediment, geomorphology, entrainment models, X-ray computed tomography, 3D imaging, vector mechanics

Fine-scale natal homing and localized movement as shaped by sex and spawning habitat in Chinook salmon: Insights from spatial autocorrelation analysis of individual genotypes

Treesearch

H. M. Neville; D. J. Isaak; J. B. Dunham; R. F. Thurow; B. E. Rieman

2006-01-01

Natal homing is a hallmark of the life history of salmonid fishes, but the spatial scale of homing within local, naturally reproducing salmon populations is still poorly understood. Accurate homing (paired with restricted movement) should lead to the existence of finescale genetic structuring due to the spatial clustering of related individuals on spawning grounds....

Estimation of Actual Crop ET of Paddy Using the Energy Balance Model SMARET and Validation with Field Water Balance Measurements and a Crop Growth Model (ORYZA)

NASA Astrophysics Data System (ADS)

Nallasamy, N. D.; Muraleedharan, B. V.; Kathirvel, K.; Narasimhan, B.

2014-12-01

Sustainable management of water resources requires reliable estimates of actual evapotranspiration (ET) at fine spatial and temporal resolution. This is significant in the case of rice based irrigation systems, one of the major consumers of surface water resources and where ET forms a major component of water consumption. However huge tradeoff in the spatial and temporal resolution of satellite images coupled with lack of adequate number of cloud free images within a growing season act as major constraints in deriving ET at fine spatial and temporal resolution using remote sensing based energy balance models. The scale at which ET is determined is decided by the spatial and temporal scale of Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI), which form inputs to energy balance models. In this context, the current study employed disaggregation algorithms (NL-DisTrad and DisNDVI) to generate time series of LST and NDVI images at fine resolution. The disaggregation algorithms aimed at generating LST and NDVI at finer scale by integrating temporal information from concurrent coarse resolution data and spatial information from a single fine resolution image. The temporal frequency of the disaggregated images is further improved by employing composite images of NDVI and LST in the spatio-temporal disaggregation method. The study further employed half-hourly incoming surface insolation and outgoing long wave radiation obtained from the Indian geostationary satellite (Kalpana-1) to convert the instantaneous ET into daily ET and subsequently to the seasonal ET, thereby improving the accuracy of ET estimates. The estimates of ET were validated with field based water balance measurements carried out in Gadana, a subbasin predominated by rice paddy fields, located in Tamil Nadu, India.

Spatial averaging of a dissipative particle dynamics model for active suspensions

NASA Astrophysics Data System (ADS)

Panchenko, Alexander; Hinz, Denis F.; Fried, Eliot

2018-03-01

Starting from a fine-scale dissipative particle dynamics (DPD) model of self-motile point particles, we derive meso-scale continuum equations by applying a spatial averaging version of the Irving-Kirkwood-Noll procedure. Since the method does not rely on kinetic theory, the derivation is valid for highly concentrated particle systems. Spatial averaging yields stochastic continuum equations similar to those of Toner and Tu. However, our theory also involves a constitutive equation for the average fluctuation force. According to this equation, both the strength and the probability distribution vary with time and position through the effective mass density. The statistics of the fluctuation force also depend on the fine scale dissipative force equation, the physical temperature, and two additional parameters which characterize fluctuation strengths. Although the self-propulsion force entering our DPD model contains no explicit mechanism for aligning the velocities of neighboring particles, our averaged coarse-scale equations include the commonly encountered cubically nonlinear (internal) body force density.

A COMPARISON OF ILLUMINATION GEOMETRY-BASED METHODS FOR TOPOGRAPHIC CORRECTION OF QUICKBIRD IMAGES OF AN UNDULANT AREA

USDA-ARS?s Scientific Manuscript database

The high spatial resolution of QuickBird satellite images makes it possible to show spatial variability at fine details. However, the effect of topography-induced illumination variations become more evident, even in moderately sloped areas. Based on a high resolution (1 m) digital elevation model ge...

2D Fast Vessel Visualization Using a Vessel Wall Mask Guiding Fine Vessel Detection

PubMed Central

Raptis, Sotirios; Koutsouris, Dimitris

2010-01-01

The paper addresses the fine retinal-vessel's detection issue that is faced in diagnostic applications and aims at assisting in better recognizing fine vessel anomalies in 2D. Our innovation relies in separating key visual features vessels exhibit in order to make the diagnosis of eventual retinopathologies easier to detect. This allows focusing on vessel segments which present fine changes detectable at different sampling scales. We advocate that these changes can be addressed as subsequent stages of the same vessel detection procedure. We first carry out an initial estimate of the basic vessel-wall's network, define the main wall-body, and then try to approach the ridges and branches of the vasculature's using fine detection. Fine vessel screening looks into local structural inconsistencies in vessels properties, into noise, or into not expected intensity variations observed inside pre-known vessel-body areas. The vessels are first modelled sufficiently but not precisely by their walls with a tubular model-structure that is the result of an initial segmentation. This provides a chart of likely Vessel Wall Pixels (VWPs) yielding a form of a likelihood vessel map mainly based on gradient filter's intensity and spatial arrangement parameters (e.g., linear consistency). Specific vessel parameters (centerline, width, location, fall-away rate, main orientation) are post-computed by convolving the image with a set of pre-tuned spatial filters called Matched Filters (MFs). These are easily computed as Gaussian-like 2D forms that use a limited range sub-optimal parameters adjusted to the dominant vessel characteristics obtained by Spatial Grey Level Difference statistics limiting the range of search into vessel widths of 16, 32, and 64 pixels. Sparse pixels are effectively eliminated by applying a limited range Hough Transform (HT) or region growing. Major benefits are limiting the range of parameters, reducing the search-space for post-convolution to only masked regions, representing almost 2% of the 2D volume, good speed versus accuracy/time trade-off. Results show the potentials of our approach in terms of time for detection ROC analysis and accuracy of vessel pixel (VP) detection. PMID:20706682

Spurious and functional correlates of the isotopic composition of a generalist across a tropical rainforest landscape

PubMed Central

2009-01-01

Background The isotopic composition of generalist consumers may be expected to vary in space as a consequence of spatial heterogeneity in isotope ratios, the abundance of resources, and competition. We aim to account for the spatial variation in the carbon and nitrogen isotopic composition of a generalized predatory species across a 500 ha. tropical rain forest landscape. We test competing models to account for relative influence of resources and competitors to the carbon and nitrogen isotopic enrichment of gypsy ants (Aphaenogaster araneoides), taking into account site-specific differences in baseline isotope ratios. Results We found that 75% of the variance in the fraction of 15N in the tissue of A. araneoides was accounted by one environmental parameter, the concentration of soil phosphorus. After taking into account landscape-scale variation in baseline resources, the most parsimonious model indicated that colony growth and leaf litter biomass accounted for nearly all of the variance in the δ15N discrimination factor, whereas the δ13C discrimination factor was most parsimoniously associated with colony size and the rate of leaf litter decomposition. There was no indication that competitor density or diversity accounted for spatial differences in the isotopic composition of gypsy ants. Conclusion Across a 500 ha. landscape, soil phosphorus accounted for spatial variation in baseline nitrogen isotope ratios. The δ15N discrimination factor of a higher order consumer in this food web was structured by bottom-up influences - the quantity and decomposition rate of leaf litter. Stable isotope studies on the trophic biology of consumers may benefit from explicit spatial design to account for edaphic properties that alter the baseline at fine spatial grains. PMID:19930701

Habitat degradation and fishing effects on the size structure of coral reef fish communities.

PubMed

Wilson, S K; Fisher, R; Pratchett, M S; Graham, N A J; Dulvy, N K; Turner, R A; Cakacaka, A; Polunin, N V C

2010-03-01

Overfishing and habitat degradation through climate change pose the greatest threats to sustainability of marine resources on coral reefs. We examined how changes in fishing pressure and benthic habitat composition influenced the size spectra of island-scale reef fish communities in Lau, Fiji. Between 2000 and 2006 fishing pressure declined in the Lau Islands due to declining human populations and reduced demand for fresh fish. At the same time, coral cover declined and fine-scale architectural complexity eroded due to coral bleaching and outbreaks of crown-of-thorns starfish, Acanthaster planci. We examined the size distribution of reef fish communities using size spectra analysis, the linearized relationship between abundance and body size class. Spatial variation in fishing pressure accounted for 31% of the variation in the slope of the size spectra in 2000, higher fishing pressure being associated with a steeper slope, which is indicative of fewer large-bodied fish and/or more small-bodied fish. Conversely, in 2006 spatial variation in habitat explained 53% of the variation in the size spectra slopes, and the relationship with fishing pressure was much weaker (approximately 12% of variation) than in 2000. Reduced cover of corals and lower structural complexity was associated with less steep size spectra slopes, primarily due to reduced abundance of fish < 20 cm. Habitat degradation will compound effects of fishing on coral reefs as increased fishing reduces large-bodied target species, while habitat loss results in fewer small-bodied juveniles and prey that replenish stocks and provide dietary resources for predatory target species. Effective management of reef resources therefore depends on both reducing fishing pressure and maintaining processes that encourage rapid recovery of coral habitat.

CONTINUOUS SPATIAL MAPPING FROM VESSELS: RESULTS AND EXPERIENCE USING VARIOUS SENSORS FOR WATER AND SEDIMENTS IN THE GREAT LAKES

EPA Science Inventory

U.S. EPA research has been exploring the use of vessel-towed sensor and underway acoustic technologies in an effort to develop spatial mapping tools and insights for a next generation of Great Lakes monitoring. Technologies allow fine-scale (meters) to meso-scale (100s of kilome...

A hierarchical spatial framework for forest landscape planning.

Treesearch

Pete Bettinger; Marie Lennette; K. Norman Johnson; Thomas A. Spies

2005-01-01

A hierarchical spatial framework for large-scale, long-term forest landscape planning is presented along with example policy analyses for a 560,000 ha area of the Oregon Coast Range. The modeling framework suggests utilizing the detail provided by satellite imagery to track forest vegetation condition and for representation of fine-scale features, such as riparian...

Dynamics of land change in India: a fine-scale spatial analysis

NASA Astrophysics Data System (ADS)

Meiyappan, P.; Roy, P. S.; Sharma, Y.; Jain, A. K.; Ramachandran, R.; Joshi, P. K.

2015-12-01

Land is scarce in India: India occupies 2.4% of worlds land area, but supports over 1/6th of worlds human and livestock population. This high population to land ratio, combined with socioeconomic development and increasing consumption has placed tremendous pressure on India's land resources for food, feed, and fuel. In this talk, we present contemporary (1985 to 2005) spatial estimates of land change in India using national-level analysis of Landsat imageries. Further, we investigate the causes of the spatial patterns of change using two complementary lines of evidence. First, we use statistical models estimated at macro-scale to understand the spatial relationships between land change patterns and their concomitant drivers. This analysis using our newly compiled extensive socioeconomic database at village level (~630,000 units), is 100x higher in spatial resolution compared to existing datasets, and covers over 200 variables. The detailed socioeconomic data enabled the fine-scale spatial analysis with Landsat data. Second, we synthesized information from over 130 survey based case studies on land use drivers in India to complement our macro-scale analysis. The case studies are especially useful to identify unobserved variables (e.g. farmer's attitude towards risk). Ours is the most detailed analysis of contemporary land change in India, both in terms of national extent, and the use of detailed spatial information on land change, socioeconomic factors, and synthesis of case studies.

A variance-decomposition approach to investigating multiscale habitat associations

USGS Publications Warehouse

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

2006-01-01

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

Signatures of Penumbral Magnetic Fields at Very High Spatial Resolution

NASA Astrophysics Data System (ADS)

Langhans, K.

2006-12-01

Full Stokes spectro-polarimetry, together with refined techniques to interpret the measurements and continual modeling efforts, have improved our understanding of sunspot penumbrae in the last years. In spite of this progress, an improvement in the spatial resolution of the observations is clearly needed to establish in a more direct way the fine structure of the penumbra. The discovery of dark penumbral cores by tet{l3 Sc02} suggests that we are starting to resolve the fundamental scales of the penumbra. Spectro-polarimetric measurements that are sensitive to the magnetic field in both the photosphere and higher layers, and obtained at a spatial resolution approaching 0.1 arcsec, may therefore allow us to draw firm conclusions about the fine scale organization of penumbral magnetic fields. In this paper I will discuss recent polarization measurements at very high spatial resolution, trying to reconcile the different scenarios put forward to explain the structure of the penumbra.

Influences of geomorphology and geology on alpine treeline in the American West - More important than climatic influences?

USGS Publications Warehouse

Butler, D.R.; Malanson, G.P.; Walsh, S.J.; Fagre, D.B.

2007-01-01

The spatial distribution and pattern of alpine treeline in the American West reflect the overarching influences of geological history, lithology and structure, and geomorphic processes and landforms, and geologic and geomorphic factors—both forms and processes—can control the spatiotemporal response of the ecotone to climate change. These influences occur at spatial scales ranging from the continental scale to fine scale processes and landforms at the slope scale. Past geomorphic influences, particularly Pleistocene glaciation, have also left their impact on treeline, and treelines across the west are still adjusting to post-Pleistocene conditions within Pleistocene-created landforms. Current fine scale processes include solifluction and changes on relict solifluction and digging by animals. These processes should be examined in detail in future studies to facilitate a better understanding of where individual tree seedlings become established as a primary response of the ecotone to climate change.

Orientation decoding depends on maps, not columns

PubMed Central

Freeman, Jeremy; Brouwer, Gijs Joost; Heeger, David J.; Merriam, Elisha P.

2011-01-01

The representation of orientation in primary visual cortex (V1) has been examined at a fine spatial scale corresponding to the columnar architecture. We present functional magnetic resonance imaging (fMRI) measurements providing evidence for a topographic map of orientation preference in human V1 at a much coarser scale, in register with the angular-position component of the retinotopic map of V1. This coarse-scale orientation map provides a parsimonious explanation for why multivariate pattern analysis methods succeed in decoding stimulus orientation from fMRI measurements, challenging the widely-held assumption that decoding results reflect sampling of spatial irregularities in the fine-scale columnar architecture. Decoding stimulus attributes and cognitive states from fMRI measurements has proven useful for a number of applications, but our results demonstrate that the interpretation cannot assume decoding reflects or exploits columnar organization. PMID:21451017

Temporal and spatial variabilities in the surface moisture content of a fine-grained beach

NASA Astrophysics Data System (ADS)

Namikas, S. L.; Edwards, B. L.; Bitton, M. C. A.; Booth, J. L.; Zhu, Y.

2010-01-01

This study examined spatial and temporal variations in the surface moisture content of a fine-grained beach at Padre Island, Texas, USA. Surface moisture measurements were collected on a 27 × 24 m grid that extended from the dune toe to the upper foreshore. The grid was surveyed at 2 to 4 h intervals for two tidal cycles, generating 17 maps of the spatial distribution of surface moisture. Simultaneous measurements of air temperature and humidity, wind speed and direction, tidal elevation, and water table elevation were used to interpret observed changes in surface moisture. It was found that the spatial distribution of surface moisture was broadly characterized by a cross-shore gradient of high to low content moving landward from the swash zone. The distribution of surface moisture was conceptualized in terms of three zones: saturated (> 25%), intermediate or transitional (5-25%), and dry (< 5%). The position of the saturated zone corresponded to the uppermost swash zone and therefore shifted in accordance with tidal elevation. Moisture contents in the intermediate and dry zones were primarily related to variation in water table depth (which was in turn controlled by tidal elevation) and to a lesser extent by evaporation. Signals associated with atmospheric processes such as evaporation were muted by the minimal degree of variation in atmospheric parameters experienced during most of the study period, but were apparent for the last few hours. The observed spatial and temporal variations in moisture content correspond reasonably well with observations of key controlling processes, but more work is needed to fully characterize this process suite.

Homogenization of the soil surface following fire in semiarid grasslands

Treesearch

Carleton S. White

2011-01-01

Semiarid grasslands accumulate soil beneath plant "islands" that are raised above bare interspaces. This fine-scale variation in microtopographic relief is plant-induced and is increased with shrub establishment. Research found that fire-induced water repellency enhanced local-scale soil erosion that reduced variation in microtopographic relief, suggesting...

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

PubMed Central

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

2015-01-01

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

Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

PubMed Central

Dechesne, Arnaud; Badawi, Nora; Aamand, Jens; Smets, Barth F.

2014-01-01

Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates inter-studies comparisons. However, it is clear that the presence and activity of pesticide degraders is often highly spatially variable with coefficients of variation often exceeding 50% and frequently displays non-random spatial patterns. A few controlling factors have tentatively been identified across pesticide classes: they include some soil characteristics (pH) and some agricultural management practices (pesticide application, tillage), while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance of spatial heterogeneity on the fate of pesticides in soil has been difficult to obtain but modeling and experimental systems that do not include soil's full complexity reveal that this heterogeneity must be considered to improve prediction of pesticide biodegradation rates or of leaching risks. Overall, studying the spatial heterogeneity of pesticide biodegradation is a relatively new field at the interface of agronomy, microbial ecology, and geosciences and a wealth of novel data is being collected from these different disciplinary perspectives. We make suggestions on possible avenues to take full advantage of these investigations for a better understanding and prediction of the fate of pesticides in soil. PMID:25538691

Spatial and temporal variation in vertical migration of dissolved 137Cs passed through the litter layer in Fukushima forests.

PubMed

Kurihara, Momo; Onda, Yuichi; Suzuki, Hiroyuki; Iwasaki, Yuichi; Yasutaka, Tetsuo

2018-05-26

We examined spatial variation in vertical 137 Cs flux from the litter layer using lysimeters combined with copper-substituted Prussian blue in two forests (deciduous broad-leaved and Japanese cedar (Cryptomeria japonica)), approximately 40 km northwest of the Fukushima Daiichi Nuclear power plant. The study ran from August 2016 to February 2017 in three periods; summer (10 Aug-4 Oct), autumn (5 Oct-30 Nov) and winter (1 Dec-27 Feb). Twenty-five and 15 lysimeters were installed in the deciduous broad-leaved and the Japanese cedar sites within 400 and 300 m 2 areas with 3-5 m intervals, respectively. The geometric means of the flux in the deciduous broad-leaved site were 0.51, 0.085 and 0.060 kBq/m 2 /month in summer, autumn and winter periods, respectively. In the Japanese cedar site, the mean fluxes were 0.45, 0.036 and 0.023 kBq/m 2 /month. The ratio of 137 Cs flux during the survey period to litter 137 Cs inventory was 6% and 1% on average in the deciduous broad-leaved and Japanese cedar sites, respectively. The 137 Cs flux in the summer period was much larger than those in other periods, resulting from higher precipitation in the summer. Our fine scale observation with 5 m interval showed very large spatial variation in the 137 Cs flux and the differences between maximum and minimum range from 8 to 104 times, but were mostly 20-25 times. The spatial variations in the 137 Cs flux were affected positively by those in the litter 137 Cs inventory and negatively by canopy openness. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Temporal and spatial variability in thalweg profiles of a gravel-bed river

USGS Publications Warehouse

Madej, Mary Ann

1999-01-01

This study used successive longitudinal thalweg profiles in gravel-bed rivers to monitor changes in bed topography following floods and associated large sediment inputs. Variations in channel bed elevations, distributions of residual water depths, percentage of channel length occupied by riffles, and a spatial autocorrelation coefficient (Moran's I) were used to quantify changes in morphological diversity and spatial structure in Redwood Creek basin, northwestern California. Bed topography in Redwood Creek and its major tributaries consists primarily of a series of pools and riffles. The size, frequency and spatial distribution of the pools and riffles have changed significantly during the past 20 years. Following large floods and high sediment input in Redwood Creek and its tributaries in 1975, variation in channel bed elevations was low and the percentage of the channel length occupied by riffles was high. Over the next 20 years, variation in bed elevations increased while the length of channel occupied by riffles decreased. An index [(standard deviation of residual water depth/bankfull depth) × 100] was developed to compare variations in bed elevation over a range of stream sizes, with a higher index being indicative of greater morphological diversity. Spatial autocorrelation in the bed elevation data was apparent at both fine and coarse scales in many of the thalweg profiles and the observed spatial pattern of bed elevations was found to be related to the dominant channel material and the time since disturbance. River reaches in which forced pools dominated, and in which large woody debris and bed particles could not be easily mobilized, exhibited a random distribution of bed elevations. In contrast, in reaches where alternate bars dominated, and both wood and gravel were readily transported, regularly spaced bed topography developed at a spacing that increased with time since disturbance. This pattern of regularly spaced bed features was reversed following a 12-year flood when bed elevations became more randomly arranged.

A Modeling Framework for Improved Characterization of Near-Road Exposure at Fine Scales

EPA Science Inventory

Traffic-related air pollutants could cause adverse health impact to communities near roadways. To estimate the population risk and locate "hotspots" in the near-road environment, quantifying the exposure at a fine spatial resolution is essential. A new state-of-the-art ...

Fine-scale genetic structure in populations of the Chagas' disease vector Triatoma infestans (Hemiptera, Reduvidae).

PubMed

Pérez de Rosas, Alicia R; Segura, Elsa L; Fusco, Octavio; Guiñazú, Adolfo L Bareiro; García, Beatriz A

2013-03-01

Fine scale patterns of genetic structure and dispersal in Triatoma infestans populations from Argentina was analysed. A total of 314 insects from 22 domestic and peridomestic sites from the locality of San Martín (Capayán department, Catamarca province) were typed for 10 polymorphic microsatellite loci. The results confirm subdivision of T. infestans populations with restricted dispersal among sampling sites and suggest inbreeding and/or stratification within the different domestic and peridomestic structures. Spatial correlation analysis showed that the scale of structuring is approximately of 400 m, indicating that active dispersal would occur within this distance range. It was detected difference in scale of structuring among sexes, with females dispersing over greater distances than males. This study suggests that insecticide treatment and surveillance should be extended within a radius of 400 m around the infested area, which would help to reduce the probability of reinfestation by covering an area of active dispersal. The inferences made from fine-scale spatial genetic structure analyses of T. infestans populations has demonstrated to be important for community-wide control programs, providing a complementary approach to help improve vector control strategies.

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

PubMed

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

2014-08-01

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

Genetic analysis reveals efficient sexual spore dispersal at a fine spatial scale in Armillaria ostoyae, the causal agent of root-rot disease in conifers.

PubMed

Dutech, Cyril; Labbé, Frédéric; Capdevielle, Xavier; Lung-Escarmant, Brigitte

Armillaria ostoyae (sometimes named Armillaria solidipes) is a fungal species causing root diseases in numerous coniferous forests of the northern hemisphere. The importance of sexual spores for the establishment of new disease centres remains unclear, particularly in the large maritime pine plantations of southwestern France. An analysis of the genetic diversity of a local fungal population distributed over 500 ha in this French forest showed genetic recombination between genotypes to be frequent, consistent with regular sexual reproduction within the population. The estimated spatial genetic structure displayed a significant pattern of isolation by distance, consistent with the dispersal of sexual spores mostly at the spatial scale studied. Using these genetic data, we inferred an effective density of reproductive individuals of 0.1-0.3 individuals/ha, and a second moment of parent-progeny dispersal distance of 130-800 m, compatible with the main models of fungal spore dispersal. These results contrast with those obtained for studies of A. ostoyae over larger spatial scales, suggesting that inferences about mean spore dispersal may be best performed at fine spatial scales (i.e. a few kilometres) for most fungal species. Copyright © 2017 British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Aerosol properties over the western Mediterranean basin: temporal and spatial variability

NASA Astrophysics Data System (ADS)

Lyamani, H.; Valenzuela, A.; Perez-Ramirez, D.; Toledano, C.; Granados-Muñoz, M. J.; Olmo, F. J.; Alados-Arboledas, L.

2015-03-01

This study focuses on the analysis of Aerosol Robotic Network (AERONET) aerosol data obtained over Alborán Island (35.90° N, 3.03° W, 15 m a.s.l.) in the western Mediterranean from July 2011 to January 2012. Additional aerosol data from the three nearest AERONET stations (Málaga, Oujda and Palma de Mallorca) and the Maritime Aerosol Network (MAN) were also analyzed in order to investigate the temporal and spatial variations of aerosol over this scarcely explored region. High aerosol loads over Alborán were mainly associated with desert dust transport from North Africa and occasional advection of anthropogenic fine particles from central European urban-industrial areas. The fine particle load observed over Alborán was surprisingly similar to that obtained over the other three nearest AERONET stations, suggesting homogeneous spatial distribution of fine particle loads over the four studied sites in spite of the large differences in local sources. The results from MAN acquired over the Mediterranean Sea, Black Sea and Atlantic Ocean from July to November 2011 revealed a pronounced predominance of fine particles during the cruise period.

Effects of Fine-Scale Landscape Variability on Satellite-Derived Land Surface Temperature Products Over Sparse Vegetation Canopies

NASA Astrophysics Data System (ADS)

Powell, R. L.; Goulden, M.; Peterson, S.; Roberts, D. A.; Still, C. J.

2015-12-01

Temperature is a primary environmental control on biological systems and processes at a range of spatial and temporal scales, from controlling biochemical processes such as photosynthesis to influencing continental-scale species distribution. The Landsat satellite series provides a long record (since the mid-1980s) of relatively high spatial resolution thermal infrared (TIR) imagery, from which we derive land surface temperature (LST) grids. Here, we investigate fine spatial resolution factors that influence Landsat-derived LST over a spectrally and spatially heterogeneous landscape. We focus on paired sites (inside/outside a 1994 fire scar) within a pinyon-juniper scrubland in Southern California. The sites have nearly identical micro-meteorology and vegetation species composition, but distinctly different vegetation abundance and structure. The tower at the unburned site includes a number of in-situ imaging tools to quantify vegetation properties, including a thermal camera on a pan-tilt mount, allowing hourly characterization of landscape component temperatures (e.g., sunlit canopy, bare soil, leaf litter). We use these in-situ measurements to assess the impact of fine-scale landscape heterogeneity on estimates of LST, including sensitivity to (i) the relative abundance of component materials, (ii) directional effects due to solar and viewing geometry, (iii) duration of sunlit exposure for each compositional type, and (iv) air temperature. To scale these properties to Landsat spatial resolution (~100-m), we characterize the sub-pixel composition of landscape components (in addition to shade) by applying spectral mixture analysis (SMA) to the Landsat Operational Land Imager (OLI) spectral bands and test the sensitivity of the relationships established with the in-situ data at this coarser scale. The effects of vegetation abundance and cover height versus other controls on satellite-derived estimates of LST will be assessed by comparing estimates at the burned vs. unburned sites across multiple seasons (~30 dates).

Modeling dynamics of western juniper under climate change in a semiarid ecosystem

NASA Astrophysics Data System (ADS)

Shrestha, R.; Glenn, N. F.; Flores, A. N.

2013-12-01

Modeling future vegetation dynamics in response to climate change and disturbances such as fire relies heavily on model parameterization. Fine-scale field-based measurements can provide the necessary parameters for constraining models at a larger scale. But the time- and labor-intensive nature of field-based data collection leads to sparse sampling and significant spatial uncertainties in retrieved parameters. In this study we quantify the fine-scale carbon dynamics and uncertainty of juniper woodland in the Reynolds Creek Experimental Watershed (RCEW) in southern Idaho, which is a proposed critical zone observatory (CZO) site for soil carbon processes. We leverage field-measured vegetation data along with airborne lidar and timeseries Landsat imagery to initialize a state-and-transition model (VDDT) and a process-based fire-model (FlamMap) to examine the vegetation dynamics in response to stochastic fire events and climate change. We utilize recently developed and novel techniques to measure biomass and canopy characteristics of western juniper at the individual tree scale using terrestrial and airborne laser scanning techniques in RCEW. These fine-scale data are upscaled across the watershed for the VDDT and FlamMap models. The results will immediately improve our understanding of fine-scale dynamics and carbon stocks and fluxes of woody vegetation in a semi-arid ecosystem. Moreover, quantification of uncertainty will also provide a basis for generating ensembles of spatially-explicit alternative scenarios to guide future land management decisions in the region.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Hi-C First Results

NASA Technical Reports Server (NTRS)

Cirtain, Jonathan

2013-01-01

Hi-C obtained the highest spatial and temporal resolution observatoins ever taken in the solar corona. Hi-C reveals dynamics and structure at the limit of its temporal and spatial resolution. Hi-C observed ubiquitous fine-scale flows consistent with the local sound speed.

Coevolution of languages and genes on the island of Sumba, eastern Indonesia.

PubMed

Lansing, J Stephen; Cox, Murray P; Downey, Sean S; Gabler, Brandon M; Hallmark, Brian; Karafet, Tatiana M; Norquest, Peter; Schoenfelder, John W; Sudoyo, Herawati; Watkins, Joseph C; Hammer, Michael F

2007-10-09

Numerous studies indicate strong associations between languages and genes among human populations at the global scale, but all broader scale genetic and linguistic patterns must arise from processes originating at the community level. We examine linguistic and genetic variation in a contact zone on the eastern Indonesian island of Sumba, where Neolithic Austronesian farming communities settled and began interacting with aboriginal foraging societies approximately 3,500 years ago. Phylogenetic reconstruction based on a 200-word Swadesh list sampled from 29 localities supports the hypothesis that Sumbanese languages derive from a single ancestral Austronesian language. However, the proportion of cognates (words with a common origin) traceable to Proto-Austronesian (PAn) varies among language subgroups distributed across the island. Interestingly, a positive correlation was found between the percentage of Y chromosome lineages that derive from Austronesian (as opposed to aboriginal) ancestors and the retention of PAn cognates. We also find a striking correlation between the percentage of PAn cognates and geographic distance from the site where many Sumbanese believe their ancestors arrived on the island. These language-gene-geography correlations, unprecedented at such a fine scale, imply that historical patterns of social interaction between expanding farmers and resident hunter-gatherers largely explain community-level language evolution on Sumba. We propose a model to explain linguistic and demographic coevolution at fine spatial and temporal scales.

Species Associations in a Species-Rich Subtropical Forest Were Not Well-Explained by Stochastic Geometry of Biodiversity

PubMed Central

Wang, Qinggang; Bao, Dachuan; Guo, Yili; Lu, Junmeng; Lu, Zhijun; Xu, Yaozhan; Zhang, Kuihan; Liu, Haibo; Meng, Hongjie; Jiang, Mingxi; Qiao, Xiujuan; Huang, Handong

2014-01-01

The stochastic dilution hypothesis has been proposed to explain species coexistence in species-rich communities. The relative importance of the stochastic dilution effects with respect to other effects such as competition and habitat filtering required to be tested. In this study, using data from a 25-ha species-rich subtropical forest plot with a strong topographic structure at Badagongshan in central China, we analyzed overall species associations and fine-scale species interactions between 2,550 species pairs. The result showed that: (1) the proportion of segregation in overall species association analysis at 2 m neighborhood in this plot followed the prediction of the stochastic dilution hypothesis that segregations should decrease with species richness but that at 10 m neighborhood was higher than the prediction. (2) The proportion of no association type was lower than the expectation of stochastic dilution hypothesis. (3) Fine-scale species interaction analyses using Heterogeneous Poisson processes as null models revealed a high proportion (47%) of significant species effects. However, the assumption of separation of scale of this method was not fully met in this plot with a strong fine-scale topographic structure. We also found that for species within the same families, fine-scale positive species interactions occurred more frequently and negative ones occurred less frequently than expected by chance. These results suggested effects of environmental filtering other than species interaction in this forest. (4) We also found that arbor species showed a much higher proportion of significant fine-scale species interactions (66%) than shrub species (18%). We concluded that the stochastic dilution hypothesis only be partly supported and environmental filtering left discernible spatial signals in the spatial associations between species in this species-rich subtropical forest with a strong topographic structure. PMID:24824996

Species associations in a species-rich subtropical forest were not well-explained by stochastic geometry of biodiversity.

PubMed

Wang, Qinggang; Bao, Dachuan; Guo, Yili; Lu, Junmeng; Lu, Zhijun; Xu, Yaozhan; Zhang, Kuihan; Liu, Haibo; Meng, Hongjie; Jiang, Mingxi; Qiao, Xiujuan; Huang, Handong

2014-01-01

The stochastic dilution hypothesis has been proposed to explain species coexistence in species-rich communities. The relative importance of the stochastic dilution effects with respect to other effects such as competition and habitat filtering required to be tested. In this study, using data from a 25-ha species-rich subtropical forest plot with a strong topographic structure at Badagongshan in central China, we analyzed overall species associations and fine-scale species interactions between 2,550 species pairs. The result showed that: (1) the proportion of segregation in overall species association analysis at 2 m neighborhood in this plot followed the prediction of the stochastic dilution hypothesis that segregations should decrease with species richness but that at 10 m neighborhood was higher than the prediction. (2) The proportion of no association type was lower than the expectation of stochastic dilution hypothesis. (3) Fine-scale species interaction analyses using Heterogeneous Poisson processes as null models revealed a high proportion (47%) of significant species effects. However, the assumption of separation of scale of this method was not fully met in this plot with a strong fine-scale topographic structure. We also found that for species within the same families, fine-scale positive species interactions occurred more frequently and negative ones occurred less frequently than expected by chance. These results suggested effects of environmental filtering other than species interaction in this forest. (4) We also found that arbor species showed a much higher proportion of significant fine-scale species interactions (66%) than shrub species (18%). We concluded that the stochastic dilution hypothesis only be partly supported and environmental filtering left discernible spatial signals in the spatial associations between species in this species-rich subtropical forest with a strong topographic structure.

Multi-scale spatial controls of understory vegetation in Douglas-fir–western hemlock forests of western Oregon, USA

Treesearch

Julia I. Burton; Lisa M. Ganio; Klaus J. Puettmann

2014-01-01

Forest understory vegetation is influenced by broad-scale variation in climate, intermediate scale variation in topography, disturbance and neighborhood interactions. However, little is known about how these multi-scale controls interact to influence observed spatial patterns. We examined relationships between the aggregated cover of understory plant species (%...

Linking complex forest fuel structure and fire behavior at fine scales

Treesearch

EL Loudermilk; Joseph O' Brien; RJ Mitchell; JK Hiers; WP Cropper; S Grunwald; J Grego; J Fernandez

2012-01-01

Improved fire management of savannas and open woodlands requires better understanding of the fundamental connection between fuel heterogeneity, variation in fire behaviour and the influence of fire variation on vegetation feedbacks. In this study, we introduce a novel approach to predicting fire behaviour at the submetre scale, including measurements of forest...

Unmanned Aircraft Systems for Studying Spatial Abundance of Ungulates: Relevance to Spatial Epidemiology

PubMed Central

Barasona, José A.; Mulero-Pázmány, Margarita; Acevedo, Pelayo; Negro, Juan J.; Torres, María J.; Gortázar, Christian; Vicente, Joaquín

2014-01-01

Complex ecological and epidemiological systems require multidisciplinary and innovative research. Low cost unmanned aircraft systems (UAS) can provide information on the spatial pattern of hosts’ distribution and abundance, which is crucial as regards modelling the determinants of disease transmission and persistence on a fine spatial scale. In this context we have studied the spatial epidemiology of tuberculosis (TB) in the ungulate community of Doñana National Park (South-western Spain) by modelling species host (red deer, fallow deer and cattle) abundance at fine spatial scale. The use of UAS high-resolution images has allowed us to collect data to model the environmental determinants of host abundance, and in a further step to evaluate their relationships with the spatial risk of TB throughout the ungulate community. We discuss the ecological, epidemiological and logistic conditions under which UAS may contribute to study the wildlife/livestock sanitary interface, where the spatial aggregation of hosts becomes crucial. These findings are relevant for planning and implementing research, fundamentally when managing disease in multi-host systems, and focusing on risky areas. Therefore, managers should prioritize the implementation of control strategies to reduce disease of conservation, economic and social relevance. PMID:25551673

Fine-scale spatio-temporal variation in tiger Panthera tigris diet: Effect of study duration and extent on estimates of tiger diet in Chitwan National Park, Nepal

USGS Publications Warehouse

Kapfer, Paul M.; Streby, Henry M.; Gurung, B.; Simcharoen, A.; McDougal, C.C.; Smith, J.L.D.

2011-01-01

Attempts to conserve declining tiger Panthera tigris populations and distributions have experienced limited success. The poaching of tiger prey is a key threat to tiger persistence; a clear understanding of tiger diet is a prerequisite to conserve dwindling populations. We used unpublished data on tiger diet in combination with two previously published studies to examine fine-scale spatio-temporal changes in tiger diet relative to prey abundance in Chitwan National Park, Nepal, and aggregated data from the three studies to examine the effect that study duration and the size of the study area have on estimates of tiger diet. Our results correspond with those of previous studies: in all three studies, tiger diet was dominated by members of Cervidae; small to medium-sized prey was important in one study. Tiger diet was unrelated to prey abundance, and the aggregation of studies indicates that increasing study duration and study area size both result in increased dietary diversity in terms of prey categories consumed, and increasing study duration changed which prey species contributed most to tiger diet. Based on our results, we suggest that managers focus their efforts on minimizing the poaching of all tiger prey, and that future studies of tiger diet be of long duration and large spatial extent to improve our understanding of spatio-temporal variation in estimates of tiger diet. ?? 2011 Wildlife Biology, NKV.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

A global Fine-Root Ecology Database to address below-ground challenges in plant ecology

DOE PAGES

Iversen, Colleen M.; McCormack, M. Luke; Powell, A. Shafer; ...

2017-02-28

Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. And while fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of rootmore » traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. There has been a continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time.« less

A global Fine-Root Ecology Database to address below-ground challenges in plant ecology

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

Iversen, Colleen M.; McCormack, M. Luke; Powell, A. Shafer

Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. And while fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of rootmore » traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. There has been a continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time.« less

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

NASA Astrophysics Data System (ADS)

DeBeer, Chris M.; Pomeroy, John W.

2017-10-01

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

Building a better foundation: improving root-trait measurements to understand and model plant and ecosystem processes

DOE PAGES

McCormack, M. Luke; Guo, Dali; Iversen, Colleen M.; ...

2017-03-13

Trait-based approaches provide a useful framework to investigate plant strategies for resource acquisition, growth, and competition, as well as plant impacts on ecosystem processes. Despite significant progress capturing trait variation within and among stems and leaves, identification of trait syndromes within fine-root systems and between fine roots and other plant organs is limited. Here we discuss three underappreciated areas where focused measurements of fine-root traits can make significant contributions to ecosystem science. These include assessment of spatiotemporal variation in fine-root traits, integration of mycorrhizal fungi into fine-root-trait frameworks, and the need for improved scaling of traits measured on individual rootsmore » to ecosystem-level processes. Progress in each of these areas is providing opportunities to revisit how below-ground processes are represented in terrestrial biosphere models. Targeted measurements of fine-root traits with clear linkages to ecosystem processes and plant responses to environmental change are strongly needed to reduce empirical and model uncertainties. Further identifying how and when suites of root and whole-plant traits are coordinated or decoupled will ultimately provide a powerful tool for modeling plant form and function at local and global scales.« less

Building a better foundation: improving root-trait measurements to understand and model plant and ecosystem processes

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

McCormack, M. Luke; Guo, Dali; Iversen, Colleen M.

Trait-based approaches provide a useful framework to investigate plant strategies for resource acquisition, growth, and competition, as well as plant impacts on ecosystem processes. Despite significant progress capturing trait variation within and among stems and leaves, identification of trait syndromes within fine-root systems and between fine roots and other plant organs is limited. Here we discuss three underappreciated areas where focused measurements of fine-root traits can make significant contributions to ecosystem science. These include assessment of spatiotemporal variation in fine-root traits, integration of mycorrhizal fungi into fine-root-trait frameworks, and the need for improved scaling of traits measured on individual rootsmore » to ecosystem-level processes. Progress in each of these areas is providing opportunities to revisit how below-ground processes are represented in terrestrial biosphere models. Targeted measurements of fine-root traits with clear linkages to ecosystem processes and plant responses to environmental change are strongly needed to reduce empirical and model uncertainties. Further identifying how and when suites of root and whole-plant traits are coordinated or decoupled will ultimately provide a powerful tool for modeling plant form and function at local and global scales.« less

Intra-annual variation in turbidity in response to terrestrial runoff on near-shore coral reefs of the Great Barrier Reef

NASA Astrophysics Data System (ADS)

Fabricius, Katharina E.; De'ath, Glenn; Humphrey, Craig; Zagorskis, Irena; Schaffelke, Britta

2013-01-01

Seawater turbidity is a fundamental driver of the ecology of coastal marine systems, and is widely used as indicator for environmental reporting. However, the time scales and processes leading to changes in turbidity in tropical coastal waters remain poorly understood. This study investigates the main determinants of inshore turbidity in four inshore regions along ˜1000 km of the Australian Great Barrier Reef, based on ˜3 years of almost continuous in situ turbidity logger data on 14 reefs. Generalized additive mixed models were used to predict spatial and temporal variation in weekly mean turbidity based on variation in resuspension and runoff conditions. At any given wave height, wave period and tidal range, turbidity was significantly affected by river flow and rainfall. Averaged across all reefs, turbidity was 13% lower (range: 5-37%) in weeks with low compared with high rainfall and river flows. Additionally, turbidity was on average 43% lower 250 days into the dry season than at the start of the dry season on reefs with long-term mean turbidity >1.1 NTU. The data suggest the time scale of winnowing or consolidation of newly imported materials in this zone is months to years. In contrast, turbidity returned to low levels within weeks after river flows and rainfall on reefs with long-term mean turbidity of <1.1 NTU. Turbidity was also up to 10-fold higher on reefs near compared to away from river mouths, suggesting inter-annual accumulation of fine resuspendible sediments. The study suggests that a reduction in the river loads of fine sediments and nutrients through improved land management should lead to measurably improved inshore water clarity in the most turbid parts of the GBR.

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Bhaskar, A.; Fleming, B.; Hogan, D. M.

2016-12-01

Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach including characterizing urban vegetation and storm water management features and their impact on watershed scale hydrology and biogeochemical cycling.

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Burke, W.; Tague, C.

2017-12-01

Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach including characterizing urban vegetation and storm water management features and their impact on watershed scale hydrology and biogeochemical cycling.

Spatial Structure of Seagrass Suggests That Size-Dependent Plant Traits Have a Strong Influence on the Distribution and Maintenance of Tropical Multispecies Meadows

PubMed Central

Ooi, Jillian L. S.; Van Niel, Kimberly P.; Kendrick, Gary A.; Holmes, Karen W.

2014-01-01

Background Seagrass species in the tropics occur in multispecies meadows. How these meadows are maintained through species co-existence and what their ecological drivers may be has been an overarching question in seagrass biogeography. In this study, we quantify the spatial structure of four co-existing species and infer potential ecological processes from these structures. Methods and Results Species presence/absence data were collected using underwater towed and dropped video cameras in Pulau Tinggi, Malaysia. The geostatistical method, utilizing semivariograms, was used to describe the spatial structure of Halophila spp, Halodule uninervis, Syringodium isoetifolium and Cymodocea serrulata. Species had spatial patterns that were oriented in the along-shore and across-shore directions, nested with larger species in meadow interiors, and consisted of multiple structures that indicate the influence of 2–3 underlying processes. The Linear Model of Coregionalization (LMC) was used to estimate the amount of variance contributing to the presence of a species at specific spatial scales. These distances were <2.5 m (micro-scale), 2.5–50 m (fine-scale) and >50 m (broad-scale) in the along-shore; and <2.5 m (micro-scale), 2.5–140 m (fine-scale) and >140 m (broad-scale) in the across-shore. The LMC suggests that smaller species (Halophila spp and H. uninervis) were most influenced by broad-scale processes such as hydrodynamics and water depth whereas large, localised species (S. isoetifolium and C. serrulata) were more influenced by finer-scale processes such as sediment burial, seagrass colonization and growth, and physical disturbance. Conclusion In this study, we provide evidence that spatial structure is distinct even when species occur in well-mixed multispecies meadows, and we suggest that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical marine plant communities. This study offers a contrast from previous spatial models of seagrasses which have largely focused on monospecific temperate meadows. PMID:24497978

Spatial structure of seagrass suggests that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical multispecies meadows.

PubMed

Ooi, Jillian L S; Van Niel, Kimberly P; Kendrick, Gary A; Holmes, Karen W

2014-01-01

Seagrass species in the tropics occur in multispecies meadows. How these meadows are maintained through species co-existence and what their ecological drivers may be has been an overarching question in seagrass biogeography. In this study, we quantify the spatial structure of four co-existing species and infer potential ecological processes from these structures. Species presence/absence data were collected using underwater towed and dropped video cameras in Pulau Tinggi, Malaysia. The geostatistical method, utilizing semivariograms, was used to describe the spatial structure of Halophila spp, Halodule uninervis, Syringodium isoetifolium and Cymodocea serrulata. Species had spatial patterns that were oriented in the along-shore and across-shore directions, nested with larger species in meadow interiors, and consisted of multiple structures that indicate the influence of 2-3 underlying processes. The Linear Model of Coregionalization (LMC) was used to estimate the amount of variance contributing to the presence of a species at specific spatial scales. These distances were <2.5 m (micro-scale), 2.5-50 m (fine-scale) and >50 m (broad-scale) in the along-shore; and <2.5 m (micro-scale), 2.5-140 m (fine-scale) and >140 m (broad-scale) in the across-shore. The LMC suggests that smaller species (Halophila spp and H. uninervis) were most influenced by broad-scale processes such as hydrodynamics and water depth whereas large, localised species (S. isoetifolium and C. serrulata) were more influenced by finer-scale processes such as sediment burial, seagrass colonization and growth, and physical disturbance. In this study, we provide evidence that spatial structure is distinct even when species occur in well-mixed multispecies meadows, and we suggest that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical marine plant communities. This study offers a contrast from previous spatial models of seagrasses which have largely focused on monospecific temperate meadows.

Local shifts in floral biotic interactions in habitat edges and their effect on quantity and quality of plant offspring

PubMed Central

Fenu, Giuseppe; Bernardo, Liliana

2017-01-01

Abstract Spatial shifts in insect fauna due to ecological heterogeneity can severely constrain plant reproduction. Nonetheless, data showing effects of insect visit patterns and intensity of mutualistic and/or antagonistic plant–insect interactions on plant reproduction over structured ecological gradients remain scarce. We investigated how changes in flower-visitor abundance, identity and behaviour over a forest-open habitat gradient affect plant biotic interactions, and quantitative and qualitative fitness in the edge-specialist Dianthus balbisii. Composition and behaviour of the insects visiting flowers of D. balbisii strongly varied over the study gradient, influencing strength and patterns of plant biotic interactions (i.e. herbivory and pollination likelihood). Seed set comparison in free- and manually pollinated flowers suggested spatial variations in the extent of quantitative pollen limitation, which appeared more pronounced at the gradient extremes. Such variations were congruent to patterns of flower visit and plant biotic interactions. The analyses on seed and seedling viability evidenced that spatial variation in amount and type of pollinators, and frequency of herbivory affected qualitative fitness of D. balbisii by influencing selfing and outcrossing rates. Our work emphasizes the role of plant biotic interactions as a fine-scale mediator of plant fitness in ecotones, highlighting that optimal plant reproduction can take place into a restricted interval of the ecological gradients occurring at forest edges. Reducing the habitat complexity typical of such transition contexts can threat edge-adapted plants. PMID:28775831

Application of ground-based LIDAR for fine-scale forest fuel modeling

Treesearch

E. Louise Loudermilk; Abhinav Singhania; Juan C. Fernandez; J. Kevin Hiers; Joseph J. O' Brien; Wendell P. Cropper Jr.; K. Clint Slatton; Robert J. Mitchell

2007-01-01

Frequent (1 to 5 year) low intensity fire regimes of longleaf pine (Pinus palustris) savannas of the Southeastern United States create a continuous fuelbed of understory grasses, forbs, flammable pine needle litter, with interstitial hardwood shrubs. Measuring the spatial heterogeneity of these fine-fuels can be difficult, requiring intensive field...

Disaggregation of remotely sensed soil moisture under all sky condition using machine learning approach in Northeast Asia

NASA Astrophysics Data System (ADS)

Kim, S.; Kim, H.; Choi, M.; Kim, K.

2016-12-01

Estimating spatiotemporal variation of soil moisture is crucial to hydrological applications such as flood, drought, and near real-time climate forecasting. Recent advances in space-based passive microwave measurements allow the frequent monitoring of the surface soil moisture at a global scale and downscaling approaches have been applied to improve the spatial resolution of passive microwave products available at local scale applications. However, most downscaling methods using optical and thermal dataset, are valid only in cloud-free conditions; thus renewed downscaling method under all sky condition is necessary for the establishment of spatiotemporal continuity of datasets at fine resolution. In present study Support Vector Machine (SVM) technique was utilized to downscale a satellite-based soil moisture retrievals. The 0.1 and 0.25-degree resolution of daily Land Parameter Retrieval Model (LPRM) L3 soil moisture datasets from Advanced Microwave Scanning Radiometer 2 (AMSR2) were disaggregated over Northeast Asia in 2015. Optically derived estimates of surface temperature (LST), normalized difference vegetation index (NDVI), and its cloud products were obtained from MODerate Resolution Imaging Spectroradiometer (MODIS) for the purpose of downscaling soil moisture in finer resolution under all sky condition. Furthermore, a comparison analysis between in situ and downscaled soil moisture products was also conducted for quantitatively assessing its accuracy. Results showed that downscaled soil moisture under all sky condition not only preserves the quality of AMSR2 LPRM soil moisture at 1km resolution, but also attains higher spatial data coverage. From this research we expect that time continuous monitoring of soil moisture at fine scale regardless of weather conditions would be available.

The influence of topographic and dynamic cyclic variables on the distribution of small cetaceans in a shallow coastal system.

PubMed

de Boer, Marijke N; Simmonds, Mark P; Reijnders, Peter J H; Aarts, Geert

2014-01-01

The influence of topographic and temporal variables on cetacean distribution at a fine-scale is still poorly understood. To study the spatial and temporal distribution of harbour porpoise Phocoena phocoena and the poorly known Risso's dolphin Grampus griseus we carried out land-based observations from Bardsey Island (Wales, UK) in summer (2001-2007). Using Kernel analysis and Generalized Additive Models it was shown that porpoises and Risso's appeared to be linked to topographic and dynamic cyclic variables with both species using different core areas (dolphins to the West and porpoises to the East off Bardsey). Depth, slope and aspect and a low variation in current speed (for Risso's) were important in explaining the patchy distributions for both species. The prime temporal conditions in these shallow coastal systems were related to the tidal cycle (Low Water Slack and the flood phase), lunar cycle (a few days following the neap tidal phase), diel cycle (afternoons) and seasonal cycle (peaking in August) but differed between species on a temporary but predictable basis. The measure of tidal stratification was shown to be important. Coastal waters generally show a stronger stratification particularly during neap tides upon which the phytoplankton biomass at the surface rises reaching its maximum about 2-3 days after neap tide. It appeared that porpoises occurred in those areas where stratification is maximised and Risso's preferred more mixed waters. This fine-scale study provided a temporal insight into spatial distribution of two species that single studies conducted over broader scales (tens or hundreds of kilometers) do not achieve. Understanding which topographic and cyclic variables drive the patchy distribution of porpoises and Risso's in a Headland/Island system may form the initial basis for identifying potentially critical habitats for these species.

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

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

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

2007-01-01

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

Pollen-mediated gene flow and fine-scale spatial genetic structure in Olea europaea subsp. europaea var. sylvestris

PubMed Central

Piotti, A.; Satovic, Z.; de la Rosa, R.; Belaj, A.

2017-01-01

Abstract Background and Aims Wild olive (Olea europaea subsp. europaea var. sylvestris) is important from an economic and ecological point of view. The effects of anthropogenic activities may lead to the genetic erosion of its genetic patrimony, which has high value for breeding programmes. In particular, the consequences of the introgression from cultivated stands are strongly dependent on the extent of gene flow and therefore this work aims at quantitatively describing contemporary gene flow patterns in wild olive natural populations. Methods The studied wild population is located in an undisturbed forest, in southern Spain, considered one of the few extant hotspots of true oleaster diversity. A total of 225 potential father trees and seeds issued from five mother trees were genotyped by eight microsatellite markers. Levels of contemporary pollen flow, in terms of both pollen immigration rates and within-population dynamics, were measured through paternity analyses. Moreover, the extent of fine-scale spatial genetic structure (SGS) was studied to assess the relative importance of seed and pollen dispersal in shaping the spatial distribution of genetic variation. Key Results The results showed that the population under study is characterized by a high genetic diversity, a relatively high pollen immigration rate (0·57), an average within-population pollen dispersal of about 107 m and weak but significant SGS up to 40 m. The population is a mosaic of several intermingled genetic clusters that is likely to be generated by spatially restricted seed dispersal. Moreover, wild oleasters were found to be self-incompatible and preferential mating between some genotypes was revealed. Conclusions Knowledge of the within-population genetic structure and gene flow dynamics will lead to identifying possible strategies aimed at limiting the effect of anthropogenic activities and improving breeding programmes for the conservation of olive tree forest genetic resources. PMID:28028015

Pollen-mediated gene flow and fine-scale spatial genetic structure in Olea europaea subsp. europaea var. sylvestris.

PubMed

Beghè, D; Piotti, A; Satovic, Z; de la Rosa, R; Belaj, A

2017-03-01

Wild olive ( Olea europaea subsp. europaea var. sylvestris ) is important from an economic and ecological point of view. The effects of anthropogenic activities may lead to the genetic erosion of its genetic patrimony, which has high value for breeding programmes. In particular, the consequences of the introgression from cultivated stands are strongly dependent on the extent of gene flow and therefore this work aims at quantitatively describing contemporary gene flow patterns in wild olive natural populations. The studied wild population is located in an undisturbed forest, in southern Spain, considered one of the few extant hotspots of true oleaster diversity. A total of 225 potential father trees and seeds issued from five mother trees were genotyped by eight microsatellite markers. Levels of contemporary pollen flow, in terms of both pollen immigration rates and within-population dynamics, were measured through paternity analyses. Moreover, the extent of fine-scale spatial genetic structure (SGS) was studied to assess the relative importance of seed and pollen dispersal in shaping the spatial distribution of genetic variation. The results showed that the population under study is characterized by a high genetic diversity, a relatively high pollen immigration rate (0·57), an average within-population pollen dispersal of about 107 m and weak but significant SGS up to 40 m. The population is a mosaic of several intermingled genetic clusters that is likely to be generated by spatially restricted seed dispersal. Moreover, wild oleasters were found to be self-incompatible and preferential mating between some genotypes was revealed. Knowledge of the within-population genetic structure and gene flow dynamics will lead to identifying possible strategies aimed at limiting the effect of anthropogenic activities and improving breeding programmes for the conservation of olive tree forest genetic resources. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Delineation and validation of river network spatial scales for water resources and fisheries management.

PubMed

Wang, Lizhu; Brenden, Travis; Cao, Yong; Seelbach, Paul

2012-11-01

Identifying appropriate spatial scales is critically important for assessing health, attributing data, and guiding management actions for rivers. We describe a process for identifying a three-level hierarchy of spatial scales for Michigan rivers. Additionally, we conduct a variance decomposition of fish occurrence, abundance, and assemblage metric data to evaluate how much observed variability can be explained by the three spatial scales as a gage of their utility for water resources and fisheries management. The process involved the development of geographic information system programs, statistical models, modification by experienced biologists, and simplification to meet the needs of policy makers. Altogether, 28,889 reaches, 6,198 multiple-reach segments, and 11 segment classes were identified from Michigan river networks. The segment scale explained the greatest amount of variation in fish abundance and occurrence, followed by segment class, and reach. Segment scale also explained the greatest amount of variation in 13 of the 19 analyzed fish assemblage metrics, with segment class explaining the greatest amount of variation in the other six fish metrics. Segments appear to be a useful spatial scale/unit for measuring and synthesizing information for managing rivers and streams. Additionally, segment classes provide a useful typology for summarizing the numerous segments into a few categories. Reaches are the foundation for the identification of segments and segment classes and thus are integral elements of the overall spatial scale hierarchy despite reaches not explaining significant variation in fish assemblage data.

Estimating of Soil Texture Using Landsat Imagery: a Case Study in Thatta Tehsil, Sindh

NASA Astrophysics Data System (ADS)

Khalil, Zahid

2016-07-01

Soil texture is considered as an important environment factor for agricultural growth. It is the most essential part for soil classification in large scale. Today the precise soil information in large scale is of great demand from various stakeholders including soil scientists, environmental managers, land use planners and traditional agricultural users. With the increasing demand of soil properties in fine scale spatial resolution made the traditional laboratory methods inadequate. In addition the costs of soil analysis with precision agriculture systems are more expensive than traditional methods. In this regard, the application of geo-spatial techniques can be used as an alternative for examining soil analysis. This study aims to examine the ability of Geo-spatial techniques in identifying the spatial patterns of soil attributes in fine scale. Around 28 samples of soil were collected from the different areas of Thatta Tehsil, Sindh, Pakistan for analyzing soil texture. An Ordinary Least Square (OLS) regression analysis was used to relate the reflectance values of Landsat8 OLI imagery with the soil variables. The analysis showed there was a significant relationship (p<0.05) of band 2 and 5 with silt% (R2 = 0.52), and band 4 and 6 with clay% (R2 =0.40). The equation derived from OLS analysis was then used for the whole study area for deriving soil attributes. The USDA textural classification triangle was implementing for the derivation of soil texture map in GIS environment. The outcome revealed that the 'sandy loam' was in great quantity followed by loam, sandy clay loam and clay loam. The outcome shows that the Geo-spatial techniques could be used efficiently for mapping soil texture of a larger area in fine scale. This technology helped in decreasing cost, time and increase detailed information by reducing field work to a considerable level.

Dispersal, mating events and fine-scale genetic structure in the lesser flat-headed bats.

PubMed

Hua, Panyu; Zhang, Libiao; Guo, Tingting; Flanders, Jon; Zhang, Shuyi

2013-01-01

Population genetic structure has important consequences in evolutionary processes and conservation genetics in animals. Fine-scale population genetic structure depends on the pattern of landscape, the permanent movement of individuals, and the dispersal of their genes during temporary mating events. The lesser flat-headed bat (Tylonycteris pachypus) is a nonmigratory Asian bat species that roosts in small groups within the internodes of bamboo stems and the habitats are fragmented. Our previous parentage analyses revealed considerable extra-group mating in this species. To assess the spatial limits and sex-biased nature of gene flow in the same population, we used 20 microsatellite loci and mtDNA sequencing of the ND2 gene to quantify genetic structure among 54 groups of adult flat-headed bats, at nine localities in South China. AMOVA and F(ST) estimates revealed significant genetic differentiation among localities. Alternatively, the pairwise F(ST) values among roosting groups appeared to be related to the incidence of associated extra-group breeding, suggesting the impact of mating events on fine-scale genetic structure. Global spatial autocorrelation analyses showed positive genetic correlation for up to 3 km, indicating the role of fragmented habitat and the specialized social organization as a barrier in the movement of individuals among bamboo forests. The male-biased dispersal pattern resulted in weaker spatial genetic structure between localities among males than among females, and fine-scale analyses supported that relatedness levels within internodes were higher among females than among males. Finally, only females were more related to their same sex roost mates than to individuals from neighbouring roosts, suggestive of natal philopatry in females.

Spatial variability in denitrification rates in an Oregon tidal salt marsh

EPA Science Inventory

Modeling denitrification (DeN) is particularly challenging in tidal systems, which play a vital role in buffering adjacent coastal waters from nitrogen inputs. These systems are hydrologically and biogeochemically complex, varying on fine temporal and spatial scales. As part of a...

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

PubMed

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

2014-01-01

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

Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J.M.; Reichle, Rolf H.; Houser, Paul R.; Arsenault, Kristi R.; Verhoest, Niko E.C.; Paulwels, Valentijn R.N.

2009-01-01

An ensemble Kalman filter (EnKF) is used in a suite of synthetic experiments to assimilate coarse-scale (25 km) snow water equivalent (SWE) observations (typical of satellite retrievals) into fine-scale (1 km) model simulations. Coarse-scale observations are assimilated directly using an observation operator for mapping between the coarse and fine scales or, alternatively, after disaggregation (re-gridding) to the fine-scale model resolution prior to data assimilation. In either case observations are assimilated either simultaneously or independently for each location. Results indicate that assimilating disaggregated fine-scale observations independently (method 1D-F1) is less efficient than assimilating a collection of neighboring disaggregated observations (method 3D-Fm). Direct assimilation of coarse-scale observations is superior to a priori disaggregation. Independent assimilation of individual coarse-scale observations (method 3D-C1) can bring the overall mean analyzed field close to the truth, but does not necessarily improve estimates of the fine-scale structure. There is a clear benefit to simultaneously assimilating multiple coarse-scale observations (method 3D-Cm) even as the entire domain is observed, indicating that underlying spatial error correlations can be exploited to improve SWE estimates. Method 3D-Cm avoids artificial transitions at the coarse observation pixel boundaries and can reduce the RMSE by 60% when compared to the open loop in this study.

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

PubMed Central

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

2014-01-01

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

Range expansion through fragmented landscapes under a variable climate

PubMed Central

Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J

2013-01-01

Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124

Sample-based synthesis of two-scale structures with anisotropy

DOE PAGES

Liu, Xingchen; Shapiro, Vadim

2017-05-19

A vast majority of natural or synthetic materials are characterized by their anisotropic properties, such as stiffness. Such anisotropy is effected by the spatial distribution of the fine-scale structure and/or anisotropy of the constituent phases at a finer scale. In design, proper control of the anisotropy may greatly enhance the efficiency and performance of synthesized structures. In this paper, we propose a sample-based two-scale structure synthesis approach that explicitly controls anisotropic effective material properties of the structure on the coarse scale by orienting sampled material neighborhoods at the fine scale. We first characterize the non-uniform orientations distribution of the samplemore » structure by showing that the principal axes of an orthotropic material may be determined by the eigenvalue decomposition of its effective stiffness tensor. Such effective stiffness tensors can be efficiently estimated based on the two-point correlation functions of the fine-scale structures. Then we synthesize the two-scale structure by rotating fine-scale structures from the sample to follow a given target orientation field. Finally, the effectiveness of the proposed approach is demonstrated through examples in both 2D and 3D.« less

Sample-based synthesis of two-scale structures with anisotropy

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

Liu, Xingchen; Shapiro, Vadim

A vast majority of natural or synthetic materials are characterized by their anisotropic properties, such as stiffness. Such anisotropy is effected by the spatial distribution of the fine-scale structure and/or anisotropy of the constituent phases at a finer scale. In design, proper control of the anisotropy may greatly enhance the efficiency and performance of synthesized structures. In this paper, we propose a sample-based two-scale structure synthesis approach that explicitly controls anisotropic effective material properties of the structure on the coarse scale by orienting sampled material neighborhoods at the fine scale. We first characterize the non-uniform orientations distribution of the samplemore » structure by showing that the principal axes of an orthotropic material may be determined by the eigenvalue decomposition of its effective stiffness tensor. Such effective stiffness tensors can be efficiently estimated based on the two-point correlation functions of the fine-scale structures. Then we synthesize the two-scale structure by rotating fine-scale structures from the sample to follow a given target orientation field. Finally, the effectiveness of the proposed approach is demonstrated through examples in both 2D and 3D.« less

Integrating population dynamics into mapping human exposure to seismic hazard

NASA Astrophysics Data System (ADS)

Freire, S.; Aubrecht, C.

2012-11-01

Disaster risk is not fully characterized without taking into account vulnerability and population exposure. Assessment of earthquake risk in urban areas would benefit from considering the variation of population distribution at more detailed spatial and temporal scales, and from a more explicit integration of this improved demographic data with existing seismic hazard maps. In the present work, "intelligent" dasymetric mapping is used to model population dynamics at high spatial resolution in order to benefit the analysis of spatio-temporal exposure to earthquake hazard in a metropolitan area. These night- and daytime-specific population densities are then classified and combined with seismic intensity levels to derive new spatially-explicit four-class-composite maps of human exposure. The presented approach enables a more thorough assessment of population exposure to earthquake hazard. Results show that there are significantly more people potentially at risk in the daytime period, demonstrating the shifting nature of population exposure in the daily cycle and the need to move beyond conventional residence-based demographic data sources to improve risk analyses. The proposed fine-scale maps of human exposure to seismic intensity are mainly aimed at benefiting visualization and communication of earthquake risk, but can be valuable in all phases of the disaster management process where knowledge of population densities is relevant for decision-making.

Intraurban Variation of Fine Particle Elemental Concentrations in New York City.

PubMed

Ito, Kazuhiko; Johnson, Sarah; Kheirbek, Iyad; Clougherty, Jane; Pezeshki, Grant; Ross, Zev; Eisl, Holger; Matte, Thomas D

2016-07-19

Few past studies have collected and analyzed within-city variation of fine particulate matter (PM2.5) elements. We developed land-use regression (LUR) models to characterize spatial variation of 15 PM2.5 elements collected at 150 street-level locations in New York City during December 2008-November 2009: aluminum, bromine, calcium, copper, iron, potassium, manganese, sodium, nickel, lead, sulfur, silicon, titanium, vanadium, and zinc. Summer- and winter-only data available at 99 locations in the subsequent 3 years, up to November 2012, were analyzed to examine variation of LUR results across years. Spatial variation of each element was modeled in LUR including six major emission indicators: boilers burning residual oil; traffic density; industrial structures; construction/demolition (these four indicators in buffers of 50 to 1000 m), commercial cooking based on a dispersion model; and ship traffic based on inverse distance to navigation path weighted by associated port berth volume. All the elements except sodium were associated with at least one source, with R(2) ranging from 0.2 to 0.8. Strong source-element associations, persistent across years, were found for residual oil burning (nickel, zinc), near-road traffic (copper, iron, and titanium), and ship traffic (vanadium). These emission source indicators were also significant and consistent predictors of PM2.5 concentrations across years.

Fine-Grained Parcellation of Brain Connectivity Improves Differentiation of States of Consciousness During Graded Propofol Sedation.

PubMed

Liu, Xiaolin; Lauer, Kathryn K; Ward, B Douglas; Roberts, Christopher J; Liu, Suyan; Gollapudy, Suneeta; Rohloff, Robert; Gross, William; Xu, Zhan; Chen, Guangyu; Binder, Jeffrey R; Li, Shi-Jiang; Hudetz, Anthony G

2017-08-01

Conscious perception relies on interactions between spatially and functionally distinct modules of the brain at various spatiotemporal scales. These interactions are altered by anesthesia, an intervention that leads to fading consciousness. Relatively little is known about brain functional connectivity and its anesthetic modulation at a fine spatial scale. Here, we used functional imaging to examine propofol-induced changes in functional connectivity in brain networks defined at a fine-grained parcellation based on a combination of anatomical and functional features. Fifteen healthy volunteers underwent resting-state functional imaging in wakeful baseline, mild sedation, deep sedation, and recovery of consciousness. Compared with wakeful baseline, propofol produced widespread, dose-dependent functional connectivity changes that scaled with the extent to which consciousness was altered. The dominant changes in connectivity were associated with the frontal lobes. By examining node pairs that demonstrated a trend of functional connectivity change between wakefulness and deep sedation, quadratic discriminant analysis differentiated the states of consciousness in individual participants more accurately at a fine-grained parcellation (e.g., 2000 nodes) than at a coarse-grained parcellation (e.g., 116 anatomical nodes). Our study suggests that defining brain networks at a high granularity may provide a superior imaging-based distinction of the graded effect of anesthesia on consciousness.

Neighborhood-Scale Spatial Models of Diesel Exhaust Concentration Profile Using 1-Nitropyrene and Other Nitroarenes

PubMed Central

Schulte, Jill K.; Fox, Julie R.; Oron, Assaf P.; Larson, Timothy V.; Simpson, Christopher D.; Paulsen, Michael; Beaudet, Nancy; Kaufman, Joel D.; Magzamen, Sheryl

2016-01-01

With emerging evidence that diesel exhaust exposure poses distinct risks to human health, the need for fine-scale models of diesel exhaust pollutants is growing. We modeled the spatial distribution of several nitrated polycyclic aromatic hydrocarbons (NPAHs) to identify fine-scale gradients in diesel exhaust pollution in two Seattle, WA neighborhoods. Our modeling approach fused land-use regression, meteorological dispersion modeling, and pollutant monitoring from both fixed and mobile platforms. We applied these modeling techniques to concentrations of 1-nitropyrene (1-NP), a highly specific diesel exhaust marker, at the neighborhood scale. We developed models of two additional nitroarenes present in secondary organic aerosol: 2-nitro-pyrene and 2-nitrofluoranthene. Summer predictors of 1-NP, including distance to railroad, truck emissions, and mobile black carbon measurements, showed a greater specificity to diesel sources than predictors of other NPAHs. Winter sampling results did not yield stable models, likely due to regional mixing of pollutants in turbulent weather conditions. The model of summer 1-NP had an R2 of 0.87 and cross-validated R2 of 0.73. The synthesis of high-density sampling and hybrid modeling was successful in predicting diesel exhaust pollution at a very fine scale and identifying clear gradients in NPAH concentrations within urban neighborhoods. PMID:26501773

Fine-scale genetic population structure in a mobile marine mammal: inshore bottlenose dolphins in Moreton Bay, Australia.

PubMed

Ansmann, Ina C; Parra, Guido J; Lanyon, Janet M; Seddon, Jennifer M

2012-09-01

Highly mobile marine species in areas with no obvious geographic barriers are expected to show low levels of genetic differentiation. However, small-scale variation in habitat may lead to resource polymorphisms and drive local differentiation by adaptive divergence. Using nuclear microsatellite genotyping at 20 loci, and mitochondrial control region sequencing, we investigated fine-scale population structuring of inshore bottlenose dolphins (Tursiops aduncus) inhabiting a range of habitats in and around Moreton Bay, Australia. Bayesian structure analysis identified two genetic clusters within Moreton Bay, with evidence of admixture between them (F(ST) = 0.05, P = 0.001). There was only weak isolation by distance but one cluster of dolphins was more likely to be found in shallow southern areas and the other in the deeper waters of the central northern bay. In further analysis removing admixed individuals, southern dolphins appeared genetically restricted with lower levels of variation (AR = 3.252, π = 0.003) and high mean relatedness (r = 0.239) between individuals. In contrast, northern dolphins were more diverse (AR = 4.850, π = 0.009) and were mixing with a group of dolphins outside the bay (microsatellite-based STRUCTURE analysis), which appears to have historically been distinct from the bay dolphins (mtDNA Φ(ST) = 0.272, P < 0.001). This study demonstrates the ability of genetic techniques to expose fine-scale patterns of population structure and explore their origins and mechanisms. A complex variety of inter-related factors including local habitat variation, differential resource use, social behaviour and learning, and anthropogenic disturbances are likely to have played a role in driving fine-scale population structure among bottlenose dolphins in Moreton Bay. © 2012 Blackwell Publishing Ltd.

Spatially explicit modeling in ecology: A review

USGS Publications Warehouse

DeAngelis, Donald L.; Yurek, Simeon

2017-01-01

The use of spatially explicit models (SEMs) in ecology has grown enormously in the past two decades. One major advancement has been that fine-scale details of landscapes, and of spatially dependent biological processes, such as dispersal and invasion, can now be simulated with great precision, due to improvements in computer technology. Many areas of modeling have shifted toward a focus on capturing these fine-scale details, to improve mechanistic understanding of ecosystems. However, spatially implicit models (SIMs) have played a dominant role in ecology, and arguments have been made that SIMs, which account for the effects of space without specifying spatial positions, have an advantage of being simpler and more broadly applicable, perhaps contributing more to understanding. We address this debate by comparing SEMs and SIMs in examples from the past few decades of modeling research. We argue that, although SIMs have been the dominant approach in the incorporation of space in theoretical ecology, SEMs have unique advantages for addressing pragmatic questions concerning species populations or communities in specific places, because local conditions, such as spatial heterogeneities, organism behaviors, and other contingencies, produce dynamics and patterns that usually cannot be incorporated into simpler SIMs. SEMs are also able to describe mechanisms at the local scale that can create amplifying positive feedbacks at that scale, creating emergent patterns at larger scales, and therefore are important to basic ecological theory. We review the use of SEMs at the level of populations, interacting populations, food webs, and ecosystems and argue that SEMs are not only essential in pragmatic issues, but must play a role in the understanding of causal relationships on landscapes.

Spatial models reveal the microclimatic buffering capacity of old-growth forests

PubMed Central

Frey, Sarah J. K.; Hadley, Adam S.; Johnson, Sherri L.; Schulze, Mark; Jones, Julia A.; Betts, Matthew G.

2016-01-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming. PMID:27152339

Spatial models reveal the microclimatic buffering capacity of old-growth forests.

PubMed

Frey, Sarah J K; Hadley, Adam S; Johnson, Sherri L; Schulze, Mark; Jones, Julia A; Betts, Matthew G

2016-04-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming.

Vegetation change alters soil profile δ15N values at the landscape scale in a subtropical savanna

NASA Astrophysics Data System (ADS)

Zhou, Y.; Mushinski, R. M.; Hyodo, A.; Wu, X. B.; Boutton, T. W.

2017-12-01

The assessment of spatial variation in soil δ15N could provide integrative insights on soil N cycling processes across multiple spatial scales. However, little is known about spatial patterns of δ15N within soil profiles in arid and semiarid ecosystems, especially those undergoing vegetation change with a distinct shift in dominance and/or functional type. We quantified how changes from grass to woody plant dominance altered spatial patterns of δ15N throughout a 1.2 m soil profile by collecting 320 spatially-specific soil cores in a 160 m × 100 m subtropical savanna landscape that has undergone encroachment by Prosopis glandulosa (an N2-fixer) during the past century. Leaf δ15N was comparable among different plant life-forms, while fine roots from woody species had significantly lower δ15N than herbaceous species across this landscape. Woody encroachment significantly decreased soil δ15N throughout the entire soil profile, and created horizontal spatial patterns of soil δ15N that strongly resembled the spatial distribution of woody patches and were evident within each depth increment. The lower soil δ15N values that characterized areas beneath woody canopies were mostly due to the encroaching woody species, especially the N2-fixer P. glandulosa, which delivered 15N-depleted organic matter via root turnover to soils along the profile. Soil δ15N increased with depth, reached maximum values at an intermediate depth, and decreased at greater depths. Higher δ15N values at intermediate soil depths were correlated with the presence of a subsurface clay-rich argillic horizon across this landscape which may favor more rapid rates of N-cycling processes that can cause N losses and 15N enrichment of the residual soil N. These results indicate that succession from grassland to woodland has altered spatial variation in soil δ15N across the landscape and to considerable depth, suggesting significant changes in the relative rates of N-inputs vs. N-losses in this subtropical system after vegetation change.

ASSESSING THE ACCURACY OF NATIONAL LAND COVER DATASET AREA ESTIMATES AT MULTIPLE SPATIAL EXTENTS

EPA Science Inventory

Site specific accuracy assessments provide fine-scale evaluation of the thematic accuracy of land use/land cover (LULC) datasets; however, they provide little insight into LULC accuracy across varying spatial extents. Additionally, LULC data are typically used to describe lands...

Assessment of Near-Source Air Pollution at a Fine Spatial Scale Utilizing Mobile Monitoring Approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle – an all-electric vehicle measuring real-time concentrations of partic...

Factors Impacting Spatial Patterns of Snow Distribution in a Small Catchment near Nome, AK

NASA Astrophysics Data System (ADS)

Chen, M.; Wilson, C. J.; Charsley-Groffman, L.; Busey, R.; Bolton, W. R.

2017-12-01

Snow cover plays an important role in the climate, hydrology and ecological systems of the Arctic due to its influence on the water balance, thermal regimes, vegetation and carbon flux. Thus, snow depth and coverage have been key components in all the earth system models but are often poorly represented for arctic regions, where fine scale snow distribution data is sparse. The snow data currently used in the models is at coarse resolution, which in turn leads to high uncertainty in model predictions. Through the DOE Office of Science Next Generation Ecosystem Experiment, NGEE-Arctic, high resolution snow distribution data is being developed and applied in catchment scale models to ultimately improve representation of snow and its interactions with other model components in the earth system models . To improve these models, it is important to identify key factors that control snow distribution and quantify the impacts of those factors on snow distribution. In this study, two intensive snow depth surveys (1 to 10 meters scale) were conducted for a 2.3 km2 catchment on the Teller road, near Nome, AK in the winter of 2016 and 2017. We used a statistical model to quantify the impacts of vegetation types, macro-topography, micro-topography, and meteorological parameters on measured snow depth. The results show that snow spatial distribution was similar between 2016 and 2017, snow depth was spatially auto correlated over small distance (2-5 meters), but not spatially auto correlated over larger distance (more than 2-5 meters). The coefficients of variation of snow depth was above 0.3 for all the snow survey transects (500-800 meters long). Variation of snow depth is governed by vegetation height, aspect, slope, surface curvature, elevation and wind speed and direction. We expect that this empirical statistical model can be used to estimate end of winter snow depth for the whole watershed and will further develop the model using data from other arctic regions to estimate seasonally dynamic snow coverage and properties for use in catchment scale to pan-Arctic models.

Multi-scale temporal and spatial variation in genotypic composition of Cladophora-borne Escherichia coli populations in Lake Michigan.

PubMed

Badgley, Brian D; Ferguson, John; Vanden Heuvel, Amy; Kleinheinz, Gregory T; McDermott, Colleen M; Sandrin, Todd R; Kinzelman, Julie; Junion, Emily A; Byappanahalli, Muruleedhara N; Whitman, Richard L; Sadowsky, Michael J

2011-01-01

High concentrations of Escherichia coli in mats of Cladophora in the Great Lakes have raised concern over the continued use of this bacterium as an indicator of microbial water quality. Determining the impacts of these environmentally abundant E. coli, however, necessitates a better understanding of their ecology. In this study, the population structure of 4285 Cladophora-borne E. coli isolates, obtained over multiple three day periods from Lake Michigan Cladophora mats in 2007-2009, was examined by using DNA fingerprint analyses. In contrast to previous studies that have been done using isolates from attached Cladophora obtained over large time scales and distances, the extensive sampling done here on free-floating mats over successive days at multiple sites provided a large dataset that allowed for a detailed examination of changes in population structure over a wide range of spatial and temporal scales. While Cladophora-borne E. coli populations were highly diverse and consisted of many unique isolates, multiple clonal groups were also present and accounted for approximately 33% of all isolates examined. Patterns in population structure were also evident. At the broadest scales, E. coli populations showed some temporal clustering when examined by year, but did not show good spatial distinction among sites. E. coli population structure also showed significant patterns at much finer temporal scales. Populations were distinct on an individual mat basis at a given site, and on individual days within a single mat. Results of these studies indicate that Cladophora-borne E. coli populations consist of a mixture of stable, and possibly naturalized, strains that persist during the life of the mat, and more unique, transient strains that can change over rapid time scales. It is clear that further study of microbial processes at fine spatial and temporal scales is needed, and that caution must be taken when interpolating short term microbial dynamics from results obtained from weekly or monthly samples. Copyright © 2010 Elsevier Ltd. All rights reserved.

Multi-scale temporal and spatial variation in genotypic composition of Cladophora-borne Escherichia coli populations in Lake Michigan

USGS Publications Warehouse

Badgley, B.D.; Ferguson, J.; Heuvel, A.V.; Kleinheinz, G.T.; McDermott, C.M.; Sandrin, T.R.; Kinzelman, J.; Junion, E.A.; Byappanahalli, M.N.; Whitman, R.L.; Sadowsky, M.J.

2011-01-01

High concentrations of Escherichia coli in mats of Cladophora in the Great Lakes have raised concern over the continued use of this bacterium as an indicator of microbial water quality. Determining the impacts of these environmentally abundant E. coli, however, necessitates a better understanding of their ecology. In this study, the population structure of 4285 Cladophora-borne E. coli isolates, obtained over multiple three day periods from Lake Michigan Cladophora mats in 2007-2009, was examined by using DNA fingerprint analyses. In contrast to previous studies that have been done using isolates from attached Cladophora obtained over large time scales and distances, the extensive sampling done here on free-floating mats over successive days at multiple sites provided a large dataset that allowed for a detailed examination of changes in population structure over a wide range of spatial and temporal scales. While Cladophora-borne E. coli populations were highly diverse and consisted of many unique isolates, multiple clonal groups were also present and accounted for approximately 33% of all isolates examined. Patterns in population structure were also evident. At the broadest scales, E. coli populations showed some temporal clustering when examined by year, but did not show good spatial distinction among sites. E. coli population structure also showed significant patterns at much finer temporal scales. Populations were distinct on an individual mat basis at a given site, and on individual days within a single mat. Results of these studies indicate that Cladophora-borne E. coli populations consist of a mixture of stable, and possibly naturalized, strains that persist during the life of the mat, and more unique, transient strains that can change over rapid time scales. It is clear that further study of microbial processes at fine spatial and temporal scales is needed, and that caution must be taken when interpolating short term microbial dynamics from results obtained from weekly or monthly samples.

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

PubMed

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

2008-03-01

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

Fine-scale spatial distribution of orchid mycorrhizal fungi in the soil of host-rich grasslands.

PubMed

Voyron, Samuele; Ercole, Enrico; Ghignone, Stefano; Perotto, Silvia; Girlanda, Mariangela

2017-02-01

Mycorrhizal fungi are essential for the survival of orchid seedlings under natural conditions. The distribution of these fungi in soil can constrain the establishment and resulting spatial arrangement of orchids at the local scale, but the actual extent of occurrence and spatial patterns of orchid mycorrhizal (OrM) fungi in soil remain largely unknown. We addressed the fine-scale spatial distribution of OrM fungi in two orchid-rich Mediterranean grasslands by means of high-throughput sequencing of fungal ITS2 amplicons, obtained from soil samples collected either directly beneath or at a distance from adult Anacamptis morio and Ophrys sphegodes plants. Like ectomycorrhizal and arbuscular mycobionts, OrM fungi (tulasnelloid, ceratobasidioid, sebacinoid and pezizoid fungi) exhibited significant horizontal spatial autocorrelation in soil. However, OrM fungal read numbers did not correlate with distance from adult orchid plants, and several of these fungi were extremely sporadic or undetected even in the soil samples containing the orchid roots. Orchid mycorrhizal 'rhizoctonias' are commonly regarded as unspecialized saprotrophs. The sporadic occurrence of mycobionts of grassland orchids in host-rich stands questions the view of these mycorrhizal fungi as capable of sustained growth in soil. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Variation of fundamental constants on sub- and super-Hubble scales: From the equivalence principle to the multiverse

NASA Astrophysics Data System (ADS)

Uzan, Jean-Philippe

2013-02-01

Fundamental constants play a central role in many modern developments in gravitation and cosmology. Most extensions of general relativity lead to the conclusion that dimensionless constants are actually dynamical fields. Any detection of their variation on sub-Hubble scales would signal a violation of the Einstein equivalence principle and hence a lead to gravity beyond general relativity. On super-Hubble scales, or maybe should we say on super-universe scales, such variations are invoked as a solution to the fine-tuning problem, in connection with an anthropic approach.

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions.

PubMed

Wilson, Adam M; Jetz, Walter

2016-03-01

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model.

PubMed

Shafer, Sarah L; Bartlein, Patrick J; Gray, Elizabeth M; Pelltier, Richard T

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0-58.0°N latitude by 136.6-103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070-2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti

PubMed Central

2013-01-01

Background Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Methods Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Results Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these “hotspots”. Conclusions Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study sites through time to track spatio-temporal dynamics of the communities. Its simplicity should also be used to encourage local participatory collaborations. PMID:23587358

A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti.

PubMed

Curtis, Andrew; Blackburn, Jason K; Widmer, Jocelyn M; Morris, J Glenn

2013-04-15

Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these "hotspots". Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study sites through time to track spatio-temporal dynamics of the communities. Its simplicity should also be used to encourage local participatory collaborations.

Modeling nutrient in-stream processes at the watershed scale using Nutrient Spiralling metrics

NASA Astrophysics Data System (ADS)

Marcé, R.; Armengol, J.

2009-01-01

One of the fundamental problems of using large-scale biogeochemical models is the uncertainty involved in aggregating the components of fine-scale deterministic models in watershed applications, and in extrapolating the results of field-scale measurements to larger spatial scales. Although spatial or temporal lumping may reduce the problem, information obtained during fine-scale research may not apply to lumped categories. Thus, the use of knowledge gained through fine-scale studies to predict coarse-scale phenomena is not straightforward. In this study, we used the nutrient uptake metrics defined in the Nutrient Spiralling concept to formulate the equations governing total phosphorus in-stream fate in a watershed-scale biogeochemical model. The rationale of this approach relies on the fact that the working unit for the nutrient in-stream processes of most watershed-scale models is the reach, the same unit used in field research based on the Nutrient Spiralling concept. Automatic calibration of the model using data from the study watershed confirmed that the Nutrient Spiralling formulation is a convenient simplification of the biogeochemical transformations involved in total phosphorus in-stream fate. Following calibration, the model was used as a heuristic tool in two ways. First, we compared the Nutrient Spiralling metrics obtained during calibration with results obtained during field-based research in the study watershed. The simulated and measured metrics were similar, suggesting that information collected at the reach scale during research based on the Nutrient Spiralling concept can be directly incorporated into models, without the problems associated with upscaling results from fine-scale studies. Second, we used results from our model to examine some patterns observed in several reports on Nutrient Spiralling metrics measured in impaired streams. Although these two exercises involve circular reasoning and, consequently, cannot validate any hypothesis, this is a powerful example of how models can work as heuristic tools to compare hypotheses and stimulate research in ecology.

Demonstration of C-Tools for Community Exposure Assessment

EPA Science Inventory

The presentation describes a new community-scale tool called C-PORT to model emissions related to all port-related activities – including, but not limited to ships, trucks, cranes, etc. – and predict concentrations at fine spatial scales in the near-source environment...

A global Fine-Root Ecology Database to address below-ground challenges in plant ecology.

PubMed

Iversen, Colleen M; McCormack, M Luke; Powell, A Shafer; Blackwood, Christopher B; Freschet, Grégoire T; Kattge, Jens; Roumet, Catherine; Stover, Daniel B; Soudzilovskaia, Nadejda A; Valverde-Barrantes, Oscar J; van Bodegom, Peter M; Violle, Cyrille

2017-07-01

Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. While fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of root traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. Continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time. © 2017 UT-Battelle LLC. New Phytologist © 2017 New Phytologist Trust.

Characterizing multiscale variability of zero intermittency in spatial rainfall

NASA Technical Reports Server (NTRS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1994-01-01

In this paper the authors study how zero intermittency in spatial rainfall, as described by the fraction of area covered by rainfall, changes with spatial scale of rainfall measurement or representation. A statistical measure of intermittency that describes the size distribution of 'voids' (nonrainy areas imbedded inside rainy areas) as a function of scale is also introduced. Morphological algorithms are proposed for reconstructing rainfall intermittency at fine scales given the intermittency at coarser scales. These algorithms are envisioned to be useful in hydroclimatological studies where the rainfall spatial variability at the subgrid scale needs to be reconstructed from the results of synoptic- or mesoscale meteorological numerical models. The developed methodologies are demsonstrated and tested using data from a severe springtime midlatitude squall line and a mild midlatitude winter storm monitored by a meteorological radar in Norman, Oklahoma.

Demonstrating the Uneven Importance of Fine-Scale Forest Structure on Snow Distributions using High Resolution Modeling

NASA Astrophysics Data System (ADS)

Broxton, P. D.; Harpold, A. A.; van Leeuwen, W.; Biederman, J. A.

2016-12-01

Quantifying the amount of snow in forested mountainous environments, as well as how it may change due to warming and forest disturbance, is critical given its importance for water supply and ecosystem health. Forest canopies affect snow accumulation and ablation in ways that are difficult to observe and model. Furthermore, fine-scale forest structure can accentuate or diminish the effects of forest-snow interactions. Despite decades of research demonstrating the importance of fine-scale forest structure (e.g. canopy edges and gaps) on snow, we still lack a comprehensive understanding of where and when forest structure has the largest impact on snowpack mass and energy budgets. Here, we use a hyper-resolution (1 meter spatial resolution) mass and energy balance snow model called the Snow Physics and Laser Mapping (SnowPALM) model along with LIDAR-derived forest structure to determine where spatial variability of fine-scale forest structure has the largest influence on large scale mass and energy budgets. SnowPALM was set up and calibrated at sites representing diverse climates in New Mexico, Arizona, and California. Then, we compared simulations at different model resolutions (i.e. 1, 10, and 100 m) to elucidate the effects of including versus not including information about fine scale canopy structure. These experiments were repeated for different prescribed topographies (i.e. flat, 30% slope north, and south-facing) at each site. Higher resolution simulations had more snow at lower canopy cover, with the opposite being true at high canopy cover. Furthermore, there is considerable scatter, indicating that different canopy arrangements can lead to different amounts of snow, even when the overall canopy coverage is the same. This modeling is contributing to the development of a high resolution machine learning algorithm called the Snow Water Artificial Network (SWANN) model to generate predictions of snow distributions over much larger domains, which has implications for improving land surface models that do not currently resolve or parameterize fine-scale canopy structure. In addition, these findings have implications for understanding the potential of different forest management strategies (i.e. thinning) based on local topography and climate to maximize the amount and retention of snow.

Toward daily monitoring of vegetation conditions at field scale through fusing data from multiple sensors

USDA-ARS?s Scientific Manuscript database

Vegetation monitoring requires remote sensing data at fine spatial and temporal resolution. While imagery from coarse resolution sensors such as MODIS/VIIRS can provide daily observations, they lack spatial detail to capture surface features for crop and rangeland monitoring. The Landsat satellite s...

Spatially explicit animal response to composition of habitat

Treesearch

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-...

Assessment of Near-Source Air Pollution at a Fine Spatial Scale Utilizing Mobile Monitoring Approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle – an all-electric vehicle measuring real-time concentrations of particulate and gaseous po...

Assessment of Near-Source Air Pollution at a Fine Spatial Scale Utilizing a Mobile Monitoring Approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle – an all-electric vehicle measuring real-time concentrations of particulate and gaseous po...

Assessment of near-source air pollution at a fine spatial scale utilizing a mobile measurement platform approach

EPA Science Inventory

Mobile monitoring is an emerging strategy to characterize spatially and temporally variable air pollution in areas near sources. EPA’s Geospatial Monitoring of Air Pollution (GMAP) vehicle, an all-electric vehicle measuring real-time concentrations of particulate and gaseous poll...

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

NASA Astrophysics Data System (ADS)

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

2003-12-01

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

Multiple drivers, scales, and interactions influence southern Appalachian stream salamander occupancy

Treesearch

Kristen K. Cecala; John C. Maerz; Brian J. Halstead; John R. Frisch; Ted L. Gragson; Jeffrey Hepinstall-Cymerman; David S. Leigh; C. Rhett Jackson; James T. Peterson; Catherine M. Pringle

2018-01-01

Understanding how factors that vary in spatial scale relate to population abundance is vital to forecasting species responses to environmental change. Stream and river ecosystems are inherently hierarchical, potentially resulting in organismal responses to fine‐scale changes in patch characteristics that are conditional on the watershed context. Here, we...

Assessing Clark's nutcracker seed-caching flights using maternally inherited mitochondrial DNA of whitebark pine

Treesearch

Bryce A. Richardson; Ned B. Klopfenstein; Steven J. Brunsfeld

2002-01-01

Maternally inherited mitochondrial DNA haplotypes in whitebark pine (Pinus albicaulis Engelm.) were used to examine the maternal genetic structure at three hierarchical spatial scales: fine scale, coarse scale, and interpopulation. These data were used to draw inferences into Clark’s nutcracker (Nucifraga columbiana Wilson)...

Tracking fine-scale seasonal evolution of surface water extent in Central Alaska and the Canadian Shield

NASA Astrophysics Data System (ADS)

Cooley, S. W.; Smith, L. C.; Pitcher, L. H.; Pavelsky, T.; Topp, S.

2017-12-01

Quantifying spatial and temporal variability in surface water storage at high latitudes is critical for assessing environmental sensitivity to climate change. Traditionally the tradeoff between high spatial and high temporal resolution space-borne optical imagery has limited the ability to track fine-scale changes in surface water extent. However, the recent launch of hundreds of earth-imaging CubeSats by commercial satellite companies such as Planet opens up new possibilities for monitoring surface water from space. In this study we present a comparison of seasonal evolution of surface water extent in two study areas with differing geologic, hydrologic and permafrost regimes, namely, the Yukon Flats in Central Alaska and the Canadian Shield north of Yellowknife, N.W.T. Using near-daily 3m Planet CubeSat imagery, we track individual lake surface area from break-up to freeze-up during summer 2017 and quantify the spatial and temporal variability in inundation extent. We validate our water delineation method and inundation extent time series using WorldView imagery, coincident in situ lake shoreline mapping and pressure transducer data for 19 lakes in the Northwest Territories and Alaska collected during the NASA Arctic Boreal Vulnerability Experiment (ABoVE) 2017 field campaign. The results of this analysis demonstrate the value of CubeSat imagery for dynamic surface water research particularly at high latitudes and illuminate fine-scale drivers of cold regions surface water extent.

Fine-scale spatial climate variation and drought mediate the likelihood of reburning.

PubMed

Parks, Sean A; Parisien, Marc-André; Miller, Carol; Holsinger, Lisa M; Baggett, Larry Scott

2018-03-01

In many forested ecosystems, it is increasingly recognized that the probability of burning is substantially reduced within the footprint of previously burned areas. This self-limiting effect of wildland fire is considered a fundamental emergent property of ecosystems and is partly responsible for structuring landscape heterogeneity (i.e., mosaics of different age classes), thereby reducing the likelihood of uncharacteristically large fires in regions with active fire regimes. However, the strength and longevity of this self-limiting phenomenon is not well understood in most fire-prone ecosystems. In this study, we quantify the self-limiting effect in terms of its strength and longevity for five fire-prone study areas in western North America and investigate how each measure varies along a spatial climatic gradient and according to temporal (i.e., annual) climatic variation. Results indicate that the longevity (i.e., number of years) of the self-limiting effect ranges between 15 yr in the warm and dry study area in the southwestern United States to 33 yr in the cold, northern study areas in located in northwestern Montana and the boreal forest of Canada. We also found that spatial climatic variation has a strong influence on wildland fire's self-limiting capacity. Specifically, the self-limiting effect within each study area was stronger and lasted longer in areas with low mean moisture deficit (i.e., wetter and cooler settings) compared to areas with high mean moisture deficit (warmer and drier settings). Last, our findings show that annual climatic variation influences wildland fire's self-limiting effect: drought conditions weakened the strength and longevity of the self-limiting effect in all study areas, albeit at varying magnitudes. Overall, our study provides support for the idea that wildland fire contributes to spatial heterogeneity in fuel ages that subsequently mediate future fire sizes and effects. However, our findings show that the strength and longevity of the self-limiting effect varies considerably according to spatial and temporal climatic variation, providing land and fire managers relevant information for effective planning and management of fire and highlighting that fire itself is an important factor contributing to fire-free intervals. © 2017 by the Ecological Society of America.

Strontium isotopes delineate fine-scale natal origins and migration histories of Pacific salmon

USGS Publications Warehouse

Brennan, Sean R.; Zimmerman, Christian E.; Fernandez, Diego P.; Cerling, Thure E.; McPhee, Megan V.; Wooller, Matthew J.

2015-01-01

Highly migratory organisms present major challenges to conservation efforts. This is especially true for exploited anadromous fish species, which exhibit long-range dispersals from natal sites, complex population structures, and extensive mixing of distinct populations during exploitation. By tracing the migratory histories of individual Chinook salmon caught in fisheries using strontium isotopes, we determined the relative production of natal habitats at fine spatial scales and different life histories. Although strontium isotopes have been widely used in provenance research, we present a new robust framework to simultaneously assess natal sources and migrations of individuals within fishery harvests through time. Our results pave the way for investigating how fine-scale habitat production and life histories of salmon respond to perturbations—providing crucial insights for conservation.

Inbreeding Avoidance Drives Consistent Variation of Fine-Scale Genetic Structure Caused by Dispersal in the Seasonal Mating System of Brandt’s Voles

PubMed Central

Liu, Xiao Hui; Yue, Ling Fen; Wang, Da Wei; Li, Ning; Cong, Lin

2013-01-01

Inbreeding depression is a major evolutionary and ecological force influencing population dynamics and the evolution of inbreeding-avoidance traits such as mating systems and dispersal. Mating systems and dispersal are fundamental determinants of population genetic structure. Resolving the relationships among genetic structure, seasonal breeding-related mating systems and dispersal will facilitate our understanding of the evolution of inbreeding avoidance. The goals of this study were as follows: (i) to determine whether females actively avoided mating with relatives in a group-living rodent species, Brandt’s voles (Lasiopodomys brandtii), by combined analysis of their mating system, dispersal and genetic structure; and (ii) to analyze the relationships among the variation in fine-genetic structure, inbreeding avoidance, season-dependent mating strategies and individual dispersal. Using both individual- and population-level analyses, we found that the majority of Brandt’s vole groups consisted of close relatives. However, both group-specific FISs, an inbreeding coefficient that expresses the expected percentage rate of homozygosity arising from a given breeding system, and relatedness of mates showed no sign of inbreeding. Using group pedigrees and paternity analysis, we show that the mating system of Brandt’s voles consists of a type of polygyny for males and extra-group polyandry for females, which may decrease inbreeding by increasing the frequency of mating among distantly-related individuals. The consistent variation in within-group relatedness, among-group relatedness and fine-scale genetic structures was mostly due to dispersal, which primarily occurred during the breeding season. Biologically relevant variation in the fine-scale genetic structure suggests that dispersal during the mating season may be a strategy to avoid inbreeding and drive the polygynous and extra-group polyandrous mating system of this species. PMID:23516435

A geostatistical approach to identify and mitigate agricultural nitrous oxide emission hotspots.

PubMed

Turner, P A; Griffis, T J; Mulla, D J; Baker, J M; Venterea, R T

2016-12-01

Anthropogenic emissions of nitrous oxide (N 2 O), a trace gas with severe environmental costs, are greatest from agricultural soils amended with nitrogen (N) fertilizer. However, accurate N 2 O emission estimates at fine spatial scales are made difficult by their high variability, which represents a critical challenge for the management of N 2 O emissions. Here, static chamber measurements (n=60) and soil samples (n=129) were collected at approximately weekly intervals (n=6) for 42-d immediately following the application of N in a southern Minnesota cornfield (15.6-ha), typical of the systems prevalent throughout the U.S. Corn Belt. These data were integrated into a geostatistical model that resolved N 2 O emissions at a high spatial resolution (1-m). Field-scale N 2 O emissions exhibited a high degree of spatial variability, and were partitioned into three classes of emission strength: hotspots, intermediate, and coldspots. Rates of emission from hotspots were 2-fold greater than non-hotspot locations. Consequently, 36% of the field-scale emissions could be attributed to hotspots, despite representing only 21% of the total field area. Variations in elevation caused hotspots to develop in predictable locations, which were prone to nutrient and moisture accumulation caused by terrain focusing. Because these features are relatively static, our data and analyses indicate that targeted management of hotspots could efficiently reduce field-scale emissions by as much 17%, a significant benefit considering the deleterious effects of atmospheric N 2 O. Copyright © 2016 Elsevier B.V. All rights reserved.

Effect of assessment scale on spatial and temporal variations in CH4, C02, and N20 fluxes in a forested wetland

Treesearch

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

2011-01-01

Emissions of methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) from a forested watershed (160 ha) in South Carolina, USA, were estimated with a spatially explicit watershed-scale modeling framework that utilizes the spatial variations in physical and biogeochemical characteristics across watersheds. The target watershed (WS80) consisting of wetland (23%) and...

In the absence of a "landscape of fear": How lions, hyenas, and cheetahs coexist.

PubMed

Swanson, Alexandra; Arnold, Todd; Kosmala, Margaret; Forester, James; Packer, Craig

2016-12-01

Aggression by top predators can create a "landscape of fear" in which subordinate predators restrict their activity to low-risk areas or times of day. At large spatial or temporal scales, this can result in the costly loss of access to resources. However, fine-scale reactive avoidance may minimize the risk of aggressive encounters for subordinate predators while maintaining access to resources, thereby providing a mechanism for coexistence. We investigated fine-scale spatiotemporal avoidance in a guild of African predators characterized by intense interference competition. Vulnerable to food stealing and direct killing, cheetahs are expected to avoid both larger predators; hyenas are expected to avoid lions. We deployed a grid of 225 camera traps across 1,125 km 2 in Serengeti National Park, Tanzania, to evaluate concurrent patterns of habitat use by lions, hyenas, cheetahs, and their primary prey. We used hurdle models to evaluate whether smaller species avoided areas preferred by larger species, and we used time-to-event models to evaluate fine-scale temporal avoidance in the hours immediately surrounding top predator activity. We found no evidence of long-term displacement of subordinate species, even at fine spatial scales. Instead, hyenas and cheetahs were positively associated with lions except in areas with exceptionally high lion use. Hyenas and lions appeared to actively track each, while cheetahs appear to maintain long-term access to sites with high lion use by actively avoiding those areas just in the hours immediately following lion activity. Our results suggest that cheetahs are able to use patches of preferred habitat by avoiding lions on a moment-to-moment basis. Such fine-scale temporal avoidance is likely to be less costly than long-term avoidance of preferred areas: This may help explain why cheetahs are able to coexist with lions despite high rates of lion-inflicted mortality, and highlights reactive avoidance as a general mechanism for predator coexistence.

Genetic drift and collective dispersal can result in chaotic genetic patchiness.

PubMed

Broquet, Thomas; Viard, Frédérique; Yearsley, Jonathan M

2013-06-01

Chaotic genetic patchiness denotes unexpected patterns of genetic differentiation that are observed at a fine scale and are not stable in time. These patterns have been described in marine species with free-living larvae, but are unexpected because they occur at a scale below the dispersal range of pelagic larvae. At the scale where most larvae are immigrants, theory predicts spatially homogeneous, temporally stable genetic variation. Empirical studies have suggested that genetic drift interacts with complex dispersal patterns to create chaotic genetic patchiness. Here we use a co-ancestry model and individual-based simulations to test this idea. We found that chaotic genetic patterns (qualified by global FST and spatio-temporal variation in FST's between pairs of samples) arise from the combined effects of (1) genetic drift created by the small local effective population sizes of the sessile phase and variance in contribution among breeding groups and (2) collective dispersal of related individuals in the larval phase. Simulations show that patchiness levels qualitatively comparable to empirical results can be produced by a combination of strong variance in reproductive success and mild collective dispersal. These results call for empirical studies of the effective number of breeders producing larval cohorts, and population genetics at the larval stage. © 2012 The Author(s). Evolution © 2012 The Society for the Study of Evolution.

Fine-scale population genetic structure and sex-biased dispersal in the smooth snake (Coronella austriaca) in southern England.

PubMed

Pernetta, A P; Allen, J A; Beebee, T J C; Reading, C J

2011-09-01

Human-induced alteration of natural habitats has the potential to impact on the genetic structuring of remnant populations at multiple spatial scales. Species from higher trophic levels, such as snakes, are expected to be particularly susceptible to land-use changes. We examined fine-scale population structure and looked for evidence of sex-biased dispersal in smooth snakes (Coronella austriaca), sampled from 10 heathland localities situated within a managed coniferous forest in Dorset, United Kingdom. Despite the limited distances between heathland areas (maximum <6 km), there was a small but significant structuring of populations based on eight microsatellite loci. This followed an isolation-by-distance model using both straight line and 'biological' distances between sampling sites, suggesting C. austriaca's low vagility as the causal factor, rather than closed canopy conifer forest exerting an effect as a barrier to dispersal. Within population comparisons of male and female snakes showed evidence for sex-biased dispersal, with three of four analyses finding significantly higher dispersal in males than in females. We suggest that the fine-scale spatial genetic structuring and sex-biased dispersal have important implications for the conservation of C. austriaca, and highlight the value of heathland areas within commercial conifer plantations with regards to their future management.

Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios.

PubMed

Yen, Haw; White, Michael J; Arnold, Jeffrey G; Keitzer, S Conor; Johnson, Mari-Vaughn V; Atwood, Jay D; Daggupati, Prasad; Herbert, Matthew E; Sowa, Scott P; Ludsin, Stuart A; Robertson, Dale M; Srinivasan, Raghavan; Rewa, Charles A

2016-11-01

Complex watershed simulation models are powerful tools that can help scientists and policy-makers address challenging topics, such as land use management and water security. In the Western Lake Erie Basin (WLEB), complex hydrological models have been applied at various scales to help describe relationships between land use and water, nutrient, and sediment dynamics. This manuscript evaluated the capacity of the current Soil and Water Assessment Tool (SWAT) to predict hydrological and water quality processes within WLEB at the finest resolution watershed boundary unit (NHDPlus) along with the current conditions and conservation scenarios. The process based SWAT model was capable of the fine-scale computation and complex routing used in this project, as indicated by measured data at five gaging stations. The level of detail required for fine-scale spatial simulation made the use of both hard and soft data necessary in model calibration, alongside other model adaptations. Limitations to the model's predictive capacity were due to a paucity of data in the region at the NHDPlus scale rather than due to SWAT functionality. Results of treatment scenarios demonstrate variable effects of structural practices and nutrient management on sediment and nutrient loss dynamics. Targeting treatment to acres with critical outstanding conservation needs provides the largest return on investment in terms of nutrient loss reduction per dollar spent, relative to treating acres with lower inherent nutrient loss vulnerabilities. Importantly, this research raises considerations about use of models to guide land management decisions at very fine spatial scales. Decision makers using these results should be aware of data limitations that hinder fine-scale model interpretation. Copyright © 2016 Elsevier B.V. All rights reserved.

Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios

USGS Publications Warehouse

Yen, Haw; White, Michael J.; Arnold, Jeffrey G.; Keitzer, S. Conor; Johnson, Mari-Vaughn V; Atwood, Jay D.; Daggupati, Prasad; Herbert, Matthew E.; Sowa, Scott P.; Ludsin, Stuart A.; Robertson, Dale M.; Srinivasan, Raghavan; Rewa, Charles A.

2016-01-01

Complex watershed simulation models are powerful tools that can help scientists and policy-makers address challenging topics, such as land use management and water security. In the Western Lake Erie Basin (WLEB), complex hydrological models have been applied at various scales to help describe relationships between land use and water, nutrient, and sediment dynamics. This manuscript evaluated the capacity of the current Soil and Water Assessment Tool (SWAT2012) to predict hydrological and water quality processes within WLEB at the finest resolution watershed boundary unit (NHDPlus) along with the current conditions and conservation scenarios. The process based SWAT model was capable of the fine-scale computation and complex routing used in this project, as indicated by measured data at five gaging stations. The level of detail required for fine-scale spatial simulation made the use of both hard and soft data necessary in model calibration, alongside other model adaptations. Limitations to the model's predictive capacity were due to a paucity of data in the region at the NHDPlus scale rather than due to SWAT functionality. Results of treatment scenarios demonstrate variable effects of structural practices and nutrient management on sediment and nutrient loss dynamics. Targeting treatment to acres with critical outstanding conservation needs provides the largest return on investment in terms of nutrient loss reduction per dollar spent, relative to treating acres with lower inherent nutrient loss vulnerabilities. Importantly, this research raises considerations about use of models to guide land management decisions at very fine spatial scales. Decision makers using these results should be aware of data limitations that hinder fine-scale model interpretation.

Fine-Scale Variability in Harbor Seal Foraging Behavior

PubMed Central

Wilson, Kenady; Lance, Monique; Jeffries, Steven; Acevedo-Gutiérrez, Alejandro

2014-01-01

Understanding the variability of foraging behavior within a population of predators is important for determining their role in the ecosystem and how they may respond to future ecosystem changes. However, such variability has seldom been studied in harbor seals on a fine spatial scale (<30 km). We used a combination of standard and Bayesian generalized linear mixed models to explore how environmental variables influenced the dive behavior of harbor seals. Time-depth recorders were deployed on harbor seals from two haul-out sites in the Salish Sea in 2007 (n = 18) and 2008 (n = 11). Three behavioral bout types were classified from six dive types within each bout; however, one of these bout types was related to haul-out activity and was excluded from analyses. Deep foraging bouts (Type I) were the predominant type used throughout the study; however, variation in the use of bout types was observed relative to haul-out site, season, sex, and light (day/night). The proportional use of Type I and Type II (shallow foraging/traveling) bouts differed dramatically between haul-out sites, seasons, sexes, and whether it was day or night; individual variability between seals also contributed to the observed differences. We hypothesize that this variation in dive behavior was related to habitat or prey specialization by seals from different haul-out sites, or individual variability between seals in the study area. The results highlight the potential influence of habitat and specialization on the foraging behavior of harbor seals, and may help explain the variability in diet that is observed between different haul-out site groups in this population. PMID:24717815

Very high resolution Earth Observation features for testing the direct and indirect effects of landscape structure on local habitat quality

NASA Astrophysics Data System (ADS)

Mairota, Paola; Cafarelli, Barbara; Labadessa, Rocco; Lovergine, Francesco P.; Tarantino, Cristina; Nagendra, Harini; Didham, Raphael K.

2015-02-01

Modelling the empirical relationships between habitat quality and species distribution patterns is the first step to understanding human impacts on biodiversity. It is important to build on this understanding to develop a broader conceptual appreciation of the influence of surrounding landscape structure on local habitat quality, across multiple spatial scales. Traditional models which report that 'habitat amount' in the landscape is sufficient to explain patterns of biodiversity, irrespective of habitat configuration or spatial variation in habitat quality at edges, implicitly treat each unit of habitat as interchangeable and ignore the high degree of interdependence between spatial components of land-use change. Here, we test the contrasting hypothesis, that local habitat units are not interchangeable in their habitat attributes, but are instead dependent on variation in surrounding habitat structure at both patch- and landscape levels. As the statistical approaches needed to implement such hierarchical causal models are observation-intensive, we utilise very high resolution (VHR) Earth Observation (EO) images to rapidly generate fine-grained measures of habitat patch internal heterogeneities over large spatial extents. We use linear mixed-effects models to test whether these remotely-sensed proxies for habitat quality were influenced by surrounding patch or landscape structure. The results demonstrate the significant influence of surrounding patch and landscape context on local habitat quality. They further indicate that such an influence can be direct, when a landscape variable alone influences the habitat structure variable, and/or indirect when the landscape and patch attributes have a conjoined effect on the response variable. We conclude that a substantial degree of interaction among spatial configuration effects is likely to be the norm in determining the ecological consequences of habitat fragmentation, thus corroborating the notion of the spatial context dependence of habitat quality.

Development of a Linear Ion Trap Mass Spectrometer (LITMS) Investigation for Future Planetary Surface Missions

NASA Technical Reports Server (NTRS)

Brinckerhoff, W.; Danell, R.; Van Ameron, F.; Pinnick, V.; Li, X.; Arevalo, R.; Glavin, D.; Getty, S.; Mahaffy, P.; Chu, P.;

Spatial Statistical and Modeling Strategy for Inventorying and Monitoring Ecosystem Resources at Multiple Scales and Resolution Levels

Treesearch

Robin M. Reich; C. Aguirre-Bravo; M.S. Williams

2006-01-01

A statistical strategy for spatial estimation and modeling of natural and environmental resource variables and indicators is presented. This strategy is part of an inventory and monitoring pilot study that is being carried out in the Mexican states of Jalisco and Colima. Fine spatial resolution estimates of key variables and indicators are outputs that will allow the...

Modeling topographic influences on fuel moisture and fire danger in complex terrain to improve wildland fire management decision support

Treesearch

Zachary A. Holden; W. Matt Jolly

2011-01-01

Fire danger rating systems commonly ignore fine scale, topographically-induced weather variations. These variations will likely create heterogeneous, landscape-scale fire danger conditions that have never been examined in detail. We modeled the evolution of fuel moistures and the Energy Release Component (ERC) from the US National Fire Danger Rating System across the...

Wild small mammals as sentinels for the environmental transmission of antimicrobial resistance.

PubMed

Furness, Lauren E; Campbell, Amy; Zhang, Lihong; Gaze, William H; McDonald, Robbie A

2017-04-01

Antimicrobial resistance (AMR) represents a serious threat to human health worldwide. We have tested the use of free-living small mammals (mice, voles and shrews) as sentinels of variation in the distribution of AMR in the environment and the potential for transmission from the natural environment to animal hosts. Escherichia coli isolated from the faeces of small mammals trapped at paired coastal and inland sites were tested for resistance to four antibiotics: trimethoprim, ampicillin, ciprofloxacin and cefotaxime. Coastal individuals were over twice as likely to carry AMR E. coli than inland individuals (79% and 35% respectively), and both between-site and between-species variation was observed. Animals from coastal populations also excreted increased numbers of AMR E. coli and a greater diversity of E. coli phylotypes, including human-associated pathogenic strains. Small mammals appear to be useful bioindicators of fine-scale spatial variation in the distribution of AMR and, potentially, of the risks of AMR transmission to mammalian hosts, including humans. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

MODELING SCALE-DEPENDENT LANDSCAPE PATTERN, DISPERSAL, AND CONNECTIVITY FROM THE PERSPECTIVE OF THE ORGANISM

EPA Science Inventory

Effects of fine- to broad-scale patterns of landscape heterogeneity on dispersal success were examined for organisms varying in life history traits. To systematically control spatial pattern, a landscape model was created by merging physiographically-based maps of simulated land...

A seascape approach to investigating fish spillover across a marine protected area boundary in Hawai'i

USGS Publications Warehouse

Stamoulis, Kostantinos A.; Friedlander, Alan M.

2013-01-01

Marine protected areas (MPAs) can benefit fisheries through export of pelagic eggs and larvae and the net emigration of adults and juveniles (spillover). Spillover was investigated for a marine protected area on the north shore of Oahu, Hawai‘i utilizing a seascape approach. This study incorporated habitat variables and underwater visual surveys of fishes and benthos measured at two distinct scales (125 m2 and 1000 m2) inside and outside the protected area at varying distance from the boundary. The relationship between fish biomass from fine-scale surveys and key habitat variables was found to account for a large portion of the variability for both resource (targeted) fish species (15%) and non-resource fish (28%). The remaining variation in resource fish biomass was significantly correlated with distance from the MPA boundary showing a decreasing gradient from inside to outside (r2 = 0.46, p = 0.001), indicating fish spillover at a local scale (p = 0.45). The evidence of spillover based on the fine-scale surveys was corroborated by results from broad-scale surveys, which also showed a significant relationship (r2 = 0.19, p < 0.01) between resource fish biomass and distance from the MPA boundary. In addition, observed spatial distribution of fishing effort was consistent with predictions that fishers respond to biomass gradients across protected area boundaries. Fish spillover can help mitigate costs associated with the establishment of marine protected areas in terms of lost fishing area and therefore have a positive effect on the attitudes of fishers toward marine reserves and marine protected areas.

Ecosystem services of boreal forests - Carbon budget mapping at high resolution.

PubMed

Akujärvi, Anu; Lehtonen, Aleksi; Liski, Jari

2016-10-01

The carbon (C) cycle of forests produces ecosystem services (ES) such as climate regulation and timber production. Mapping these ES using simple land cover -based proxies might add remarkable inaccuracy to the estimates. A framework to map the current status of the C budget of boreal forested landscapes was developed. The C stocks of biomass and soil and the annual change in these stocks were quantified in a 20 × 20 m resolution at the regional level on mineral soils in southern Finland. The fine-scale variation of the estimates was analyzed geo-statistically. The reliability of the estimates was evaluated by comparing them to measurements from the national multi-source forest inventory. The C stocks of forests increased slightly from the south coast to inland whereas the changes in these stocks were more uniform. The spatial patches of C stocks were larger than those of C stock changes. The patch size of the C stocks reflected the spatial variation in the environmental conditions, and that of the C stock changes the typical area of forest management compartments. The simulated estimates agreed well with the measurements indicating a good mapping framework performance. The mapping framework is the basis for evaluating the effects of forest management alternatives on C budget at high resolution across large spatial scales. It will be coupled with the assessment of other ES and biodiversity to study their relationships. The framework integrated a wide suite of simulation models and extensive inventory data. It provided reliable estimates of the human influence on C cycle in forested landscapes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fine-scale thermal adaptation in a green turtle nesting population

PubMed Central

Weber, Sam B.; Broderick, Annette C.; Groothuis, Ton G. G.; Ellick, Jacqui; Godley, Brendan J.; Blount, Jonathan D.

2012-01-01

The effect of climate warming on the reproductive success of ectothermic animals is currently a subject of major conservation concern. However, for many threatened species, we still know surprisingly little about the extent of naturally occurring adaptive variation in heat-tolerance. Here, we show that the thermal tolerances of green turtle (Chelonia mydas) embryos in a single, island-breeding population have diverged in response to the contrasting incubation temperatures of nesting beaches just a few kilometres apart. In natural nests and in a common-garden rearing experiment, the offspring of females nesting on a naturally hot (black sand) beach survived better and grew larger at hot incubation temperatures compared with the offspring of females nesting on a cooler (pale sand) beach nearby. These differences were owing to shallower thermal reaction norms in the hot beach population, rather than shifts in thermal optima, and could not be explained by egg-mediated maternal effects. Our results suggest that marine turtle nesting behaviour can drive adaptive differentiation at remarkably fine spatial scales, and have important implications for how we define conservation units for protection. In particular, previous studies may have underestimated the extent of adaptive structuring in marine turtle populations that may significantly affect their capacity to respond to environmental change. PMID:21937495

Using Mobile Monitoring to Assess Spatial Variability in Urban Air Pollution Levels: Opportunities and Challenges (Invited)

NASA Astrophysics Data System (ADS)

Larson, T.

2010-12-01

Measuring air pollution concentrations from a moving platform is not a new idea. Historically, however, most information on the spatial variability of air pollutants have been derived from fixed site networks operating simultaneously over space. While this approach has obvious advantages from a regulatory perspective, with the increasing need to understand ever finer scales of spatial variability in urban pollution levels, the use of mobile monitoring to supplement fixed site networks has received increasing attention. Here we present examples of the use of this approach: 1) to assess existing fixed-site fine particle networks in Seattle, WA, including the establishment of new fixed-site monitoring locations; 2) to assess the effectiveness of a regulatory intervention, a wood stove burning ban, on the reduction of fine particle levels in the greater Puget Sound region; and 3) to assess spatial variability of both wood smoke and mobile source impacts in both Vancouver, B.C. and Tacoma, WA. Deducing spatial information from the inherently spatio-temporal measurements taken from a mobile platform is an area that deserves further attention. We discuss the use of “fuzzy” points to address the fine-scale spatio-temporal variability in the concentration of mobile source pollutants, specifically to deduce the broader distribution and sources of fine particle soot in the summer in Vancouver, B.C. We also discuss the use of principal component analysis to assess the spatial variability in multivariate, source-related features deduced from simultaneous measurements of light scattering, light absorption and particle-bound PAHs in Tacoma, WA. With increasing miniaturization and decreasing power requirements of air monitoring instruments, the number of simultaneous measurements that can easily be made from a mobile platform is rapidly increasing. Hopefully the methods used to design mobile monitoring experiments for differing purposes, and the methods used to interpret those measurements will keep pace.

[Spatial distribution and scale effect of species diversity of secondary forests in montane region of eastern Liaoning Province, China.

PubMed

Deng, Li Ping; Bai, Xue Jiao; Qin, Sheng Jin; Wei, Ya Wei; Zhou, Yong Bin; Li, Lu Lu; Niu, Sha Sha; Han, Mei Na

2016-07-01

With secondary forest in the montane region of eastern Liaoning Province as research object, this paper analyzed the spatial distribution and scale effect of Gleason richness index, Simpson dominance index, Shannon diversity index and Pielou evenness index in a 4 hm 2 plot. The results showed that spatial distributions of the four diversity indices showed higher spatial heterogeneity. Variance of the four diversity indices varied with increasing scale. Coefficients of variation of the four diversity indices decreased with increasing scale. The four diversity indices of the tree layer were higher than those of the shrub layer, and the variation tendency varied with increasing scale. The results indicated that sampling scale should be taken into account when studying species diversity in the montane region of eastern Liaoning Province.

Evaluating Sentinel-2 for Lakeshore Habitat Mapping Based on Airborne Hyperspectral Data.

PubMed

Stratoulias, Dimitris; Balzter, Heiko; Sykioti, Olga; Zlinszky, András; Tóth, Viktor R

2015-09-11

Monitoring of lakeshore ecosystems requires fine-scale information to account for the high biodiversity typically encountered in the land-water ecotone. Sentinel-2 is a satellite with high spatial and spectral resolution and improved revisiting frequency and is expected to have significant potential for habitat mapping and classification of complex lakeshore ecosystems. In this context, investigations of the capabilities of Sentinel-2 in regard to the spatial and spectral dimensions are needed to assess its potential and the quality of the expected output. This study presents the first simulation of the high spatial resolution (i.e., 10 m and 20 m) bands of Sentinel-2 for lakeshore mapping, based on the satellite's Spectral Response Function and hyperspectral airborne data collected over Lake Balaton, Hungary in August 2010. A comparison of supervised classifications of the simulated products is presented and the information loss from spectral aggregation and spatial upscaling in the context of lakeshore vegetation classification is discussed. We conclude that Sentinel-2 imagery has a strong potential for monitoring fine-scale habitats, such as reed beds.

Evaluating Sentinel-2 for Lakeshore Habitat Mapping Based on Airborne Hyperspectral Data

PubMed Central

Stratoulias, Dimitris; Balzter, Heiko; Sykioti, Olga; Zlinszky, András; Tóth, Viktor R.

2015-01-01

Monitoring of lakeshore ecosystems requires fine-scale information to account for the high biodiversity typically encountered in the land-water ecotone. Sentinel-2 is a satellite with high spatial and spectral resolution and improved revisiting frequency and is expected to have significant potential for habitat mapping and classification of complex lakeshore ecosystems. In this context, investigations of the capabilities of Sentinel-2 in regard to the spatial and spectral dimensions are needed to assess its potential and the quality of the expected output. This study presents the first simulation of the high spatial resolution (i.e., 10 m and 20 m) bands of Sentinel-2 for lakeshore mapping, based on the satellite’s Spectral Response Function and hyperspectral airborne data collected over Lake Balaton, Hungary in August 2010. A comparison of supervised classifications of the simulated products is presented and the information loss from spectral aggregation and spatial upscaling in the context of lakeshore vegetation classification is discussed. We conclude that Sentinel-2 imagery has a strong potential for monitoring fine-scale habitats, such as reed beds. PMID:26378538

Spatial and temporal variation in evapotranspiration

USDA-ARS?s Scientific Manuscript database

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

Population genomics reveals structure at the individual, host-tree scale and persistence of genotypic variants of the undomesticated yeast Saccharomyces paradoxus in a natural woodland.

PubMed

Xia, Wenjing; Nielly-Thibault, Lou; Charron, Guillaume; Landry, Christian R; Kasimer, Dahlia; Anderson, James B; Kohn, Linda M

2017-02-01

Genetic diversity in experimental, domesticated and wild populations of the related yeasts, Saccharomyces cerevisiae and Saccharomyces paradoxus, has been well described at the global scale. We investigated the population genomics of a local population on a small spatial scale to address two main questions. First, is there genomic variation in a S. paradoxus population at a spatial scale spanning centimetres (microsites) to tens of metres? Second, does the distribution of genomic variants persist over time? Our sample consisted of 42 S. paradoxus strains from 2014 and 43 strains from 2015 collected from the same 72 microsites around four host trees (Quercus rubra and Quercus alba) within 1 km 2 in a mixed hardwood forest in southern Ontario. Six additional S. paradoxus strains recovered from adjacent maple and beech trees in 2015 are also included in the sample. Whole-genome sequencing and genomic SNP analysis revealed five differentiated groups (clades) within the sampled area. The signal of persistence of genotypes in their microsites from 2014 to 2015 was highly significant. Isolates from the same tree tended to be more related than strains from different trees, with limited evidence of dispersal between trees. In growth assays, one genotype had a significantly longer lag phase than the other strains. Our results indicate that different clades coexist at fine spatial scale and that population structure persists over at least a one-year interval in these wild yeasts, suggesting the efficacy of yearly sampling to follow longer term genetic dynamics in future studies. © 2016 John Wiley & Sons Ltd.

Adaptive self-organization in the embryo: its importance to adult anatomy and to tissue engineering.

PubMed

Davies, Jamie A

2018-04-01

The anatomy of healthy humans shows much minor variation, and twin-studies reveal at least some of this variation cannot be explained genetically. A plausible explanation is that fine-scale anatomy is not specified directly in a genetic programme, but emerges from self-organizing behaviours of cells that, for example, place a new capillary where it happens to be needed to prevent local hypoxia. Self-organizing behaviour can be identified by manipulating growing tissues (e.g. putting them under a spatial constraint) and observing an adaptive change that conserves the character of the normal tissue while altering its precise anatomy. Self-organization can be practically useful in tissue engineering but it is limited; generally, it is good for producing realistic small-scale anatomy but large-scale features will be missing. This is because self-organizing organoids miss critical symmetry-breaking influences present in the embryo: simulating these artificially, for example, with local signal sources, makes anatomy realistic even at large scales. A growing understanding of the mechanisms of self-organization is now allowing synthetic biologists to take their first tentative steps towards constructing artificial multicellular systems that spontaneously organize themselves into patterns, which may soon be extended into three-dimensional shapes. © 2017 The Authors Journal of Anatomy published by John Wiley & Sons Ltd on behalf of Anatomical Society.

Fine-Scale Microclimatic Variation Can Shape the Responses of Organisms to Global Change in Both Natural and Urban Environments.

PubMed

Pincebourde, Sylvain; Murdock, Courtney C; Vickers, Mathew; Sears, Michael W

2016-07-01

When predicting the response of organisms to global change, models use measures of climate at a coarse resolution from general circulation models or from downscaled regional models. Organisms, however, do not experience climate at such large scales. The climate heterogeneity over a landscape and how much of that landscape an organism can sample will determine ultimately the microclimates experienced by organisms. This past few decades has seen an important increase in the number of studies reporting microclimatic patterns at small scales. This synthesis intends to unify studies reporting microclimatic heterogeneity (mostly temperature) at various spatial scales, to infer any emerging trends, and to discuss the causes and consequences of such heterogeneity for organismal performance and with respect to changing land use patterns and climate. First, we identify the environmental drivers of heterogeneity across the various spatial scales that are pertinent to ectotherms. The thermal heterogeneity at the local and micro-scales is mostly generated by the architecture or the geometrical features of the microhabitat. Then, the thermal heterogeneity experienced by individuals is modulated by behavior. Second, we survey the literature to quantify thermal heterogeneity from the micro-scale up to the scale of a landscape in natural habitats. Despite difficulties in compiling studies that differ much in their design and aims, we found that there is as much thermal heterogeneity across micro-, local and landscape scales, and that the temperature range is large in general (>9 °C on average, and up to 26 °C). Third, we examine the extent to which urban habitats can be used to infer the microclimatic patterns of the future. Urban areas generate globally drier and warmer microclimatic patterns and recent evidence suggest that thermal traits of ectotherms are adapted to them. Fourth, we explore the interplay between microclimate heterogeneity and the behavioral thermoregulatory abilities of ectotherms in setting their overall performance. We used a random walk framework to show that the thermal heterogeneity allows a more precise behavioral thermoregulation and a narrower temperature distribution of the ectotherm compared to less heterogeneous microhabitats. Finally, we discuss the potential impacts of global change on the fine scale mosaics of microclimates. The amplitude of change may differ between spatial scales. In heterogeneous microhabitats, the amplitude of change at micro-scale, caused by atmospheric warming, can be substantial while it can be limited at the local and landscape scales. We suggest that the warming signal will influence species performance and biotic interactions by modulating the mosaic of microclimates. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Structural Variation Shapes the Landscape of Recombination in Mouse

PubMed Central

Morgan, Andrew P.; Gatti, Daniel M.; Najarian, Maya L.; Keane, Thomas M.; Galante, Raymond J.; Pack, Allan I.; Mott, Richard; Churchill, Gary A.; de Villena, Fernando Pardo-Manuel

2017-01-01

Meiotic recombination is an essential feature of sexual reproduction that ensures faithful segregation of chromosomes and redistributes genetic variants in populations. Multiparent populations such as the Diversity Outbred (DO) mouse stock accumulate large numbers of crossover (CO) events between founder haplotypes, and thus present a unique opportunity to study the role of genetic variation in shaping the recombination landscape. We obtained high-density genotype data from 6886 DO mice, and localized 2.2 million CO events to intervals with a median size of 28 kb. The resulting sex-averaged genetic map of the DO population is highly concordant with large-scale (order 10 Mb) features of previously reported genetic maps for mouse. To examine fine-scale (order 10 kb) patterns of recombination in the DO, we overlaid putative recombination hotspots onto our CO intervals. We found that CO intervals are enriched in hotspots compared to the genomic background. However, as many as 26% of CO intervals do not overlap any putative hotspots, suggesting that our understanding of hotspots is incomplete. We also identified coldspots encompassing 329 Mb, or 12% of observable genome, in which there is little or no recombination. In contrast to hotspots, which are a few kilobases in size, and widely scattered throughout the genome, coldspots have a median size of 2.1 Mb and are spatially clustered. Coldspots are strongly associated with copy-number variant (CNV) regions, especially multi-allelic clusters, identified from whole-genome sequencing of 228 DO mice. Genes in these regions have reduced expression, and epigenetic features of closed chromatin in male germ cells, which suggests that CNVs may repress recombination by altering chromatin structure in meiosis. Our findings demonstrate how multiparent populations, by bridging the gap between large-scale and fine-scale genetic mapping, can reveal new features of the recombination landscape. PMID:28592499

Structural Variation Shapes the Landscape of Recombination in Mouse.

PubMed

Morgan, Andrew P; Gatti, Daniel M; Najarian, Maya L; Keane, Thomas M; Galante, Raymond J; Pack, Allan I; Mott, Richard; Churchill, Gary A; de Villena, Fernando Pardo-Manuel

2017-06-01

Meiotic recombination is an essential feature of sexual reproduction that ensures faithful segregation of chromosomes and redistributes genetic variants in populations. Multiparent populations such as the Diversity Outbred (DO) mouse stock accumulate large numbers of crossover (CO) events between founder haplotypes, and thus present a unique opportunity to study the role of genetic variation in shaping the recombination landscape. We obtained high-density genotype data from [Formula: see text] DO mice, and localized 2.2 million CO events to intervals with a median size of 28 kb. The resulting sex-averaged genetic map of the DO population is highly concordant with large-scale (order 10 Mb) features of previously reported genetic maps for mouse. To examine fine-scale (order 10 kb) patterns of recombination in the DO, we overlaid putative recombination hotspots onto our CO intervals. We found that CO intervals are enriched in hotspots compared to the genomic background. However, as many as [Formula: see text] of CO intervals do not overlap any putative hotspots, suggesting that our understanding of hotspots is incomplete. We also identified coldspots encompassing 329 Mb, or [Formula: see text] of observable genome, in which there is little or no recombination. In contrast to hotspots, which are a few kilobases in size, and widely scattered throughout the genome, coldspots have a median size of 2.1 Mb and are spatially clustered. Coldspots are strongly associated with copy-number variant (CNV) regions, especially multi-allelic clusters, identified from whole-genome sequencing of 228 DO mice. Genes in these regions have reduced expression, and epigenetic features of closed chromatin in male germ cells, which suggests that CNVs may repress recombination by altering chromatin structure in meiosis. Our findings demonstrate how multiparent populations, by bridging the gap between large-scale and fine-scale genetic mapping, can reveal new features of the recombination landscape. Copyright © 2017 by the Genetics Society of America.

Sedimentation processes in a coral reef embayment: Hanalei Bay, Kauai

USGS Publications Warehouse

Storlazzi, C.D.; Field, M.E.; Bothner, Michael H.; Presto, M.K.; Draut, A.E.

2009-01-01

Oceanographic measurements and sediment samples were collected during the summer of 2006 as part of a multi-year study of coastal circulation and the fate of terrigenous sediment on coral reefs in Hanalei Bay, Kauai. The goal of this study was to better understand sediment dynamics in a coral reef-lined embayment where winds, ocean surface waves, and river floods are important processes. During a summer period that was marked by two wave events and one river flood, we documented significant differences in sediment trap collection rates and the composition, grain size, and magnitude of sediment transported in the bay. Sediment trap collection rates were well correlated with combined wave-current near-bed shear stresses during the non-flood periods but were not correlated during the flood. The flood's delivery of fine-grained sediment to the bay initially caused high turbidity and sediment collection rates off the river mouth but the plume dispersed relatively quickly. Over the next month, the flood deposit was reworked by mild waves and currents and the fine-grained terrestrial sediment was advected around the bay and collected in sediment traps away from the river mouth, long after the turbid surface plume was gone. The reworked flood deposits, due to their longer duration of influence and proximity to the seabed, appear to pose a greater long-term impact to benthic coral reef communities than the flood plumes themselves. The results presented here display how spatial and temporal differences in hydrodynamic processes, which result from variations in reef morphology and orientation, cause substantial variations in the deposition, residence time, resuspension, and advection of both reef-derived and fluvial sediment over relatively short spatial scales in a coral reef embayment.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Variational Data Assimilation of AirSWOT Data into the 2D Shallow Water Model DassFlow. Method and Test Case on the Garonne River (France)

NASA Astrophysics Data System (ADS)

Garambois, Pierre-Andre; Biancamaria, Sylvian; Monnier, Jerome; Roux, Helene; Dartus, Denis

2013-09-01

For continental water bodies and river hydraulic studies, water level measurements are fundamental information, yet they are currently mostly provided by punctual gauging stations located on the main river channel. That is why they are sparsely distributed in space and can have gaps in their time series (e.g. sensors failures). These issues can be compensated by remote sensing data, which have considerably contributed to improve the observation and understanding of physical processes in hydrology and hydraulics in general. Satellites such as SWOT (Surface Water and Ocean Topography) would give spatially distributed information on water elevations at an unprecedented resolution. Gathering pre-mission data over specific and varied science targets is the purpose of the AirSWOT airborne campaign in order to implement and test SWOT products retrieval algorithms. A reach of the Garonne River, downstream of Toulouse (FRANCE), is a proposed study area for AirSWOT flights. This choice is motivated by previous studies already performed on this section of 100km reach of the river. Moreover, on this highly instrumented and studied portion of river many typical free surface flow modelling issue has been encountered, and this river reach represents the limit of SWOT observation capability. The 2D hydrodynamic model DassFlow especially designed for variational data assimilation will be used on this portion of the Garonne River with cartographic sensitivity analysis. An identification strategy would allow retrieving spatial roughness along the main channel, variation of the local topographic slope or else temporal evolution of the streamflow. Addressing such problems and studying horizontal and vertical river sinuosity would improve fine scale hydraulics representation and understanding, which could additionally help to improve global discharge algorithms with different scales and complexity levels.

The distribution of intra-genomically variable dinoflagellate symbionts at Lord Howe Island, Australia

NASA Astrophysics Data System (ADS)

Wilkinson, Shaun P.; Pontasch, Stefanie; Fisher, Paul L.; Davy, Simon K.

2016-06-01

The symbiotic dinoflagellates of corals and other marine invertebrates ( Symbiodinium) are essential to the development of shallow-water coral reefs. This genus contains considerable genetic diversity and a corresponding range of physiological and ecological traits. Most genetic variation arises through the accumulation of somatic mutations that arise during asexual reproduction. Yet growing evidence suggests that occasional sexual reproductive events also occur within, and perhaps between, Symbiodinium lineages, further contributing to the pool of genetic variation available for evolutionary adaptation. Intra-genomic variation can therefore arise from both sexual and asexual reproductive processes, making it difficult to discern its underlying causes and consequences. We used quantitative PCR targeting the ITS2 locus to estimate proportions of genetically homogeneous symbionts and intra-genomically variable Symbiodinium (IGV Symbiodinium) in the reef-building coral Pocillopora damicornis at Lord Howe Island, Australia. We then sampled colonies through time and at a variety of spatial scales to find out whether the distribution of these symbionts followed patterns consistent with niche partitioning. Estimated ratios of homogeneous to IGV Symbiodinium varied between colonies within sites (metres to tens of metres) and between sites separated by hundreds to thousands of metres, but remained stable within colonies through time. Symbiont ratios followed a temperature gradient, with the local thermal maximum emerging as a negative predictor for the estimated proportional abundance of IGV Symbiodinium. While this pattern may result from fine-scale spatial population structure, it is consistent with an increased susceptibility to thermal stress, suggesting that the evolutionary processes that generate IGV (such as inter-lineage recombination and the accumulation of somatic mutations at the ITS2 locus) may have important implications for the fitness of the symbiont and that of the coral host.

Estimating the spatial scales of landscape effects on abundance

Treesearch

Richard Chandler; Jeffrey Hepinstall-Cymerman

2016-01-01

Spatial variation in abundance is influenced by local- and landscape-level environmental variables, but modeling landscape effects is challenging because the spatial scales of the relationships are unknown. Current approaches involve buffering survey locations with polygons of various sizes and using model selection to identify the best scale. The buffering...

Predation Risk Shapes Social Networks in Fission-Fusion Populations

PubMed Central

Kelley, Jennifer L.; Morrell, Lesley J.; Inskip, Chloe; Krause, Jens; Croft, Darren P.

2011-01-01

Predation risk is often associated with group formation in prey, but recent advances in methods for analysing the social structure of animal societies make it possible to quantify the effects of risk on the complex dynamics of spatial and temporal organisation. In this paper we use social network analysis to investigate the impact of variation in predation risk on the social structure of guppy shoals and the frequency and duration of shoal splitting (fission) and merging (fusion) events. Our analyses revealed that variation in the level of predation risk was associated with divergent social dynamics, with fish in high-risk populations displaying a greater number of associations with overall greater strength and connectedness than those from low-risk sites. Temporal patterns of organisation also differed according to predation risk, with fission events more likely to occur over two short time periods (5 minutes and 20 minutes) in low-predation fish and over longer time scales (>1.5 hours) in high-predation fish. Our findings suggest that predation risk influences the fine-scale social structure of prey populations and that the temporal aspects of organisation play a key role in defining social systems. PMID:21912627

Variations in the fine-structure constant constraining gravity theories

NASA Astrophysics Data System (ADS)

Bezerra, V. B.; Cunha, M. S.; Muniz, C. R.; Tahim, M. O.; Vieira, H. S.

2016-08-01

In this paper, we investigate how the fine-structure constant, α, locally varies in the presence of a static and spherically symmetric gravitational source. The procedure consists in calculating the solution and the energy eigenvalues of a massive scalar field around that source, considering the weak-field regime. From this result, we obtain expressions for a spatially variable fine-structure constant by considering suitable modifications in the involved parameters admitting some scenarios of semi-classical and quantum gravities. Constraints on free parameters of the approached theories are calculated from astrophysical observations of the emission spectra of a white dwarf. Such constraints are finally compared with those obtained in the literature.

The utility of satellite observations for constraining fine-scale and transient methane sources

NASA Astrophysics Data System (ADS)

Turner, A. J.; Jacob, D.; Benmergui, J. S.; Brandman, J.; White, L.; Randles, C. A.

2017-12-01

Resolving differences between top-down and bottom-up emissions of methane from the oil and gas industry is difficult due, in part, to their fine-scale and often transient nature. There is considerable interest in using atmospheric observations to detect these sources. Satellite-based instruments are an attractive tool for this purpose and, more generally, for quantifying methane emissions on fine scales. A number of instruments are planned for launch in the coming years from both low earth and geostationary orbit, but the extent to which they can provide fine-scale information on sources has yet to be explored. Here we present an observation system simulation experiment (OSSE) exploring the tradeoffs between pixel resolution, measurement frequency, and instrument precision on the fine-scale information content of a space-borne instrument measuring methane. We use the WRF-STILT Lagrangian transport model to generate more than 200,000 column footprints at 1.3×1.3 km2 spatial resolution and hourly temporal resolution over the Barnett Shale in Texas. We sub-sample these footprints to match the observing characteristics of the planned TROPOMI and GeoCARB instruments as well as different hypothetical observing configurations. The information content of the various observing systems is evaluated using the Fisher information matrix and its singular values. We draw conclusions on the capabilities of the planned satellite instruments and how these capabilities could be improved for fine-scale source detection.

The walk is never random: subtle landscape effects shape gene flow in a continuous white-tailed deer population in the Midwestern United States

USGS Publications Warehouse

Robinson, Stacie J.; Samuel, Michael D.; Lopez, Davin L.; Shelton, Paul

2012-01-01

One of the pervasive challenges in landscape genetics is detecting gene flow patterns within continuous populations of highly mobile wildlife. Understanding population genetic structure within a continuous population can give insights into social structure, movement across the landscape and contact between populations, which influence ecological interactions, reproductive dynamics or pathogen transmission. We investigated the genetic structure of a large population of deer spanning the area of Wisconsin and Illinois, USA, affected by chronic wasting disease. We combined multiscale investigation, landscape genetic techniques and spatial statistical modelling to address the complex questions of landscape factors influencing population structure. We sampled over 2000 deer and used spatial autocorrelation and a spatial principal components analysis to describe the population genetic structure. We evaluated landscape effects on this pattern using a spatial autoregressive model within a model selection framework to test alternative hypotheses about gene flow. We found high levels of genetic connectivity, with gradients of variation across the large continuous population of white-tailed deer. At the fine scale, spatial clustering of related animals was correlated with the amount and arrangement of forested habitat. At the broader scale, impediments to dispersal were important to shaping genetic connectivity within the population. We found significant barrier effects of individual state and interstate highways and rivers. Our results offer an important understanding of deer biology and movement that will help inform the management of this species in an area where overabundance and disease spread are primary concerns.

Evaluation of aquatic biota in relation to environmental characteristics measured at multiple scales in agricultural streams of the Midwest, 1993-2004

USGS Publications Warehouse

Hambrook Berkman, Julie A.; Scudder, Barbara C.; Lutz, Michelle A.; Harris, Mitchell A.

2010-01-01

This study evaluated the relations between algal, invertebrate, and fish assemblages and physical environmental characteristics of streams at the reach, segment, and watershed scale in agricultural settings in the Midwest. The 86 stream sites selected for study were in predominantly agricultural watersheds sampled as part of the U.S. Geological Survey's National Water-Quality Assessment Program. Species abundance and over 130 biological metrics were used to determine which aspects of the assemblages were most sensitive to change at the three spatial scales. Digital orthophotograph-based riparian land use/land cover was used for analyses of riparian conditions at the reach and segment scales. The percentage area of different land-use/land-cover types was also determined for each watershed. Out of over 230 environmental characteristics examined, those that best explained variation in the biotic assemblages at each spatial scale include the following: 1) reach: bank vegetative cover, fine silty substrate, and open canopy angle; 2) segment: woody vegetation and cropland in the 250-m riparian buffer, and average length of undisturbed buffer; and 3) watershed: land use/land cover (both total forested and row crop), low-permeability soils, slope, drainage area, and latitude. All three biological assemblages, especially fish, correlated more with land use/land cover and other physical characteristics at the watershed scale than at the reach or segment scales. This study identifies biotic measures that can be used to evaluate potential improvements resulting from agricultural best-management practices and other conservation efforts, as well as evaluate potential impairment from urban development or other disturbances.

Stable genetic structure and connectivity in pollution-adapted and nearby pollution-sensitive populations of Fundulus heteroclitus

PubMed Central

Biancani, Leann M.; Flight, Patrick A.; Nacci, Diane E.; Rand, David M.; Crawford, Douglas L.; Oleksiak, Marjorie F.

2018-01-01

Populations of the non-migratory estuarine fish Fundulus heteroclitus inhabiting the heavily polluted New Bedford Harbour (NBH) estuary have shown inherited tolerance to local pollutants introduced to their habitats in the past 100 years. Here we examine two questions: (i) Is there pollution-driven selection on the mitochondrial genome across a fine geographical scale? and (ii) What is the pattern of migration among sites spanning a strong pollution gradient? Whole mitochondrial genomes were analysed for 133 F. heteroclitus from seven nearby collection sites: four sites along the NBH pollution cline (approx. 5 km distance), which had pollution-adapted fish, as well as one site adjacent to the pollution cline and two relatively unpolluted sites about 30 km away, which had pollution-sensitive fish. Additionally, we used microsatellite analyses to quantify genetic variation over three F. heteroclitus generations in both pollution-adapted and sensitive individuals collected from two sites at two different time points (1999/2000 and 2007/2008). Our results show no evidence for a selective sweep of mtDNA in the polluted sites. Moreover, mtDNA analyses revealed that both pollution-adapted and sensitive populations harbour similar levels of genetic diversity. We observed a high level of non-synonymous mutations in the most polluted site. This is probably associated with a reduction in Ne and concomitant weakening of purifying selection, a demographic expansion following a pollution-related bottleneck or increased mutation rates. Our demographic analyses suggest that isolation by distance influences the distribution of mtDNA genetic variation between the pollution cline and the clean populations at broad spatial scales. At finer scales, population structure is patchy, and neither spatial distance, pollution concentration or pollution tolerance is a good predictor of mtDNA variation. Lastly, microsatellite analyses revealed stable population structure over the last decade. PMID:29892357

Fine structure of striations observed in barium plasma injections in the magnetospheric cleft

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

Simons, D.J.; Eastman, T.E.; Pongratz, M.B.

1976-01-01

In January and November of 1975, the Los Alamos Scientific Laboratory sponsored four high altitude shaped charge barium plasma injections in the magnetospheric cleft region. These experiments were TORDO UNO (January 6), TORDO DOS (January 11), PERIQUITO UNO (November 25), and PERIQUITO DOS (November 28). All four injections took place near 500 km altitude, and optical data were taken from two aircraft and a ground station. The TORDO DOS and the PERIQUITO experiments showed rapid formation of striations (within one minute after injection), and fast horizontal spreading in contrast with TORDO UNO. In PERIQUITO DOS, the debris cloud spread magneticallymore » east-west with a small net northerly motion. TORDO UNO shows very rapid poleward motion, and the remaining two events resulted in magnetically east-west horizontal spreading, with no noticeable poleward motion. Striations observed in the PERIQUITO DOS experiment separate in opposite directions with relative velocities of up to 3 km/sec. These field-aligned structures appear to form in sheets of approximately constant magnetic latitude. Significant spatial variations occur on a scale of less than 200 meters. Spatial frequency power spectra across these striations have been determined at various times. Observations of the debris cloud and the fast barium streak show strong field-aligned coherency of striation fine structure, indicating a field line mapping of transverse electric fields and gradients.« less

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions

PubMed Central

Wilson, Adam M.; Jetz, Walter

2016-01-01

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties. PMID:27031693

Can basin land use effects on physical characteristics of streams be determined at broad geographic scales?

USGS Publications Warehouse

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.

Modeling spatial variation in avian survival and residency probabilities

USGS Publications Warehouse

Saracco, James F.; Royle, J. Andrew; DeSante, David F.; Gardner, Beth

2010-01-01

The importance of understanding spatial variation in processes driving animal population dynamics is widely recognized. Yet little attention has been paid to spatial modeling of vital rates. Here we describe a hierarchical spatial autoregressive model to provide spatially explicit year-specific estimates of apparent survival (phi) and residency (pi) probabilities from capture-recapture data. We apply the model to data collected on a declining bird species, Wood Thrush (Hylocichla mustelina), as part of a broad-scale bird-banding network, the Monitoring Avian Productivity and Survivorship (MAPS) program. The Wood Thrush analysis showed variability in both phi and pi among years and across space. Spatial heterogeneity in residency probability was particularly striking, suggesting the importance of understanding the role of transients in local populations. We found broad-scale spatial patterning in Wood Thrush phi and pi that lend insight into population trends and can direct conservation and research. The spatial model developed here represents a significant advance over approaches to investigating spatial pattern in vital rates that aggregate data at coarse spatial scales and do not explicitly incorporate spatial information in the model. Further development and application of hierarchical capture-recapture models offers the opportunity to more fully investigate spatiotemporal variation in the processes that drive population changes.

Fine-Scale Spatial Variability of Precipitation, Soil, and Plant Water Isotopes

NASA Astrophysics Data System (ADS)

Goldsmith, G. R.; Braun, S.; Romero, C.; Engbersen, N.; Gessler, A.; Siegwolf, R. T.; Schmid, L.

2015-12-01

Introduction: The measurement of stable isotope ratios of water has become fundamental in advancing our understanding of environmental patterns and processes, particularly with respect to understanding the movement of water within the soil-plant-atmosphere continuum. While considerable research has explored the temporal variation in stable isotope ratios of water in the environment, our understanding of the spatial variability of these isotopes remains poorly understood. Methods: We collected spatially explicit samples of throughfall and soil water (n=150 locations) from a 1 ha plot delineated in a mixed deciduous forest in the northern Alps of Switzerland. We complemented this with fully sunlit branch and leaf samples (n = 60 individuals) collected from Picea abies and Fagus sylvatica between 14:00 and 16:00 on the same day by means of a helicopter. Soil and plant waters were extracted using cryogenic vacuum distillation and all samples were analyzed for δ18O using an isotope ratio mass spectrometer. Results: The mean δ18O of throughfall (-3.3 ± 0.8‰) indicated some evaporative enrichment associated with passage through the canopy, but this did not significantly differ from the precipitation collected in nearby open sites (-4.05‰). However, soil was depleted (-7.0 ± 1.8‰) compared to throughfall and there was no significant relationship between the two, suggesting that the sampling for precipitation inputs did not capture all the sources (e.g. stream water, which was -11.5‰) contributing to soil water δ18O ratios. Evaporative enrichment of δ18O was higher in leaves of Fagus (14.8 ± 1.8‰) than in leaves of Picea (11.8 ± 1.7‰). Sampling within crowns of each species (n = 5 branches each from 5 individuals) indicated that variability in a single individual is similar to that among individuals. Discussion: Stable isotopes of water are frequently engaged for studies of ecohydrology, plant ecophysiology, and paleoclimatology. Our results help constrain the variability within different water sources across space (e.g. when vizualized as isoscapes), as well as the extent of fractionation among those sources as water moves through the critical zone. In doing so, we also provide insight into how environment shapes this fine-scale variation in order to inform future applications of water isotopes.

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.

Does Encope emarginata (Echinodermata: Echinoidea) affect spatial variation patterns of estuarine subtidal meiofauna and microphytobenthos?

NASA Astrophysics Data System (ADS)

Brustolin, Marco C.; Thomas, Micheli C.; Mafra, Luiz L.; Lana, Paulo da Cunha

2014-08-01

Foraging macrofauna, such as the sand dollar Encope emarginata, can modify sediment properties and affect spatial distribution patterns of microphytobenthos and meiobenthos at different spatial scales. We adopted a spatial hierarchical approach composed of five spatial levels (km, 100 s m, 10 s m, 1 s m and cm) to describe variation patterns of microphytobenthos, meiobenthos and sediment variables in shallow subtidal regions in the subtropical Paranaguá Bay (Southern Brazil) with live E. emarginata (LE), dead E. emarginata (only skeletons - (DE), and no E. emarginata (WE). The overall structure of microphytobenthos and meiofauna was always less variable at WE and much of variation at the scale of 100 s m was related to variability within LE and DE, due to foraging activities or to the presence of shell hashes. Likewise, increased variability in chlorophyll-a and phaeopigment contents was observed among locations within LE, although textural parameters of sediment varied mainly at smaller scales. Variations within LE were related to changes on the amount and quality of food as a function of sediment heterogeneity induced by the foraging behavior of sand dollars. We provide strong evidence that top-down effects related to the occurrence of E. emarginata act in synergy with bottom-up structuring related to hydrodynamic processes in determining overall benthic spatial variability. Conversely, species richness is mainly influenced by environmental heterogeneity at small spatial scales (centimeters to meters), which creates a mosaic of microhabitats.

Spatial identification of tributary impacts in river networks

Treesearch

Christian E. Torgersen; Robert E. Gresswell; Douglas S. Bateman; Kelly M. Burnett

2008-01-01

The ability to assess spatial patterns of ecological conditions in river networks has been confounded by difficulties of measuring and perceiving features that are essentially invisible to observers on land and to aircraft and satellites from above. The nature of flowing water, which is opaque or at best semi-transparent, makes it difficult to visualize fine-scale...

Linking movement behavior and fine-scale genetic structure to model landscape connectivity for bobcats (Lynx rufus)

Treesearch

Dawn M. Reding; Samuel A. Cushman; Todd E. Gosselink; William R. Clark

2013-01-01

Spatial heterogeneity can constrain the movement of individuals and consequently genes across a landscape, influencing demographic and genetic processes. In this study, we linked information on landscape composition, movement behavior, and genetic differentiation to gain a mechanistic understanding of how spatial heterogeneity may influence movement and gene flow of...

Shape-driven 3D segmentation using spherical wavelets.

PubMed

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2006-01-01

This paper presents a novel active surface segmentation algorithm using a multiscale shape representation and prior. We define a parametric model of a surface using spherical wavelet functions and learn a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial locations in a training set. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior in the segmentation framework. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to the segmentation of brain caudate nucleus, of interest in the study of schizophrenia. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm by capturing finer shape details.

Method for identifying subsurface fluid migration and drainage pathways in and among oil and gas reservoirs using 3-D and 4-D seismic imaging

DOEpatents

Anderson, R.N.; Boulanger, A.; Bagdonas, E.P.; Xu, L.; He, W.

1996-12-17

The invention utilizes 3-D and 4-D seismic surveys as a means of deriving information useful in petroleum exploration and reservoir management. The methods use both single seismic surveys (3-D) and multiple seismic surveys separated in time (4-D) of a region of interest to determine large scale migration pathways within sedimentary basins, and fine scale drainage structure and oil-water-gas regions within individual petroleum producing reservoirs. Such structure is identified using pattern recognition tools which define the regions of interest. The 4-D seismic data sets may be used for data completion for large scale structure where time intervals between surveys do not allow for dynamic evolution. The 4-D seismic data sets also may be used to find variations over time of small scale structure within individual reservoirs which may be used to identify petroleum drainage pathways, oil-water-gas regions and, hence, attractive drilling targets. After spatial orientation, and amplitude and frequency matching of the multiple seismic data sets, High Amplitude Event (HAE) regions consistent with the presence of petroleum are identified using seismic attribute analysis. High Amplitude Regions are grown and interconnected to establish plumbing networks on the large scale and reservoir structure on the small scale. Small scale variations over time between seismic surveys within individual reservoirs are identified and used to identify drainage patterns and bypassed petroleum to be recovered. The location of such drainage patterns and bypassed petroleum may be used to site wells. 22 figs.

Method for identifying subsurface fluid migration and drainage pathways in and among oil and gas reservoirs using 3-D and 4-D seismic imaging

DOEpatents

Anderson, Roger N.; Boulanger, Albert; Bagdonas, Edward P.; Xu, Liqing; He, Wei

1996-01-01

The invention utilizes 3-D and 4-D seismic surveys as a means of deriving information useful in petroleum exploration and reservoir management. The methods use both single seismic surveys (3-D) and multiple seismic surveys separated in time (4-D) of a region of interest to determine large scale migration pathways within sedimentary basins, and fine scale drainage structure and oil-water-gas regions within individual petroleum producing reservoirs. Such structure is identified using pattern recognition tools which define the regions of interest. The 4-D seismic data sets may be used for data completion for large scale structure where time intervals between surveys do not allow for dynamic evolution. The 4-D seismic data sets also may be used to find variations over time of small scale structure within individual reservoirs which may be used to identify petroleum drainage pathways, oil-water-gas regions and, hence, attractive drilling targets. After spatial orientation, and amplitude and frequency matching of the multiple seismic data sets, High Amplitude Event (HAE) regions consistent with the presence of petroleum are identified using seismic attribute analysis. High Amplitude Regions are grown and interconnected to establish plumbing networks on the large scale and reservoir structure on the small scale. Small scale variations over time between seismic surveys within individual reservoirs are identified and used to identify drainage patterns and bypassed petroleum to be recovered. The location of such drainage patterns and bypassed petroleum may be used to site wells.

Soil moisture variability across different scales in an Indian watershed for satellite soil moisture product validation

NASA Astrophysics Data System (ADS)

Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra B.

2016-05-01

Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA's Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected at two nested scale extents (0.5 km and 3 km) to understand the trend of soil moisture variability across these scales. This ground-based soil moisture sampling was conducted in the 500 km2 Rana watershed situated in eastern India. The study area is characterized as sub-humid, sub-tropical climate with average annual rainfall of about 1456 mm. Three 3x3 km square grids were sampled intensively once a day at 49 locations each, at a spacing of 0.5 km. These intensive sampling locations were selected on the basis of different topography, soil properties and vegetation characteristics. In addition, measurements were also made at 9 locations around each intensive sampling grid at 3 km spacing to cover a 9x9 km square grid. Intensive fine scale soil moisture sampling as well as coarser scale samplings were made using both impedance probes and gravimetric analyses in the study watershed. The ground-based soil moisture samplings were conducted during the day, concurrent with the SMAP descending overpass. Analysis of soil moisture spatial variability in terms of areal mean soil moisture and the statistics of higher-order moments, i.e., the standard deviation, and the coefficient of variation are presented. Results showed that the standard deviation and coefficient of variation of measured soil moisture decreased with extent scale by increasing mean soil moisture.

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

Aridity and decomposition processes in complex landscapes

NASA Astrophysics Data System (ADS)

Ossola, Alessandro; Nyman, Petter

2015-04-01

Decomposition of organic matter is a key biogeochemical process contributing to nutrient cycles, carbon fluxes and soil development. The activity of decomposers depends on microclimate, with temperature and rainfall being major drivers. In complex terrain the fine-scale variation in microclimate (and hence water availability) as a result of slope orientation is caused by differences in incoming radiation and surface temperature. Aridity, measured as the long-term balance between net radiation and rainfall, is a metric that can be used to represent variations in water availability within the landscape. Since aridity metrics can be obtained at fine spatial scales, they could theoretically be used to investigate how decomposition processes vary across complex landscapes. In this study, four research sites were selected in tall open sclerophyll forest along a aridity gradient (Budyko dryness index ranging from 1.56 -2.22) where microclimate, litter moisture and soil moisture were monitored continuously for one year. Litter bags were packed to estimate decomposition rates (k) using leaves of a tree species not present in the study area (Eucalyptus globulus) in order to avoid home-field advantage effects. Litter mass loss was measured to assess the activity of macro-decomposers (6mm litter bag mesh size), meso-decomposers (1 mm mesh), microbes above-ground (0.2 mm mesh) and microbes below-ground (2 cm depth, 0.2 mm mesh). Four replicates for each set of bags were installed at each site and bags were collected at 1, 2, 4, 7 and 12 months since installation. We first tested whether differences in microclimate due to slope orientation have significant effects on decomposition processes. Then the dryness index was related to decomposition rates to evaluate if small-scale variation in decomposition can be predicted using readily available information on rainfall and radiation. Decomposition rates (k), calculated fitting single pool negative exponential models, generally decreased with increasing aridity with k going from 0.0025 day-1 on equatorial (dry) facing slopes to 0.0040 day-1 on polar (wet) facing slopes. However, differences in temperature as a result of morning vs afternoon sun on east and west aspects, respectively, (not captured in the aridity metric) resulted in poor prediction of decomposition for the sites located in the intermediate aridity range. Overall the results highlight that relatively small differences in microclimate due to slope orientation can have large effects on decomposition. Future research will aim to refine the aridity metric to better resolve small scale variation in surface temperature which is important when up-scaling decomposition processes to landscapes.

SEARCH: Spatially Explicit Animal Response to Composition of Habitat.

PubMed

Pauli, Benjamin P; McCann, Nicholas P; Zollner, Patrick A; Cummings, Robert; Gilbert, Jonathan H; Gustafson, Eric J

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-based models (IBMs), however, vastly oversimplify animal behavior and such behavioral minimalism diminishes the value of these models. We present program SEARCH (Spatially Explicit Animal Response to Composition of Habitat), a spatially explicit, individual-based, population model of animal dispersal through realistic landscapes. SEARCH uses values in Geographic Information System (GIS) maps to apply rules that animals follow during dispersal, thus allowing virtual animals to respond to fine-scale features of the landscape and maintain a detailed memory of areas sensed during movement. SEARCH also incorporates temporally dynamic landscapes so that the environment to which virtual animals respond can change during the course of a simulation. Animals in SEARCH are behaviorally dynamic and able to respond to stimuli based upon their individual experiences. Therefore, SEARCH is able to model behavioral traits of dispersing animals at fine scales and with many dynamic aspects. Such added complexity allows investigation of unique ecological questions. To illustrate SEARCH's capabilities, we simulated case studies using three mammals. We examined the impact of seasonally variable food resources on the weight distribution of dispersing raccoons (Procyon lotor), the effect of temporally dynamic mortality pressure in combination with various levels of behavioral responsiveness in eastern chipmunks (Tamias striatus), and the impact of behavioral plasticity and home range selection on disperser mortality and weight change in virtual American martens (Martes americana). These simulations highlight the relevance of SEARCH for a variety of applications and illustrate benefits it can provide for conservation planning.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau.

PubMed

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.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau

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.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau

PubMed Central

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

Hybrid Multiscale Finite Volume method for multiresolution simulations of flow and reactive transport in porous media

NASA Astrophysics Data System (ADS)

Barajas-Solano, D. A.; Tartakovsky, A. M.

2017-12-01

We present a multiresolution method for the numerical simulation of flow and reactive transport in porous, heterogeneous media, based on the hybrid Multiscale Finite Volume (h-MsFV) algorithm. The h-MsFV algorithm allows us to couple high-resolution (fine scale) flow and transport models with lower resolution (coarse) models to locally refine both spatial resolution and transport models. The fine scale problem is decomposed into various "local'' problems solved independently in parallel and coordinated via a "global'' problem. This global problem is then coupled with the coarse model to strictly ensure domain-wide coarse-scale mass conservation. The proposed method provides an alternative to adaptive mesh refinement (AMR), due to its capacity to rapidly refine spatial resolution beyond what's possible with state-of-the-art AMR techniques, and the capability to locally swap transport models. We illustrate our method by applying it to groundwater flow and reactive transport of multiple species.

Spatial multi-scale variability of soil nutrients in relation to environmental factors in a typical agricultural region, eastern China.

PubMed

Liu, Yang; Lv, Jianshu; Zhang, Bing; Bi, Jun

2013-04-15

Identifying the sources of spatial variability and deficiency risk of soil nutrients is a crucial issue for soil and agriculture management. A total of 1247 topsoil samples (0-20 cm) were collected at the nodes of a 2×2 km grid in Rizhao City and the contents of soil organic carbon (OC), total nitrogen (TN), and total phosphorus (TP) were determined. Factorial kriging analysis (FKA), stepwise multiple regression, and indicator kriging (IK) were appled to investigate the scale dependent correlations among soil nutrients, identify the sources of spatial variability at each spatial scale, and delineate the potential risk of soil nutrient deficiency. Linear model of co-regionalization (LMC) fitting indicated that the presence of multi-scale variation was comprised of nugget effect, an exponential structure with a range of 12 km (local scale), and a spherical structure with a range of 84 km (regional scale). The short-range variation of OC and TN was mainly dominated by land use types, and TP was controlled by terrain. At long-range scale, spatial variation of OC, TN, and TP was dominated by parent material. Indicator kriging maps depicted the probability of soil nutrient deficiency compared with the background values in eastern Shandong province. The high deficiency risk area of all nutrient integration was mainly located in eastern and northwestern parts. Copyright © 2013 Elsevier B.V. All rights reserved.

Effects of Spatial Variability of Soil Properties on the Triggering of Rainfall-Induced Shallow Landslides

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.

Implications of the Observed Mesoscale Variations of Clouds for Earth's Radiation Budget

NASA Technical Reports Server (NTRS)

Rossow, William B.; Delo, Carl; Cairns, Brian; Hansen, James E. (Technical Monitor)

2001-01-01

The effect of small-spatial-scale cloud variations on radiative transfer in cloudy atmospheres currently receives a lot of research attention, but the available studies are not very clear about which spatial scales are important and report a very large range of estimates of the magnitude of the effects. Also, there have been no systematic investigations of how to measure and represent these cloud variations. We exploit the cloud climatology produced by the International Satellite Cloud Climatology Project (ISCCP) to: (1) define and test different methods of representing cloud variation statistics, (2) investigate the range of spatial scales that should be included, (3) characterize cloud variations over a range of space and time scales covering mesoscale (30 - 300 km, 3-12 hr) into part of the lower part of the synoptic scale (300 - 3000 km, 1-30 days), (4) obtain a climatology of the optical thickness, emissivity and cloud top temperature variability of clouds that can be used in weather and climate GCMS, together with the parameterization proposed by Cairns et al. (1999), to account for the effects of small-scale cloud variations on radiative fluxes, and (5) evaluate the effect of observed cloud variations on Earth's radiation budget. These results lead to the formulation of a revised conceptual model of clouds for use in radiative transfer calculations in GCMS. The complete variability climatology can be obtained from the ISCCP Web site at http://isccp.giss.nasa.gov.

Diagnostic modeling of trace metal partitioning in south San Francisco Bay

USGS Publications Warehouse

Wood, T. W.; Baptista, A. M.; Kuwabara, J.S.; Flegal, A.R.

1995-01-01

The numerical results indicate that aqueous speciation will control basin-scale spatial variations in the apparent distribution coefficient, Kda, if the system is close to equilibrium. However, basin-scale spatial variations in Kda are determined by the location of the sources of metal and the suspended solids concentration of the receiving water if the system is far from equilibrium. The overall spatial variability in Kda also increases as the system moves away from equilibrium.

Distributions of soil phosphorus in China's densely populated village landscapes

Treesearch

Jiaguo Jiao; Erle C. Ellis; Ian Yesilonis; Junxi Wu; Hongqing Wang; Huixin Li; Linzhang Yang

2010-01-01

Purpose Village landscapes, which integrate small-scale agriculture with housing, forestry and a host of other land use practices, cover more than 2x106 km2 across China. Village lands tend to be managed at very fine spatial scales (≤30 m), with managers altering soil fertility and even terrain by terracing,...

The Spatial Scale and Spatial Configuration of Residential Settlement: Measuring Segregation in the Postbellum South

PubMed Central

Logan, John R.; Martinez, Matthew

2018-01-01

Studies of residential segregation typically focus on its degree without questioning its scale and configuration. We study Southern cities in 1880 to emphasize the salience of these spatial dimensions. Distance-based and sequence indices can reflect spatial patterns but with some limitations, while geocoded 100% population data make possible more informative measures. One improvement is flexibility in spatial scale, ranging from adjacent buildings to whole districts of the city. Another is the ability to map patterns in fine detail. In Southern cities we find qualitatively distinct configurations that include not only black “neighborhoods” as usually imagined, but also backyard housing, alley housing, and side streets that were predominantly black. These configurations represent the sort of symbolic boundaries recognized by urban ethnographers. By mapping residential configurations and interpreting them in light of historical accounts, our intention is to capture meanings that are too often missed by quantitative studies of segregation. PMID:29479108

Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.

USGS Publications Warehouse

Shafer, Sarah; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model

PubMed Central

Shafer, Sarah L.; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750

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

USGS Publications Warehouse

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

2011-01-01

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

Predation risk, elk, and aspen: tests of a behaviorally mediated trophic cascade in the Greater Yellowstone Ecosystem.

PubMed

Winnie, John A

2012-12-01

Aspen in the Greater Yellowstone Ecosystem are hypothesized to be recovering from decades of heavy browsing by elk due to a behaviorally mediated trophic cascade (BMTC). Several authors have suggested that wolves interact with certain terrain features, creating places of high predation risk at fine spatial scales, and that elk avoid these places, which creates refugia for plants. This hypothesized BMTC could release aspen from elk browsing pressure, leading to a patchy recovery in places of high risk. I tested whether four specific, hypothesized fine-scale risk factors are correlated with changes in current elk browsing pressure on aspen, or with aspen recruitment since wolf reintroduction, in the Daly Creek drainage in Yellowstone National Park, and near two aspen enclosures outside of the park boundary. Aspen were not responding to hypothesized fine-scale risk factors in ways consistent with the current BMTC hypothesis.

Fine-scale genetic structure and cryptic associations reveal evidence of kin-based sociality in the African forest elephant.

PubMed

Schuttler, Stephanie G; Philbrick, Jessica A; Jeffery, Kathryn J; Eggert, Lori S

2014-01-01

Spatial patterns of relatedness within animal populations are important in the evolution of mating and social systems, and have the potential to reveal information on species that are difficult to observe in the wild. This study examines the fine-scale genetic structure and connectivity of groups within African forest elephants, Loxodonta cyclotis, which are often difficult to observe due to forest habitat. We tested the hypothesis that genetic similarity will decline with increasing geographic distance, as we expect kin to be in closer proximity, using spatial autocorrelation analyses and Tau K(r) tests. Associations between individuals were investigated through a non-invasive genetic capture-recapture approach using network models, and were predicted to be more extensive than the small groups found in observational studies, similar to fission-fusion sociality found in African savanna (Loxodonta africana) and Asian (Elephas maximus) species. Dung samples were collected in Lopé National Park, Gabon in 2008 and 2010 and genotyped at 10 microsatellite loci, genetically sexed, and sequenced at the mitochondrial DNA control region. We conducted analyses on samples collected at three different temporal scales: a day, within six-day sampling sessions, and within each year. Spatial autocorrelation and Tau K(r) tests revealed genetic structure, but results were weak and inconsistent between sampling sessions. Positive spatial autocorrelation was found in distance classes of 0-5 km, and was strongest for the single day session. Despite weak genetic structure, individuals within groups were significantly more related to each other than to individuals between groups. Social networks revealed some components to have large, extensive groups of up to 22 individuals, and most groups were composed of individuals of the same matriline. Although fine-scale population genetic structure was weak, forest elephants are typically found in groups consisting of kin and based on matrilines, with some individuals having more associates than observed from group sizes alone.

Mortality and long-term exposure to ambient air pollution: ongoing analyses based on the American Cancer Society cohort.

PubMed

Krewski, Daniel; Burnett, Richard; Jerrett, Michael; Pope, C Arden; Rainham, Daniel; Calle, Eugenia; Thurston, George; Thun, Michael

This article provides an overview of previous analysis and reanalysis of the American Cancer Society (ACS) cohort, along with an indication of current ongoing analyses of the cohort with additional follow-up information through to 2000. Results of the first analysis conducted by Pope et al. (1995) showed that higher average sulfate levels were associated with increased mortality, particularly from cardiopulmonary disease. A reanalysis of the ACS cohort, undertaken by Krewski et al. (2000), found the original risk estimates for fine-particle and sulfate air pollution to be highly robust against alternative statistical techniques and spatial modeling approaches. A detailed investigation of covariate effects found a significant modifying effect of education with risk of mortality associated with fine particles declining with increasing educational attainment. Pope et al. (2002) subsequently reported results of a subsequent study using an additional 10 yr of follow-up of the ACS cohort. This updated analysis included gaseous copollutant and new fine-particle measurements, more comprehensive information on occupational exposures, dietary variables, and the most recent developments in statistical modeling integrating random effects and nonparametric spatial smoothing into the Cox proportional hazards model. Robust associations between ambient fine particulate air pollution and elevated risks of cardiopulmonary and lung cancer mortality were clearly evident, providing the strongest evidence to date that long-term exposure to fine particles is an important health risk. Current ongoing analysis using the extended follow-up information will explore the role of ecologic, economic, and, demographic covariates in the particulate air pollution and mortality association. This analysis will also provide insight into the role of spatial autocorrelation at multiple geographic scales, and whether critical instances in time of exposure to fine particles influence the risk of mortality from cardiopulmonary and lung cancer. Information on the influence of covariates at multiple scales and of critical exposure time windows can assist policymakers in establishing timelines for regulatory interventions that maximize population health benefits.

A space-time analysis of the WikiLeaks Afghan War Diary: a resource for analyzing the conflict-health nexus.

PubMed

Curtis, Andrew; Ye, Xinyue; Hachey, Kevin; Bourdeaux, Margaret; Norris, Alison

2015-10-16

Although it is widely acknowledged that areas of conflict are associated with a high health burden, from a geospatial perspective it is difficult to establish these patterns at fine scales because of a lack of data. The release of the "WikiLeaks" Afghan War Diary (AWD) provides an interesting opportunity to advance analysis and theory into this interrelationship. This paper will apply two different space time analyses to identify patterns of improvised explosive devices (IED) detonations for the period of 2004 to 2009 in Afghanistan. There is considerable spatial and temporal heterogeneity in IED explosions, with concentrations often following transportation links. The results are framed in terms of a resource for subsequent analyses to other existing health research in Afghanistan. To facilitate this, in our discussion we present a Google Earth file of overlapping rates that can be distributed to any researcher interested in combining his/her fine scale health data with a similarly granular layer of violence. The release of the AWD presents a previously unavailable opportunity to consider how spatially detailed data about violence can be incorporated into understanding, and predicting, health related spillover effects. The AWD can enrich previous research conducted on Afghanistan, and provide a justification for future "official" data sharing at appropriately fine scales.

On the feasibility of measuring urban air pollution by wireless distributed sensor networks.

PubMed

Moltchanov, Sharon; Levy, Ilan; Etzion, Yael; Lerner, Uri; Broday, David M; Fishbain, Barak

2015-01-01

Accurate evaluation of air pollution on human-wellbeing requires high-resolution measurements. Standard air quality monitoring stations provide accurate pollution levels but due to their sparse distribution they cannot capture the highly resolved spatial variations within cities. Similarly, dedicated field campaigns can use tens of measurement devices and obtain highly dense spatial coverage but normally deployment has been limited to short periods of no more than few weeks. Nowadays, advances in communication and sensory technologies enable the deployment of dense grids of wireless distributed air monitoring nodes, yet their sensor ability to capture the spatiotemporal pollutant variability at the sub-neighborhood scale has never been thoroughly tested. This study reports ambient measurements of gaseous air pollutants by a network of six wireless multi-sensor miniature nodes that have been deployed in three urban sites, about 150 m apart. We demonstrate the network's capability to capture spatiotemporal concentration variations at an exceptional fine resolution but highlight the need for a frequent in-situ calibration to maintain the consistency of some sensors. Accordingly, a procedure for a field calibration is proposed and shown to improve the system's performance. Overall, our results support the compatibility of wireless distributed sensor networks for measuring urban air pollution at a sub-neighborhood spatial resolution, which suits the requirement for highly spatiotemporal resolved measurements at the breathing-height when assessing exposure to urban air pollution. Copyright © 2014 Elsevier B.V. All rights reserved.

Towards Improved Forecasts of Atmospheric and Oceanic Circulations over the Complex Terrain of the Eastern Mediterranean

NASA Technical Reports Server (NTRS)

Chronis, Themis; Case, Jonathan L.; Papadopoulos, Anastasios; Anagnostou, Emmanouil N.; Mecikalski, John R.; Haines, Stephanie L.

2008-01-01

Forecasting atmospheric and oceanic circulations accurately over the Eastern Mediterranean has proved to be an exceptional challenge. The existence of fine-scale topographic variability (land/sea coverage) and seasonal dynamics variations can create strong spatial gradients in temperature, wind and other state variables, which numerical models may have difficulty capturing. The Hellenic Center for Marine Research (HCMR) is one of the main operational centers for wave forecasting in the eastern Mediterranean. Currently, HCMR's operational numerical weather/ocean prediction model is based on the coupled Eta/Princeton Ocean Model (POM). Since 1999, HCMR has also operated the POSEIDON floating buoys as a means of state-of-the-art, real-time observations of several oceanic and surface atmospheric variables. This study attempts a first assessment at improving both atmospheric and oceanic prediction by initializing a regional Numerical Weather Prediction (NWP) model with high-resolution sea surface temperatures (SST) from remotely sensed platforms in order to capture the small-scale characteristics.

Atomic-scale observation of structural and electronic orders in the layered compound α-RuCl3

NASA Astrophysics Data System (ADS)

Ziatdinov, M.; Banerjee, A.; Maksov, A.; Berlijn, T.; Zhou, W.; Cao, H. B.; Yan, J.-Q.; Bridges, C. A.; Mandrus, D. G.; Nagler, S. E.; Baddorf, A. P.; Kalinin, S. V.

2016-12-01

A pseudospin-1/2 Mott phase on a honeycomb lattice is proposed to host the celebrated two-dimensional Kitaev model which has an elusive quantum spin liquid ground state, and fascinating physics relevant to the development of future templates towards topological quantum bits. Here we report a comprehensive, atomically resolved real-space study by scanning transmission electron and scanning tunnelling microscopies on a novel layered material displaying Kitaev physics, α-RuCl3. Our local crystallography analysis reveals considerable variations in the geometry of the ligand sublattice in thin films of α-RuCl3 that opens a way to realization of a spatially inhomogeneous magnetic ground state at the nanometre length scale. Using scanning tunnelling techniques, we observe the electronic energy gap of ~0.25 eV and intra-unit cell symmetry breaking of charge distribution in individual α-RuCl3 surface layer. The corresponding charge-ordered pattern has a fine structure associated with two different types of charge disproportionation at Cl-terminated surface.

Pervasive and strong effects of plants on soil chemistry: a meta-analysis of individual plant 'Zinke' effects.

PubMed

Waring, Bonnie G; Álvarez-Cansino, Leonor; Barry, Kathryn E; Becklund, Kristen K; Dale, Sarah; Gei, Maria G; Keller, Adrienne B; Lopez, Omar R; Markesteijn, Lars; Mangan, Scott; Riggs, Charlotte E; Rodríguez-Ronderos, María Elizabeth; Segnitz, R Max; Schnitzer, Stefan A; Powers, Jennifer S

2015-08-07

Plant species leave a chemical signature in the soils below them, generating fine-scale spatial variation that drives ecological processes. Since the publication of a seminal paper on plant-mediated soil heterogeneity by Paul Zinke in 1962, a robust literature has developed examining effects of individual plants on their local environments (individual plant effects). Here, we synthesize this work using meta-analysis to show that plant effects are strong and pervasive across ecosystems on six continents. Overall, soil properties beneath individual plants differ from those of neighbours by an average of 41%. Although the magnitudes of individual plant effects exhibit weak relationships with climate and latitude, they are significantly stronger in deserts and tundra than forests, and weaker in intensively managed ecosystems. The ubiquitous effects of plant individuals and species on local soil properties imply that individual plant effects have a role in plant-soil feedbacks, linking individual plants with biogeochemical processes at the ecosystem scale. © 2015 The Author(s).

A Spatial Framework to Map Heat Health Risks at Multiple Scales.

PubMed

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.

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

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

Iliopoulos, AS; Sun, X; Floros, D

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

A spatial scaling relationship for soil moisture in a semiarid landscape, using spatial scaling relationships for pedology

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.

2013-12-01

In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.

Spatially distributed potential evapotranspiration modeling and climate projections.

PubMed

Gharbia, Salem S; Smullen, Trevor; Gill, Laurence; Johnston, Paul; Pilla, Francesco

2018-08-15

Evapotranspiration integrates energy and mass transfer between the Earth's surface and atmosphere and is the most active mechanism linking the atmosphere, hydrosphsophere, lithosphere and biosphere. This study focuses on the fine resolution modeling and projection of spatially distributed potential evapotranspiration on the large catchment scale as response to climate change. Six potential evapotranspiration designed algorithms, systematically selected based on a structured criteria and data availability, have been applied and then validated to long-term mean monthly data for the Shannon River catchment with a 50m 2 cell size. The best validated algorithm was therefore applied to evaluate the possible effect of future climate change on potential evapotranspiration rates. Spatially distributed potential evapotranspiration projections have been modeled based on climate change projections from multi-GCM ensembles for three future time intervals (2020, 2050 and 2080) using a range of different Representative Concentration Pathways producing four scenarios for each time interval. Finally, seasonal results have been compared to baseline results to evaluate the impact of climate change on the potential evapotranspiration and therefor on the catchment dynamical water balance. The results present evidence that the modeled climate change scenarios would have a significant impact on the future potential evapotranspiration rates. All the simulated scenarios predicted an increase in potential evapotranspiration for each modeled future time interval, which would significantly affect the dynamical catchment water balance. This study addresses the gap in the literature of using GIS-based algorithms to model fine-scale spatially distributed potential evapotranspiration on the large catchment systems based on climatological observations and simulations in different climatological zones. Providing fine-scale potential evapotranspiration data is very crucial to assess the dynamical catchment water balance to setup management scenarios for the water abstractions. This study illustrates a transferable systematic method to design GIS-based algorithms to simulate spatially distributed potential evapotranspiration on the large catchment systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Indications of a spatial variation of the fine structure constant.

PubMed

Webb, J K; King, J A; Murphy, M T; Flambaum, V V; Carswell, R F; Bainbridge, M B

2011-11-04

We previously reported Keck telescope observations suggesting a smaller value of the fine structure constant α at high redshift. New Very Large Telescope (VLT) data, probing a different direction in the Universe, shows an inverse evolution; α increases at high redshift. Although the pattern could be due to as yet undetected systematic effects, with the systematics as presently understood the combined data set fits a spatial dipole, significant at the 4.2 σ level, in the direction right ascension 17.5 ± 0.9 h, declination -58 ± 9 deg. The independent VLT and Keck samples give consistent dipole directions and amplitudes, as do high and low redshift samples. A search for systematics, using observations duplicated at both telescopes, reveals none so far which emulate this result.

Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

NASA Astrophysics Data System (ADS)

Diao, Chunyuan

In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of saltcedar. The multiyear spectral angle clustering model could guide the selection of the most representative remotely sensed image for repetitive saltcedar mapping over space and time. Through incorporating spatial autocorrelation, the species distribution model developed in the study could identify the suitable habitats of saltcedar at a fine spatial scale and locate appropriate areas at high risk of saltcedar infestation. Among 10 environmental variables, the distance to the river and the phenological attributes summarized by the time series remote sensing were regarded as the most important. These methods developed in the study provide new perspectives on how the continuous time series can be leveraged under various conditions to investigate the plant invasion dynamics.

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

USGS Publications Warehouse

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

2017-01-01

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

Alpine Ecohydrology Across Scales: Propagating Fine-scale Heterogeneity to the Catchment and Beyond

NASA Astrophysics Data System (ADS)

Mastrotheodoros, T.; Pappas, C.; Molnar, P.; Burlando, P.; Hadjidoukas, P.; Fatichi, S.

2017-12-01

In mountainous ecosystems, complex topography and landscape heterogeneity govern ecohydrological states and fluxes. Here, we investigate topographic controls on water, energy and carbon fluxes across different climatic regimes and vegetation types representative of the European Alps. We use an ecohydrological model to perform fine-scale numerical experiments on a synthetic domain that comprises a symmetric mountain with eight catchments draining along the cardinal and intercardinal directions. Distributed meteorological model input variables are generated using observations from Switzerland. The model computes the incoming solar radiation based on the local topography. We implement a multivariate statistical framework to disentangle the impact of landscape heterogeneity (i.e., elevation, aspect, flow contributing area, vegetation type) on the simulated water, carbon, and energy dynamics. This allows us to identify the sensitivities of several ecohydrological variables (including leaf area index, evapotranspiration, snow-cover and net primary productivity) to topographic and meteorological inputs at different spatial and temporal scales. We also use an alpine catchment as a real case study to investigate how the natural variability of soil and land cover affects the idealized relationships that arise from the synthetic domain. In accordance with previous studies, our analysis shows a complex pattern of vegetation response to radiation. We find also different patterns of ecosystem sensitivity to topography-driven heterogeneity depending on the hydrological regime (i.e., wet vs. dry conditions). Our results suggest that topography-driven variability in ecohydrological variables (e.g. transpiration) at the fine spatial scale can exceed 50%, but it is substantially reduced ( 5%) when integrated at the catchment scale.

Global Night-Time Lights for Observing Human Activity

NASA Technical Reports Server (NTRS)

Hipskind, Stephen R.; Elvidge, Chris; Gurney, K.; Imhoff, Mark; Bounoua, Lahouari; Sheffner, Edwin; Nemani, Ramakrishna R.; Pettit, Donald R.; Fischer, Marc

2011-01-01

We present a concept for a small satellite mission to make systematic, global observations of night-time lights with spatial resolution suitable for discerning the extent, type and density of human settlements. The observations will also allow better understanding of fine scale fossil fuel CO2 emission distribution. The NASA Earth Science Decadal Survey recommends more focus on direct observations of human influence on the Earth system. The most dramatic and compelling observations of human presence on the Earth are the night light observations taken by the Defence Meteorological System Program (DMSP) Operational Linescan System (OLS). Beyond delineating the footprint of human presence, night light data, when assembled and evaluated with complementary data sets, can determine the fine scale spatial distribution of global fossil fuel CO2 emissions. Understanding fossil fuel carbon emissions is critical to understanding the entire carbon cycle, and especially the carbon exchange between terrestrial and oceanic systems.

Reduced fine-scale spatial genetic structure in grazed populations of Dianthus carthusianorum

PubMed Central

Rico, Y; Wagner, H H

2016-01-01

Strong spatial genetic structure in plant populations can increase homozygosity, reducing genetic diversity and adaptive potential. The strength of spatial genetic structure largely depends on rates of seed dispersal and pollen flow. Seeds without dispersal adaptations are likely to be dispersed over short distances within the vicinity of the mother plant, resulting in spatial clustering of related genotypes (fine-scale spatial genetic structure, hereafter spatial genetic structure (SGS)). However, primary seed dispersal by zoochory can promote effective dispersal, increasing the mixing of seeds and influencing SGS within plant populations. In this study, we investigated the effects of seed dispersal by rotational sheep grazing on the strength of SGS and genetic diversity using 11 nuclear microsatellites for 49 populations of the calcareous grassland forb Dianthus carthusianorum. Populations connected by rotational sheep grazing showed significantly weaker SGS and higher genetic diversity than populations in ungrazed grasslands. Independent of grazing treatment, small populations showed significantly stronger SGS and lower genetic diversity than larger populations, likely due to genetic drift. A lack of significant differences in the strength of SGS and genetic diversity between populations that were recently colonized and pre-existing populations suggested that populations colonized after the reintroduction of rotational sheep grazing were likely founded by colonists from diverse source populations. We conclude that dispersal by rotational sheep grazing has the potential to considerably reduce SGS within D. carthusianorum populations. Our study highlights the effectiveness of landscape management by rotational sheep grazing to importantly reduce genetic structure at local scales within restored plant populations. PMID:27381322

Reduced fine-scale spatial genetic structure in grazed populations of Dianthus carthusianorum.

PubMed

Rico, Y; Wagner, H H

2016-11-01

Strong spatial genetic structure in plant populations can increase homozygosity, reducing genetic diversity and adaptive potential. The strength of spatial genetic structure largely depends on rates of seed dispersal and pollen flow. Seeds without dispersal adaptations are likely to be dispersed over short distances within the vicinity of the mother plant, resulting in spatial clustering of related genotypes (fine-scale spatial genetic structure, hereafter spatial genetic structure (SGS)). However, primary seed dispersal by zoochory can promote effective dispersal, increasing the mixing of seeds and influencing SGS within plant populations. In this study, we investigated the effects of seed dispersal by rotational sheep grazing on the strength of SGS and genetic diversity using 11 nuclear microsatellites for 49 populations of the calcareous grassland forb Dianthus carthusianorum. Populations connected by rotational sheep grazing showed significantly weaker SGS and higher genetic diversity than populations in ungrazed grasslands. Independent of grazing treatment, small populations showed significantly stronger SGS and lower genetic diversity than larger populations, likely due to genetic drift. A lack of significant differences in the strength of SGS and genetic diversity between populations that were recently colonized and pre-existing populations suggested that populations colonized after the reintroduction of rotational sheep grazing were likely founded by colonists from diverse source populations. We conclude that dispersal by rotational sheep grazing has the potential to considerably reduce SGS within D. carthusianorum populations. Our study highlights the effectiveness of landscape management by rotational sheep grazing to importantly reduce genetic structure at local scales within restored plant populations.

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.

Dark energy with fine redshift sampling

NASA Astrophysics Data System (ADS)

Linder, Eric V.

2007-03-01

The cosmological constant and many other possible origins for acceleration of the cosmic expansion possess variations in the dark energy properties slow on the Hubble time scale. Given that models with more rapid variation, or even phase transitions, are possible though, we examine the fineness in redshift with which cosmological probes can realistically be employed, and what constraints this could impose on dark energy behavior. In particular, we discuss various aspects of baryon acoustic oscillations, and their use to measure the Hubble parameter H(z). We find that currently considered cosmological probes have an innate resolution no finer than Δz≈0.2 0.3.

Quantifying Diurnal and Seasonal Variation in On-road CO2 Emissions Across the Northeastern U.S.

NASA Astrophysics Data System (ADS)

Gately, C.; Hutyra, L.

2014-12-01

On-road emissions comprised 29% of U.S. fossil fuel carbon dioxide emissions in 2012, with 64% of those emissions occurring in urban areas. Understanding the social, economic and technological factors that influence urban emissions requires the development of emissions inventories that are resolved at fine spatial and temporal scales. As city governments are increasingly at the forefront of developing policies to mitigate greenhouse gas emissions from vehicles, high-resolution, bottom-up inventories will support local and regional emissions benchmarking, as well as the monitoring, reporting, and verification of trends in emissions across time and space. To that end, we combine a large regional dataset of hourly traffic counts with the 1km gridded estimates of on-road CO2 emissions from the Database of Road Transportation Emissions (DARTE) to develop hourly CO2 emissions estimates for the year 2012 that cover 12 northeastern states. The inventory scope covers several large metropolitan regions as well as many small- and medium-sized urban, suburban and exurban population centers, altogether representing 20% of urban and 17% of total U.S. on-road CO2 emissions in 2012. We identify significant variation in the time structure of vehicle emissions across the urban-suburban gradients of the Boston, New York, and Washington, D.C. metropolitan areas. In particular we note considerable spatial variation between morning and evening peak periods, both within and between cities, as well as variations in the duration of peak periods, depending on time of year and spatial location. We also examine the relationship between the temporal and spatial structure of morning and evening peak period emissions and the spatial distribution of population and employment density across urban to rural gradients. Finally we utilize data on minute-by-minute vehicle speeds to quantify the effect of traffic congestion on vehicle CO2 emission rates across the Boston metro area, and we highlight the sensitivity of congestion to small sub-hourly variations in traffic flows at key periods of the morning and evening rush hours. Results from our analysis demonstrate the potential for reducing vehicle emissions through time-sensitive toll pricing or commuter incentive schemes targeting peak period vehicle use on urban freeways.

Effects of soil spatial variability at the hillslope and catchment scales on characteristics of rainfall-induced landslides

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.

SEASONAL MODELING OF THE EXPORT OF POLLUTANTS FROM NORTH AMERICA USING THE MULTI-SCALE AIR QUALITY SIMULATION PLATFORM (MAQSIP)

EPA Science Inventory

Attention in recent years has focused on the trans-boundary transport of ozone and fine particulate matte between the United States and Mexico and Canada and across state boundaries in the United States. In a similar manner, but on a larger spatial scale, the export of pollutant...

Fine resolution probabilistic land cover classification of landscapes in the southeastern United States

Treesearch

Joseph St. Peter; John Hogland; Nathaniel Anderson; Jason Drake; Paul Medley

2018-01-01

Land cover classification provides valuable information for prioritizing management and conservation operations across large landscapes. Current regional scale land cover geospatial products within the United States have a spatial resolution that is too coarse to provide the necessary information for operations at the local and project scales. This paper describes a...

The influence of multi-season imagery on models of canopy cover: A case study

Treesearch

John W. Coulston; Dennis M. Jacobs; Chris R. King; Ivey C. Elmore

2013-01-01

Quantifying tree canopy cover in a spatially explicit fashion is important for broad-scale monitoring of ecosystems and for management of natural resources. Researchers have developed empirical models of tree canopy cover to produce geospatial products. For subpixel models, percent tree canopy cover estimates (derived from fine-scale imagery) serve as the response...

Habitat associations of sympatric red-tailed hawks and northern goshawks on the Kaibab Plateau

Treesearch

Frank A. La Sorte; R. William Mannan; Richard T. Reynolds; Teryl G. Grubb

2004-01-01

We investigated habitat association of sympatric red-tailed hawks (Buteo jamaicensis) and northern goshawks (Accipiter gentilis) at 2 spatial scales centered on nest sites: (1) fine-scale patterns of forest structure and topography within 16-m radius circles (0.08 ha), and (2) midscale patterns of forested and nonforested areas,...

Kilometric Scale Modeling of the North West European Shelf Seas: Exploring the Spatial and Temporal Variability of Internal Tides

NASA Astrophysics Data System (ADS)

Guihou, K.; Polton, J.; Harle, J.; Wakelin, S.; O'Dea, E.; Holt, J.

2018-01-01

The North West European Shelf break acts as a barrier to the transport and exchange between the open ocean and the shelf seas. The strong spatial variability of these exchange processes is hard to fully explore using observations, and simulations generally are too coarse to simulate the fine-scale processes over the whole region. In this context, under the FASTNEt program, a new NEMO configuration of the North West European Shelf and Atlantic Margin at 1/60° (˜1.8 km) has been developed, with the objective to better understand and quantify the seasonal and interannual variability of shelf break processes. The capability of this configuration to reproduce the seasonal cycle in SST, the barotropic tide, and fine-resolution temperature profiles is assessed against a basin-scale (1/12°, ˜9 km) configuration and a standard regional configuration (7 km resolution). The seasonal cycle is well reproduced in all configurations though the fine-resolution allows the simulation of smaller scale processes. Time series of temperature at various locations on the shelf show the presence of internal waves with a strong spatiotemporal variability. Spectral analysis of the internal waves reveals peaks at the diurnal, semidiurnal, inertial, and quarter-diurnal bands, which are only realistically reproduced in the new configuration. Tidally induced pycnocline variability is diagnosed in the model and shown to vary with the spring neap cycle with mean displacement amplitudes in excess of 2 m for 30% of the stratified domain. With sufficiently fine resolution, internal tides are shown to be generated at numerous bathymetric features resulting in a complex pycnocline displacement superposition pattern.

The Eagle Nebula: a spectral template for star forming regions

NASA Astrophysics Data System (ADS)

Flagey, Nicolas; Boulanger, Francois; Carey, Sean; Compiegne, Mathieu; Dwek, Eli; Habart, Emilie; Indebetouw, Remy; Montmerle, Thierry; Noriega-Crespo, Alberto

2008-03-01

IRAC and MIPS have revealed spectacular images of massive star forming regions in the Galaxy. These vivid illustrations of the interaction between the stars, through their winds and radiation, and their environment, made of gas and dust, still needs to be explained. The large scale picture of layered shells of gas components, is affected by the small scale interaction of stars with the clumpy medium that surrounds them. To understand spatial variations of physical conditions and dust properties on small scales, spectroscopic imaging observations are required on a nearby object. The iconic Eagle Nebula (M16) is one of the nearest and most observed star forming region of our Galaxy and as such, is a well suited template to obtain this missing data set. We thus propose a complete spectral map of the Eagle Nebula (M16) with the IRS/Long Low module (15-38 microns) and MIPS/SED mode (55-95 microns). Analysis of the dust emission, spectral features and continuum, and of the H2 and fine-structure gas lines within our models will provide us with constraints on the physical conditions (gas ionization state, pressure, radiation field) and dust properties (temperature, size distribution) at each position within the nebula. Only such a spatially and spectrally complete map will allow us to characterize small scale structure and dust evolution within the global context and understand the impact of small scale structure on the evolution of dusty star forming regions. This project takes advantage of the unique ability of IRS at obtaining sensitive spectral maps covering large areas.

Estimating daily surface NO2 concentrations from satellite data - a case study over Hong Kong using land use regression models

NASA Astrophysics Data System (ADS)

Anand, Jasdeep S.; Monks, Paul S.

2017-07-01

Land use regression (LUR) models have been used in epidemiology to determine the fine-scale spatial variation in air pollutants such as nitrogen dioxide (NO2) in cities and larger regions. However, they are often limited in their temporal resolution, which may potentially be rectified by employing the synoptic coverage provided by satellite measurements. In this work a mixed-effects LUR model is developed to model daily surface NO2 concentrations over the Hong Kong SAR during the period 2005-2015. In situ measurements from the Hong Kong Air Quality Monitoring Network, along with tropospheric vertical column density (VCD) data from the OMI, GOME-2A, and SCIAMACHY satellite instruments were combined with fine-scale land use parameters to provide the spatiotemporal information necessary to predict daily surface concentrations. Cross-validation with the in situ data shows that the mixed-effects LUR model using OMI data has a high predictive power (adj. R2 = 0. 84), especially when compared with surface concentrations derived using the MACC-II reanalysis model dataset (adj. R2 = 0. 11). Time series analysis shows no statistically significant trend in NO2 concentrations during 2005-2015, despite a reported decline in NOx emissions. This study demonstrates the utility in combining satellite data with LUR models to derive daily maps of ambient surface NO2 for use in exposure studies.

APPLYING MULTIMETRIC INDICES AT HIGH RESOLUTION ...

EPA Pesticide Factsheets

Like many inland waters worldwide, streams and rivers of the Western U.S. are faced with a multitude of challenges stemming from past land use practices and changing future conditions. To address these issues, the USEPA has developed empirical tools for evaluating instream conditions and monitoring the status of our freshwater resources over time. These efforts have made substantial progress in integrating quantitative methods into multimetric indices (MMIs) used for national and regional assessments and have provided an enhanced understanding of condition patterns across the broader landscape. To examine the extent of spatial and temporal variability not captured by the sparse distribution of sample sites used in these large-scale assessments, we applied two existing MMIs to inter-seasonal fish and macroinvertebrate data from the Calapooia Basin in Oregon’s Willamette Valley. Our chosen indices revealed a high degree of variation in biotic condition within our study area. With notable exceptions, indices were seasonally robust, indicating potential flexibility for scheduling sampling. An increased understanding of condition patterns occurring at fine spatial scales and the natural and anthropogenic effects influencing them can help guide and prioritize restoration and management. Multimetric indices (MMIs) that incorporate data on the biological and physical characteristics of freshwater systems and provide meaningful indicators of instream conditions

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Impacts of precipitation and potential evapotranspiration patterns on downscaling soil moisture in regions with large topographic relief

NASA Astrophysics Data System (ADS)

Cowley, Garret S.; Niemann, Jeffrey D.; Green, Timothy R.; Seyfried, Mark S.; Jones, Andrew S.; Grazaitis, Peter J.

2017-02-01

Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution soil moisture using fine-resolution topographic, vegetation, and soil data to produce fine-resolution (10-30 m) estimates of soil moisture. The EMT+VS model performs well at catchments with low topographic relief (≤124 m), but it has not been applied to regions with larger ranges of elevation. Large relief can produce substantial variations in precipitation and potential evapotranspiration (PET), which might affect the fine-resolution patterns of soil moisture. In this research, simple methods to downscale temporal average precipitation and PET are developed and included in the EMT+VS model, and the effects of spatial variations in these variables on the surface soil moisture estimates are investigated. The methods are tested against ground truth data at the 239 km2 Reynolds Creek watershed in southern Idaho, which has 1145 m of relief. The precipitation and PET downscaling methods are able to capture the main features in the spatial patterns of both variables. The space-time Nash-Sutcliffe coefficients of efficiency of the fine-resolution soil moisture estimates improve from 0.33 to 0.36 and 0.41 when the precipitation and PET downscaling methods are included, respectively. PET downscaling provides a larger improvement in the soil moisture estimates than precipitation downscaling likely because the PET pattern is more persistent through time, and thus more predictable, than the precipitation pattern.

Species richness and biomass explain spatial turnover in ecosystem functioning across tropical and temperate ecosystems.

PubMed

Barnes, Andrew D; Weigelt, Patrick; Jochum, Malte; Ott, David; Hodapp, Dorothee; Haneda, Noor Farikhah; Brose, Ulrich

2016-05-19

Predicting ecosystem functioning at large spatial scales rests on our ability to scale up from local plots to landscapes, but this is highly contingent on our understanding of how functioning varies through space. Such an understanding has been hampered by a strong experimental focus of biodiversity-ecosystem functioning research restricted to small spatial scales. To address this limitation, we investigate the drivers of spatial variation in multitrophic energy flux-a measure of ecosystem functioning in complex communities-at the landscape scale. We use a structural equation modelling framework based on distance matrices to test how spatial and environmental distances drive variation in community energy flux via four mechanisms: species composition, species richness, niche complementarity and biomass. We found that in both a tropical and a temperate study region, geographical and environmental distance indirectly influence species richness and biomass, with clear evidence that these are the dominant mechanisms explaining variability in community energy flux over spatial and environmental gradients. Our results reveal that species composition and trait variability may become redundant in predicting ecosystem functioning at the landscape scale. Instead, we demonstrate that species richness and total biomass may best predict rates of ecosystem functioning at larger spatial scales. © 2016 The Author(s).

Environmental drivers of spatial variation in whole-tree transpiration in an aspen-dominated upland-to-wetland forest gradient

NASA Astrophysics Data System (ADS)

Loranty, Michael M.; Mackay, D. Scott; Ewers, Brent E.; Adelman, Jonathan D.; Kruger, Eric L.

2008-02-01

Assumed representative center-of-stand measurements are typical inputs to models that scale forest transpiration to stand and regional extents. These inputs do not consider gradients in transpiration at stand boundaries or along moisture gradients and therefore potentially bias the large-scale estimates. We measured half-hourly sap flux (JS) for 173 trees in a spatially explicit cyclic sampling design across a topographically controlled gradient between a forested wetland and upland forest in northern Wisconsin. Our analyses focused on three dominant species in the site: quaking aspen (Populus tremuloides Michx), speckled alder (Alnus incana (DuRoi) Spreng), and white cedar (Thuja occidentalis L.). Sapwood area (AS) was used to scale JS to whole tree transpiration (EC). Because spatial patterns imply underlying processes, geostatistical analyses were employed to quantify patterns of spatial autocorrelation across the site. A simple Jarvis type model parameterized using a Monte Carlo sampling approach was used to simulate EC (EC-SIM). EC-SIM was compared with observed EC(EC-OBS) and found to reproduce both the temporal trends and spatial variance of canopy transpiration. EC-SIM was then used to examine spatial autocorrelation as a function of environmental drivers. We found no spatial autocorrelation in JS across the gradient from forested wetland to forested upland. EC was spatially autocorrelated and this was attributed to spatial variation in AS which suggests species spatial patterns are important for understanding spatial estimates of transpiration. However, the range of autocorrelation in EC-SIM decreased linearly with increasing vapor pressure deficit, implying that consideration of spatial variation in the sensitivity of canopy stomatal conductance to D is also key to accurately scaling up transpiration in space.

Spatial variation in climate mediates gene flow across an island archipelago.

PubMed

Logan, Michael L; Duryea, M C; Molnar, Orsolya R; Kessler, Benji J; Calsbeek, Ryan

2016-10-01

High levels of gene flow among partially isolated populations can overwhelm selection and limit local adaptation. This process, known as "gene swamping," can homogenize genetic diversity among populations and reduce the capacity of a species to withstand rapid environmental change. We studied brown anole lizards (Anolis sagrei) distributed across seven islands in The Bahamas. We used microsatellite markers to estimate gene flow among islands and then examined the correlation between thermal performance and island temperature. The thermal optimum for sprint performance was correlated with both mean and maximum island temperature, whereas performance breadth was not correlated with any measure of temperature variation. Gene flow between islands decreased as the difference between mean island temperatures increased, even when those islands were adjacent to one another. These data suggest that phenotypic variation is the result of either (1) local genetic adaptation with selection against immigrants maintaining variation in the thermal optimum, (2) irreversible forms of adaptive plasticity such that immigrants have reduced fitness, or (3) an interaction between fixed genetic differences and plasticity. In general, the patterns of gene flow we observed suggest that local thermal environments represent important ecological filters that can mediate gene flow on relatively fine geographic scales. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Spatial and Temporal Dynamics of Pacific Oyster Hemolymph Microbiota across Multiple Scales

PubMed Central

Lokmer, Ana; Goedknegt, M. Anouk; Thieltges, David W.; Fiorentino, Dario; Kuenzel, Sven; Baines, John F.; Wegner, K. Mathias

2016-01-01

Unveiling the factors and processes that shape the dynamics of host associated microbial communities (microbiota) under natural conditions is an important part of understanding and predicting an organism's response to a changing environment. The microbiota is shaped by host (i.e., genetic) factors as well as by the biotic and abiotic environment. Studying natural variation of microbial community composition in multiple host genetic backgrounds across spatial as well as temporal scales represents a means to untangle this complex interplay. Here, we combined a spatially-stratified with a longitudinal sampling scheme within differentiated host genetic backgrounds by reciprocally transplanting Pacific oysters between two sites in the Wadden Sea (Sylt and Texel). To further differentiate contingent site from host genetic effects, we repeatedly sampled the same individuals over a summer season to examine structure, diversity and dynamics of individual hemolymph microbiota following experimental removal of resident microbiota by antibiotic treatment. While a large proportion of microbiome variation could be attributed to immediate environmental conditions, we observed persistent effects of antibiotic treatment and translocation suggesting that hemolymph microbial community dynamics is subject to within-microbiome interactions and host population specific factors. In addition, the analysis of spatial variation revealed that the within-site microenvironmental heterogeneity resulted in high small-scale variability, as opposed to large-scale (between-site) stability. Similarly, considerable within-individual temporal variability was in contrast with the overall temporal stability at the site level. Overall, our longitudinal, spatially-stratified sampling design revealed that variation in hemolymph microbiota is strongly influenced by site and immediate environmental conditions, whereas internal microbiome dynamics and oyster-related factors add to their long-term stability. The combination of small and large scale resolution of spatial and temporal observations therefore represents a crucial but underused tool to study host-associated microbiome dynamics. PMID:27630625

The beta-diversity of species interactions: Untangling the drivers of geographic variation in plant-pollinator diversity and function across scales.

PubMed

Burkle, Laura A; Myers, Jonathan A; Belote, R Travis

2016-01-01

Geographic patterns of biodiversity have long inspired interest in processes that shape the assembly, diversity, and dynamics of communities at different spatial scales. To study mechanisms of community assembly, ecologists often compare spatial variation in community composition (beta-diversity) across environmental and spatial gradients. These same patterns inspired evolutionary biologists to investigate how micro- and macro-evolutionary processes create gradients in biodiversity. Central to these perspectives are species interactions, which contribute to community assembly and geographic variation in evolutionary processes. However, studies of beta-diversity have predominantly focused on single trophic levels, resulting in gaps in our understanding of variation in species-interaction networks (interaction beta-diversity), especially at scales most relevant to evolutionary studies of geographic variation. We outline two challenges and their consequences in scaling-up studies of interaction beta-diversity from local to biogeographic scales using plant-pollinator interactions as a model system in ecology, evolution, and conservation. First, we highlight how variation in regional species pools may contribute to variation in interaction beta-diversity among biogeographic regions with dissimilar evolutionary history. Second, we highlight how pollinator behavior (host-switching) links ecological networks to geographic patterns of plant-pollinator interactions and evolutionary processes. Third, we outline key unanswered questions regarding the role of geographic variation in plant-pollinator interactions for conservation and ecosystem services (pollination) in changing environments. We conclude that the largest advances in the burgeoning field of interaction beta-diversity will come from studies that integrate frameworks in ecology, evolution, and conservation to understand the causes and consequences of interaction beta-diversity across scales. © 2016 Botanical Society of America.

Shape-Driven 3D Segmentation Using Spherical Wavelets

PubMed Central

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2013-01-01

This paper presents a novel active surface segmentation algorithm using a multiscale shape representation and prior. We define a parametric model of a surface using spherical wavelet functions and learn a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial locations in a training set. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior in the segmentation framework. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to the segmentation of brain caudate nucleus, of interest in the study of schizophrenia. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm by capturing finer shape details. PMID:17354875

Scale-dependent effects of nonnative plant invasion on host-seeking tick abundance

PubMed Central

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

The Genetics of Mexico Recapitulates Native American Substructure and Affects Biomedical Traits

PubMed Central

Moreno-Estrada, Andrés; Gignoux, Christopher R.; Fernández-López, Juan Carlos; Zakharia, Fouad; Sikora, Martin; Contreras, Alejandra V.; Acuña-Alonzo, Victor; Sandoval, Karla; Eng, Celeste; Romero-Hidalgo, Sandra; Ortiz-Tello, Patricia; Robles, Victoria; Kenny, Eimear E.; Nuño-Arana, Ismael; Barquera-Lozano, Rodrigo; Macín-Pérez, Gastón; Granados-Arriola, Julio; Huntsman, Scott; Galanter, Joshua M.; Via, Marc; Ford, Jean G.; Chapela, Rocío; Rodriguez-Cintron, William; Rodríguez-Santana, Jose R.; Romieu, Isabelle; Sienra-Monge, Juan José; Navarro, Blanca del Rio; London, Stephanie J.; Ruiz-Linares, Andrés; Garcia-Herrera, Rodrigo; Estrada, Karol; Hidalgo-Miranda, Alfredo; Jimenez-Sanchez, Gerardo; Carnevale, Alessandra; Soberón, Xavier; Canizales-Quinteros, Samuel; Rangel-Villalobos, Héctor; Silva-Zolezzi, Irma; Burchard, Esteban Gonzalez; Bustamante, Carlos D.

2014-01-01

Mexico harbors great cultural and ethnic diversity, yet fine-scale patterns of human genome-wide variation from this region remain largely uncharacterized. We studied genomic variation within Mexico from over 1,000 individuals representing 20 indigenous and 11 mestizo populations. We found striking genetic stratification among indigenous populations within Mexico at varying degrees of geographic isolation. Some groups were as differentiated as Europeans are from East Asians. Pre-Columbian genetic substructure is recapitulated in the indigenous ancestry of admixed mestizo individuals across the country. Furthermore, two independently phenotyped cohorts of Mexicans and Mexican Americans showed a significant association between sub-continental ancestry and lung function. Thus, accounting for fine-scale ancestry patterns is critical for medical and population genetic studies within Mexico, in Mexican-descent populations, and likely in many other populations worldwide. PMID:24926019

Behavioral adjustments of African herbivores to predation risk by lions: spatiotemporal variations influence habitat use.

PubMed

Valeix, M; Loveridge, A J; Chamaillé-Jammes, S; Davidson, Z; Murindagomo, F; Fritz, H; Macdonald, D W

2009-01-01

Predators may influence their prey populations not only through direct lethal effects, but also through indirect behavioral changes. Here, we combined spatiotemporal fine-scale data from GPS radio collars on lions with habitat use information on 11 African herbivores in Hwange National Park (Zimbabwe) to test whether the risk of predation by lions influenced the distribution of herbivores in the landscape. Effects of long-term risk of predation (likelihood of lion presence calculated over four months) and short-term risk of predation (actual presence of lions in the vicinity in the preceding 24 hours) were contrasted. The long-term risk of predation by lions appeared to influence the distributions of all browsers across the landscape, but not of grazers. This result strongly suggests that browsers and grazers, which face different ecological constraints, are influenced at different spatial and temporal scales in the variation of the risk of predation by lions. The results also show that all herbivores tend to use more open habitats preferentially when lions are in their vicinity, probably an effective anti-predator behavior against such an ambush predator. Behaviorally induced effects of lions may therefore contribute significantly to structuring African herbivore communities, and hence possibly their effects on savanna ecosystems.

Denitrification in a large river: consideration of geomorphic controls on microbial activity and community structure.

PubMed

Tatariw, Corianne; Chapman, Elise L; Sponseller, Ryan A; Mortazavi, Behzad; Edmonds, Jennifer W

2013-10-01

Ecological theory argues that the controls over ecosystem processes are structured hierarchically, with broader-scale drivers acting as constraints over the interactions and dynamics at nested levels of organization. In river ecosystems, these interactions may arise from broadscale variation in channel form that directly shapes benthic habitat structure and indirectly constrains resource supply and biological activity within individual reaches. To evaluate these interactions, we identified sediment characteristics, water chemistry, and denitrifier community structure as factors influencing benthic denitrification rates in a sixth-order river that flows through two physiographic provinces and the transitional zone between them, each with distinct geomorphological properties. We found that denitrification rates tracked spatial changes in sediment characteristics and varied seasonally with expected trends in stream primary production. Highest rates were observed during the spring and summer seasons in the physiographic province dominated by fine-grained sediments, illustrating how large-scale changes in river structure can constrain the location of denitrification hotspots. In addition, nirS and nirK community structure each responded differently to variation in channel form, possibly due to changes in dissolved oxygen and organic matter supply. This shift in denitrifier community structure coincident with higher rates of N removal via denitrification suggests that microbial community structure may influence biogeochemical processes.

A generic method for improving the spatial interoperability of medical and ecological databases.

PubMed

Ghenassia, A; Beuscart, J B; Ficheur, G; Occelli, F; Babykina, E; Chazard, E; Genin, M

2017-10-03

The availability of big data in healthcare and the intensive development of data reuse and georeferencing have opened up perspectives for health spatial analysis. However, fine-scale spatial studies of ecological and medical databases are limited by the change of support problem and thus a lack of spatial unit interoperability. The use of spatial disaggregation methods to solve this problem introduces errors into the spatial estimations. Here, we present a generic, two-step method for merging medical and ecological databases that avoids the use of spatial disaggregation methods, while maximizing the spatial resolution. Firstly, a mapping table is created after one or more transition matrices have been defined. The latter link the spatial units of the original databases to the spatial units of the final database. Secondly, the mapping table is validated by (1) comparing the covariates contained in the two original databases, and (2) checking the spatial validity with a spatial continuity criterion and a spatial resolution index. We used our novel method to merge a medical database (the French national diagnosis-related group database, containing 5644 spatial units) with an ecological database (produced by the French National Institute of Statistics and Economic Studies, and containing with 36,594 spatial units). The mapping table yielded 5632 final spatial units. The mapping table's validity was evaluated by comparing the number of births in the medical database and the ecological databases in each final spatial unit. The median [interquartile range] relative difference was 2.3% [0; 5.7]. The spatial continuity criterion was low (2.4%), and the spatial resolution index was greater than for most French administrative areas. Our innovative approach improves interoperability between medical and ecological databases and facilitates fine-scale spatial analyses. We have shown that disaggregation models and large aggregation techniques are not necessarily the best ways to tackle the change of support problem.

Recovering the fine structures in solar images

NASA Technical Reports Server (NTRS)

Karovska, Margarita; Habbal, S. R.; Golub, L.; Deluca, E.; Hudson, Hugh S.

1994-01-01

Several examples of the capability of the blind iterative deconvolution (BID) technique to recover the real point spread function, when limited a priori information is available about its characteristics. To demonstrate the potential of image post-processing for probing the fine scale and temporal variability of the solar atmosphere, the BID technique is applied to different samples of solar observations from space. The BID technique was originally proposed for correction of the effects of atmospheric turbulence on optical images. The processed images provide a detailed view of the spatial structure of the solar atmosphere at different heights in regions with different large-scale magnetic field structures.

Statistics of spatial derivatives of velocity and pressure in turbulent channel flow

NASA Astrophysics Data System (ADS)

Vreman, A. W.; Kuerten, J. G. M.

2014-08-01

Statistical profiles of the first- and second-order spatial derivatives of velocity and pressure are reported for turbulent channel flow at Reτ = 590. The statistics were extracted from a high-resolution direct numerical simulation. To quantify the anisotropic behavior of fine-scale structures, the variances of the derivatives are compared with the theoretical values for isotropic turbulence. It is shown that appropriate combinations of first- and second-order velocity derivatives lead to (directional) viscous length scales without explicit occurrence of the viscosity in the definitions. To quantify the non-Gaussian and intermittent behavior of fine-scale structures, higher-order moments and probability density functions of spatial derivatives are reported. Absolute skewnesses and flatnesses of several spatial derivatives display high peaks in the near wall region. In the logarithmic and central regions of the channel flow, all first-order derivatives appear to be significantly more intermittent than in isotropic turbulence at the same Taylor Reynolds number. Since the nine variances of first-order velocity derivatives are the distinct elements of the turbulence dissipation, the budgets of these nine variances are shown, together with the budget of the turbulence dissipation. The comparison of the budgets in the near-wall region indicates that the normal derivative of the fluctuating streamwise velocity (∂u'/∂y) plays a more important role than other components of the fluctuating velocity gradient. The small-scale generation term formed by triple correlations of fluctuations of first-order velocity derivatives is analyzed. A typical mechanism of small-scale generation near the wall (around y+ = 1), the intensification of positive ∂u'/∂y by local strain fluctuation (compression in normal and stretching in spanwise direction), is illustrated and discussed.

Genetic differentiation over a small spatial scale of the sand fly Lutzomyia vexator (Diptera: Psychodidae).

PubMed

Neal, Allison T; Ross, Max S; Schall, Jos J; Vardo-Zalik, Anne M

2016-10-18

The geographic scale and degree of genetic differentiation for arthropod vectors that transmit parasites play an important role in the distribution, prevalence and coevolution of pathogens of human and wildlife significance. We determined the genetic diversity and population structure of the sand fly Lutzomyia vexator over spatial scales from 0.56 to 3.79 km at a study region in northern California. The study was provoked by observations of differentiation at fine spatial scales of a lizard malaria parasite vectored by Lu. vexator. A microsatellite enrichment/next-generation sequencing protocol was used to identify variable microsatellite loci within the genome of Lu. vexator. Alleles present at these loci were examined in four populations of Lu. vexator in Hopland, CA. Population differentiation was assessed using Fst and D (of Cavalli-Sforza and Edwards), and the program Structure was used to determine the degree of subdivision present. The effective population size for the sand fly populations was also calculated. Eight microsatellite markers were characterized and revealed high genetic diversity (uHe = 0.79-0.92, Na = 12-24) and slight but significant differentiation across the fine spatial scale examined (average pairwise D = 0.327; F ST  = 0.0185 (95 % bootstrapped CI: 0.0102-0.0264). Even though the insects are difficult to capture using standard methods, the estimated population size was thousands per local site. The results argue that Lu. vexator at the study sites are abundant and not highly mobile, which may influence the overall transmission dynamics of the lizard malaria parasite, Plasmodium mexicanum, and other parasites transmitted by this species.

The spatial coherence structure of infrasonic waves: analysis of data from International Monitoring System arrays

NASA Astrophysics Data System (ADS)

Green, David N.

2015-04-01

The spatial coherence structure of 30 infrasound array detections, with source-to-receiver ranges of 25-6500 km, has been measured within the 0.25-1 Hz passband. The data were recorded at International Monitoring System (IMS) microbarograph arrays with apertures of between 1 and 4 km. Such array detections are of interest for Comprehensive Nuclear-Test-Ban Treaty monitoring. The majority of array detections (e.g. 80 per cent of recordings in the third-octave passband centred on 0.63 Hz) exhibit spatial coherence loss anisotropy that is consistent with previous lower frequency atmospheric acoustic studies; coherence loss is more rapid perpendicular to the acoustic propagation direction than parallel to it. The thirty array detections display significant interdetection variation in the magnitude of spatial coherence loss. The measurements can be explained by the simultaneous arrival of wave fronts at the recording array with angular beamwidths of between 0.4 and 7° and velocity bandwidths of between 2 and 40 m s-1. There is a statistically significant positive correlation between source-to-receiver range and the magnitude of coherence loss. Acoustic multipathing generated by interactions with fine-scale wind and temperature gradients along stratospheric propagation paths is qualitatively consistent with the observations. In addition, the study indicates that to isolate coherence loss generated by propagation effects, analysis of signals exhibiting high signal-to-noise ratios (SNR) is required (SNR2 > 11 in this study). The rapid temporal variations in infrasonic noise observed in recordings at IMS arrays indicates that correcting measured coherence values for the effect of noise, using pre-signal estimates of noise power, is ineffective.

Fine-scale human genetic structure in Western France.

PubMed

Karakachoff, Matilde; Duforet-Frebourg, Nicolas; Simonet, Floriane; Le Scouarnec, Solena; Pellen, Nadine; Lecointe, Simon; Charpentier, Eric; Gros, Françoise; Cauchi, Stéphane; Froguel, Philippe; Copin, Nane; Le Tourneau, Thierry; Probst, Vincent; Le Marec, Hervé; Molinaro, Sabrina; Balkau, Beverley; Redon, Richard; Schott, Jean-Jacques; Blum, Michael Gb; Dina, Christian

2015-06-01

The difficulties arising from association analysis with rare variants underline the importance of suitable reference population cohorts, which integrate detailed spatial information. We analyzed a sample of 1684 individuals from Western France, who were genotyped at genome-wide level, from two cohorts D.E.S.I.R and CavsGen. We found that fine-scale population structure occurs at the scale of Western France, with distinct admixture proportions for individuals originating from the Brittany Region and the Vendée Department. Genetic differentiation increases with distance at a high rate in these two parts of Northwestern France and linkage disequilibrium is higher in Brittany suggesting a lower effective population size. When looking for genomic regions informative about Breton origin, we found two prominent associated regions that include the lactase region and the HLA complex. For both the lactase and the HLA regions, there is a low differentiation between Bretons and Irish, and this is also found at the genome-wide level. At a more refined scale, and within the Pays de la Loire Region, we also found evidence of fine-scale population structure, although principal component analysis showed that individuals from different departments cannot be confidently discriminated. Because of the evidence for fine-scale genetic structure in Western France, we anticipate that rare and geographically localized variants will be identified in future full-sequence analyses.

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.

Mapping spatial patterns of denitrifiers at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Ramette, A.; Saby, N.; Bru, D.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Effects of spatiotemporal variation of soil salinity on fine root distribution in different plant configuration modes in new reclamation coastal saline field.

PubMed

Jiang, Hong; Du, Hongyu; Bai, Yingying; Hu, Yue; Rao, Yingfu; Chen, Chong; Cai, Yongli

2016-04-01

In order to study the effects of salinity on plant fine roots, we considered three different plant configuration modes (tree stand model (TSM), shrub stand model (SSM), and tree-shrub stand model (TSSM)). Soil samples were collected with the method of soil drilling. Significant differences of electrical conductivity (EC) in the soil depth of 0-60 cm were observed among the three modes (p < 0.05). In the above three modes, the variation of soil salinity among various soil layers and monthly variation of soil salinity were the highest in SSM and reached 2.30 and 2.23 mS/cm (EC1:5), respectively. Due to the effect of salinity, fine root biomass (FRB) showed significant differences in different soil depths (p < 0.05). More than 60% of FRB was concentrated in the soil depth above 30 cm. FRB showed exponential decline with soil depth (p < 0.05). FRB showed spatial heterogeneity in the 40-cm soil depth. In the above three modes, compared with FRB, specific root length (SRL) and fine root length density (FRLD) showed the similar changing trend. Fine roots showed significant seasonal differences among different modes (p < 0.05). FRB showed the bimodal variation and was the highest in July. However, we found that the high content of salts had obvious inhibitory effect on the distribution of FRB. Therefore, the salinity should be below 1.5 mS/cm, which was suitable for the growth of plant roots. Among the three modes, TSSM had the highest FRB, SRL, and FRLD and no obvious soil salt accumulation was observed. The results indicated that fine root biomass was affected by high salt and that TSSM had the strong effects of salt suppression and control. In our study, TSSM may be the optimal configuration mode for salt suppression and control in saline soil.

Air pollution, health and social deprivation: A fine-scale risk assessment.

PubMed

Morelli, Xavier; Rieux, Camille; Cyrys, Josef; Forsberg, Bertil; Slama, Rémy

2016-05-01

Risk assessment studies often ignore within-city variations of air pollutants. Our objective was to quantify the risk associated with fine particulate matter (PM2.5) exposure in 2 urban areas using fine-scale air pollution modeling and to characterize how this risk varied according to social deprivation. In Grenoble and Lyon areas (0.4 and 1.2 million inhabitants, respectively) in 2012, PM2.5 exposure was estimated on a 10×10m grid by coupling a dispersion model to population density. Outcomes were mortality, lung cancer and term low birth weight incidences. Cases attributable to air pollution were estimated overall and stratifying areas according to the European Deprivation Index (EDI), taking 10µg/m(3) yearly average as reference (counterfactual) level. Estimations were repeated assuming spatial homogeneity of air pollutants within urban area. Median PM2.5 levels were 18.1 and 19.6μg/m(3) in Grenoble and Lyon urban areas, respectively, corresponding to 114 (5.1% of total, 95% confidence interval, CI, 3.2-7.0%) and 491 non-accidental deaths (6.0% of total, 95% CI 3.7-8.3%) attributable to long-term exposure to PM2.5, respectively. Attributable term low birth weight cases represented 23.6% of total cases (9.0-37.1%) in Grenoble and 27.6% of cases (10.7-42.6%) in Lyon. In Grenoble, 6.8% of incident lung cancer cases were attributable to air pollution (95% CI 3.1-10.1%). Risk was lower by 8 to 20% when estimating exposure through background stations. Risk was highest in neighborhoods with intermediate to higher social deprivation. Risk assessment studies relying on background stations to estimate air pollution levels may underestimate the attributable risk. Copyright © 2016 Elsevier Inc. All rights reserved.

Demographic controls of aboveground forest biomass across North America.

PubMed

Vanderwel, Mark C; Zeng, Hongcheng; Caspersen, John P; Kunstler, Georges; Lichstein, Jeremy W

2016-04-01

Ecologists have limited understanding of how geographic variation in forest biomass arises from differences in growth and mortality at continental to global scales. Using forest inventories from across North America, we partitioned continental-scale variation in biomass growth and mortality rates of 49 tree species groups into (1) species-independent spatial effects and (2) inherent differences in demographic performance among species. Spatial factors that were separable from species composition explained 83% and 51% of the respective variation in growth and mortality. Moderate additional variation in mortality (26%) was attributable to differences in species composition. Age-dependent biomass models showed that variation in forest biomass can be explained primarily by spatial gradients in growth that were unrelated to species composition. Species-dependent patterns of mortality explained additional variation in biomass, with forests supporting less biomass when dominated by species that are highly susceptible to competition (e.g. Populus spp.) or to biotic disturbances (e.g. Abies balsamea). © 2016 John Wiley & Sons Ltd/CNRS.

Cloud-based computation for accelerating vegetation mapping and change detection at regional to national scales

Treesearch

Matthew J. Gregory; Zhiqiang Yang; David M. Bell; Warren B. Cohen; Sean Healey; Janet L. Ohmann; Heather M. Roberts

2015-01-01

Mapping vegetation and landscape change at fine spatial scales is needed to inform natural resource and conservation planning, but such maps are expensive and time-consuming to produce. For Landsat-based methodologies, mapping efforts are hampered by the daunting task of manipulating multivariate data for millions to billions of pixels. The advent of cloud-based...

Elk resource selection at parturition sites, Black Hills, South Dakota

Treesearch

Chadwick P. Lehman; Mark A. Rumble; Christopher T. Rota; Benjamin J. Bird; Dillon T. Fogarty; Joshua J. Millspaugh

2015-01-01

We studied elk (Cervus canadensis nelsoni) parturition sites at coarse (314-km2 and 7-km2) and fine (0.2-ha) scales in the Black Hills, South Dakota, 2011-2013, following a period of population decline and poor calf recruitment. Our objective was to test whether female elk selected parturition sites across spatial scales in association with forage, terrain...

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.

On the Fidelity of Semi-distributed Hydrologic Model Simulations for Large Scale Catchment Applications

NASA Astrophysics Data System (ADS)

Ajami, H.; Sharma, A.; Lakshmi, V.

2017-12-01

Application of semi-distributed hydrologic modeling frameworks is a viable alternative to fully distributed hyper-resolution hydrologic models due to computational efficiency and resolving fine-scale spatial structure of hydrologic fluxes and states. However, fidelity of semi-distributed model simulations is impacted by (1) formulation of hydrologic response units (HRUs), and (2) aggregation of catchment properties for formulating simulation elements. Here, we evaluate the performance of a recently developed Soil Moisture and Runoff simulation Toolkit (SMART) for large catchment scale simulations. In SMART, topologically connected HRUs are delineated using thresholds obtained from topographic and geomorphic analysis of a catchment, and simulation elements are equivalent cross sections (ECS) representative of a hillslope in first order sub-basins. Earlier investigations have shown that formulation of ECSs at the scale of a first order sub-basin reduces computational time significantly without compromising simulation accuracy. However, the implementation of this approach has not been fully explored for catchment scale simulations. To assess SMART performance, we set-up the model over the Little Washita watershed in Oklahoma. Model evaluations using in-situ soil moisture observations show satisfactory model performance. In addition, we evaluated the performance of a number of soil moisture disaggregation schemes recently developed to provide spatially explicit soil moisture outputs at fine scale resolution. Our results illustrate that the statistical disaggregation scheme performs significantly better than the methods based on topographic data. Future work is focused on assessing the performance of SMART using remotely sensed soil moisture observations using spatially based model evaluation metrics.

Fine resolution mapping of population age-structures for health and development applications.

PubMed

Alegana, V A; Atkinson, P M; Pezzulo, C; Sorichetta, A; Weiss, D; Bird, T; Erbach-Schoenberg, E; Tatem, A J

2015-04-06

The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates of numbers of children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery. Traditionally, such estimates are derived from population censuses, but these can often be unreliable, outdated and of coarse resolution for resource-poor settings. Focusing on Nigeria, we use nationally representative household surveys and their cluster locations to predict the proportion of the under-five population in 1 × 1 km using a Bayesian hierarchical spatio-temporal model. Results showed that land cover, travel time to major settlements, night-time lights and vegetation index were good predictors and that accounting for fine-scale variation, rather than assuming a uniform proportion of under 5 year olds can result in significant differences in health metrics. The largest gaps in estimated bednet and vaccination coverage were in Kano, Katsina and Jigawa. Geolocated household surveys are a valuable resource for providing detailed, contemporary and regularly updated population age-structure data in the absence of recent census data. By combining these with covariate layers, age-structure maps of unprecedented detail can be produced to guide the targeting of interventions in resource-poor settings.

Ground Layer Plant Species Turnover and Beta Diversity in Southern-European Old-Growth Forests

PubMed Central

Sabatini, Francesco Maria; Burrascano, Sabina; Tuomisto, Hanna; Blasi, Carlo

2014-01-01

Different assembly processes may simultaneously affect local-scale variation of species composition in temperate old-growth forests. Ground layer species diversity reflects chance colonization and persistence of low-dispersal species, as well as fine-scale environmental heterogeneity. The latter depends on both purely abiotic factors, such as soil properties and topography, and factors primarily determined by overstorey structure, such as light availability. Understanding the degree to which plant diversity in old-growth forests is associated with structural heterogeneity and/or to dispersal limitation will help assessing the effectiveness of silvicultural practices that recreate old-growth patterns and structures for the conservation or restoration of plant diversity. We used a nested sampling design to assess fine-scale species turnover, i.e. the proportion of species composition that changes among sampling units, across 11 beech-dominated old-growth forests in Southern Europe. For each stand, we also measured a wide range of environmental and structural variables that might explain ground layer species turnover. Our aim was to quantify the relative importance of dispersal limitation in comparison to that of stand structural heterogeneity while controlling for other sources of environmental heterogeneity. For this purpose, we used multiple regression on distance matrices at the within-stand extent, and mixed effect models at the extent of the whole dataset. Species turnover was best predicted by structural and environmental heterogeneity, especially by differences in light availability and in topsoil nutrient concentration and texture. Spatial distances were significant only in four out of eleven stands with a relatively low explanatory power. This suggests that structural heterogeneity is a more important driver of local-scale ground layer species turnover than dispersal limitation in southern European old-growth beech forests. PMID:24748155

Analysing and correcting the differences between multi-source and multi-scale spatial remote sensing observations.

PubMed

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.

Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing Observations

PubMed Central

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

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

USGS Publications Warehouse

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

2007-01-01

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

Partial Least Square Discriminant Analysis Based on Normalized Two-Stage Vegetation Indices for Mapping Damage from Rice Diseases Using PlanetScope Datasets.

PubMed

Shi, Yue; Huang, Wenjiang; Ye, Huichun; Ruan, Chao; Xing, Naichen; Geng, Yun; Dong, Yingying; Peng, Dailiang

2018-06-11

In recent decades, rice disease co-epidemics have caused tremendous damage to crop production in both China and Southeast Asia. A variety of remote sensing based approaches have been developed and applied to map diseases distribution using coarse- to moderate-resolution imagery. However, the detection and discrimination of various disease species infecting rice were seldom assessed using high spatial resolution data. The aims of this study were (1) to develop a set of normalized two-stage vegetation indices (VIs) for characterizing the progressive development of different diseases with rice; (2) to explore the performance of combined normalized two-stage VIs in partial least square discriminant analysis (PLS-DA); and (3) to map and evaluate the damage caused by rice diseases at fine spatial scales, for the first time using bi-temporal, high spatial resolution imagery from PlanetScope datasets at a 3 m spatial resolution. Our findings suggest that the primary biophysical parameters caused by different disease (e.g., changes in leaf area, pigment contents, or canopy morphology) can be captured using combined normalized two-stage VIs. PLS-DA was able to classify rice diseases at a sub-field scale, with an overall accuracy of 75.62% and a Kappa value of 0.47. The approach was successfully applied during a typical co-epidemic outbreak of rice dwarf (Rice dwarf virus, RDV), rice blast ( Magnaporthe oryzae ), and glume blight ( Phyllosticta glumarum ) in Guangxi Province, China. Furthermore, our approach highlighted the feasibility of the method in capturing heterogeneous disease patterns at fine spatial scales over the large spatial extents.

Fatal Attraction? Intraguild Facilitation and Suppression among Predators.

PubMed

Sivy, Kelly J; Pozzanghera, Casey B; Grace, James B; Prugh, Laura R

2017-11-01

Competition and suppression are recognized as dominant forces that structure predator communities. Facilitation via carrion provisioning, however, is a ubiquitous interaction among predators that could offset the strength of suppression. Understanding the relative importance of these positive and negative interactions is necessary to anticipate community-wide responses to apex predator declines and recoveries worldwide. Using state-sponsored wolf (Canis lupus) control in Alaska as a quasi experiment, we conducted snow track surveys of apex, meso-, and small predators to test for evidence of carnivore cascades (e.g., mesopredator release). We analyzed survey data using an integrative occupancy and structural equation modeling framework to quantify the strengths of hypothesized interaction pathways, and we evaluated fine-scale spatiotemporal responses of nonapex predators to wolf activity clusters identified from radio-collar data. Contrary to the carnivore cascade hypothesis, both meso- and small predator occupancy patterns indicated guild-wide, negative responses of nonapex predators to wolf abundance variations at the landscape scale. At the local scale, however, we observed a near guild-wide, positive response of nonapex predators to localized wolf activity. Local-scale association with apex predators due to scavenging could lead to landscape patterns of mesopredator suppression, suggesting a key link between occupancy patterns and the structure of predator communities at different spatial scales.

Fatal attraction? Intraguild facilitation and suppression among predators

USGS Publications Warehouse

Sivy, Kelly J.; Pozzanghera, Casey B.; Grace, James B.; Prugh, Laura R.

2017-01-01

Competition and suppression are recognized as dominant forces that structure predator communities. Facilitation via carrion provisioning, however, is a ubiquitous interaction among predators that could offset the strength of suppression. Understanding the relative importance of these positive and negative interactions is necessary to anticipate community-wide responses to apex predator declines and recoveries worldwide. Using state-sponsored wolf (Canis lupus) control in Alaska as a quasi experiment, we conducted snow track surveys of apex, meso-, and small predators to test for evidence of carnivore cascades (e.g., mesopredator release). We analyzed survey data using an integrative occupancy and structural equation modeling framework to quantify the strengths of hypothesized interaction pathways, and we evaluated fine-scale spatiotemporal responses of nonapex predators to wolf activity clusters identified from radio-collar data. Contrary to the carnivore cascade hypothesis, both meso- and small predator occupancy patterns indicated guild-wide, negative responses of nonapex predators to wolf abundance variations at the landscape scale. At the local scale, however, we observed a near guild-wide, positive response of nonapex predators to localized wolf activity. Local-scale association with apex predators due to scavenging could lead to landscape patterns of mesopredator suppression, suggesting a key link between occupancy patterns and the structure of predator communities at different spatial scales.

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

PubMed Central

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

Design of an Air Pollution Monitoring Campaign in Beijing for Application to Cohort Health Studies.

PubMed

Vedal, Sverre; Han, Bin; Xu, Jia; Szpiro, Adam; Bai, Zhipeng

2017-12-15

No cohort studies in China on the health effects of long-term air pollution exposure have employed exposure estimates at the fine spatial scales desirable for cohort studies with individual-level health outcome data. Here we assess an array of modern air pollution exposure estimation approaches for assigning within-city exposure estimates in Beijing for individual pollutants and pollutant sources to individual members of a cohort. Issues considered in selecting specific monitoring data or new monitoring campaigns include: needed spatial resolution, exposure measurement error and its impact on health effect estimates, spatial alignment and compatibility with the cohort, and feasibility and expense. Sources of existing data largely include administrative monitoring data, predictions from air dispersion or chemical transport models and remote sensing (specifically satellite) data. New air monitoring campaigns include additional fixed site monitoring, snapshot monitoring, passive badge or micro-sensor saturation monitoring and mobile monitoring, as well as combinations of these. Each of these has relative advantages and disadvantages. It is concluded that a campaign in Beijing that at least includes a mobile monitoring component, when coupled with currently available spatio-temporal modeling methods, should be strongly considered. Such a campaign is economical and capable of providing the desired fine-scale spatial resolution for pollutants and sources.

Design of an Air Pollution Monitoring Campaign in Beijing for Application to Cohort Health Studies

PubMed Central

Vedal, Sverre; Han, Bin; Szpiro, Adam; Bai, Zhipeng

2017-01-01

No cohort studies in China on the health effects of long-term air pollution exposure have employed exposure estimates at the fine spatial scales desirable for cohort studies with individual-level health outcome data. Here we assess an array of modern air pollution exposure estimation approaches for assigning within-city exposure estimates in Beijing for individual pollutants and pollutant sources to individual members of a cohort. Issues considered in selecting specific monitoring data or new monitoring campaigns include: needed spatial resolution, exposure measurement error and its impact on health effect estimates, spatial alignment and compatibility with the cohort, and feasibility and expense. Sources of existing data largely include administrative monitoring data, predictions from air dispersion or chemical transport models and remote sensing (specifically satellite) data. New air monitoring campaigns include additional fixed site monitoring, snapshot monitoring, passive badge or micro-sensor saturation monitoring and mobile monitoring, as well as combinations of these. Each of these has relative advantages and disadvantages. It is concluded that a campaign in Beijing that at least includes a mobile monitoring component, when coupled with currently available spatio-temporal modeling methods, should be strongly considered. Such a campaign is economical and capable of providing the desired fine-scale spatial resolution for pollutants and sources. PMID:29244738

Accounting for groundwater in stream fish thermal habitat responses to climate change

USGS Publications Warehouse

Snyder, Craig D.; Hitt, Nathaniel P.; Young, John A.

2015-01-01

Forecasting climate change effects on aquatic fauna and their habitat requires an understanding of how water temperature responds to changing air temperature (i.e., thermal sensitivity). Previous efforts to forecast climate effects on brook trout habitat have generally assumed uniform air-water temperature relationships over large areas that cannot account for groundwater inputs and other processes that operate at finer spatial scales. We developed regression models that accounted for groundwater influences on thermal sensitivity from measured air-water temperature relationships within forested watersheds in eastern North America (Shenandoah National Park, USA, 78 sites in 9 watersheds). We used these reach-scale models to forecast climate change effects on stream temperature and brook trout thermal habitat, and compared our results to previous forecasts based upon large-scale models. Observed stream temperatures were generally less sensitive to air temperature than previously assumed, and we attribute this to the moderating effect of shallow groundwater inputs. Predicted groundwater temperatures from air-water regression models corresponded well to observed groundwater temperatures elsewhere in the study area. Predictions of brook trout future habitat loss derived from our fine-grained models were far less pessimistic than those from prior models developed at coarser spatial resolutions. However, our models also revealed spatial variation in thermal sensitivity within and among catchments resulting in a patchy distribution of thermally suitable habitat. Habitat fragmentation due to thermal barriers therefore may have an increasingly important role for trout population viability in headwater streams. Our results demonstrate that simple adjustments to air-water temperature regression models can provide a powerful and cost-effective approach for predicting future stream temperatures while accounting for effects of groundwater.

Spatio-temporal dynamics of a tree-killing beetle and its predator

Treesearch

Aaron S. Weed; Matthew P. Ayres; Andrew M. Liebhold; Ronald F. Billings

2016-01-01

Resolving linkages between local-scale processes and regional-scale patterns in abundance of interacting species is important for understanding long-term population stability across spatial scales. Landscape patterning in consumer population dynamics may be largely the result of interactions between consumers and their predators, or driven by spatial variation in basal...

Heterogeneity and anisotropy in the lithospheric mantle

NASA Astrophysics Data System (ADS)

Tommasi, Andréa; Vauchez, Alain

2015-10-01

The lithospheric mantle is intrinsically heterogeneous and anisotropic. These two properties govern the repartition of deformation, controlling intraplate strain localization and development of new plate boundaries. Geophysical and geological observations provide clues on the types, ranges, and characteristic length scales of heterogeneity and anisotropy in the lithospheric mantle. Seismic tomography points to variations in geothermal gradient and hence in rheological behavior at scales of hundreds of km. Seismic anisotropy data substantiate anisotropic physical properties consistent at scales of tens to hundreds of km. Receiver functions imply lateral and vertical heterogeneity at scales < 10 km, which might record gradients in composition or anisotropy. Observations on naturally deformed peridotites establish that compositional heterogeneity and Crystal Preferred Orientations (CPOs) are ubiquitous from the mm to the km scales. These data allow discussing the processes that produce/destroy heterogeneity and anisotropy and constraining the time scales over which they are active. This analysis highlights: (i) the role of deformation and reactive percolation of melts and fluids in producing compositional and structural heterogeneity and the feedbacks between these processes, (ii) the weak mechanical effect of mineralogical variations, and (iii) the low volumes of fine-grained microstructures and difficulty to preserve them. In contrast, olivine CPO and the resulting anisotropy of mechanical and thermal properties are only modified by deformation. Based on this analysis, we propose that strain localization at the plate scale is, at first order, controlled by large-scale variations in thermal structure and in CPO-induced anisotropy. In cold parts of the lithospheric mantle, grain size reduction may contribute to strain localization, but the low volume of fine-grained domains limits this effect.

Responses of infaunal populations to benthoscape structure and the potential importance of transition zones

USGS Publications Warehouse

Zajac, R.N.; Lewis, R.S.; Poppe, L.J.; Twichell, D.C.; Vozarik, J.; DiGiacomo-Cohen, M. L.

2003-01-01

Relationships between population abundance and seafloor landscape, or benthoscape, structure were examined for 16 infaunal taxa in eastern Long Island Sound. Based on analyses of a side-scan sonar mosaic, the 19.4-km2 study area was comprised of six distinct large-scale (> km2) benthoscape elements, with varying levels of mesoscale (km2-m2) and small-scale (2) physical and biological habitat heterogeneity. Transition zones among elements varied from ~50 to 200 m in width, comprised ~32% of the benthoscape, and added to overall benthoscape heterogeneity. Population abundances of nine taxa varied significantly among the large-scale elements. Most species were found at high abundances only in one benthoscape element, but three had several foci of elevated abundances. Analyses of population responses to habitat heterogeneity at different spatial scales indicated that abundances of eight taxa varied significantly among spatial scales, but the significant scales were mixed among these species. Relatively large residual variations suggest significant amounts of mesoscale spatial variation were unaccounted for, varying from ~1 km2 to several m2. Responses to transition zones were mixed as well. Abundances of nine taxa varied significantly among transition zones and interiors of benthoscape elements, most with elevated abundances in transition zones. Our results show that infaunal populations exhibit complex and spatially varying patterns of abundance in relation to benthoscape structure and suggest that mesoscale variation may be particularly critical in this regard. Also, transition zones among benthoscape features add considerably to this variation and may be ecological important areas in seafloor environments.

Membrane properties change in fine-pore aeration diffusers: full-scale variations of transfer efficiency and headloss.

PubMed

Rosso, Diego; Libra, Judy A; Wiehe, Wolfgang; Stenstrom, Michael K

2008-05-01

Fine-pore diffusers are the most common aeration system in municipal wastewater treatment. Punched polymeric membranes are often used in fine-pore aeration due to their advantageous initial performance. These membranes are subject to fouling and scaling, resulting in increased headloss and reduced oxygen transfer efficiency, both contributing to increased plant energy costs. This paper describes and discusses the change in material properties for polymeric fine-pore diffusers, comparing new and used membranes. Three different diffuser technologies were tested and sample diffusers from two wastewater treatment facilities were analysed. The polymeric membranes analysed in this paper were composed of ethylene-propylene-diene monomer (EPDM), polyurethane, and silicon. Transfer efficiency is usually lower with longer times in operation, as older, dilated orifices produce larger bubbles, which are unfavourable to mass transfer. At the same time, headloss increases with time in operation, since membranes increase in rigidity and hardness, and fouling and scaling phenomena occur at the orifice opening. Change in polymer properties and laboratory test results correlate with the decrease in oxygen transfer efficiency.

Interspecific interference competition at the resource patch scale: do large herbivores spatially avoid elephants while accessing water?

PubMed

Ferry, Nicolas; Dray, Stéphane; Fritz, Hervé; Valeix, Marion

2016-11-01

Animals may anticipate and try to avoid, at some costs, physical encounters with other competitors. This may ultimately impact their foraging distribution and intake rates. Such cryptic interference competition is difficult to measure in the field, and extremely little is known at the interspecific level. We tested the hypothesis that smaller species avoid larger ones because of potential costs of interference competition and hence expected them to segregate from larger competitors at the scale of a resource patch. We assessed fine-scale spatial segregation patterns between three African herbivore species (zebra Equus quagga, kudu Tragelaphus strepsiceros and giraffe Giraffa camelopardalis) and a megaherbivore, the African elephant Loxodonta africana, at the scale of water resource patches in the semi-arid ecosystem of Hwange National Park, Zimbabwe. Nine waterholes were monitored every two weeks during the dry season of a drought year, and observational scans of the spatial distribution of all herbivores were performed every 15 min. We developed a methodological approach to analyse such fine-scale spatial data. Elephants increasingly used waterholes as the dry season progressed, as did the probability of co-occurrence and agonistic interaction with elephants for the three study species. All three species segregated from elephants at the beginning of the dry season, suggesting a spatial avoidance of elephants and the existence of costs of being close to them. However, contrarily to our expectations, herbivores did not segregate from elephants the rest of the dry season but tended to increasingly aggregate with elephants as the dry season progressed. We discuss these surprising results and the existence of a trade-off between avoidance of interspecific interference competition and other potential factors such as access to quality water, which may have relative associated costs that change with the time of the year. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Determining Tidal Phase Differences from X-Band Radar Images

NASA Astrophysics Data System (ADS)

Newman, Kieran; Bell, Paul; Brown, Jennifer; Plater, Andrew

2017-04-01

Introduction Previous work by Bell et. al. (2016) has developed a method using X-band marine radar to measure intertidal bathymetry, using the waterline as a level over a spring-neap tidal cycle. This has been used in the Dee Estuary to give a good representation of the bathymetry in the area. However, there are some sources of inaccuracy in the method, as a uniform spatial tidal signal is assumed over the entire domain. Motivation The method used by Bell et. al. (2016) applies a spatially uniform tidal signal to the entire domain. This fails to account for fine-scale variations in water level and tidal phase. While methods are being developed to account for small-scale water level variations using high resolution modelling, a method to determine tidal phase variations directly from the radar intensity images could be advantageous operationally. Methods The tidal phase has been computed using two different methods, with hourly averaged images from 2008. In the first method, the cross-correlation between each raw pixel time series and a tidal signal at a number of lags is calculated, and the lag with the highest correlation to the pixel series is recorded. For the second method, the same method of correlation is used on signals generated by tracking movement of buoys, which show up strongly in the radar image as they move on their moorings with the tidal currents. There is a broad agreement between the two methods, but validation is needed to determine the relative accuracy. The phase has also been calculated using a Fourier decomposition, and agrees broadly with the above methods. Work also needs to be done to separate areas where the recorded phase is due to tidal current (mostly subtidal areas) or due to elevation (mostly the wetting/drying signal in intertidal areas), by classifying radar intensities by the phases and amplitudes of the tides. Filtering out signal variations due to wind strength and attenuation of the radar signal will also be applied. Validation Validation will be attempted using data from a POLCOMS-WAM model run for Liverpool Bay at 180m resolution for February 2008 (Brown, 2011), and ongoing work to develop a model at 5m resolution using DELFT3D-FLOW. There are also a series of ADCP and other direct measurements of tidal current and elevation available, although periods of measurement do not all overlap. However, this could still be used for some validation. Conclusion While this work is in very early stages, it could present a method to determine fine-scale variations in tidal phase without a network of current recorders, and an improvement in the accuracy of bathymetric methods using X-band Radar. References Bell, P.S., Bird, C.O., Plater, A.J., 2016. A temporal waterline approach to mapping intertidal areas using X-band marine radar. Coastal Engineering, 07: 84-101. Brown, J.M., Bolaños, R., Wolf, J., 2011. Impact assessment of advanced coupling features in a tide-surge-wave model, POLCOMS-WAM, in a shallow water application. Journal of Marine Systems, 87: 13-24. Deltares, 2010. Delft3D FLOW. Delft: Deltares.

GOCE, Satellite Gravimetry and Antarctic Mass Transports

NASA Astrophysics Data System (ADS)

Rummel, Reiner; Horwath, Martin; Yi, Weiyong; Albertella, Alberta; Bosch, Wolfgang; Haagmans, Roger

2011-09-01

In 2009 the European Space Agency satellite mission GOCE (Gravity Field and Steady-State Ocean Circulation Explorer) was launched. Its objectives are the precise and detailed determination of the Earth's gravity field and geoid. Its core instrument, a three axis gravitational gradiometer, measures the gravity gradient components V xx , V yy , V zz and V xz (second-order derivatives of the gravity potential V) with high precision and V xy , V yz with low precision, all in the instrument reference frame. The long wavelength gravity field is recovered from the orbit, measured by GPS (Global Positioning System). Characteristic elements of the mission are precise star tracking, a Sun-synchronous and very low (260 km) orbit, angular control by magnetic torquing and an extremely stiff and thermally stable instrument environment. GOCE is complementary to GRACE (Gravity Recovery and Climate Experiment), another satellite gravity mission, launched in 2002. While GRACE is designed to measure temporal gravity variations, albeit with limited spatial resolution, GOCE is aiming at maximum spatial resolution, at the expense of accuracy at large spatial scales. Thus, GOCE will not provide temporal variations but is tailored to the recovery of the fine scales of the stationary field. GRACE is very successful in delivering time series of large-scale mass changes of the Antarctic ice sheet, among other things. Currently, emphasis of respective GRACE analyses is on regional refinement and on changes of temporal trends. One of the challenges is the separation of ice mass changes from glacial isostatic adjustment. Already from a few months of GOCE data, detailed gravity gradients can be recovered. They are presented here for the area of Antarctica. As one application, GOCE gravity gradients are an important addition to the sparse gravity data of Antarctica. They will help studies of the crustal and lithospheric field. A second area of application is ocean circulation. The geoid surface from the gravity field model GOCO01S allows us now to generate rather detailed maps of the mean dynamic ocean topography and of geostrophic flow velocities in the region of the Antarctic Circumpolar Current.

Analytical SuperSTEM for extraterrestrial materials research

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

Bradley, J P; Dai, Z R

2009-09-08

Electron-beam studies of extraterrestrial materials with significantly improved spatial resolution, energy resolution and sensitivity are enabled using a 300 keV SuperSTEM scanning transmission electron microscope with a monochromator and two spherical aberration correctors. The improved technical capabilities enable analyses previously not possible. Mineral structures can be directly imaged and analyzed with single-atomic-column resolution, liquids and implanted gases can be detected, and UV-VIS optical properties can be measured. Detection limits for minor/trace elements in thin (<100 nm thick) specimens are improved such that quantitative measurements of some extend to the sub-500 ppm level. Electron energy-loss spectroscopy (EELS) can be carried outmore » with 0.10-0.20 eV energy resolution and atomic-scale spatial resolution such that variations in oxidation state from one atomic column to another can be detected. Petrographic mapping is extended down to the atomic scale using energy-dispersive x-ray spectroscopy (EDS) and energy-filtered transmission electron microscopy (EFTEM) imaging. Technical capabilities and examples of the applications of SuperSTEM to extraterrestrial materials are presented, including the UV spectral properties and organic carbon K-edge fine structure of carbonaceous matter in interplanetary dust particles (IDPs), x-ray elemental maps showing the nanometer-scale distribution of carbon within GEMS (glass with embedded metal and sulfides), the first detection and quantification of trace Ti in GEMS using EDS, and detection of molecular H{sub 2}O in vesicles and implanted H{sub 2} and He in irradiated mineral and glass grains.« less

Predicting habitat suitability for rare plants at local spatial scales using a species distribution model.

PubMed

Gogol-Prokurat, Melanie

2011-01-01

If species distribution models (SDMs) can rank habitat suitability at a local scale, they may be a valuable conservation planning tool for rare, patchily distributed species. This study assessed the ability of Maxent, an SDM reported to be appropriate for modeling rare species, to rank habitat suitability at a local scale for four edaphic endemic rare plants of gabbroic soils in El Dorado County, California, and examined the effects of grain size, spatial extent, and fine-grain environmental predictors on local-scale model accuracy. Models were developed using species occurrence data mapped on public lands and were evaluated using an independent data set of presence and absence locations on surrounding lands, mimicking a typical conservation-planning scenario that prioritizes potential habitat on unsurveyed lands surrounding known occurrences. Maxent produced models that were successful at discriminating between suitable and unsuitable habitat at the local scale for all four species, and predicted habitat suitability values were proportional to likelihood of occurrence or population abundance for three of four species. Unfortunately, models with the best discrimination (i.e., AUC) were not always the most useful for ranking habitat suitability. The use of independent test data showed metrics that were valuable for evaluating which variables and model choices (e.g., grain, extent) to use in guiding habitat prioritization for conservation of these species. A goodness-of-fit test was used to determine whether habitat suitability values ranked habitat suitability on a continuous scale. If they did not, a minimum acceptable error predicted area criterion was used to determine the threshold for classifying habitat as suitable or unsuitable. I found a trade-off between model extent and the use of fine-grain environmental variables: goodness of fit was improved at larger extents, and fine-grain environmental variables improved local-scale accuracy, but fine-grain variables were not available at large extents. No single model met all habitat prioritization criteria, and the best models were overlaid to identify consensus areas of high suitability. Although the four species modeled here co-occur and are treated together for conservation planning, model accuracy and predicted suitable areas varied among species.

Effects of seed bank disturbance on the fine-scale genetic structure of populations of the rare shrub Grevillea macleayana.

PubMed

England, P R; Whelan, R J; Ayre, D J

2003-11-01

Dispersal in most plants is mediated by the movement of seeds and pollen, which move genes across the landscape differently. Grevillea macleayana is a rare, fire-dependent Australian shrub with large seeds lacking adaptations for dispersal; yet it produces inflorescences adapted to pollination by highly mobile vertebrates (eg birds). Interpreting fine-scale genetic structure in the light of these two processes is confounded by the recent imposition of anthropogenic disturbances with potentially contrasting genetic consequences: (1) the unusual foraging behaviour of exotic honeybees and 2. widespread disturbance of the soil-stored seedbank by road building and quarrying. To test for evidence of fine-scale genetic structure within G. macleayana populations and to test the prediction that such structure might be masked by disturbance of the seed bank, we sampled two sites in undisturbed habitat and compared their genetic structure with two sites that had been strongly affected by road building using a test for spatial autocorrelation of genotypes. High selfing levels inferred from genotypes at all four sites implies that pollen dispersal is limited. Consistent with this, we observed substantial spatial clustering of genes at 10 m or less in the two undisturbed populations and argue that this reflects the predicted effects of both high selfing levels and limited seed dispersal. In contrast, at the two sites disturbed by road building, spatial autocorrelation was weak. This suggests there has been mixing of the seed bank, counteracting the naturally low dispersal and elevated selfing due to honeybees. Pollination between near neighbours with reduced relatedness potentially has fitness consequences for G. macleayana in disturbed sites.

Multiscale patterns and drivers of arbuscular mycorrhizal fungal communities in the roots and root-associated soil of a wild perennial herb.

PubMed

Rasmussen, Pil U; Hugerth, Luisa W; Blanchet, F Guillaume; Andersson, Anders F; Lindahl, Björn D; Tack, Ayco J M

2018-03-24

Arbuscular mycorrhizal (AM) fungi form diverse communities and are known to influence above-ground community dynamics and biodiversity. However, the multiscale patterns and drivers of AM fungal composition and diversity are still poorly understood. We sequenced DNA markers from roots and root-associated soil from Plantago lanceolata plants collected across multiple spatial scales to allow comparison of AM fungal communities among neighbouring plants, plant subpopulations, nearby plant populations, and regions. We also measured soil nutrients, temperature, humidity, and community composition of neighbouring plants and nonAM root-associated fungi. AM fungal communities were already highly dissimilar among neighbouring plants (c. 30 cm apart), albeit with a high variation in the degree of similarity at this small spatial scale. AM fungal communities were increasingly, and more consistently, dissimilar at larger spatial scales. Spatial structure and environmental drivers explained a similar percentage of the variation, from 7% to 25%. A large fraction of the variation remained unexplained, which may be a result of unmeasured environmental variables, species interactions and stochastic processes. We conclude that AM fungal communities are highly variable among nearby plants. AM fungi may therefore play a major role in maintaining small-scale variation in community dynamics and biodiversity. © 2018 The Authors New Phytologist © 2018 New Phytologist Trust.

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

PubMed

Herrera-Vásquez, Jonathan

2009-01-01

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

Heavy precipitation episodes in the Western Mediterranean : Use of a semi-Lagrangian advection model for the fine-scale description of upper-level troughs

NASA Astrophysics Data System (ADS)

Gauthier, N.; Claud, C.; Funatsu, B. M.; Chaboureau, J.-P.; Argence, S.; Lambert, D.; Richard, E.; Hauchecorne, A.; Arbogast, P.; Maynard, K.

2009-09-01

Heavy precipitation events over the Mediterranean Sea are generally associated with upper-level troughs. The mesoscale structures of such troughs are however not well reproduced by the atmospheric analyses due to inappropriate spatial resolution. We propose here to use a semi-Lagrangian advection model called MIMOSA (Modélisation Isentrope du transport Méso-échelle de l'Ozone Stratosphérique par Advection) initially developed to describe stratospheric filaments, to calculate fine-scale Potential Vorticity (PV) fields on isentropic surfaces near the tropopause. After a description of MIMOSA, we will focus on the model-generated PV fields for several high impact weather cases that occurred over the Western Mediterreanean Sea. We will demonstrate the ability of MIMOSA to resolve fine scale structures of upper-level troughs considering the Algiers' flash flood, which occurred on November 2001, and then a heavy precipitation event over southeast France on the 5-6 September 2005. Finally, with a PV inversion method, we will show the impact of the fine scales PV structures as depicted by MIMOSA to improve the numerical simulation of a « hurricane » that hit Italy in September 2006, both in terms of surface pressure and precipitation forecasts.

Exploring fine-scale variability of stratospheric wind above the tropical la reunion island using rayleigh-mie doppler lidar

NASA Astrophysics Data System (ADS)

Khaykin, S. M.; Hauchecorne, A.; Cammas, J.-P.; Marqestaut, N.; Mariscal, J.-F.; Posny, F.; Payen, G.; Porteneuve, J.; Keckhut, P.

2018-04-01

A unique Rayleigh-Mie Doppler lidar capable of wind measurements in the 5-50 km altitude range is operated routinely at La Reunion island (21° S, 55° E) since 2015. We evaluate instrument's capacities in capturing fine structures in stratospheric wind profiles and their temporal and spatial variability through comparison with collocated radiosoundings and ECMWF analysis. Perturbations in the wind velocity are used to retrieve gravity wave frequency spectrum.

Host identity matters in the amphibian-Batrachochytrium dendrobatidis system: fine-scale patterns of variation in responses to a multi-host pathogen

Treesearch

Stephanie Gervasi; Carmen Gondhalekar; Deanna H. Olson; Andrew R. Blaustein

2013-01-01

Species composition within ecological assemblages can drive disease dynamics including pathogen invasion, spread, and persistence. In multi-host pathogen systems, interspecific variation in responses to infection creates important context dependency when predicting the outcome of disease. Here, we examine the responses of three sympatric host species to a single fungal...

Modeling solute transport in a heterogeneous unsaturated porous medium under dynamic boundary conditions on different spatial scales

NASA Astrophysics Data System (ADS)

Cremer, Clemens; Neuweiler, Insa; Bechtold, Michel

2013-04-01

Understanding transport of solutes/contaminants through unsaturated soil in the shallow subsurface is vital to assess groundwater quality, nutrient cycling or to plan remediation projects. Alternating precipitation and evaporation conditions causing upward and downward flux with differing flow paths, changes in saturation and related structural heterogeneity make the description of transport in the unsaturated zone near the soil-surface a complex problem. Preferential flow paths strongly depend, among other things, on the saturation of a medium. Recent studies (e.g. Bechtold et al., 2011) showed lateral flow and solute transport during evaporation conditions (upward flux) in vertically layered sand columns. Results revealed that during evaporation water and solute are redistributed laterally from coarse to fine media deeper in the soil, and towards zones of lowest hydraulic head near to the soil surface. These zones at the surface can be coarse or fine grained depending on saturation status and evaporation flux. However, if boundary conditions are reversed and precipitation is applied, the flow field is not reversed in the same manner, resulting in entirely different transport patterns for downward and upward flow. Therefore, considering net-flow rates alone is misleading when describing transport in the shallow unsaturated zone. In this contribution, we analyze transport of a solute in the shallow subsurface to assess effects resulting from the superposition of heterogeneous soil structures and dynamic flow conditions on various spatial scales. Two-dimensional numerical simulations of unsaturated flow and transport in heterogeneous porous media under changing boundary conditions are carried out using a finite-volume code coupled to a particle tracking algorithm to quantify solute transport and leaching rates. In order to validate numerical simulations, results are qualitatively compared to those of a physical experiment (Bechtold et al., 2011). Numerical simulations differ in lateral scale reaching from 0.2 m to 1.5 m, while the height of the domain is kept constant to 1.5m. Strong material heterogeneity is realized through vertical layers of coarse and fine sand. Both materials remain permanently under liquid-flow-dominated ('stage1') evaporation conditions. Spatial moments as well as the dilution index (Kitanidis, 1994) are used for quantification of transport behaviour. Results show that, while all simulations led to anomalous transport, infiltration-evaporation cycles lead to faster solute leaching rates than solely infiltration at the same net-infiltration rate in both homogeneous and heterogeneous media. Flow and transport-paths significantly differed between infiltration and evaporation, resulting in lateral water fluxes and hence lateral solute transport. Variation of the width of the model domain shows faster leaching rates for domains with small horizontal extent.

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

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

Substituting root numbers for length: Improving the use of minirhizotrons to study fine root dynamics

Treesearch

Tracey L. Crocker; Ron L. Hendrick; Roger W. Ruess; Kurt S. Pregitzer; Andrew J. Burton; Michael F. Allen; Jianping Shan; Lawrence A. Morris

2003-01-01

Minirhizotrons provide a unique way to repeatedly measure the production and fate of individual root segments, while minimizing soil disturbance and the confounding of spatial-temporal variation. However, the time associated with processing videotaped minirhizotron images limits the amount of data that can be extracted in a reasonable amount of time. We found that this...

High-resolution observations of combustion in heterogeneous surface fuels

Treesearch

E. Louise Loudermilk; Gary L. Achtemeier; Joseph J. O' Brien; J. Kevin Hiers; Benjamin S. Hornsby

2014-01-01

In ecosystems with frequent surface fires, fire and fuel heterogeneity at relevant scales have been largely ignored. This could be because complete burns give an impression of homogeneity, or due to the difficulty in capturing fine-scale variation in fuel characteristics and fire behaviour. Fire movement between patches of fuel can have implications for modelling fire...

Spatial analysis and land use regression of VOCs and NO(2) from school-based urban air monitoring in Detroit/Dearborn, USA.

PubMed

Mukerjee, Shaibal; Smith, Luther A; Johnson, Mary M; Neas, Lucas M; Stallings, Casson A

2009-08-01

Passive ambient air sampling for nitrogen dioxide (NO(2)) and volatile organic compounds (VOCs) was conducted at 25 school and two compliance sites in Detroit and Dearborn, Michigan, USA during the summer of 2005. Geographic Information System (GIS) data were calculated at each of 116 schools. The 25 selected schools were monitored to assess and model intra-urban gradients of air pollutants to evaluate impact of traffic and urban emissions on pollutant levels. Schools were chosen to be statistically representative of urban land use variables such as distance to major roadways, traffic intensity around the schools, distance to nearest point sources, population density, and distance to nearest border crossing. Two approaches were used to investigate spatial variability. First, Kruskal-Wallis analyses and pairwise comparisons on data from the schools examined coarse spatial differences based on city section and distance from heavily trafficked roads. Secondly, spatial variation on a finer scale and as a response to multiple factors was evaluated through land use regression (LUR) models via multiple linear regression. For weeklong exposures, VOCs did not exhibit spatial variability by city section or distance from major roads; NO(2) was significantly elevated in a section dominated by traffic and industrial influence versus a residential section. Somewhat in contrast to coarse spatial analyses, LUR results revealed spatial gradients in NO(2) and selected VOCs across the area. The process used to select spatially representative sites for air sampling and the results of coarse and fine spatial variability of air pollutants provide insights that may guide future air quality studies in assessing intra-urban gradients.

Natural Models for Autonomous Control of Spatial Navigation, Sensing, and Guidance. Part 1

DTIC Science & Technology

2012-02-13

ketocarotenoid pigment astaxanthin is deposited in the antennal scale of a stomatopod crustacean, Odontodactylus scyllarus. Positive correlation between...partial polarization and the presence of astaxanthin indicates that the antennal scale polarizes light with astaxanthin . Both the optical properties and...the fine structure of the polarizationally-active cuticle suggest that the dipole axes of the astaxanthin molecules are oriented nearly normal to the

The roles of competition and habitat in the dynamics of populations and species distributions Ecology

Treesearch

Charles B. Yackulic; Janice Reid; James D. Nichols; James E. Hines; Raymond Davis; Eric Forsman

2014-01-01

The role of competition in structuring biotic communities at fine spatial scales is well known from detailed process-based studies. Our understanding of competition’s importance at broader scales is less resolved and mainly based on static species distribution maps. Here, we bridge this gap by examining the joint occupancy dynamics of an invading species (Barred Owl,...

Generating high temporal and spatial resolution thermal band imagery using robust sharpening approach

USDA-ARS?s Scientific Manuscript database

Thermal infrared band imagery provides key information for detecting wild fires, mapping land surface energy fluxes and evapotranspiration, monitoring urban heat fluxes and drought monitoring. Thermal infrared (TIR) imagery at fine resolution is required for field scale applications. However, therma...

Comment on: Polar Plumes and Fine-scale Coronal Structures - On the Interpretation of Coronal Radio Sounding Data by Patzold and Bird

NASA Technical Reports Server (NTRS)

Woo, R.; Habbal, S. R.

1998-01-01

Radio occultation measurements, which probe electron density over a wide dynamic range with high sensitivity and high spatial and temporal resolution reveal a solar corona permeated by a hierarchy of filamentary structures.

STOCHASTIC DESCRIPTION OF SUBGRID POLLUTANT VARIABILITY IN CMAQ

EPA Science Inventory

This paper describes a tool for investigating and describing fine scale spatial variability in model concentration fields with the goal of improving the use of air quality models for driving exposure modeling to assess human risk to hazardous air pollutants or air toxics. Region...

Climate Change and Macro-Economic Cycles in Pre-Industrial Europe

PubMed Central

Pei, Qing; Zhang, David D.; Lee, Harry F.; Li, Guodong

2014-01-01

Climate change has been proven to be the ultimate cause of social crisis in pre-industrial Europe at a large scale. However, detailed analyses on climate change and macro-economic cycles in the pre-industrial era remain lacking, especially within different temporal scales. Therefore, fine-grained, paleo-climate, and economic data were employed with statistical methods to quantitatively assess the relations between climate change and agrarian economy in Europe during AD 1500 to 1800. In the study, the Butterworth filter was adopted to filter the data series into a long-term trend (low-frequency) and short-term fluctuations (high-frequency). Granger Causality Analysis was conducted to scrutinize the associations between climate change and macro-economic cycle at different frequency bands. Based on quantitative results, climate change can only show significant effects on the macro-economic cycle within the long-term. In terms of the short-term effects, society can relieve the influences from climate variations by social adaptation methods and self-adjustment mechanism. On a large spatial scale, temperature holds higher importance for the European agrarian economy than precipitation. By examining the supply-demand mechanism in the grain market, population during the study period acted as the producer in the long term, whereas as the consumer in the short term. These findings merely reflect the general interactions between climate change and macro-economic cycles at the large spatial region with a long-term study period. The findings neither illustrate individual incidents that can temporarily distort the agrarian economy nor explain some specific cases. In the study, the scale thinking in the analysis is raised as an essential methodological issue for the first time to interpret the associations between climatic impact and macro-economy in the past agrarian society within different temporal scales. PMID:24516601

Climate change and macro-economic cycles in pre-industrial europe.

PubMed

Pei, Qing; Zhang, David D; Lee, Harry F; Li, Guodong

2014-01-01

Climate change has been proven to be the ultimate cause of social crisis in pre-industrial Europe at a large scale. However, detailed analyses on climate change and macro-economic cycles in the pre-industrial era remain lacking, especially within different temporal scales. Therefore, fine-grained, paleo-climate, and economic data were employed with statistical methods to quantitatively assess the relations between climate change and agrarian economy in Europe during AD 1500 to 1800. In the study, the Butterworth filter was adopted to filter the data series into a long-term trend (low-frequency) and short-term fluctuations (high-frequency). Granger Causality Analysis was conducted to scrutinize the associations between climate change and macro-economic cycle at different frequency bands. Based on quantitative results, climate change can only show significant effects on the macro-economic cycle within the long-term. In terms of the short-term effects, society can relieve the influences from climate variations by social adaptation methods and self-adjustment mechanism. On a large spatial scale, temperature holds higher importance for the European agrarian economy than precipitation. By examining the supply-demand mechanism in the grain market, population during the study period acted as the producer in the long term, whereas as the consumer in the short term. These findings merely reflect the general interactions between climate change and macro-economic cycles at the large spatial region with a long-term study period. The findings neither illustrate individual incidents that can temporarily distort the agrarian economy nor explain some specific cases. In the study, the scale thinking in the analysis is raised as an essential methodological issue for the first time to interpret the associations between climatic impact and macro-economy in the past agrarian society within different temporal scales.

Detecting ecological change on coral reefs

NASA Astrophysics Data System (ADS)

Dustan, P.

2011-12-01

Remote sensing offers the potential to observe the response of coral reef ecosystems to environmental perturbations on a geographical scale not previously accessible. However, coral reef environments are optically, spatially, and temporally complex habitats which all present significant challenges for extracting meaningful information. Virtually every member of the reef community possesses some degree of photosynthetic capability. The community thus generates a matrix of fine scale features with bio-optical signatures that blend as the scale of observation increases. Furthermore, to have any validity, the remotely sensed signal must be "calibrated" to the bio-optics of the reef, a difficult and resource intensive process due to a convergence of photosynthetic light harvesting by green, red, and brown algal pigment systems. To make matters more complex, reefs are overlain by a seawater skin with its own set of hydrological optical challenges. Rather than concentrating on classification, my research has attempted to track change by following the variation in geo-referenced pixel brightness over time with a technique termed temporal texture. Environmental periodicities impart a phenology to the variation in brightness and departures from the norm are easily detected as statistical outliers. This opens the door to using current orbiting technology to efficiently examine large areas of sea for change. If hot spots are detected, higher resolution sensors and field studies can be focused as resources permit. While this technique does not identify the type of change, it is sensitive, simple to compute, easy to automate and grounded in ecological niche theory

Connecting Mobility to Infectious Diseases: The Promise and Limits of Mobile Phone Data.

PubMed

Wesolowski, Amy; Buckee, Caroline O; Engø-Monsen, Kenth; Metcalf, C J E

2016-12-01

Human travel can shape infectious disease dynamics by introducing pathogens into susceptible populations or by changing the frequency of contacts between infected and susceptible individuals. Quantifying infectious disease-relevant travel patterns on fine spatial and temporal scales has historically been limited by data availability. The recent emergence of mobile phone calling data and associated locational information means that we can now trace fine scale movement across large numbers of individuals. However, these data necessarily reflect a biased sample of individuals across communities and are generally aggregated for both ethical and pragmatic reasons that may further obscure the nuance of individual and spatial heterogeneities. Additionally, as a general rule, the mobile phone data are not linked to demographic or social identifiers, or to information about the disease status of individual subscribers (although these may be made available in smaller-scale specific cases). Combining data on human movement from mobile phone data-derived population fluxes with data on disease incidence requires approaches that can tackle varying spatial and temporal resolutions of each data source and generate inference about dynamics on scales relevant to both pathogen biology and human ecology. Here, we review the opportunities and challenges of these novel data streams, illustrating our examples with analyses of 2 different pathogens in Kenya, and conclude by outlining core directions for future research. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Need for improved methods to collect and present spatial epidemiologic data for vectorborne diseases.

PubMed

Eisen, Lars; Eisen, Rebecca J

2007-12-01

Improved methods for collection and presentation of spatial epidemiologic data are needed for vectorborne diseases in the United States. Lack of reliable data for probable pathogen exposure site has emerged as a major obstacle to the development of predictive spatial risk models. Although plague case investigations can serve as a model for how to ideally generate needed information, this comprehensive approach is cost-prohibitive for more common and less severe diseases. New methods are urgently needed to determine probable pathogen exposure sites that will yield reliable results while taking into account economic and time constraints of the public health system and attending physicians. Recent data demonstrate the need for a change from use of the county spatial unit for presentation of incidence of vectorborne diseases to more precise ZIP code or census tract scales. Such fine-scale spatial risk patterns can be communicated to the public and medical community through Web-mapping approaches.

PROPERTIES AND MODELING OF UNRESOLVED FINE STRUCTURE LOOPS OBSERVED IN THE SOLAR TRANSITION REGION BY IRIS

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

Brooks, David H.; Reep, Jeffrey W.; Warren, Harry P.

Recent observations from the Interface Region Imaging Spectrograph ( IRIS ) have discovered a new class of numerous low-lying dynamic loop structures, and it has been argued that they are the long-postulated unresolved fine structures (UFSs) that dominate the emission of the solar transition region. In this letter, we combine IRIS measurements of the properties of a sample of 108 UFSs (intensities, lengths, widths, lifetimes) with one-dimensional non-equilibrium ionization simulations, using the HYDRAD hydrodynamic model to examine whether the UFSs are now truly spatially resolved in the sense of being individual structures rather than being composed of multiple magnetic threads.more » We find that a simulation of an impulsively heated single strand can reproduce most of the observed properties, suggesting that the UFSs may be resolved, and the distribution of UFS widths implies that they are structured on a spatial scale of 133 km on average. Spatial scales of a few hundred kilometers appear to be typical for a range of chromospheric and coronal structures, and we conjecture that this could be an important clue for understanding the coronal heating process.« less

Separating spatial search and efficiency rates as components of predation risk

PubMed Central

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

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

NASA Astrophysics Data System (ADS)

Mock, Cary Jeffrey

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

Small-area spatiotemporal analysis of heatwave impacts on elderly mortality in Paris: A cluster analysis approach.

PubMed

Benmarhnia, Tarik; Kihal-Talantikite, Wahida; Ragettli, Martina S; Deguen, Séverine

2017-08-15

Heat-waves have a substantial public health burden. Understanding spatial heterogeneity at a fine spatial scale in relation to heat and related mortality is central to target interventions towards vulnerable communities. To determine the spatial variability of heat-wave-related mortality risk among elderly in Paris, France at the census block level. We also aimed to assess area-level social and environmental determinants of high mortality risk within Paris. We used daily mortality data from 2004 to 2009 among people aged >65 at the French census block level within Paris. We used two heat wave days' definitions that were compared to non-heat wave days. A Bernoulli cluster analysis method was applied to identify high risk clusters of mortality during heat waves. We performed random effects meta-regression analyses to investigate factors associated with the magnitude of the mortality risk. The spatial approach revealed a spatial aggregation of death cases during heat wave days. We found that small scale chronic PM 10 exposure was associated with a 0.02 (95% CI: 0.001; 0.045) increase of the risk of dying during a heat wave episode. We also found a positive association with the percentage of foreigners and the percentage of labor force, while the proportion of elderly people living in the neighborhood was negatively associated. We also found that green space density had a protective effect and inversely that the density of constructed feature increased the risk of dying during a heat wave episode. We showed that a spatial variation in terms of heat-related vulnerability exists within Paris and that it can be explained by some contextual factors. This study can be useful for designing interventions targeting more vulnerable areas and reduce the burden of heat waves. Copyright © 2017 Elsevier B.V. All rights reserved.

Developing and Delivering National-Scale Gridded Phenology Data Products

NASA Astrophysics Data System (ADS)

Marsh, L.; Crimmins, M.; Crimmins, T. M.; Gerst, K.; Rosemartin, A.; Switzer, J.; Weltzin, J. F.

2016-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) is now producing and freely delivering daily maps and short-term forecasts of accumulated growing degree days and spring onset dates (based on the Extended Spring Indices) at fine spatial scale for the conterminous United States. These data products have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, determining planting dates, anticipating allergy outbreaks and planning agricultural harvest dates. Accumulated growing degree day (AGDD) maps were selected because accumulated temperature is a strong driver of phenological transitions in plants and animals, including leaf-out, flowering, fruit ripening and migration. The Extended Spring Indices (SI-x) are based on predictive climate models for lilac and honeysuckle leaf and bloom; they have been widely used to summarize changes in the timing of spring onset. The SI-x is used as a national indicator of climate change impacts by the US Global Change Research Program and the Environmental Protection Agency. The USA-NPN is a national-scale program that supports scientific advancement and decision-making by collecting, storing, and sharing phenology data and information. To best serve various audiences, the AGDD and SI-x gridded maps are available in various formats through a range of access tools, including the USA-NPN online visualization tool as well as industry standards compliant web services. We plan to expand the suite of gridded map products offered by the USA-NPN to include predictive maps of phenological transitions for additional plant and animal species at fine spatial and temporal resolution in the near future. USA-NPN invites you to use freely available daily and short-term forecast maps of accumulated growing degree days and spring onset dates at fine spatial scale for the conterminous United States.

Fine-scale habitat modeling of a top marine predator: do prey data improve predictive capacity?

PubMed

Torres, Leigh G; Read, Andrew J; Halpin, Patrick

2008-10-01

Predators and prey assort themselves relative to each other, the availability of resources and refuges, and the temporal and spatial scale of their interaction. Predictive models of predator distributions often rely on these relationships by incorporating data on environmental variability and prey availability to determine predator habitat selection patterns. This approach to predictive modeling holds true in marine systems where observations of predators are logistically difficult, emphasizing the need for accurate models. In this paper, we ask whether including prey distribution data in fine-scale predictive models of bottlenose dolphin (Tursiops truncatus) habitat selection in Florida Bay, Florida, U.S.A., improves predictive capacity. Environmental characteristics are often used as predictor variables in habitat models of top marine predators with the assumption that they act as proxies of prey distribution. We examine the validity of this assumption by comparing the response of dolphin distribution and fish catch rates to the same environmental variables. Next, the predictive capacities of four models, with and without prey distribution data, are tested to determine whether dolphin habitat selection can be predicted without recourse to describing the distribution of their prey. The final analysis determines the accuracy of predictive maps of dolphin distribution produced by modeling areas of high fish catch based on significant environmental characteristics. We use spatial analysis and independent data sets to train and test the models. Our results indicate that, due to high habitat heterogeneity and the spatial variability of prey patches, fine-scale models of dolphin habitat selection in coastal habitats will be more successful if environmental variables are used as predictor variables of predator distributions rather than relying on prey data as explanatory variables. However, predictive modeling of prey distribution as the response variable based on environmental variability did produce high predictive performance of dolphin habitat selection, particularly foraging habitat.

Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study.

PubMed

Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard J A; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F

2014-01-01

The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state fluctuations map to the well known architecture of the visual system. We investigated resting state connectivity at both a fine and large scale within and across visual areas V1, V2 and V3 in ten human subjects using a 7Tesla scanner. We found evidence for several coexisting and overlapping connectivity structures at different spatial scales. At the fine-scale level we found enhanced connectivity between the same topographic locations in the fieldmaps of V1, V2 and V3, enhanced connectivity to the contralateral functional homologue, and to a lesser extent enhanced connectivity between iso-eccentric locations within the same visual area. However, by far the largest proportion of the resting state fluctuations occurred within large-scale bilateral networks. These large-scale networks mapped to some extent onto the architecture of the visual system and could thereby obscure fine-scale connectivity. In fact, most of the fine-scale connectivity only became apparent after the large-scale network fluctuations were filtered from the timeseries. We conclude that fMRI resting state fluctuations in the visual cortex may in fact be a composite signal of different overlapping sources. Isolating the different sources could enhance correlations between BOLD and electrophysiological correlates of resting state activity. © 2013 Elsevier Inc. All rights reserved.

Network-scale spatial and temporal variation in Chinook salmon (Oncorhynchus tshawytscha) redd distributions: patterns inferred from spatially continuous replicate surveys

Treesearch

Daniel J. Isaak; Russell F. Thurow

2006-01-01

Spatially continuous sampling designs, when temporally replicated, provide analytical flexibility and are unmatched in their ability to provide a dynamic system view. We have compiled such a data set by georeferencing the network-scale distribution of Chinook salmon (Oncorhynchus tshawytscha) redds across a large wilderness basin (7330 km2) in...

Uncovering Spatial Variation in Acoustic Environments Using Sound Mapping.

PubMed

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

2016-01-01

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

Soil organic matter dynamics and CO2 fluxes in relation to landscape scale processes: linking process understanding to regional scale carbon mass-balances

NASA Astrophysics Data System (ADS)

Van Oost, Kristof; Nadeu, Elisabet; Wiaux, François; Wang, Zhengang; Stevens, François; Vanclooster, Marnik; Tran, Anh; Bogaert, Patrick; Doetterl, Sebastian; Lambot, Sébastien; Van wesemael, Bas

2014-05-01

In this paper, we synthesize the main outcomes of a collaborative project (2009-2014) initiated at the UCL (Belgium). The main objective of the project was to increase our understanding of soil organic matter dynamics in complex landscapes and use this to improve predictions of regional scale soil carbon balances. In a first phase, the project characterized the emergent spatial variability in soil organic matter storage and key soil properties at the regional scale. Based on the integration of remote sensing, geomorphological and soil analysis techniques, we quantified the temporal and spatial variability of soil carbon stock and pool distribution at the local and regional scales. This work showed a linkage between lateral fluxes of C in relation with sediment transport and the spatial variation in carbon storage at multiple spatial scales. In a second phase, the project focused on characterizing key controlling factors and process interactions at the catena scale. In-situ experiments of soil CO2 respiration showed that the soil carbon response at the catena scale was spatially heterogeneous and was mainly controlled by the catenary variation of soil physical attributes (soil moisture, temperature, C quality). The hillslope scale characterization relied on advanced hydrogeophysical techniques such as GPR (Ground Penetrating Radar), EMI (Electromagnetic induction), ERT (Electrical Resistivity Tomography), and geophysical inversion and data mining tools. Finally, we report on the integration of these insights into a coupled and spatially explicit model and its application. Simulations showed that C stocks and redistribution of mass and energy fluxes are closely coupled, they induce structured spatial and temporal patterns with non negligible attached uncertainties. We discuss the main outcomes of these activities in relation to sink-source behavior and relevance of erosion processes for larger-scale C budgets.

Spatial and topographic trends in forest expansion and biomass change, from regional to local scales.

PubMed

Buma, Brian; Barrett, Tara M

2015-09-01

Natural forest growth and expansion are important carbon sequestration processes globally. Climate change is likely to increase forest growth in some regions via CO2 fertilization, increased temperatures, and altered precipitation; however, altered disturbance regimes and climate stress (e.g. drought) will act to reduce carbon stocks in forests as well. Observations of asynchrony in forest change is useful in determining current trends in forest carbon stocks, both in terms of forest density (e.g. Mg ha(-1) ) and spatially (extent and location). Monitoring change in natural (unmanaged) areas is particularly useful, as while afforestation and recovery from historic land use are currently large carbon sinks, the long-term viability of those sinks depends on climate change and disturbance dynamics at their particular location. We utilize a large, unmanaged biome (>135 000 km(2) ) which spans a broad latitudinal gradient to explore how variation in location affects forest density and spatial patterning: the forests of the North American temperate rainforests in Alaska, which store >2.8 Pg C in biomass and soil, equivalent to >8% of the C in contiguous US forests. We demonstrate that the regional biome is shifting; gains exceed losses and are located in different spatio-topographic contexts. Forest gains are concentrated on northerly aspects, lower elevations, and higher latitudes, especially in sheltered areas, whereas loss is skewed toward southerly aspects and lower latitudes. Repeat plot-scale biomass data (n = 759) indicate that within-forest biomass gains outpace losses (live trees >12.7 cm diameter, 986 Gg yr(-1) ) on gentler slopes and in higher latitudes. This work demonstrates that while temperate rainforest dynamics occur at fine spatial scales (<1000 m(2) ), the net result of thousands of individual events is regionally patterned change. Correlations between the disturbance/establishment imbalance and biomass accumulation suggest the potential for relatively rapid biome shifts and biomass changes. © 2015 John Wiley & Sons Ltd.

The effects of biotic and abiotic factors on the spatial heterogeneity of alpine grassland vegetation at a small scale on the Qinghai-Tibet Plateau (QTP), China.

PubMed

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.

Spreading speeds for plant populations in landscapes with low environmental variation.

PubMed

Gilbert, Mark A; Gaffney, Eamonn A; Bullock, James M; White, Steven M

2014-12-21

Characterising the spread of biological populations is crucial in responding to both biological invasions and the shifting of habitat under climate change. Spreading speeds can be studied through mathematical models such as the discrete-time integro-difference equation (IDE) framework. The usual approach in implementing IDE models has been to ignore spatial variation in the demographic and dispersal parameters and to assume that these are spatially homogeneous. On the other hand, real landscapes are rarely spatially uniform with environmental variation being very important in determining biological spread. This raises the question of under what circumstances spatial structure need not be modelled explicitly. Recent work has shown that spatial variation can be ignored for the specific case where the scale of landscape variation is much smaller than the spreading population׳s dispersal scale. We consider more general types of landscape, where the spatial scales of environmental variation are arbitrarily large, but the maximum change in environmental parameters is relatively small. We find that the difference between the wave-speeds of populations spreading in a spatially structured periodic landscape and its homogenisation is, in general, proportional to ϵ(2), where ϵ governs the degree of environmental variation. For stochastically generated landscapes we numerically demonstrate that the error decays faster than ϵ. In both cases, this means that for sufficiently small ϵ, the homogeneous approximation is better than might be expected. Hence, in many situations, the precise details of the landscape can be ignored in favour of spatially homogeneous parameters. This means that field ecologists can use the homogeneous IDE as a relatively simple modelling tool--in terms of both measuring parameter values and doing the modelling itself. However, as ϵ increases, this homogeneous approximation loses its accuracy. The change in wave-speed due to the extrinsic (landscape) variation can be positive or negative, which is in contrast to the reduction in wave-speed caused by intrinsic stochasticity. To deal with the loss of accuracy as ϵ increases, we formulate a second-order approximation to the wave-speed for periodic landscapes and compare both approximations against the results of numerical simulation and show that they are both accurate for the range of landscapes considered. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predictive Modelling to Identify Near-Shore, Fine-Scale Seabird Distributions during the Breeding Season

PubMed Central

Warwick-Evans, Victoria C.; Atkinson, Philip W.; Robinson, Leonie A.; Green, Jonathan A.

2016-01-01

During the breeding season seabirds are constrained to coastal areas and are restricted in their movements, spending much of their time in near-shore waters either loafing or foraging. However, in using these areas they may be threatened by anthropogenic activities such as fishing, watersports and coastal developments including marine renewable energy installations. Although many studies describe large scale interactions between seabirds and the environment, the drivers behind near-shore, fine-scale distributions are not well understood. For example, Alderney is an important breeding ground for many species of seabird and has a diversity of human uses of the marine environment, thus providing an ideal location to investigate the near-shore fine-scale interactions between seabirds and the environment. We used vantage point observations of seabird distribution, collected during the 2013 breeding season in order to identify and quantify some of the environmental variables affecting the near-shore, fine-scale distribution of seabirds in Alderney’s coastal waters. We validate the models with observation data collected in 2014 and show that water depth, distance to the intertidal zone, and distance to the nearest seabird nest are key predictors in the distribution of Alderney’s seabirds. AUC values for each species suggest that these models perform well, although the model for shags performed better than those for auks and gulls. While further unexplained underlying localised variation in the environmental conditions will undoubtedly effect the fine-scale distribution of seabirds in near-shore waters we demonstrate the potential of this approach in marine planning and decision making. PMID:27031616

Quantifying Neighborhood-Scale Spatial Variations of Ozone at Open Space and Urban Sites in Boulder, Colorado Using Low-Cost Sensor Technology.

PubMed

Cheadle, Lucy; Deanes, Lauren; Sadighi, Kira; Gordon Casey, Joanna; Collier-Oxandale, Ashley; Hannigan, Michael

2017-09-10

Recent advances in air pollution sensors have led to a new wave of low-cost measurement systems that can be deployed in dense networks to capture small-scale spatio-temporal variations in ozone, a pollutant known to cause negative human health impacts. This study deployed a network of seven low-cost ozone metal oxide sensor systems (UPods) in both an open space and an urban location in Boulder, Colorado during June and July of 2015, to quantify ozone variations on spatial scales ranging from 12 m between UPods to 6.7 km between open space and urban measurement sites with a measurement uncertainty of ~5 ppb. The results showed spatial variability of ozone at both deployment sites, with the largest differences between UPod measurements occurring during the afternoons. The peak median hourly difference between UPods was 6 ppb at 1:00 p.m. at the open space site, and 11 ppb at 4:00 p.m. at the urban site. Overall, the urban ozone measurements were higher than in the open space measurements. This study evaluates the effectiveness of using low-cost sensors to capture microscale spatial and temporal variation of ozone; additionally, it highlights the importance of field calibrations and measurement uncertainty quantification when deploying low-cost sensors.

The influence of fine-scale habitat features on regional variation in population performance of alpine White-tailed Ptarmigan

USGS Publications Warehouse

Fedy, B.; Martin, K.

2011-01-01

It is often assumed (explicitly or implicitly) that animals select habitat features to maximize fitness. However, there is often a mismatch between preferred habitats and indices of individual and population measures of performance. We examined the influence of fine-scale habitat selection on the overall population performance of the White-tailed Ptarmigan (Lagopus leucura), an alpine specialist, in two subdivided populations whose habitat patches are configured differently. The central region of Vancouver Island, Canada, has more continuous and larger habitat patches than the southern region. In 2003 and 2004, using paired logistic regression between used (n = 176) and available (n = 324) sites, we identified food availability, distance to standing water, and predator cover as preferred habitat components . We then quantified variation in population performance in the two regions in terms of sex ratio, age structure (n = 182 adults and yearlings), and reproductive success (n = 98 females) on the basis of 8 years of data (1995-1999, 2002-2004). Region strongly influenced females' breeding success, which, unsuccessful hens included, was consistently higher in the central region (n = 77 females) of the island than in the south (n = 21 females, P = 0.01). The central region also had a much higher proportion of successful hens (87%) than did the south (55%, P < 0.001). In light of our findings, we suggest that population performance is influenced by a combination of fine-scale habitat features and coarse-scale habitat configuration. ?? The Cooper Ornithological Society 2011.

How does complex terrain influence responses of carbon and water cycle processes to climate variability and climate change? (Invited)

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.

Mapping lava morphology of the Galapagos Spreading Center at 92°W: fuzzy logic provides a classification of high-resolution bathymetry and backscatter

NASA Astrophysics Data System (ADS)

McClinton, J. T.; White, S. M.; Sinton, J. M.; Rubin, K. H.; Bowles, J. A.

2010-12-01

Differences in axial lava morphology along the Galapagos Spreading Center (GSC) can indicate variations in magma supply and emplacement dynamics due to the influence of the adjacent Galapagos hot spot. Unfortunately, the ability to discriminate fine-scale lava morphology has historically been limited to observations of the small coverage areas of towed camera surveys and submersible operations. This research presents a neuro-fuzzy approach to automated seafloor classification using spatially coincident, high-resolution bathymetry and backscatter data. The classification method implements a Sugeno-type fuzzy inference system trained by a multi-layered adaptive neural network and is capable of rapidly classifying seafloor morphology based on attributes of surface geometry and texture. The system has been applied to the 92°W segment of the western GSC in order to quantify coverage areas and distributions of pillow, lobate, and sheet lava morphology. An accuracy assessment has been performed on the classification results. The resulting classified maps provide a high-resolution view of GSC axial morphology and indicate the study area terrain is approximately 40% pillow flows, 40% lobate and sheet flows, and 10% fissured or faulted area, with about 10% of the study area unclassifiable. Fine-scale features such as eruptive fissures, tumuli, and individual pillowed lava flow fronts are also visible. Although this system has been applied to lava morphology, its design and implementation are applicable to other undersea mapping applications.

Habitat Hydrology and Geomorphology Control the Distribution of Malaria Vector Larvae in Rural Africa

PubMed Central

Hardy, Andrew J.; Gamarra, Javier G. P.; Cross, Dónall E.; Macklin, Mark G.; Smith, Mark W.; Kihonda, Japhet; Killeen, Gerry F.; Ling’ala, George N.; Thomas, Chris J.

2013-01-01

Background Larval source management is a promising component of integrated malaria control and elimination. This requires development of a framework to target productive locations through process-based understanding of habitat hydrology and geomorphology. Methods We conducted the first catchment scale study of fine resolution spatial and temporal variation in Anopheles habitat and productivity in relation to rainfall, hydrology and geomorphology for a high malaria transmission area of Tanzania. Results Monthly aggregates of rainfall, river stage and water table were not significantly related to the abundance of vector larvae. However, these metrics showed strong explanatory power to predict mosquito larval abundances after stratification by water body type, with a clear seasonal trend for each, defined on the basis of its geomorphological setting and origin. Conclusion Hydrological and geomorphological processes governing the availability and productivity of Anopheles breeding habitat need to be understood at the local scale for which larval source management is implemented in order to effectively target larval source interventions. Mapping and monitoring these processes is a well-established practice providing a tractable way forward for developing important malaria management tools. PMID:24312606

Atomic-scale observation of structural and electronic orders in the layered compound α-RuCl3

PubMed Central

Ziatdinov, M.; Banerjee, A.; Maksov, A.; Berlijn, T.; Zhou, W.; Cao, H. B.; Yan, J.-Q.; Bridges, C. A.; Mandrus, D. G.; Nagler, S. E.; Baddorf, A. P.; Kalinin, S. V.

2016-01-01

A pseudospin-1/2 Mott phase on a honeycomb lattice is proposed to host the celebrated two-dimensional Kitaev model which has an elusive quantum spin liquid ground state, and fascinating physics relevant to the development of future templates towards topological quantum bits. Here we report a comprehensive, atomically resolved real-space study by scanning transmission electron and scanning tunnelling microscopies on a novel layered material displaying Kitaev physics, α-RuCl3. Our local crystallography analysis reveals considerable variations in the geometry of the ligand sublattice in thin films of α-RuCl3 that opens a way to realization of a spatially inhomogeneous magnetic ground state at the nanometre length scale. Using scanning tunnelling techniques, we observe the electronic energy gap of ≈0.25 eV and intra-unit cell symmetry breaking of charge distribution in individual α-RuCl3 surface layer. The corresponding charge-ordered pattern has a fine structure associated with two different types of charge disproportionation at Cl-terminated surface. PMID:27941761

Atomic-scale observation of structural and electronic orders in the layered compound α-RuCl3.

PubMed

Ziatdinov, M; Banerjee, A; Maksov, A; Berlijn, T; Zhou, W; Cao, H B; Yan, J-Q; Bridges, C A; Mandrus, D G; Nagler, S E; Baddorf, A P; Kalinin, S V

2016-12-12

A pseudospin-1/2 Mott phase on a honeycomb lattice is proposed to host the celebrated two-dimensional Kitaev model which has an elusive quantum spin liquid ground state, and fascinating physics relevant to the development of future templates towards topological quantum bits. Here we report a comprehensive, atomically resolved real-space study by scanning transmission electron and scanning tunnelling microscopies on a novel layered material displaying Kitaev physics, α-RuCl 3 . Our local crystallography analysis reveals considerable variations in the geometry of the ligand sublattice in thin films of α-RuCl 3 that opens a way to realization of a spatially inhomogeneous magnetic ground state at the nanometre length scale. Using scanning tunnelling techniques, we observe the electronic energy gap of ≈0.25 eV and intra-unit cell symmetry breaking of charge distribution in individual α-RuCl 3 surface layer. The corresponding charge-ordered pattern has a fine structure associated with two different types of charge disproportionation at Cl-terminated surface.

Atomic-scale observation of structural and electronic orders in the layered compound α-RuCl 3

DOE PAGES

Ziatdinov, Maxim A.; Banerjee, Arnab; Maksov, Artem B.; ...

2016-12-12

A pseudospin-1/2 Mott phase on a honeycomb lattice is proposed to host the celebrated two-dimensional Kitaev model which has an elusive quantum spin liquid ground state, and fascinating physics relevant to the development of future templates towards topological quantum bits. Here we report a comprehensive, atomically resolved real-space study by scanning transmission electron and scanning tunnelling microscopies on a novel layered material displaying Kitaev physics, -RuCl3. Our local crystallography analysis reveals considerable variations in the geometry of the ligand sublattice in thin films of -RuCl3 that opens a way to realization of a spatially inhomogeneous magnetic ground state at themore » nanometre length scale. Using scanning tunnelling techniques, we observe the electronic energy gap of 0.25 eV and intra-unit cell symmetry breaking of charge distribution in individual -RuCl3 surface layer. The corresponding charge-ordered pattern has a fine structure associated with two different types of charge disproportionation at Cl-terminated surface.« less

Habitat hydrology and geomorphology control the distribution of malaria vector larvae in rural Africa.

PubMed

Hardy, Andrew J; Gamarra, Javier G P; Cross, Dónall E; Macklin, Mark G; Smith, Mark W; Kihonda, Japhet; Killeen, Gerry F; Ling'ala, George N; Thomas, Chris J

2013-01-01

Larval source management is a promising component of integrated malaria control and elimination. This requires development of a framework to target productive locations through process-based understanding of habitat hydrology and geomorphology. We conducted the first catchment scale study of fine resolution spatial and temporal variation in Anopheles habitat and productivity in relation to rainfall, hydrology and geomorphology for a high malaria transmission area of Tanzania. Monthly aggregates of rainfall, river stage and water table were not significantly related to the abundance of vector larvae. However, these metrics showed strong explanatory power to predict mosquito larval abundances after stratification by water body type, with a clear seasonal trend for each, defined on the basis of its geomorphological setting and origin. Hydrological and geomorphological processes governing the availability and productivity of Anopheles breeding habitat need to be understood at the local scale for which larval source management is implemented in order to effectively target larval source interventions. Mapping and monitoring these processes is a well-established practice providing a tractable way forward for developing important malaria management tools.

Multi-approaches analysis reveals local adaptation in the emmer wheat (Triticum dicoccoides) at macro- but not micro-geographical scale.

PubMed

Volis, Sergei; Ormanbekova, Danara; Yermekbayev, Kanat; Song, Minshu; Shulgina, Irina

2015-01-01

Detecting local adaptation and its spatial scale is one of the most important questions of evolutionary biology. However, recognition of the effect of local selection can be challenging when there is considerable environmental variation across the distance at the whole species range. We analyzed patterns of local adaptation in emmer wheat, Triticum dicoccoides, at two spatial scales, small (inter-population distance less than one km) and large (inter-population distance more than 50 km) using several approaches. Plants originating from four distinct habitats at two geographic scales (cold edge, arid edge and two topographically dissimilar core locations) were reciprocally transplanted and their success over time was measured as 1) lifetime fitness in a year of planting, and 2) population growth four years after planting. In addition, we analyzed molecular (SSR) and quantitative trait variation and calculated the QST/FST ratio. No home advantage was detected at the small spatial scale. At the large spatial scale, home advantage was detected for the core population and the cold edge population in the year of introduction via measuring life-time plant performance. However, superior performance of the arid edge population in its own environment was evident only after several generations via measuring experimental population growth rate through genotyping with SSRs allowing counting the number of plants and seeds per introduced genotype per site. These results highlight the importance of multi-generation surveys of population growth rate in local adaptation testing. Despite predominant self-fertilization of T. dicoccoides and the associated high degree of structuring of genetic variation, the results of the QST - FST comparison were in general agreement with the pattern of local adaptation at the two spatial scales detected by reciprocal transplanting.

Hydrological networks and associated topographic variation as templates for the spatial organization of tropical forest vegetation.

PubMed

Detto, Matteo; Muller-Landau, Helene C; Mascaro, Joseph; Asner, Gregory P

2013-01-01

An understanding of the spatial variability in tropical forest structure and biomass, and the mechanisms that underpin this variability, is critical for designing, interpreting, and upscaling field studies for regional carbon inventories. We investigated the spatial structure of tropical forest vegetation and its relationship to the hydrological network and associated topographic structure across spatial scales of 10-1000 m using high-resolution maps of LiDAR-derived mean canopy profile height (MCH) and elevation for 4930 ha of tropical forest in central Panama. MCH was strongly associated with the hydrological network: canopy height was highest in areas of positive convexity (valleys, depressions) close to channels draining 1 ha or more. Average MCH declined strongly with decreasing convexity (transition to ridges, hilltops) and increasing distance from the nearest channel. Spectral analysis, performed with wavelet decomposition, showed that the variance in MCH had fractal similarity at scales of ∼30-600 m, and was strongly associated with variation in elevation, with peak correlations at scales of ∼250 m. Whereas previous studies of topographic correlates of tropical forest structure conducted analyses at just one or a few spatial grains, our study found that correlations were strongly scale-dependent. Multi-scale analyses of correlations of MCH with slope, aspect, curvature, and Laplacian convexity found that MCH was most strongly related to convexity measured at scales of 20-300 m, a topographic variable that is a good proxy for position with respect to the hydrological network. Overall, our results support the idea that, even in these mesic forests, hydrological networks and associated topographical variation serve as templates upon which vegetation is organized over specific ranges of scales. These findings constitute an important step towards a mechanistic understanding of these patterns, and can guide upscaling and downscaling.

Utilizing 1-meter Landcover Data to Assess Associations between Green Space and Stress

EPA Science Inventory

Purpose: When using remotely-sensed data to study health, researchers must identify an appropriate spatial resolution to capture potential exposures. Investigations into urban green space are often limited by the unavailability of fine-scale landcover data. We analyzed 1-meter gr...

Landscape capability predicts upland game bird abundance and occurrence

USGS Publications Warehouse

Loman, Zachary G.; Blomberg, Erik J.; DeLuca, William; Harrison, Daniel J.; Loftin, Cyndy; Wood, Petra B.

2017-01-01

Landscape capability (LC) models are a spatial tool with potential applications in conservation planning. We used survey data to validate LC models as predictors of occurrence and abundance at broad and fine scales for American woodcock (Scolopax minor) and ruffed grouse (Bonasa umbellus). Landscape capability models were reliable predictors of occurrence but were less indicative of relative abundance at route (11.5–14.6 km) and point scales (0.5–1 km). As predictors of occurrence, LC models had high sensitivity (0.71–0.93) and were accurate (0.71–0.88) and precise (0.88 and 0.92 for woodcock and grouse, respectively). Models did not predict point-scale abundance independent of the ability to predict occurrence of either species. The LC models are useful predictors of patterns of occurrences in the northeastern United States, but they have limited utility as predictors of fine-scale or route-specific abundances. 

Predicting and quantifying soil processes using “geomorphon” landform Classification

USDA-ARS?s Scientific Manuscript database

Soil development and behavior vary spatially at multiple observation scales. Predicting and quantifying soil properties and processes via a catena integrates predictable landscape scale variation relevant to both management decisions and soil survey. Soil maps generally convey variation as a set of ...

The Urban Food-Water Nexus: Modeling Water Footprints of Urban Agriculture using CityCrop

NASA Astrophysics Data System (ADS)

Tooke, T. R.; Lathuilliere, M. J.; Coops, N. C.; Johnson, M. S.

2014-12-01

Urban agriculture provides a potential contribution towards more sustainable food production and mitigating some of the human impacts that accompany volatility in regional and global food supply. When considering the capacity of urban landscapes to produce food products, the impact of urban water demand required for food production in cities is often neglected. Urban agricultural studies also tend to be undertaken at broad spatial scales, overlooking the heterogeneity of urban form that exerts an extreme influence on the urban energy balance. As a result, urban planning and management practitioners require, but often do not have, spatially explicit and detailed information to support informed urban agricultural policy, especially as it relates to potential conflicts with sustainability goals targeting water-use. In this research we introduce a new model, CityCrop, a hybrid evapotranspiration-plant growth model that incorporates detailed digital representations of the urban surface and biophysical impacts of the built environment and urban trees to account for the daily variations in net surface radiation. The model enables very fine-scale (sub-meter) estimates of water footprints of potential urban agricultural production. Results of the model are demonstrated for an area in the City of Vancouver, Canada and compared to aspatial model estimates, demonstrating the unique considerations and sensitivities for current and future water footprints of urban agriculture and the implications for urban water planning and policy.

Impact of Variable SST on Simulated Warm Season Precipitation

NASA Astrophysics Data System (ADS)

Saleeby, S. M.; Cotton, W. R.

2007-05-01

The Colorado State University - Regional Atmospheric Modeling System (CSU-RAMS) is being used to examine the variability in monsoon-related warm season precipitation over Mexico and the United States due to variability in SST. Given recent improvements and increased resolution in satellite derived SSTs it is pertinent to examine the sensitivity of the RAMS model to the variety of SST data sources that are available. In particular, we are examining this dependence across continental scales over the full warm season, as well as across the regional scale centered around the Gulf of California on time scales of individual surge events. In this study we performed an ensemble of simulations that include the 2002, 2003, and 2004 warm seasons with use of the Climatology, Reynold's, AVHRR, and MODIS SSTs. From the seasonal 90-day simulations with 30km grid spacing, it was found that variations in surface latent heat flux are directly linked to differences in SST. Regions with cooler (warmer) SST have decreased (increased) moisture flux from the ocean which is in proportion to the magnitude of the SST difference. Over the eastern Pacific, differences in low-level horizontal moisture flux show a general trend toward reduced fluxes over cooler waters and very little inland impact. Over the Gulf of Mexico, however, there is substantial variability for each dataset comparison, despite having only limited variability among the SST data. Causes of this unexpected variability are not straight-forward. Precipitation impacts are greatest near the southern coast of Mexico and along the Sierra Madres. Precipitation variability over the CONUS is rather chaotic and is limited to areas impacted by the Gulf of Mexico or monsoon convection. Another unexpected outcome is the lack of variability in areas near the northern Gulf of California where SST and latent heat flux variability is a maximum. From the 7-day surge period simulations at 7km grid spacing, we found that SST differences on the higher resolution nested grid reveal fine scale variability that is otherwise smoothed out or unapparent on the coarser grid. Unlike the coarse grid, the latent heat flux, temperature, and moisture transport differences on the fine grid reveal an inland impact. This is likely due to fine scale variability in onshore moisture transport and sea- breeze circulations which may alter monsoonal convection and precipitation. However, only the largest SST differences (spatially and in magnitude) tend to invoke large, coherent responses in moisture flux. The SST variability at high resolution produces relatively large differences in precipitation that are focused along the slopes of the SMO, with a tendency toward greater variability along the western slope adjacent to the coast. The precipitation differences are of fine resolution, with variability of +/- 30 mm (over 5 days) along the length of the SMO. Variability on the fine grid also invokes precipitation changes over AZ/NM that are not resolved on the coarse grid. Vertical cross-sections examined along the GoC during the surge episode revealed variations in the moisture and temperature structure of the surge. The cooler SSTs in the climatological dataset produced the greatest variability compared to the other datasets. The surge produced from climatology SSTs was nearly 5g/kg drier and up to 4°C cooler compared to surges influenced by the SST datasets. The overall northward propagation of the surge appeared unaffected by the SSTs.

Structural heritage, reactivation and distribution of fault and fracture network in a rifting context: Case study of the western shoulder of the Upper Rhine Graben

NASA Astrophysics Data System (ADS)

Bertrand, Lionel; Jusseaume, Jessie; Géraud, Yves; Diraison, Marc; Damy, Pierre-Clément; Navelot, Vivien; Haffen, Sébastien

2018-03-01

In fractured reservoirs in the basement of extensional basins, fault and fracture parameters like density, spacing and length distribution are key properties for modelling and prediction of reservoir properties and fluids flow. As only large faults are detectable using basin-scale geophysical investigations, these fine-scale parameters need to be inferred from faults and fractures in analogous rocks at the outcrop. In this study, we use the western shoulder of the Upper Rhine Graben as an outcropping analogue of several deep borehole projects in the basement of the graben. Geological regional data, DTM (Digital Terrain Model) mapping and outcrop studies with scanlines are used to determine the spatial arrangement of the faults from the regional to the reservoir scale. The data shows that: 1) The fault network can be hierarchized in three different orders of scale and structural blocks with a characteristic structuration. This is consistent with other basement rocks studies in other rifting system allowing the extrapolation of the important parameters for modelling. 2) In the structural blocks, the fracture network linked to the faults is linked to the interplay between rock facies variation linked to the rock emplacement and the rifting event.

Multi-scale investigation of shrub encroachment in southern Africa

NASA Astrophysics Data System (ADS)

Aplin, Paul; Marston, Christopher; Wilkinson, David; Field, Richard; O'Regan, Hannah

2016-04-01

There is growing speculation that savannah environments throughout Africa have been subject to shrub encroachment in recent years, whereby grassland is lost to woody vegetation cover. Changes in the relative proportions of grassland and woodland are important in the context of conservation of savannah systems, with implications for faunal distributions, environmental management and tourism. Here, we focus on southern Kruger National Park, South Africa, and investigate whether or not shrub encroachment has occurred over the last decade and a half. We use a multi-scale approach, examining the complementarity of medium (e.g. Landsat TM and OLI) and fine (e.g. QuickBird and WorldView-2) spatial resolution satellite sensor imagery, supported by intensive field survey in 2002 and 2014. We employ semi-automated land cover classification, involving a hybrid unsupervised clustering approach with manual class grouping and checking, followed by change detection post-classification comparison analysis. The results show that shrub encroachment is indeed occurring, a finding evidenced through three fine resolution replicate images plus medium resolution imagery. The results also demonstrate the complementarity of medium and fine resolution imagery, though some thematic information must be sacrificed to maintain high medium resolution classification accuracy. Finally, the findings have broader implications for issues such as vegetation seasonality, spatial transferability and management practices.

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

PubMed Central

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

2012-01-01

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

Fine root dynamics along an elevational gradient in tropical Amazonian and Andean forests

NASA Astrophysics Data System (ADS)

Girardin, C. A. J.; Aragão, L. E. O. C.; Malhi, Y.; Huaraca Huasco, W.; Metcalfe, D. B.; Durand, L.; Mamani, M.; Silva-Espejo, J. E.; Whittaker, R. J.

2013-01-01

The key role of tropical forest belowground carbon stocks and fluxes is well recognised as one of the main components of the terrestrial ecosystem carbon cycle. This study presents the first detailed investigation of spatial and temporal patterns of fine root stocks and fluxes in tropical forests along an elevational gradient, ranging from the Peruvian Andes (3020 m) to lowland Amazonia (194 m), with mean annual temperatures of 11.8°C to 26.4 °C and annual rainfall values of 1900 to 1560 mm yr-1, respectively. Specifically, we analyse abiotic parameters controlling fine root dynamics, fine root growth characteristics, and seasonality of net primary productivity along the elevation gradient. Root and soil carbon stocks were measured by means of soil cores, and fine root productivity was recorded using rhizotron chambers and ingrowth cores. We find that mean annual fine root below ground net primary productivity in the montane forests (0-30 cm depth) ranged between 4.27±0.56 Mg C ha-1 yr-1 (1855 m) and 1.72±0.87 Mg C ha-1 yr-1 (3020 m). These values include a correction for finest roots (<0.6 mm diameter), which we suspect are under sampled, resulting in an underestimation of fine roots by up to 31% in current ingrowth core counting methods. We investigate the spatial and seasonal variation of fine root dynamics using soil depth profiles and an analysis of seasonal amplitude along the elevation gradient. We report a stronger seasonality of NPPFineRoot within the cloud immersion zone, most likely synchronised to seasonality of solar radiation. Finally, we provide the first insights into root growth characteristics along a tropical elevation transect: fine root area and fine root length increase significantly in the montane cloud forest. These insights into belowground carbon dynamics of tropical lowland and montane forests have significant implications for our understanding of the global tropical forest carbon cycle.

Distribution of melt along the East Pacific Rise from 9°30' to 10°N from an amplitude variation with angle of incidence (AVA) technique

NASA Astrophysics Data System (ADS)

Marjanović, Milena; Carton, Hélène; Carbotte, Suzanne M.; Nedimović, Mladen R.; Mutter, John C.; Canales, J. Pablo

2015-10-01

We examine along-axis variations in melt content of the axial magma lens (AML) beneath the fast-spreading East Pacific Rise (EPR) using an amplitude variation with angle of incidence (AVA) crossplotting method applied to multichannel seismic data acquired in 2008. The AVA crossplotting method, which has been developed for and, so far, applied for hydrocarbon prospection in sediments, is for the first time applied to a hardrock environment. We focus our analysis on 2-D data collected along the EPR axis from 9°29.8'N to 9°58.4'N, a region which encompasses the sites of two well-documented submarine volcanic eruptions (1991-1992 and 2005-2006). AVA crossplotting is performed for a ˜53 km length of the EPR spanning nine individual AML segments (ranging in length from ˜3.2 to 8.5 km) previously identified from the geometry of the AML and disruptions in continuity. Our detailed analyses conducted at 62.5 m interval show that within most of the analysed segments melt content varies at spatial scales much smaller (a few hundred of metres) than the length of the fine-scale AML segments, suggesting high heterogeneity in melt concentration. At the time of our survey, about 2 yr after the eruption, our results indicate that the three AML segments that directly underlie the 2005-2006 lava flow are on average mostly molten. However, detailed analysis at finer-scale intervals for these three segments reveals AML pockets (from >62.5 to 812.5 m long) with a low melt fraction. The longest such mushy section is centred beneath the main eruption site at ˜9°50.4'N, possibly reflecting a region of primary melt drainage during the 2005-2006 event. The complex geometry of fluid flow pathways within the crust above the AML and the different response times of fluid flow and venting to eruption and magma reservoir replenishment may contribute to the poor spatial correlation between incidence of hydrothermal vents and presence of highly molten AML. The presented results are an important step forward in our ability to resolve small-scale characteristics of the AML and recommend the AVA crossplotting as a tool for examining mid-ocean ridge magma-systems elsewhere.

Spatial variation in disease resistance: from molecules to metapopulations

PubMed Central

Laine, Anna-Liisa; Burdon, Jeremy J.; Dodds, Peter N.; Thrall, Peter H.

2010-01-01

Summary Variation in disease resistance is a widespread phenomenon in wild plant-pathogen associations. Here, we review current literature on natural plant-pathogen associations to determine how diversity in disease resistance is distributed at different hierarchical levels – within host individuals, within host populations, among host populations at the metapopulation scale and at larger regional scales. We find diversity in resistance across all spatial scales examined. Furthermore, variability seems to be the best counter-defence of plants against their rapidly evolving pathogens. We find that higher diversity of resistance phenotypes also results in higher levels of resistance at the population level. Overall, we find that wild plant populations are more likely to be susceptible than resistant to their pathogens. However, the degree of resistance differs strikingly depending on the origin of the pathogen strains used in experimental inoculation studies. Plant populations are on average 16% more resistant to allopatric pathogen strains than they are to strains that occur within the same population (48 % vs. 32 % respectively). Pathogen dispersal mode affects levels of resistance in natural plant populations with lowest levels detected for hosts of airborne pathogens and highest for waterborne pathogens. Detailed analysis of two model systems, Linum marginale infected by Melampsora lini, and Plantago lanceolata infected by Podosphaera plantaginis, show that the amount of variation in disease resistance declines towards higher spatial scales as we move from individual hosts to metapopulations, but evaluation of multiple spatial scales is needed to fully capture the structure of disease resistance. Synthesis: Variation in disease resistance is ubiquitous in wild plant-pathogen associations. While the debate over whether the resistance structure of plant populations is determined by pathogen-imposed selection versus non-adaptive processes remains unresolved, we do report examples of pathogen-imposed selection on host resistance. Here we highlight the importance of measuring resistance across multiple spatial scales, and of using sympatric strains when looking for signs of coevolution in wild plant-pathogen interactions. PMID:21243068

Multi-scale soil salinity mapping and monitoring with proximal and remote sensing

USDA-ARS?s Scientific Manuscript database

This talk is part of a technical short course on “Soil mapping and process modelling at diverse scales”. In the talk, guidelines, special considerations, protocols, and strengths and limitations are presented for characterizing spatial and temporal variation in soil salinity at several spatial scale...

Spatial heterogeneity in human activities favors the persistence of wolves in agroecosystems.

PubMed

Ahmadi, Mohsen; López-Bao, José Vicente; Kaboli, Mohammad

2014-01-01

As human populations expand, there is increasing demand and pressure for land. Under this scenario, behavioural flexibility and adaptation become important processes leading to the persistence of large carnivores in human-dominated landscapes such as agroecosystems. A growing interest has recently emerged on the outcome of the coexistence between wolves and humans in these systems. It has been suggested that spatial heterogeneity in human activities would be a major environmental factor modulating vulnerability and persistence of this contentious species in agroecosystems. Here, we combined information from 35 den sites detected between 2011 and 2012 in agroecosystems of western Iran (Hamedan province), a set of environmental variables measured at landscape and fine spatial scales, and generalized linear models to identify patterns of den site selection by wolves in a highly-modified agroecosystem. On a landscape level, wolves selected a mixture of rangelands with scattered dry-farms on hillsides (showing a low human use) to locate their dens, avoiding areas with high densities of settlements and primary roads. On a fine spatial scale, wolves primarily excavated dens into the sides of elevated steep-slope hills with availability of water bodies in the vicinity of den sites, and wolves were relegated to dig in places with coarse-soil particles. Our results suggest that vulnerability of wolves in human-dominated landscapes could be compensated by the existence of spatial heterogeneity in human activities. Such heterogeneity would favor wolf persistence in agroecosystems favoring a land sharing model of coexistence between wolves and people.

Spatial Heterogeneity in Human Activities Favors the Persistence of Wolves in Agroecosystems

PubMed Central

Ahmadi, Mohsen; López-Bao, José Vicente; Kaboli, Mohammad

2014-01-01

As human populations expand, there is increasing demand and pressure for land. Under this scenario, behavioural flexibility and adaptation become important processes leading to the persistence of large carnivores in human-dominated landscapes such as agroecosystems. A growing interest has recently emerged on the outcome of the coexistence between wolves and humans in these systems. It has been suggested that spatial heterogeneity in human activities would be a major environmental factor modulating vulnerability and persistence of this contentious species in agroecosystems. Here, we combined information from 35 den sites detected between 2011 and 2012 in agroecosystems of western Iran (Hamedan province), a set of environmental variables measured at landscape and fine spatial scales, and generalized linear models to identify patterns of den site selection by wolves in a highly-modified agroecosystem. On a landscape level, wolves selected a mixture of rangelands with scattered dry-farms on hillsides (showing a low human use) to locate their dens, avoiding areas with high densities of settlements and primary roads. On a fine spatial scale, wolves primarily excavated dens into the sides of elevated steep-slope hills with availability of water bodies in the vicinity of den sites, and wolves were relegated to dig in places with coarse-soil particles. Our results suggest that vulnerability of wolves in human-dominated landscapes could be compensated by the existence of spatial heterogeneity in human activities. Such heterogeneity would favor wolf persistence in agroecosystems favoring a land sharing model of coexistence between wolves and people. PMID:25251567

Drivers of protogynous sex change differ across spatial scales.

PubMed

Taylor, Brett M

2014-01-22

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