Recent Regional Climate State and Change - Derived through Downscaling Homogeneous Large-scale Components of Re-analyses

NASA Astrophysics Data System (ADS)

Von Storch, H.; Klehmet, K.; Geyer, B.; Li, D.; Schubert-Frisius, M.; Tim, N.; Zorita, E.

2015-12-01

Global re-analyses suffer from inhomogeneities, as they process data from networks under development. However, the large-scale component of such re-analyses is mostly homogeneous; additional observational data add in most cases to a better description of regional details and less so on large-scale states. Therefore, the concept of downscaling may be applied to homogeneously complementing the large-scale state of the re-analyses with regional detail - wherever the condition of homogeneity of the large-scales is fulfilled. Technically this can be done by using a regional climate model, or a global climate model, which is constrained on the large scale by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional risks - in particular marine risks - was identified. While the data density in Europe is considerably better than in most other regions of the world, even here insufficient spatial and temporal coverage is limiting risk assessments. Therefore, downscaled data-sets are frequently used by off-shore industries. We have run this system also in regions with reduced or absent data coverage, such as the Lena catchment in Siberia, in the Yellow Sea/Bo Hai region in East Asia, in Namibia and the adjacent Atlantic Ocean. Also a global (large scale constrained) simulation has been. It turns out that spatially detailed reconstruction of the state and change of climate in the three to six decades is doable for any region of the world.The different data sets are archived and may freely by used for scientific purposes. Of course, before application, a careful analysis of the quality for the intended application is needed, as sometimes unexpected changes in the quality of the description of large-scale driving states prevail.

Spatially resolved Spectroscopy of Europa’s Large-scale Compositional Units at 3-4 μm with Keck NIRSPEC

NASA Astrophysics Data System (ADS)

Fischer, P. D.; Brown, M. E.; Trumbo, S. K.; Hand, K. P.

2017-01-01

We present spatially resolved spectroscopic observations of Europa’s surface at 3-4 μm obtained with the near-infrared spectrograph and adaptive optics system on the Keck II telescope. These are the highest quality spatially resolved reflectance spectra of Europa’s surface at 3-4 μm. The observations spatially resolve Europa’s large-scale compositional units at a resolution of several hundred kilometers. The spectra show distinct features and geographic variations associated with known compositional units; in particular, large-scale leading hemisphere chaos shows a characteristic longward shift in peak reflectance near 3.7 μm compared to icy regions. These observations complement previous spectra of large-scale chaos, and can aid efforts to identify the endogenous non-ice species.

Spatial and temporal synchrony in reptile population dynamics in variable environments.

PubMed

Greenville, Aaron C; Wardle, Glenda M; Nguyen, Vuong; Dickman, Chris R

2016-10-01

Resources are seldom distributed equally across space, but many species exhibit spatially synchronous population dynamics. Such synchrony suggests the operation of large-scale external drivers, such as rainfall or wildfire, or the influence of oasis sites that provide water, shelter, or other resources. However, testing the generality of these factors is not easy, especially in variable environments. Using a long-term dataset (13-22 years) from a large (8000 km(2)) study region in arid Central Australia, we tested firstly for regional synchrony in annual rainfall and the dynamics of six reptile species across nine widely separated sites. For species that showed synchronous spatial dynamics, we then used multivariate follow a multivariate auto-regressive state-space (MARSS) models to predict that regional rainfall would be positively associated with their populations. For asynchronous species, we used MARSS models to explore four other possible population structures: (1) populations were asynchronous, (2) differed between oasis and non-oasis sites, (3) differed between burnt and unburnt sites, or (4) differed between three sub-regions with different rainfall gradients. Only one species showed evidence of spatial population synchrony and our results provide little evidence that rainfall synchronizes reptile populations. The oasis or the wildfire hypotheses were the best-fitting models for the other five species. Thus, our six study species appear generally to be structured in space into one or two populations across the study region. Our findings suggest that for arid-dwelling reptile populations, spatial and temporal dynamics are structured by abiotic events, but individual responses to covariates at smaller spatial scales are complex and poorly understood.

Large-scale derived flood frequency analysis based on continuous simulation

NASA Astrophysics Data System (ADS)

Dung Nguyen, Viet; Hundecha, Yeshewatesfa; Guse, Björn; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

There is an increasing need for spatially consistent flood risk assessments at the regional scale (several 100.000 km2), in particular in the insurance industry and for national risk reduction strategies. However, most large-scale flood risk assessments are composed of smaller-scale assessments and show spatial inconsistencies. To overcome this deficit, a large-scale flood model composed of a weather generator and catchments models was developed reflecting the spatially inherent heterogeneity. The weather generator is a multisite and multivariate stochastic model capable of generating synthetic meteorological fields (precipitation, temperature, etc.) at daily resolution for the regional scale. These fields respect the observed autocorrelation, spatial correlation and co-variance between the variables. They are used as input into catchment models. A long-term simulation of this combined system enables to derive very long discharge series at many catchment locations serving as a basic for spatially consistent flood risk estimates at the regional scale. This combined model was set up and validated for major river catchments in Germany. The weather generator was trained by 53-year observation data at 528 stations covering not only the complete Germany but also parts of France, Switzerland, Czech Republic and Australia with the aggregated spatial scale of 443,931 km2. 10.000 years of daily meteorological fields for the study area were generated. Likewise, rainfall-runoff simulations with SWIM were performed for the entire Elbe, Rhine, Weser, Donau and Ems catchments. The validation results illustrate a good performance of the combined system, as the simulated flood magnitudes and frequencies agree well with the observed flood data. Based on continuous simulation this model chain is then used to estimate flood quantiles for the whole Germany including upstream headwater catchments in neighbouring countries. This continuous large scale approach overcomes the several drawbacks reported in traditional approaches for the derived flood frequency analysis and therefore is recommended for large scale flood risk case studies.

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

NASA Astrophysics Data System (ADS)

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

2002-12-01

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

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

NASA Astrophysics Data System (ADS)

Niesterowicz, Jacek; Stepinski, Tomasz F.

2017-10-01

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

National land-cover pattern data

Treesearch

Kurt H. Riitters; James D. Wickham; James E. Vogelmann; K. Bruce Jones

2000-01-01

Land cover and its spatial patterns are key ingredients in ecological studies that consider large regions and the impacts of human activities. Because humanity is a principal driver of land-cover change over large regions (Turner et al. 1990), land-cover data provide direct measures of human activity, and both direct and indirect measures of ecological conditions...

SPATIALLY RESOLVED SPECTROSCOPY OF EUROPA’S LARGE-SCALE COMPOSITIONAL UNITS AT 3–4 μ m WITH KECK NIRSPEC

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

Fischer, P. D.; Brown, M. E.; Trumbo, S. K.

2017-01-01

We present spatially resolved spectroscopic observations of Europa’s surface at 3–4 μ m obtained with the near-infrared spectrograph and adaptive optics system on the Keck II telescope. These are the highest quality spatially resolved reflectance spectra of Europa’s surface at 3–4 μ m. The observations spatially resolve Europa’s large-scale compositional units at a resolution of several hundred kilometers. The spectra show distinct features and geographic variations associated with known compositional units; in particular, large-scale leading hemisphere chaos shows a characteristic longward shift in peak reflectance near 3.7 μ m compared to icy regions. These observations complement previous spectra of large-scalemore » chaos, and can aid efforts to identify the endogenous non-ice species.« less

Reserch on Spatial and Temporal Distribution of Color Steel Building Based on Multi-Source High-Resolution Satellite Imagery

NASA Astrophysics Data System (ADS)

Yang, S. W.; Ma, J. J.; Wang, J. M.

2018-04-01

As representative vulnerable regions of the city, dense distribution areas of temporary color steel building are a major target for control of fire risks, illegal buildings, environmental supervision, urbanization quality and enhancement for city's image. In the domestic and foreign literature, the related research mainly focuses on fire risks and violation monitoring. However, due to temporary color steel building's special characteristics, the corresponding research about temporal and spatial distribution, and influence on urban spatial form etc. has not been reported. Therefore, firstly, the paper research aim plans to extract information of large-scale color steel building from high-resolution images. Secondly, the color steel plate buildings were classified, and the spatial and temporal distribution and aggregation characteristics of small (temporary buildings) and large (factory building, warehouse, etc.) buildings were studied respectively. Thirdly, the coupling relationship between the spatial distribution of color steel plate and the spatial pattern of urban space was analysed. The results show that there is a good coupling relationship between the color steel plate building and the urban spatial form. Different types of color steel plate building represent the pattern of regional differentiation of urban space and the phased pattern of urban development.

Dorso-medial and ventro-lateral functional specialization of the human retrosplenial complex in spatial updating and orienting.

PubMed

Burles, Ford; Slone, Edward; Iaria, Giuseppe

2017-04-01

The retrosplenial complex is a region within the posterior cingulate cortex implicated in spatial navigation. Here, we investigated the functional specialization of this large and anatomically heterogeneous region using fMRI and resting-state functional connectivity combined with a spatial task with distinct phases of spatial 'updating' (i.e., integrating and maintaining object locations in memory during spatial displacement) and 'orienting' (i.e., recalling unseen locations from current position in space). Both spatial 'updating' and 'orienting' produced bilateral activity in the retrosplenial complex, among other areas. However, spatial 'updating' produced slightly greater activity in ventro-lateral portions, of the retrosplenial complex, whereas spatial 'orienting' produced greater activity in a more dorsal and medial portion of it (both regions localized along the parieto-occipital fissure). At rest, both ventro-lateral and dorso-medial subregions of the retrosplenial complex were functionally connected to the hippocampus and parahippocampus, regions both involved in spatial orientation and navigation. However, the ventro-lateral subregion of the retrosplenial complex displayed more positive functional connectivity with ventral occipital and temporal object recognition regions, whereas the dorso-medial subregion activity was more correlated to dorsal activity and frontal activity, as well as negatively correlated with more ventral parietal structures. These findings provide evidence for a dorso-medial to ventro-lateral functional specialization within the human retrosplenial complex that may shed more light on the complex neural mechanisms underlying spatial orientation and navigation in humans.

Landscape, demographic and climatic associations with human West Nile virus occurrence regionally in 2012 in the United States of America.

PubMed

DeGroote, John P; Sugumaran, Ramanathan; Ecker, Mark

2014-11-01

After several years of low West Nile virus (WNV) occurrence in the United States of America (USA), 2012 witnessed large outbreaks in several parts of the country. In order to understand the outbreak dynamics, spatial clustering and landscape, demographic and climatic associations with WNV occurrence were investigated at a regional level in the USA. Previous research has demonstrated that there are a handful of prominent WNV mosquito vectors with varying ecological requirements responsible for WNV transmission in the USA. Published range maps of these important vectors were georeferenced and used to define eight functional ecological regions in the coterminous USA. The number of human WNV cases and human populations by county were attained in order to calculate a WNV rate for each county in 2012. Additionally, a binary value (high/low) was calculated for each county based on whether the county WNV rate was above or below the rate for the region it fell in. Global Moran's I and Anselin Local Moran's I statistics of spatial association were used per region to examine and visualize clustering of the WNV rate and the high/low rating. Spatial data on landscape, demographic and climatic variables were compiled and derived from a variety of sources and then investigated in relation to human WNV using both Spearman rho correlation coefficients and Poisson regression models. Findings demonstrated significant spatial clustering of WNV and substantial inter-regional differences in relationships between WNV occurrence and landscape, demographic and climatically related variables. The regional associations were consistent with the ecologies of the dominant vectors for those regions. The large outbreak in the Southeast region was preceded by higher than normal winter and spring precipitation followed by dry and hot conditions in the summer.

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

PubMed Central

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

PubMed

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

The History of the M31 Disk from Resolved Stellar Populations as Seen by PHAT

NASA Astrophysics Data System (ADS)

Lewis, A. R.; Dalcanton, J. J.; Dolphin, A. E.; Weisz, D. R.; Williams, B. F.; PHAT Collaboration

2014-03-01

The Panchromatic Hubble Andromeda Treasury (PHAT) is an HST multi-cycle treasury program that is mapping the resolved stellar populations of ˜1/3 of M31 from the UV through the near-IR. These data provide color and luminosity information for more than 150 million stars in the M31 disk. We use stellar evolution models to fit the luminous main sequence to derive spatially-resolved recent star formation histories (SFHs) over large areas of M31 with 50-100 pc resolution. These include individual star-forming regions as well as quiescent portions of the disk. We use the gridded SFHs to create movies of star formation activity to study the evolution of individual star-forming events across the disk. Outside of the star-forming regions, we use our resolved stellar photometry to derive the full SFHs of larger regions. These allow us to probe spatial and temporal trends in age and metallicity across a large radial baseline, providing constraints on the global formation and evolution of the disk over a Hubble time. M31 is the only large disk galaxy that is close enough to obtain the photometry necessary for this type of spatially-resolved SFH mapping.

Spatial organization of chromatin domains and compartments in single chromosomes

NASA Astrophysics Data System (ADS)

Wang, Siyuan; Su, Jun-Han; Beliveau, Brian; Bintu, Bogdan; Moffitt, Jeffrey; Wu, Chao-Ting; Zhuang, Xiaowei

The spatial organization of chromatin critically affects genome function. Recent chromosome-conformation-capture studies have revealed topologically associating domains (TADs) as a conserved feature of chromatin organization, but how TADs are spatially organized in individual chromosomes remains unknown. Here, we developed an imaging method for mapping the spatial positions of numerous genomic regions along individual chromosomes and traced the positions of TADs in human interphase autosomes and X chromosomes. We observed that chromosome folding deviates from the ideal fractal-globule model at large length scales and that TADs are largely organized into two compartments spatially arranged in a polarized manner in individual chromosomes. Active and inactive X chromosomes adopt different folding and compartmentalization configurations. These results suggest that the spatial organization of chromatin domains can change in response to regulation.

Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

NASA Astrophysics Data System (ADS)

Mateo, Cherry May R.; Yamazaki, Dai; Kim, Hyungjun; Champathong, Adisorn; Vaze, Jai; Oki, Taikan

2017-10-01

Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

Beta-globin locus activation regions: conservation of organization, structure, and function.

PubMed Central

Li, Q L; Zhou, B; Powers, P; Enver, T; Stamatoyannopoulos, G

1990-01-01

The human beta-globin locus activation region (LAR) comprises four erythroid-specific DNase I hypersensitive sites (I-IV) thought to be largely responsible for activating the beta-globin domain and facilitating high-level erythroid-specific globin gene expression. We identified the goat beta-globin LAR, determined 10.2 kilobases of its sequence, and demonstrated its function in transgenic mice. The human and goat LARs share 6.5 kilobases of homologous sequences that are as highly conserved as the epsilon-globin gene promoters. Furthermore, the overall spatial organization of the two LARs has been conserved. These results suggest that the functionally relevant regions of the LAR are large and that in addition to their primary structure, the spatial relationship of the conserved elements is important for LAR function. Images PMID:2236034

Moon-based visibility analysis for the observation of “The Belt and Road”

NASA Astrophysics Data System (ADS)

REN, Yuanzhen; GUO, Huadong; LIU, Guang; YE, Hanlin; DING, Yixing; RUAN, Zhixing; LV, Mingyang

2016-11-01

Aiming at promoting the economic prosperity and regional economic cooperation, the “Silk Road Economic Belt” and the “21st Century Maritime Silk Road” (hereinafter referred to as the Belt and Road) was raised. To get a better understanding of “the Belt and Road” whole region, considering the large-scale characteristic, the Moon platform is a good choice. In this paper, the ephemeris is taken as data source and the positions and attitudes of Sun, Earth and Moon are obtained based on the reference systems transformation. Then we construct a simplified observation model and calculate the spatial and angular visibility of the Moon platform for “the Belt and Road” region. It turns out that Moon-based observation of this region shows a good performance of spatial visibility and variable angular visibility, indicating the Moon being a new potential platform for large-scale Earth observation.

Insights and challenges to Intergrating data from diverse ecological networks

USDA-ARS?s Scientific Manuscript database

Many of the most dramatic and surprising effects of global change occur across large spatial extents, from regions to continents, that impact multiple ecosystem types across a range of interacting spatial and temporal scales. The ability of ecologists and interdisciplinary scientists to understand a...

INTEGRATING FIELD-BASED SAMPLING AND LANDSCAPE DATA FOR REGIONAL SCALE ASSESSMENTS: EXAMPLES FROM THE UNITED STATES MID-ATLANTIC REGION

EPA Science Inventory

Spatially explicit identification of status and changes in ecological conditions over large, regional areas is key to targeting and prioritizing areas for potential further study and environmental protection and restoration. A critical limitation to this point has been our abili...

The effects of transient attention on spatial resolution and the size of the attentional cue.

PubMed

Yeshurun, Yaffa; Carrasco, Marisa

2008-01-01

It has been shown that transient attention enhances spatial resolution, but is the effect of transient attention on spatial resolution modulated by the size of the attentional cue? Would a gradual increase in the size of the cue lead to a gradual decrement in spatial resolution? To test these hypotheses, we used a texture segmentation task in which performance depends on spatial resolution, and systematically manipulated the size of the attentional cue: A bar of different lengths (Experiment 1) or a frame of different sizes (Experiments 2-3) indicated the target region in a texture segmentation display. Observers indicated whether a target patch region (oriented line elements in a background of an orthogonal orientation), appearing at a range of eccentricities, was present in the first or the second interval. We replicated the attentional enhancement of spatial resolution found with small cues; attention improved performance at peripheral locations but impaired performance at central locations. However, there was no evidence of gradual resolution decrement with large cues. Transient attention enhanced spatial resolution at the attended location when it was attracted to that location by a small cue but did not affect resolution when it was attracted by a large cue. These results indicate that transient attention cannot adapt its operation on spatial resolution on the basis of the size of the attentional cue.

Towards a global harmonized permafrost soil organic carbon stock estimates.

NASA Astrophysics Data System (ADS)

Hugelius, G.; Mishra, U.; Yang, Y.

2017-12-01

Permafrost affected soils store disproportionately large amount of organic carbon stocks due to multiple cryopedogenic processes. Previous permafrost soil organic carbon (SOC) stock estimates used a variety of approaches and reported substantial uncertainty in SOC stocks of permafrost soils. Here, we used spatially referenced data of soil-forming factors (topographic attributes, land cover types, climate, and bedrock geology) and SOC pedon description data (n = 2552) in a regression kriging approach to predict the spatial and vertical heterogeneity of SOC stocks across the Northern Circumpolar and Tibetan permafrost regions. Our approach allowed us to take into account both environmental correlation and spatial autocorrelation to separately estimate SOC stocks and their spatial uncertainties (95% CI) for three depth intervals at 250 m spatial resolution. In Northern Circumpolar region, our results show 1278.1 (1009.33 - 1550.45) Pg C in 0-3 m depth interval, with 542.09 (451.83 - 610.15), 422.46 (306.48 - 550.82), and 313.55 (251.02 - 389.48) Pg C in 0 - 1, 1 - 2, and 2 - 3 m depth intervals, respectively. In Tibetan region, our results show 26.68 (9.82 - 79.92) Pg C in 0 - 3 m depth interval, with 13.98 (6.2 - 32.96), 6.49 (1.73 - 25.86), and 6.21 (1.889 - 20.90) Pg C in 0 - 1, 1 - 2, and 2 - 3 m depth intervals, respectively. Our estimates show large spatial variability (50 - 100% coefficient of variation, depending upon the study region and depth interval) and higher uncertainty range in comparison to existing estimates. We will present the observed controls of different environmental factors on SOC at the AGU meeting.

Regional gradient analysis and spatial pattern of woody plant communities in Oregon forests.

Treesearch

J.L. Ohmann; T.A. Spies

1998-01-01

Knowledge of regional-scale patterns of ecological community structure, and of factors that control them, is largely conceptual. Regional- and local-scale factors associated with regional variation in community composition have not been quantified. We analyzed data on woody plant species abundance from 2443 field plots across natural and seminatural forests and...

Local and Regional Impacts of Pollution on Coral Reefs along the Thousand Islands North of the Megacity Jakarta, Indonesia.

PubMed

Baum, Gunilla; Januar, Hedi I; Ferse, Sebastian C A; Kunzmann, Andreas

2015-01-01

Worldwide, coral reefs are challenged by multiple stressors due to growing urbanization, industrialization and coastal development. Coral reefs along the Thousand Islands off Jakarta, one of the largest megacities worldwide, have degraded dramatically over recent decades. The shift and decline in coral cover and composition has been extensively studied with a focus on large-scale gradients (i.e. regional drivers), however special focus on local drivers in shaping spatial community composition is still lacking. Here, the spatial impact of anthropogenic stressors on local and regional scales on coral reefs north of Jakarta was investigated. Results indicate that the direct impact of Jakarta is mainly restricted to inshore reefs, separating reefs in Jakarta Bay from reefs along the Thousand Islands further north. A spatial patchwork of differentially degraded reefs is present along the islands as a result of localized anthropogenic effects rather than regional gradients. Pollution is the main anthropogenic stressor, with over 80% of variation in benthic community composition driven by sedimentation rate, NO2, PO4 and Chlorophyll a. Thus, the spatial structure of reefs is directly related to intense anthropogenic pressure from local as well as regional sources. Therefore, improved spatial management that accounts for both local and regional stressors is needed for effective marine conservation.

Local and Regional Impacts of Pollution on Coral Reefs along the Thousand Islands North of the Megacity Jakarta, Indonesia

PubMed Central

Baum, Gunilla; Januar, Hedi I.; Ferse, Sebastian C. A.; Kunzmann, Andreas

2015-01-01

Worldwide, coral reefs are challenged by multiple stressors due to growing urbanization, industrialization and coastal development. Coral reefs along the Thousand Islands off Jakarta, one of the largest megacities worldwide, have degraded dramatically over recent decades. The shift and decline in coral cover and composition has been extensively studied with a focus on large-scale gradients (i.e. regional drivers), however special focus on local drivers in shaping spatial community composition is still lacking. Here, the spatial impact of anthropogenic stressors on local and regional scales on coral reefs north of Jakarta was investigated. Results indicate that the direct impact of Jakarta is mainly restricted to inshore reefs, separating reefs in Jakarta Bay from reefs along the Thousand Islands further north. A spatial patchwork of differentially degraded reefs is present along the islands as a result of localized anthropogenic effects rather than regional gradients. Pollution is the main anthropogenic stressor, with over 80% of variation in benthic community composition driven by sedimentation rate, NO2, PO4 and Chlorophyll a. Thus, the spatial structure of reefs is directly related to intense anthropogenic pressure from local as well as regional sources. Therefore, improved spatial management that accounts for both local and regional stressors is needed for effective marine conservation. PMID:26378910

Modeling spatially-varying landscape change points in species occurrence thresholds

USGS Publications Warehouse

Wagner, Tyler; Midway, Stephen R.

2014-01-01

Predicting species distributions at scales of regions to continents is often necessary, as large-scale phenomena influence the distributions of spatially structured populations. Land use and land cover are important large-scale drivers of species distributions, and landscapes are known to create species occurrence thresholds, where small changes in a landscape characteristic results in abrupt changes in occurrence. The value of the landscape characteristic at which this change occurs is referred to as a change point. We present a hierarchical Bayesian threshold model (HBTM) that allows for estimating spatially varying parameters, including change points. Our model also allows for modeling estimated parameters in an effort to understand large-scale drivers of variability in land use and land cover on species occurrence thresholds. We use range-wide detection/nondetection data for the eastern brook trout (Salvelinus fontinalis), a stream-dwelling salmonid, to illustrate our HBTM for estimating and modeling spatially varying threshold parameters in species occurrence. We parameterized the model for investigating thresholds in landscape predictor variables that are measured as proportions, and which are therefore restricted to values between 0 and 1. Our HBTM estimated spatially varying thresholds in brook trout occurrence for both the proportion agricultural and urban land uses. There was relatively little spatial variation in change point estimates, although there was spatial variability in the overall shape of the threshold response and associated uncertainty. In addition, regional mean stream water temperature was correlated to the change point parameters for the proportion of urban land use, with the change point value increasing with increasing mean stream water temperature. We present a framework for quantify macrosystem variability in spatially varying threshold model parameters in relation to important large-scale drivers such as land use and land cover. Although the model presented is a logistic HBTM, it can easily be extended to accommodate other statistical distributions for modeling species richness or abundance.

Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome.

PubMed

Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

2015-01-01

Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate "wall-to-wall" remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution.

The characteristic and influence factors of extinction depth of shallow groundwater on the high-latitude region: a case study on the Sanjiang Plain, northeast China.

PubMed

Wang, Xihua

2018-03-01

Accurate estimation of extinction depth of shallow groundwater (EDSG) and identification of its influence factors are important for sustainable management of groundwater resources, ecological protection, and human health in intensively irrigated region. In this study, the ratio of actual groundwater depth and EDSG (RAE) method was used to understand the spatial variability of EDSG in the Sanjiang Plain, one of China's largest grain production bases and China's largest inland freshwater wetland region. The study showed a large spatial variation of EDSG in the region. Spatially, the sites, which were in the northeast and center had the deepest and the shallowest EDSG, whereby, indicate that it has higher and lower pumping potential capacity. Many factors including climate, soil parameters, vegetation and topography affected the EDSG. We also identified an area of 3.86 × 10 10  m 2 , which accounting for 35.3% of the entire Sanjiang Plain, has exceeded the ESGD by over exploited for years. Knowledge of the variation and influence factors of EDSG for a certain plant system and the current shallow groundwater condition in the higher latitude region can be a key to the development of preventive actions for large quantity pumping groundwater and protection regional and sustainable development of irrigated agriculture.

Spatial occupancy models for large data sets

USGS Publications Warehouse

Johnson, Devin S.; Conn, Paul B.; Hooten, Mevin B.; Ray, Justina C.; Pond, Bruce A.

2013-01-01

Since its development, occupancy modeling has become a popular and useful tool for ecologists wishing to learn about the dynamics of species occurrence over time and space. Such models require presence–absence data to be collected at spatially indexed survey units. However, only recently have researchers recognized the need to correct for spatially induced overdisperison by explicitly accounting for spatial autocorrelation in occupancy probability. Previous efforts to incorporate such autocorrelation have largely focused on logit-normal formulations for occupancy, with spatial autocorrelation induced by a random effect within a hierarchical modeling framework. Although useful, computational time generally limits such an approach to relatively small data sets, and there are often problems with algorithm instability, yielding unsatisfactory results. Further, recent research has revealed a hidden form of multicollinearity in such applications, which may lead to parameter bias if not explicitly addressed. Combining several techniques, we present a unifying hierarchical spatial occupancy model specification that is particularly effective over large spatial extents. This approach employs a probit mixture framework for occupancy and can easily accommodate a reduced-dimensional spatial process to resolve issues with multicollinearity and spatial confounding while improving algorithm convergence. Using open-source software, we demonstrate this new model specification using a case study involving occupancy of caribou (Rangifer tarandus) over a set of 1080 survey units spanning a large contiguous region (108 000 km2) in northern Ontario, Canada. Overall, the combination of a more efficient specification and open-source software allows for a facile and stable implementation of spatial occupancy models for large data sets.

Precipitation climatology over India: validation with observations and reanalysis datasets and spatial trends

NASA Astrophysics Data System (ADS)

Kishore, P.; Jyothi, S.; Basha, Ghouse; Rao, S. V. B.; Rajeevan, M.; Velicogna, Isabella; Sutterley, Tyler C.

2016-01-01

Changing rainfall patterns have significant effect on water resources, agriculture output in many countries, especially the country like India where the economy depends on rain-fed agriculture. Rainfall over India has large spatial as well as temporal variability. To understand the variability in rainfall, spatial-temporal analyses of rainfall have been studied by using 107 (1901-2007) years of daily gridded India Meteorological Department (IMD) rainfall datasets. Further, the validation of IMD precipitation data is carried out with different observational and different reanalysis datasets during the period from 1989 to 2007. The Global Precipitation Climatology Project data shows similar features as that of IMD with high degree of comparison, whereas Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation data show similar features but with large differences, especially over northwest, west coast and western Himalayas. Spatially, large deviation is observed in the interior peninsula during the monsoon season with National Aeronautics Space Administration-Modern Era Retrospective-analysis for Research and Applications (NASA-MERRA), pre-monsoon with Japanese 25 years Re Analysis (JRA-25), and post-monsoon with climate forecast system reanalysis (CFSR) reanalysis datasets. Among the reanalysis datasets, European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) shows good comparison followed by CFSR, NASA-MERRA, and JRA-25. Further, for the first time, with high resolution and long-term IMD data, the spatial distribution of trends is estimated using robust regression analysis technique on the annual and seasonal rainfall data with respect to different regions of India. Significant positive and negative trends are noticed in the whole time series of data during the monsoon season. The northeast and west coast of the Indian region shows significant positive trends and negative trends over western Himalayas and north central Indian region.

Temporal and spatial variations of Gutenberg-Richter parameter and fractal dimension in Western Anatolia, Turkey

NASA Astrophysics Data System (ADS)

Bayrak, Erdem; Yılmaz, Şeyda; Bayrak, Yusuf

2017-05-01

The temporal and spatial variations of Gutenberg-Richter parameter (b-value) and fractal dimension (DC) during the period 1900-2010 in Western Anatolia was investigated. The study area is divided into 15 different source zones based on their tectonic and seismotectonic regimes. We calculated the temporal variation of b and DC values in each region using Zmap. The temporal variation of these parameters for the prediction of major earthquakes was calculated. The spatial distribution of these parameters is related to the stress levels of the faults. We observed that b and DC values change before the major earthquakes in the 15 seismic regions. To evaluate the spatial distribution of b and DC values, 0.50° × 0.50° grid interval were used. The b-values smaller than 0.70 are related to the Aegean Arc and Eskisehir Fault. The highest values are related to Sultandağı and Sandıklı Faults. Fractal correlation dimension varies from 1.65 to 2.60, which shows that the study area has a higher DC value. The lowest DC values are related to the joining area between Aegean and Cyprus arcs, Burdur-Fethiye fault zone. Some have concluded that b-values drop instantly before large shocks. Others suggested that temporally stable low b value zones identify future large earthquake locations. The results reveal that large earthquakes occur when b decreases and DC increases, suggesting that variation of b and DC can be used as an earthquake precursor. Mapping of b and DC values provide information about the state of stress in the region, i.e. lower b and higher DC values associated with epicentral areas of large earthquakes.

Optimization of Decision-Making for Spatial Sampling in the North China Plain, Based on Remote-Sensing a Priori Knowledge

NASA Astrophysics Data System (ADS)

Feng, J.; Bai, L.; Liu, S.; Su, X.; Hu, H.

2012-07-01

In this paper, the MODIS remote sensing data, featured with low-cost, high-timely and moderate/low spatial resolutions, in the North China Plain (NCP) as a study region were firstly used to carry out mixed-pixel spectral decomposition to extract an useful regionalized indicator parameter (RIP) (i.e., an available ratio, that is, fraction/percentage, of winter wheat planting area in each pixel as a regionalized indicator variable (RIV) of spatial sampling) from the initial selected indicators. Then, the RIV values were spatially analyzed, and the spatial structure characteristics (i.e., spatial correlation and variation) of the NCP were achieved, which were further processed to obtain the scalefitting, valid a priori knowledge or information of spatial sampling. Subsequently, founded upon an idea of rationally integrating probability-based and model-based sampling techniques and effectively utilizing the obtained a priori knowledge or information, the spatial sampling models and design schemes and their optimization and optimal selection were developed, as is a scientific basis of improving and optimizing the existing spatial sampling schemes of large-scale cropland remote sensing monitoring. Additionally, by the adaptive analysis and decision strategy the optimal local spatial prediction and gridded system of extrapolation results were able to excellently implement an adaptive report pattern of spatial sampling in accordance with report-covering units in order to satisfy the actual needs of sampling surveys.

Regional Population Dynamics

Treesearch

Andrew Birt

2011-01-01

The population dynamics of the southern pine beetle (SPB) exhibit characteristic fluctuations between relatively long endemic and shorter outbreak periods. Populations exhibit complex and hierarchical spatial structure with beetles and larvae aggregating within individual trees, infestations with multiple infested trees, and regional outbreaks that comprise a large...

Spatial Fluctuations of the Intergalactic Temperature-Density Relation After Hydrogen Reionization

NASA Astrophysics Data System (ADS)

Keating, Laura C.; Puchwein, Ewald; Haehnelt, Martin G.

2018-04-01

The thermal state of the post-reionization IGM is sensitive to the timing of reionization and the nature of the ionizing sources. We have modelled here the thermal state of the IGM in cosmological radiative transfer simulations of a realistic, extended, spatially inhomogeneous hydrogen reionization process, carefully calibrated with Lyα forest data. We compare these with cosmological simulations run using a spatially homogeneous ionizing background. The simulations with a realistic growth of ionized regions and a realistic spread in reionization redshifts show, as expected, significant spatial fluctuations in the temperature-density relation (TDR) of the post-reionization IGM. The most recently ionized regions are hottest and exhibit a flatter TDR. In simulations consistent with the average TDR inferred from Lyα forest data, these spatial fluctuations have a moderate but noticeable effect on the statistical properties of the Lyα opacity of the IGM at z ˜ 4 - 6. This should be taken into account in accurate measurements of the thermal properties of the IGM and the free-streaming of dark matter from Lyα forest data in this redshift range. The spatial variations of the TDR predicted by our simulations are, however, smaller by about a factor two than would be necessary to explain the observed large spatial opacity fluctuations on large (≥ 50 h-1 comoving Mpc) scales at z ≳ 5.5.

Spatial fluctuations of the intergalactic temperature-density relation after hydrogen reionization

NASA Astrophysics Data System (ADS)

Keating, Laura C.; Puchwein, Ewald; Haehnelt, Martin G.

2018-07-01

The thermal state of the post-reionization IGM is sensitive to the timing of reionization and the nature of the ionizing sources. We have modelled here the thermal state of the IGM in cosmological radiative transfer simulations of a realistic, extended, spatially inhomogeneous hydrogen reionization process, carefully calibrated with Ly α forest data. We compare these with cosmological simulations run using a spatially homogeneous ionizing background. The simulations with a realistic growth of ionized regions and a realistic spread in reionization redshifts show, as expected, significant spatial fluctuations in the temperature-density relation (TDR) of the post-reionization IGM. The most recently ionized regions are hottest and exhibit a flatter TDR. In simulations consistent with the average TDR inferred from Ly α forest data, these spatial fluctuations have a moderate but noticeable effect on the statistical properties of the Ly α opacity of the IGM at z ˜ 4-6. This should be taken into account in accurate measurements of the thermal properties of the IGM and the free-streaming of dark matter from Ly α forest data in this redshift range. The spatial variations of the TDR predicted by our simulations are, however, smaller by about a factor of 2 than would be necessary to explain the observed large spatial opacity fluctuations on large (≥50 h-1 comoving Mpc) scales atz ≳ 5.5.

Forest Ecosystem Analysis Using a GIS

Treesearch

S.G. McNulty; W.T. Swank

1996-01-01

Forest ecosystem studies have expanded spatially in recent years to address large scale environmental issues. We are using a geographic information system (GIS) to understand and integrate forest processes at landscape to regional spatial scales. This paper presents three diverse research studies using a GIS. First, we used a GIS to develop a landscape scale model to...

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...

A Category Adjustment Approach to Memory for Spatial Location in Natural Scenes

ERIC Educational Resources Information Center

Holden, Mark P.; Curby, Kim M.; Newcombe, Nora S.; Shipley, Thomas F.

2010-01-01

Memories for spatial locations often show systematic errors toward the central value of the surrounding region. This bias has been explained using a Bayesian model in which fine-grained and categorical information are combined (Huttenlocher, Hedges, & Duncan, 1991). However, experiments testing this model have largely used locations contained in…

Expanded spatial extent of the Medieval Climate Anomaly revealed in lake-sediment records across the boreal region in northwest Ontario.

PubMed

Laird, Kathleen R; Haig, Heather A; Ma, Susan; Kingsbury, Melanie V; Brown, Thomas A; Lewis, C F Michael; Oglesby, Robert J; Cumming, Brian F

2012-09-01

Multi-decadal to centennial-scale shifts in effective moisture over the past two millennia are inferred from sedimentary records from six lakes spanning a ~250 km region in northwest Ontario. This is the first regional application of a technique developed to reconstruct drought from drainage lakes (open lakes with surface outlets). This regional network of proxy drought records is based on individual within-lake calibration models developed using diatom assemblages collected from surface sediments across a water-depth gradient. Analysis of diatom assemblages from sediment cores collected close to the near-shore ecological boundary between benthic and planktonic diatom taxa indicated this boundary shifted over time in all lakes. These shifts are largely dependent on climate-driven influences, and can provide a sensitive record of past drought. Our lake-sediment records indicate two periods of synchronous signals, suggesting a common large-scale climate forcing. The first is a period of prolonged aridity during the Medieval Climate Anomaly (MCA, c. 900-1400 CE). Documentation of aridity across this region expands the known spatial extent of the MCA megadrought into a region that historically has not experienced extreme droughts such as those in central and western north America. The second synchronous period is the recent signal of the past ~100 years, which indicates a change to higher effective moisture that may be related to anthropogenic forcing on climate. This approach has the potential to fill regional gaps, where many previous paleo-lake depth methods (based on deeper centrally located cores) were relatively insensitive. By filling regional gaps, a better understanding of past spatial patterns in drought can be used to assess the sensitivity and realism of climate model projections of future climate change. This type of data is especially important for validating high spatial resolution, regional climate models. © 2012 Blackwell Publishing Ltd.

Regional hydro-climatic impacts of contemporary Amazonian deforestation

NASA Astrophysics Data System (ADS)

Khanna, Jaya

More than 17% of the Amazon rainforest has been cleared in the past three decades triggering important climatological and societal impacts. This thesis is devoted to identifying and explaining the regional hydroclimatic impacts of this change employing multidecadal satellite observations and numerical simulations providing an integrated perspective on this topic. The climatological nature of this study motivated the implementation and application of a cloud detection technique to a new geostationary satellite dataset. The resulting sub daily, high spatial resolution, multidecadal time series facilitated the detection of trends and variability in deforestation triggered cloud cover changes. The analysis was complemented by satellite precipitation, reanalysis and ground based datasets and attribution with the variable resolution Ocean-Land-Atmosphere-Model. Contemporary Amazonian deforestation affects spatial scales of hundreds of kilometers. But, unlike the well-studied impacts of a few kilometers scale deforestation, the climatic response to contemporary, large scale deforestation is neither well observed nor well understood. Employing satellite datasets, this thesis shows a transition in the regional hydroclimate accompanying increasing scales of deforestation, with downwind deforested regions receiving 25% more and upwind deforested regions receiving 25% less precipitation from the deforested area mean. Simulations robustly reproduce these shifts when forced with increasing deforestation alone, suggesting a negligible role of large-scale decadal climate variability in causing the shifts. Furthermore, deforestation-induced surface roughness variations are found necessary to reproduce the observed spatial patterns in recent times illustrating the strong scale-sensitivity of the climatic response to Amazonian deforestation. This phenomenon, inconsequential during the wet season, is found to substantially affect the regional hydroclimate in the local dry and parts of transition seasons, hence occurring in atmospheric conditions otherwise less conducive to thermal convection. Evidence of this phenomenon is found at two large scale deforested areas considered in this thesis. Hence, the 'dynamical' mechanism, which affects the seasons most important for regional ecology, emerges as an impactful convective triggering mechanism. The phenomenon studied in this thesis provides context for thinking about the climate of a future, more patchily forested Amazonia, by articulating relationships between climate and spatial scales of deforestation.

Spatial patterns of ecosystem carbon residence time and NPP-driven carbon uptake in the conterminous United States

NASA Astrophysics Data System (ADS)

Zhou, Tao; Luo, Yiqi

2008-09-01

Ecosystem carbon (C) uptake is determined largely by C residence times and increases in net primary production (NPP). Therefore, evaluation of C uptake at a regional scale requires knowledge on spatial patterns of both residence times and NPP increases. In this study, we first applied an inverse modeling method to estimate spatial patterns of C residence times in the conterminous United States. Then we combined the spatial patterns of estimated residence times with a NPP change trend to assess the spatial patterns of regional C uptake in the United States. The inverse analysis was done by using the genetic algorithm and was based on 12 observed data sets of C pools and fluxes. Residence times were estimated by minimizing the total deviation between modeled and observed values. Our results showed that the estimated C residence times were highly heterogeneous over the conterminous United States, with most of the regions having values between 15 and 65 years; and the averaged C residence time was 46 years. The estimated C uptake for the whole conterminous United States was 0.15 P g C a-1. Large portions of the taken C were stored in soil for grassland and cropland (47-70%) but in plant pools for forests and woodlands (73-82%). The proportion of C uptake in soil was found to be determined primarily by C residence times and be independent of the magnitude of NPP increase. Therefore, accurate estimation of spatial patterns of C residence times is crucial for the evaluation of terrestrial ecosystem C uptake.

Exploring links between juvenile offenders and social disorganization at a large map scale: a Bayesian spatial modeling approach

NASA Astrophysics Data System (ADS)

Law, Jane; Quick, Matthew

2013-01-01

This paper adopts a Bayesian spatial modeling approach to investigate the distribution of young offender residences in York Region, Southern Ontario, Canada, at the census dissemination area level. Few geographic researches have analyzed offender (as opposed to offense) data at a large map scale (i.e., using a relatively small areal unit of analysis) to minimize aggregation effects. Providing context is the social disorganization theory, which hypothesizes that areas with economic deprivation, high population turnover, and high ethnic heterogeneity exhibit social disorganization and are expected to facilitate higher instances of young offenders. Non-spatial and spatial Poisson models indicate that spatial methods are superior to non-spatial models with respect to model fit and that index of ethnic heterogeneity, residential mobility (1 year moving rate), and percentage of residents receiving government transfer payments are, respectively, the most significant explanatory variables related to young offender location. These findings provide overwhelming support for social disorganization theory as it applies to offender location in York Region, Ontario. Targeting areas where prevalence of young offenders could or could not be explained by social disorganization through decomposing the estimated risk map are helpful for dealing with juvenile offenders in the region. Results prompt discussion into geographically targeted police services and young offender placement pertaining to risk of recidivism. We discuss possible reasons for differences and similarities between the previous findings (that analyzed offense data and/or were conducted at a smaller map scale) and our findings, limitations of our study, and practical outcomes of this research from a law enforcement perspective.

The statistical power to detect cross-scale interactions at macroscales

USGS Publications Warehouse

Wagner, Tyler; Fergus, C. Emi; Stow, Craig A.; Cheruvelil, Kendra S.; Soranno, Patricia A.

2016-01-01

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

How global extinctions impact regional biodiversity in mammals.

PubMed

Huang, Shan; Davies, T Jonathan; Gittleman, John L

2012-04-23

Phylogenetic diversity (PD) represents the evolutionary history of a species assemblage and is a valuable measure of biodiversity because it captures not only species richness but potentially also genetic and functional diversity. Preserving PD could be critical for maintaining the functional integrity of the world's ecosystems, and species extinction will have a large impact on ecosystems in areas where the ecosystem cost per species extinction is high. Here, we show that impacts from global extinctions are linked to spatial location. Using a phylogeny of all mammals, we compare regional losses of PD against a model of random extinction. At regional scales, losses differ dramatically: several biodiversity hotspots in southern Asia and Amazonia will lose an unexpectedly large proportion of PD. Global analyses may therefore underestimate the impacts of extinction on ecosystem processes and function because they occur at finer spatial scales within the context of natural biogeography.

Evacuation simulation using Hybrid Space Discretisation and Application to Large Underground Rail Tunnel Station

NASA Astrophysics Data System (ADS)

Chooramun, N.; Lawrence, P. J.; Galea, E. R.

2017-08-01

In all evacuation simulation tools, the space through which agents navigate and interact is represented by one the following methods, namely Coarse regions, Fine nodes and Continuous regions. Each of the spatial representation methods has its benefits and limitations. For instance, the Coarse approach allows simulations to be processed very rapidly, but is unable to represent the interactions of the agents from an individual perspective; the Continuous approach provides a detailed representation of agent movement and interaction but suffers from relatively poor computational performance. The Fine nodal approach presents a compromise between the Continuous and Coarse approaches such that it allows agent interaction to be modelled while providing good computational performance. Our approach for representing space in an evacuation simulation tool differs such that it allows evacuation simulations to be run using a combination of Coarse regions, Fine nodes and Continuous regions. This approach, which we call Hybrid Spatial Discretisation (HSD), is implemented within the buildingEXODUS evacuation simulation software. The HSD incorporates the benefits of each of the spatial representation methods whilst providing an optimal environment for representing agent movement and interaction. In this work, we demonstrate the effectiveness of the HSD through its application to a moderately large case comprising of an underground rail tunnel station with a population of 2,000 agents.

Spatial Structure of Large-Scale Plasma Density Perturbations HF-Induced in the Ionospheric F 2 Region

NASA Astrophysics Data System (ADS)

Frolov, V. L.; Komrakov, G. P.; Glukhov, Ya. V.; Andreeva, E. S.; Kunitsyn, V. E.; Kurbatov, G. A.

2016-07-01

We consider the experimental results obtained by studying the large-scale structure of the HF-disturbed ionospheric region. The experiments were performed using the SURA heating facility. The disturbed ionospheric region was sounded by signals radiated by GPS navigation satellite beacons as well as by signals of low-orbit satellites (radio tomography). The results of the experiments show that large-scale plasma density perturbations induced at altitudes higher than the F2 layer maximum can contribute significantly to the measured variations of the total electron density and can, with a certain arrangement of the reception points, be measured by the GPS sounding method.

Biased figure-ground assignment affects conscious object recognition in spatial neglect.

PubMed

Eramudugolla, Ranmalee; Driver, Jon; Mattingley, Jason B

2010-09-01

Unilateral spatial neglect is a disorder of attention and spatial representation, in which early visual processes such as figure-ground segmentation have been assumed to be largely intact. There is evidence, however, that the spatial attention bias underlying neglect can bias the segmentation of a figural region from its background. Relatively few studies have explicitly examined the effect of spatial neglect on processing the figures that result from such scene segmentation. Here, we show that a neglect patient's bias in figure-ground segmentation directly influences his conscious recognition of these figures. By varying the relative salience of figural and background regions in static, two-dimensional displays, we show that competition between elements in such displays can modulate a neglect patient's ability to recognise parsed figures in a scene. The findings provide insight into the interaction between scene segmentation, explicit object recognition, and attention.

CLIMATE CONSTRAINTS AND ISSUES OF SCALE CONTROLLING REGIONAL BIOMES

EPA Science Inventory

The prosepct of climate change threatens to cause large changes in regional biomes. hese effects could be in the form of qualitative changes within biomes, as well as spatial changes in the boundaries of biomes. he boundaries, or ecotones, between biomes have been suggested as po...

Biocapacity optimization in regional planning

PubMed Central

Guo, Jianjun; Yue, Dongxia; Li, Kai; Hui, Cang

2017-01-01

Ecological overshoot has been accelerating across the globe. Optimizing biocapacity has become a key to resolve the overshoot of ecological demand in regional sustainable development. However, most literature has focused on reducing ecological footprint but ignores the potential of spatial optimization of biocapacity through regional planning of land use. Here we develop a spatial probability model and present four scenarios for optimizing biocapacity of a river basin in Northwest China. The potential of enhanced biocapacity and its effects on ecological overshoot and water consumption in the region were explored. Two scenarios with no restrictions on croplands and water use reduced the overshoot by 29 to 53%, and another two scenarios which do not allow croplands and water use to increase worsened the overshoot by 11 to 15%. More spatially flexible transition rules of land use led to higher magnitude of change after optimization. However, biocapacity optimization required a large amount of additional water resources, casting considerable pressure on the already water-scarce socio-ecological system. Our results highlight the potential for policy makers to manage/optimize regional land use which addresses ecological overshoot. Investigation on the feasibility of such spatial optimization complies with the forward-looking policies for sustainable development and deserves further attention. PMID:28112224

Unleashing spatially distributed ecohydrology modeling using Big Data tools

NASA Astrophysics Data System (ADS)

Miles, B.; Idaszak, R.

2015-12-01

Physically based spatially distributed ecohydrology models are useful for answering science and management questions related to the hydrology and biogeochemistry of prairie, savanna, forested, as well as urbanized ecosystems. However, these models can produce hundreds of gigabytes of spatial output for a single model run over decadal time scales when run at regional spatial scales and moderate spatial resolutions (~100-km2+ at 30-m spatial resolution) or when run for small watersheds at high spatial resolutions (~1-km2 at 3-m spatial resolution). Numerical data formats such as HDF5 can store arbitrarily large datasets. However even in HPC environments, there are practical limits on the size of single files that can be stored and reliably backed up. Even when such large datasets can be stored, querying and analyzing these data can suffer from poor performance due to memory limitations and I/O bottlenecks, for example on single workstations where memory and bandwidth are limited, or in HPC environments where data are stored separately from computational nodes. The difficulty of storing and analyzing spatial data from ecohydrology models limits our ability to harness these powerful tools. Big Data tools such as distributed databases have the potential to surmount the data storage and analysis challenges inherent to large spatial datasets. Distributed databases solve these problems by storing data close to computational nodes while enabling horizontal scalability and fault tolerance. Here we present the architecture of and preliminary results from PatchDB, a distributed datastore for managing spatial output from the Regional Hydro-Ecological Simulation System (RHESSys). The initial version of PatchDB uses message queueing to asynchronously write RHESSys model output to an Apache Cassandra cluster. Once stored in the cluster, these data can be efficiently queried to quickly produce both spatial visualizations for a particular variable (e.g. maps and animations), as well as point time series of arbitrary variables at arbitrary points in space within a watershed or river basin. By treating ecohydrology modeling as a Big Data problem, we hope to provide a platform for answering transformative science and management questions related to water quantity and quality in a world of non-stationary climate.

Spatial patterns of drought persistence in East China

NASA Astrophysics Data System (ADS)

Meng, L.; Ford, T.

2017-12-01

East China has experienced a number of severe droughts in recent decades. Understanding the characteristics of droughts and their persistence will provide operational guidelines for water resource management and agricultural production. This study uses a logistic regression model to measure the probability of drought occurrence in the current season given the previous season's Standardized Precipitation Index (SPI) and Southern Oscillation Index (SOI) as well as drought persistence. Results reveal large spatial and seasonal variations in the relationship between the previous season's SPI and the drought occurrence probability in a given season. The drought persistence averaged over the entire study area for all the four seasons is approximately 34% with large variations from season to season and from region to region. The East and Northeast regions have the largest summer drought persistence ( 40%) and lowest fall drought persistence ( 28%). The spatial pattern in winter and spring drought persistence is dissimilar with stronger winter and weaker spring drought persistence in the Southwest and Northeast relative to other regions. Logistic regression analysis indicates a stronger negative relationship in summer-to-fall (or between fall drought occurrence and summer SPI) than other inter-season relationships. This study demonstrates that the impact of previous season SPI and SOI on current season drought varies substantially from region to region and from season to season. This study also shows stronger drought persistence in summer than in other seasons. In other words, the probability of fall drought occurrence is closely related to summer moisture conditions in the East China.

Ownership and ecosystem as sources of spatial heterogeneity in a forested landscape, Wisconsin, USA

Treesearch

Thomas R. Crow; George E. Host; David J. Mladenoff

1999-01-01

The interaction between physical environment and land ownership in creating spatial heterogeneity was studied in largely forested landscapes of northern Wisconsin, USA. A stratified random approach was used in which 2500-ha plots representing two ownerships (National Forest and private non-industrial) were located within two regional ecosystems (extremely well-drained...

Spatial synchrony propagates through a forest food web via consumer-resource interactions

Treesearch

Kyle J. ​Haynes; Andrew M. Liebhold; Todd M. Fearer; Guiming Wang; Gary W. Norman; Derek M. Johnson

2009-01-01

In many study systems, populations fluctuate synchronously across large regions. Several mechanisms have been advanced to explain this, but their importance in nature is often uncertain. Theoretical studies suggest that spatial synchrony initiated in one species through Moran effects may propagate among trophically linked species, but evidence for this in nature is...

Numerical Study of the Response of an Atmospheric Surface Layer to a Spatially Nonuniform Plant Canopy

NASA Astrophysics Data System (ADS)

Qiu, J.; Gu, Z. L.; Wang, Z. S.

2008-05-01

High-accuracy large-eddy simulations of neutral atmospheric surface-layer flow over a gapped plant canopy strip have been performed. Subgrid-scale (SGS) motions are parameterized by the Sagaut mixed length SGS model, with a modification to compute the SGS characteristic length self-adaptively. Shaw’s plant canopy model, taking the vertical variation of leaf area density into account, is applied to study the response of the atmospheric surface layer to the gapped dense forest strip. Differences in the region far away from the gap and in the middle of the gap are investigated, according to the instantaneous velocity magnitude, the zero-plane displacement, the potential temperature and the streamlines. The large-scale vortex structure, in the form of a roll vortex, is revealed in the region far away from the gap. The nonuniform spatial distribution of plants appears to cause the formation of the coherent structure. The roll vortex starts in the wake of the canopy, and results in strong fluctuations throughout the entire canopy region. Wind sweeps and ejections in the plant canopy are also attributed to the large vortex structure.

Three dimensional simulation of spatial and temporal variability of stratospheric hydrogen chloride

NASA Technical Reports Server (NTRS)

Kaye, Jack A.; Rood, Richard B.; Jackman, Charles H.; Allen, Dale J.; Larson, Edmund M.

1989-01-01

Spatial and temporal variability of atmospheric HCl columns are calculated for January 1979 using a three-dimensional chemistry-transport model designed to provide the best possible representation of stratospheric transport. Large spatial and temporal variability of the HCl columns is shown to be correlated with lower stratospheric potential vorticity and thus to be of dynamical origin. Systematic longitudinal structure is correlated with planetary wave structure. These results can help place spatially and temporally isolated column and profile measurements in a regional and/or global perspective.

Neurophysiological Organization of the Middle Face Patch in Macaque Inferior Temporal Cortex

PubMed Central

Aparicio, Paul L.; Issa, Elias B.

2016-01-01

While early cortical visual areas contain fine scale spatial organization of neuronal properties, such as orientation preference, the spatial organization of higher-level visual areas is less well understood. The fMRI demonstration of face-preferring regions in human ventral cortex and monkey inferior temporal cortex (“face patches”) raises the question of how neural selectivity for faces is organized. Here, we targeted hundreds of spatially registered neural recordings to the largest fMRI-identified face-preferring region in monkeys, the middle face patch (MFP), and show that the MFP contains a graded enrichment of face-preferring neurons. At its center, as much as 93% of the sites we sampled responded twice as strongly to faces than to nonface objects. We estimate the maximum neurophysiological size of the MFP to be ∼6 mm in diameter, consistent with its previously reported size under fMRI. Importantly, face selectivity in the MFP varied strongly even between neighboring sites. Additionally, extremely face-selective sites were ∼40 times more likely to be present inside the MFP than outside. These results provide the first direct quantification of the size and neural composition of the MFP by showing that the cortical tissue localized to the fMRI defined region consists of a very high fraction of face-preferring sites near its center, and a monotonic decrease in that fraction along any radial spatial axis. SIGNIFICANCE STATEMENT The underlying organization of neurons that give rise to the large spatial regions of activity observed with fMRI is not well understood. Neurophysiological studies that have targeted the fMRI identified face patches in monkeys have provided evidence for both large-scale clustering and a heterogeneous spatial organization. Here we used a novel x-ray imaging system to spatially map the responses of hundreds of sites in and around the middle face patch. We observed that face-selective signal localized to the middle face patch was characterized by a gradual spatial enrichment. Furthermore, strongly face-selective sites were ∼40 times more likely to be found inside the patch than outside of the patch. PMID:27810930

Neurophysiological Organization of the Middle Face Patch in Macaque Inferior Temporal Cortex.

PubMed

Aparicio, Paul L; Issa, Elias B; DiCarlo, James J

2016-12-14

While early cortical visual areas contain fine scale spatial organization of neuronal properties, such as orientation preference, the spatial organization of higher-level visual areas is less well understood. The fMRI demonstration of face-preferring regions in human ventral cortex and monkey inferior temporal cortex ("face patches") raises the question of how neural selectivity for faces is organized. Here, we targeted hundreds of spatially registered neural recordings to the largest fMRI-identified face-preferring region in monkeys, the middle face patch (MFP), and show that the MFP contains a graded enrichment of face-preferring neurons. At its center, as much as 93% of the sites we sampled responded twice as strongly to faces than to nonface objects. We estimate the maximum neurophysiological size of the MFP to be ∼6 mm in diameter, consistent with its previously reported size under fMRI. Importantly, face selectivity in the MFP varied strongly even between neighboring sites. Additionally, extremely face-selective sites were ∼40 times more likely to be present inside the MFP than outside. These results provide the first direct quantification of the size and neural composition of the MFP by showing that the cortical tissue localized to the fMRI defined region consists of a very high fraction of face-preferring sites near its center, and a monotonic decrease in that fraction along any radial spatial axis. The underlying organization of neurons that give rise to the large spatial regions of activity observed with fMRI is not well understood. Neurophysiological studies that have targeted the fMRI identified face patches in monkeys have provided evidence for both large-scale clustering and a heterogeneous spatial organization. Here we used a novel x-ray imaging system to spatially map the responses of hundreds of sites in and around the middle face patch. We observed that face-selective signal localized to the middle face patch was characterized by a gradual spatial enrichment. Furthermore, strongly face-selective sites were ∼40 times more likely to be found inside the patch than outside of the patch. Copyright © 2016 the authors 0270-6474/16/3612729-17$15.00/0.

Numerical analysis of the spatial nonuniformity in a Cs-seeded H{sup -} ion source

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

Takado, N.; Hanatani, J.; Mizuno, T.

The H{sup -} ion production and transport processes are numerically simulated to clarify the origin of H{sup -} beam nonuniformity. The three-dimensional transport code using the Monte Carlo method has been applied to H{sup 0} atoms and H{sup -} ions in the large 'JAERI 10A negative ion source' under the Cs-seeded condition, in which negative ions are dominantly produced by the surface production process. The results show that a large fraction of hydrogen atoms is produced in the region with high electron temperature. This leads to a spatial nonuniformity of H{sup 0} atom flux to the plasma grid and themore » resultant H{sup -} ion surface production. In addition, most surface-produced H{sup -} ions are extracted even through the high T{sub e} region without destruction. These results indicate a correlation between the production process of the H{sup -} ion and the spatial nonuniformity of the H{sup -} ion beam.« less

Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA

NASA Astrophysics Data System (ADS)

Deo, Ram K.; Domke, Grant M.; Russell, Matthew B.; Woodall, Christopher W.; Andersen, Hans-Erik

2018-05-01

Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, the accuracy of AGB predictions based on passive optical data depends on spatial resolution and spatial extent of target area as fine resolution (small pixels) data are associated with smaller coverage and longer repeat cycles compared to coarse resolution data. This study evaluated various spatial resolutions of Landsat-derived predictors on the accuracy of regional AGB models at three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We combined national forest inventory data with Landsat-derived predictors at spatial resolutions ranging from 30–1000 m to understand the optimal spatial resolution of optical data for large-area (regional) AGB estimation. Ten generic models were developed using the data collected in 2014, 2015 and 2016, and the predictions were evaluated (i) at the county-level against the estimates of the USFS Forest Inventory and Analysis Program which relied on EVALIDator tool and national forest inventory data from the 2009–2013 cycle and (ii) within a large number of strips (~1 km wide) predicted via LiDAR metrics at 30 m spatial resolution. The county-level estimates by the EVALIDator and Landsat models were highly related (R 2 > 0.66), although the R 2 varied significantly across sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of coarser resolution. The Landsat-based total AGB estimates were larger than the LiDAR-based total estimates within the strips, however the mean of AGB predictions by LiDAR were mostly within one-standard deviations of the mean predictions obtained from the Landsat-based model at any of the resolutions. We conclude that satellite data at resolutions up to 1000 m provide acceptable accuracy for continental scale analysis of AGB.

Pacific Northwest Regional and Ecozone-scale Carbon Cycle Responses to 25 Years of Variation in Climate and Disturbance

NASA Astrophysics Data System (ADS)

Turner, D. P.; Ritts, W. D.; Kennedy, R. E.; Gray, A. N.; Yang, Z.

2015-12-01

Spatial variation in climate, soils, disturbance regime, and forest management - as well as temporal variation in weather - all influence terrestrial carbon sources and sinks. Spatially-distributed, process-based, carbon cycle simulation models provide a means to integrate information from these various influences to estimate carbon pools and flux over large domains. Here we apply the Biome-BGC model over the 4 state (OR, WA, ID, Western MT) Northwest U.S. region for the interval from 1986-2010. Landsat data was used to characterize disturbances and revealed that the overall disturbance rate on forest land across the region was 0.8 % yr-1, with 49 % as harvests, 28 % as fire, and 23 % as pest/pathogen. A large proportion of the harvested area was on private forestland (62 %) and a large proportion of total burned area was on public forestland (89 %). Net ecosystem production (NEP) for the 2006-2010 interval on forestland was predominantly positive (a carbon sink) throughout the region, with maximum values in the Coast Range, intermediate values in the Cascade Mountains, and relatively low values in the Inland Rocky Mountain ecoregions. Croplands throughout the region had consistently high NEP. Localized negative NEPs were mostly associated with recent disturbances. There was large interannual variation in regional NEP, with notably low values across the region in 2003. In all ecoregions there was a downward trend in NEP over the 25 year study period. The net ecosystem carbon balance was positive in OR, near neutral in ID and WA, and negative (a carbon source) MT. The Northwest region as a whole was a carbon sink in the 2006-2010 period.

Autonomous rock detection on mars through region contrast

NASA Astrophysics Data System (ADS)

Xiao, Xueming; Cui, Hutao; Yao, Meibao; Tian, Yang

2017-08-01

In this paper, we present a new autonomous rock detection approach through region contrast. Unlike current state-of-art pixel-level rock segmenting methods, new method deals with this issue in region level, which will significantly reduce the computational cost. Image is firstly splitted into homogeneous regions based on intensity information and spatial layout. Considering the high-water memory constraints of onboard flight processor, only low-level features, average intensity and variation of superpixel, are measured. Region contrast is derived as the integration of intensity contrast and smoothness measurement. Rocks are then segmented from the resulting contrast map by an adaptive threshold. Since the merely intensity-based method may cause false detection in background areas with different illuminations from surroundings, a more reliable method is further proposed by introducing spatial factor and background similarity to the region contrast. Spatial factor demonstrates the locality of contrast, while background similarity calculates the probability of each subregion belonging to background. Our method is efficient in dealing with large images and only few parameters are needed. Preliminary experimental results show that our algorithm outperforms edge-based methods in various grayscale rover images.

Future of applied watershed science at regional scales

Treesearch

Lee Benda; Daniel Miller; Steve Lanigan; Gordon Reeves

2009-01-01

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

THE CONSEQUENCES OF LANDSCAPE CHANGE ON ECOLOGICAL RESOURCES: AN ASSESSMENT OF THE UNITED STATES MID-ATLANTIC REGION

EPA Science Inventory

Spatially explicit identification of changes in ecological conditions over large areas is key to targeting and prioritizing areas for environmental protection and restoration by managers at watershed, basin, and regional scales. A critical limitation to this point has bee...

UTILIZING SATELLITE OBSERVATIONS TO EXPAND EPA'S AIR MONITORING NETWORK: A NEW PARTNERSHIP BETWEEN NASA AND EPA

EPA Science Inventory

Over the next decade, data requirements to inform air quality management decisions and policies will need to be expanded to large spatial domains to accommodate decisions which more frequently cross geo-political boundaries; from urban (local) and regional scales to regional, sup...

Range contractions of the world's large carnivores

PubMed Central

2017-01-01

The majority of the world's terrestrial large carnivores have undergone substantial range contractions and many of these species are currently threatened with extinction. However, there has been little effort to fully quantify the extent of large carnivore range contractions, which hinders our ability to understand the roles and relative drivers of such trends. Here we present and analyse a newly constructed and comprehensive set of large carnivore range contraction maps. We reveal the extent to which ranges have contracted since historical times and identify regions and biomes where range contractions have been particularly large. In summary, large carnivores that have experienced the greatest range contractions include the red wolf (Canis rufus) (greater than 99%), Ethiopian wolf (Canis simensis) (99%), tiger (Panthera tigris) (95%) and lion (Panthera leo) (94%). In general, the greatest range contractions occurred in Southeastern Asia and Africa. Motivated by the ecological importance of intact large carnivore guilds, we also examined the spatial extent of intact large carnivore guilds both for the entire world and regionally. We found that intact carnivore guilds occupy just 34% of the world's land area. This compares to 96% in historic times. Spatial modelling of range contractions showed that contractions were significantly more likely in regions with high rural human population density, cattle density or cropland. Our results offer new insights into how best to prevent further range contractions for the world's largest carnivores, which will assist efforts to conserve these species and their important ecological effects. PMID:28791136

Range contractions of the world's large carnivores.

PubMed

Wolf, Christopher; Ripple, William J

2017-07-01

The majority of the world's terrestrial large carnivores have undergone substantial range contractions and many of these species are currently threatened with extinction. However, there has been little effort to fully quantify the extent of large carnivore range contractions, which hinders our ability to understand the roles and relative drivers of such trends. Here we present and analyse a newly constructed and comprehensive set of large carnivore range contraction maps. We reveal the extent to which ranges have contracted since historical times and identify regions and biomes where range contractions have been particularly large. In summary, large carnivores that have experienced the greatest range contractions include the red wolf ( Canis rufus ) (greater than 99%), Ethiopian wolf ( Canis simensis ) (99%), tiger ( Panthera tigris ) (95%) and lion ( Panthera leo ) (94%). In general, the greatest range contractions occurred in Southeastern Asia and Africa. Motivated by the ecological importance of intact large carnivore guilds, we also examined the spatial extent of intact large carnivore guilds both for the entire world and regionally. We found that intact carnivore guilds occupy just 34% of the world's land area. This compares to 96% in historic times. Spatial modelling of range contractions showed that contractions were significantly more likely in regions with high rural human population density, cattle density or cropland. Our results offer new insights into how best to prevent further range contractions for the world's largest carnivores, which will assist efforts to conserve these species and their important ecological effects.

Resolution Analysis of finite fault inversions: A back-projection approach.

NASA Astrophysics Data System (ADS)

Ji, C.; Shao, G.

2007-12-01

The resolution of inverted source models of large earthquakes is controlled by frequency contents of "coherent" (or "useful") seismic observations and their spatial distribution. But it is difficult to distinguish whether some features consistent during different inversions are really required by data or a consequence of "prior" information, such as velocity structures, fault geometry, model parameterizations. Here, we investigate the model spatial resolution by first back projecting and stacking the data at the source regions and then analyzing the spatial- temporal variations of the focusing regions, which arbitrarily defined as the regions with 90% of the peak focusing amplitude. Our preliminary results indicated 1) The spatial-temporal resolution at a particularly direction is controlled by the region of directivity parameter [pcos(θ)] within the seismic network, where p is the horizontal slowness from the hypocenter and θ is the difference between the station azimuth and this orientation. Therefore, the network aperture is more important than the number of stations. 2) Simple stacking method is a robust method to capture the asperities but the sizes of focusing regions are usually much larger than what data could resolve. By carefully weighting the data before the stacking could enhance the spatial resolution in a particular direction. 3) The results based on the teleseismic P waves of a local network usually surfers the trade-off between the source's spatial location and its rupture time. The resolution of the 2001 Kunlunshan earthquake and 2006 Kuril island earthquake will be investigated.

Using Remote Sensing to Determine the Spatial Scales of Estuaries

NASA Astrophysics Data System (ADS)

Davis, C. O.; Tufillaro, N.; Nahorniak, J.

2016-02-01

One challenge facing Earth system science is to understand and quantify the complexity of rivers, estuaries, and coastal zone regions. Earlier studies using data from airborne hyperspectral imagers (Bissett et al., 2004, Davis et al., 2007) demonstrated from a very limited data set that the spatial scales of the coastal ocean could be resolved with spatial sampling of 100 m Ground Sample Distance (GSD) or better. To develop a much larger data set (Aurin et al., 2013) used MODIS 250 m data for a wide range of coastal regions. Their conclusion was that farther offshore 500 m GSD was adequate to resolve large river plume features while nearshore regions (a few kilometers from the coast) needed higher spatial resolution data not available from MODIS. Building on our airborne experience, the Hyperspectral Imager for the Coastal Ocean (HICO, Lucke et al., 2011) was designed to provide hyperspectral data for the coastal ocean at 100 m GSD. HICO operated on the International Space Station for 5 years and collected over 10,000 scenes of the coastal ocean and other regions around the world. Here we analyze HICO data from an example set of major river delta regions to assess the spatial scales of variability in those systems. In one system, the San Francisco Bay and Delta, we also analyze Landsat 8 OLI data at 30 m and 15 m to validate the 100 m GSD sampling scale for the Bay and assess spatial sampling needed as you move up river.

Large-scale coherent structures of suspended dust concentration in the neutral atmospheric surface layer: A large-eddy simulation study

NASA Astrophysics Data System (ADS)

Zhang, Yangyue; Hu, Ruifeng; Zheng, Xiaojing

2018-04-01

Dust particles can remain suspended in the atmospheric boundary layer, motions of which are primarily determined by turbulent diffusion and gravitational settling. Little is known about the spatial organizations of suspended dust concentration and how turbulent coherent motions contribute to the vertical transport of dust particles. Numerous studies in recent years have revealed that large- and very-large-scale motions in the logarithmic region of laboratory-scale turbulent boundary layers also exist in the high Reynolds number atmospheric boundary layer, but their influence on dust transport is still unclear. In this study, numerical simulations of dust transport in a neutral atmospheric boundary layer based on an Eulerian modeling approach and large-eddy simulation technique are performed to investigate the coherent structures of dust concentration. The instantaneous fields confirm the existence of very long meandering streaks of dust concentration, with alternating high- and low-concentration regions. A strong negative correlation between the streamwise velocity and concentration and a mild positive correlation between the vertical velocity and concentration are observed. The spatial length scales and inclination angles of concentration structures are determined, compared with their flow counterparts. The conditionally averaged fields vividly depict that high- and low-concentration events are accompanied by a pair of counter-rotating quasi-streamwise vortices, with a downwash inside the low-concentration region and an upwash inside the high-concentration region. Through the quadrant analysis, it is indicated that the vertical dust transport is closely related to the large-scale roll modes, and ejections in high-concentration regions are the major mechanisms for the upward motions of dust particles.

Mapping UV properties throughout the Cosmic Horseshoe: lessons from VLT-MUSE

NASA Astrophysics Data System (ADS)

James, Bethan L.; Auger, Matt; Pettini, Max; Stark, Daniel P.; Belokurov, V.; Carniani, Stefano

2018-05-01

We present the first spatially resolved rest-frame ultraviolet (UV) study of the gravitationally lensed galaxy, the `Cosmic Horseshoe' (J1148+1930) at z = 2.38. Our gravitational lens model shows that the system is made up of four star-forming regions, each ˜4-8 kpc2 in size, from which we extract four spatially exclusive regional spectra. We study the interstellar and wind absorption lines, along with C III] doublet emission lines, in each region to investigate any variation in emission/absorption line properties. The mapped C III] emission shows distinct kinematical structure, with velocity offsets of ˜±50 km s-1 between regions suggestive of a merging system, and a variation in equivalent width that indicates a change in ionization parameter and/or metallicity between the regions. Absorption line velocities reveal a range of outflow strengths, with gas outflowing in the range -200 ≲ v (km s-1) ≲ -50 relative to the systemic velocity of that region. Interestingly, the strongest gas outflow appears to emanate from the most diffuse star-forming region. The star formation rates remain relatively constant (˜8-16 M⊙ yr-1), mostly due to large uncertainties in reddening estimates. As such, the outflows appear to be `global' rather than `locally' sourced. We measure electron densities with a range of log (Ne) = 3.92-4.36 cm-3, and point out that such high densities may be common when measured using the C III] doublet due to its large critical density. Overall, our observations demonstrate that while it is possible to trace variations in large-scale gas kinematics, detecting inhomogeneities in physical gas properties and their effects on the outflowing gas may be more difficult. This study provides important lessons for the spatially resolved rest-frame UV studies expected with future observatories, such as James Webb Space Telescope.

Spatial Structure of Above-Ground Biomass Limits Accuracy of Carbon Mapping in Rainforest but Large Scale Forest Inventories Can Help to Overcome

PubMed Central

Guitet, Stéphane; Hérault, Bruno; Molto, Quentin; Brunaux, Olivier; Couteron, Pierre

2015-01-01

Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate “wall-to-wall” remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution. PMID:26402522

Scaling up the diversity-resilience relationship with trait databases and remote sensing data: the recovery of productivity after wildfire.

PubMed

Spasojevic, Marko J; Bahlai, Christie A; Bradley, Bethany A; Butterfield, Bradley J; Tuanmu, Mao-Ning; Sistla, Seeta; Wiederholt, Ruscena; Suding, Katharine N

2016-04-01

Understanding the mechanisms underlying ecosystem resilience - why some systems have an irreversible response to disturbances while others recover - is critical for conserving biodiversity and ecosystem function in the face of global change. Despite the widespread acceptance of a positive relationship between biodiversity and resilience, empirical evidence for this relationship remains fairly limited in scope and localized in scale. Assessing resilience at the large landscape and regional scales most relevant to land management and conservation practices has been limited by the ability to measure both diversity and resilience over large spatial scales. Here, we combined tools used in large-scale studies of biodiversity (remote sensing and trait databases) with theoretical advances developed from small-scale experiments to ask whether the functional diversity within a range of woodland and forest ecosystems influences the recovery of productivity after wildfires across the four-corner region of the United States. We additionally asked how environmental variation (topography, macroclimate) across this geographic region influences such resilience, either directly or indirectly via changes in functional diversity. Using path analysis, we found that functional diversity in regeneration traits (fire tolerance, fire resistance, resprout ability) was a stronger predictor of the recovery of productivity after wildfire than the functional diversity of seed mass or species richness. Moreover, slope, elevation, and aspect either directly or indirectly influenced the recovery of productivity, likely via their effect on microclimate, while macroclimate had no direct or indirect effects. Our study provides some of the first direct empirical evidence for functional diversity increasing resilience at large spatial scales. Our approach highlights the power of combining theory based on local-scale studies with tools used in studies at large spatial scales and trait databases to understand pressing environmental issues. © 2015 John Wiley & Sons Ltd.

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.

Evaluating the Impact of Spatial Resolution of Landsat Predictors on the Accuracy of Biomass Models for Large-area Estimation Across the Eastern USA

NASA Astrophysics Data System (ADS)

Deo, R. K.; Domke, G. M.; Russell, M.; Woodall, C. W.

2017-12-01

Landsat data have been widely used to support strategic forest inventory and management decisions despite the limited success of passive optical remote sensing for accurate estimation of aboveground biomass (AGB). The archive of publicly available Landsat data, available at 30-m spatial resolutions since 1984, has been a valuable resource for cost-effective large-area estimation of AGB to inform national requirements such as for the US national greenhouse gas inventory (NGHGI). In addition, other optical satellite data such as MODIS imagery of wider spatial coverage and higher temporal resolution are enriching the domain of spatial predictors for regional scale mapping of AGB. Because NGHGIs require national scale AGB information and there are tradeoffs in the prediction accuracy versus operational efficiency of Landsat, this study evaluated the impact of various resolutions of Landsat predictors on the accuracy of regional AGB models across three different sites in the eastern USA: Maine, Pennsylvania-New Jersey, and South Carolina. We used recent national forest inventory (NFI) data with numerous Landsat-derived predictors at ten different spatial resolutions ranging from 30 to 1000 m to understand the optimal spatial resolution of the optical data for enhanced spatial inventory of AGB for NGHGI reporting. Ten generic spatial models at different spatial resolutions were developed for all sites and large-area estimates were evaluated (i) at the county-level against the independent designed-based estimates via the US NFI Evalidator tool and (ii) within a large number of strips ( 1 km wide) predicted via LiDAR metrics at a high spatial resolution. The county-level estimates by the Evalidator and Landsat models were statistically equivalent and produced coefficients of determination (R2) above 0.85 that varied with sites and resolution of predictors. The mean and standard deviation of county-level estimates followed increasing and decreasing trends, respectively, with models of decreasing resolutions. The Landsat-based total AGB estimates within the strips against the total AGB obtained using LiDAR metrics did not differ significantly and were within ±15 Mg/ha for each of the sites. We conclude that the optical satellite data at resolutions up to 1000 m provide acceptable accuracy for the US' NGHGI.

The effect of radiation pressure on spatial distribution of dust inside H II regions

NASA Astrophysics Data System (ADS)

Ishiki, Shohei; Okamoto, Takashi; Inoue, Akio K.

2018-02-01

We investigate the impact of radiation pressure on spatial dust distribution inside H II regions using one-dimensional radiation hydrodynamic simulations, which include absorption and re-emission of photons by dust. In order to investigate grain-size effects as well, we introduce two additional fluid components describing large and small dust grains in the simulations. Relative velocity between dust and gas strongly depends on the drag force. We include collisional drag force and coulomb drag force. We find that, in a compact H II region, a dust cavity region is formed by radiation pressure. Resulting dust cavity sizes (˜0.2 pc) agree with observational estimates reasonably well. Since dust inside an H II region is strongly charged, relative velocity between dust and gas is mainly determined by the coulomb drag force. Strength of the coulomb drag force is about 2 order of magnitude larger than that of the collisional drag force. In addition, in a cloud of mass 105 M⊙, we find that the radiation pressure changes the grain-size distribution inside H II regions. Since large (0.1 μm) dust grains are accelerated more efficiently than small (0.01 μm) grains, the large-to-small grain mass ratio becomes smaller by an order of magnitude compared with the initial one. Resulting dust-size distributions depend on the luminosity of the radiation source. The large and small grain segregation becomes weaker when we assume stronger radiation source, since dust grain charges become larger under stronger radiation and hence coulomb drag force becomes stronger.

Spatial synchrony of malaria outbreaks in a highland region of Ethiopia.

PubMed

Wimberly, Michael C; Midekisa, Alemayehu; Semuniguse, Paulos; Teka, Hiwot; Henebry, Geoffrey M; Chuang, Ting-Wu; Senay, Gabriel B

2012-10-01

To understand the drivers and consequences of malaria in epidemic-prone regions, it is important to know whether epidemics emerge independently in different areas as a consequence of local contingencies, or whether they are synchronised across larger regions as a result of climatic fluctuations and other broad-scale drivers. To address this question, we collected historical malaria surveillance data for the Amhara region of Ethiopia and analysed them to assess the consistency of various indicators of malaria risk and determine the dominant spatial and temporal patterns of malaria within the region. We collected data from a total of 49 districts from 1999-2010. Data availability was better for more recent years and more data were available for clinically diagnosed outpatient malaria cases than confirmed malaria cases. Temporal patterns of outpatient malaria case counts were correlated with the proportion of outpatients diagnosed with malaria and confirmed malaria case counts. The proportion of outpatients diagnosed with malaria was spatially clustered, and these cluster locations were generally consistent from year to year. Outpatient malaria cases exhibited spatial synchrony at distances up to 300 km, supporting the hypothesis that regional climatic variability is an important driver of epidemics. Our results suggest that decomposing malaria risk into separate spatial and temporal components may be an effective strategy for modelling and forecasting malaria risk across large areas. They also emphasise both the value and limitations of working with historical surveillance datasets and highlight the importance of enhancing existing surveillance efforts. © 2012 Blackwell Publishing Ltd.

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

Treesearch

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

2004-01-01

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

Phase synchrony reveals organization in human atrial fibrillation

PubMed Central

Vidmar, David; Narayan, Sanjiv M.

2015-01-01

It remains unclear if human atrial fibrillation (AF) is spatially nonhierarchical or exhibits a hierarchy of organization sustained by sources. We utilize activation times obtained at discrete locations during AF to compute the phase synchrony between tissue regions, to examine underlying spatial dynamics throughout both atria. We construct a binary synchronization network and show that this network can accurately define regions of coherence in coarse-grained in silico data. Specifically, domains controlled by spiral waves exhibit regions of high phase synchrony. We then apply this analysis to clinical data from patients experiencing cardiac arrhythmias using multielectrode catheters to simultaneously record from a majority of both atria. We show that pharmaceutical intervention with ibutilide organizes activation by increasing the size of the synchronized domain in AF and quantify the increase in temporal organization when arrhythmia changes from fibrillation to tachycardia. Finally, in recordings from 24 patients in AF we show that the level of synchrony is spatially broad with some patients showing large spatially contiguous regions of synchronization, while in others synchrony is localized to small pockets. Using computer simulations, we show that this distribution is inconsistent with distributions obtained from simulations that mimic multiwavelet reentry but is consistent with mechanisms in which one or more spatially conserved spiral waves is surrounded by tissue in which activation is disorganized. PMID:26475585

Transformation of environmental conditions in large former Soviet countries: regional analysis

NASA Astrophysics Data System (ADS)

Bityukova, V. R.; Borovikov, M. S.

2018-01-01

The article studies changes in the structure of environmental conditions of regions in the large former Soviet countries (case study of Russia and Kazakhstan) that have formed considerable contrasts in the placement of industrial complex and population settlement during the previous development stages. The changes related to the transition to market economy have led to essential transformation of environmental conditions. A complex index allowing to assess changes at the regional level in Kazakhstan and Russia and to reveal main similarities and differences between those changes is applied to studying the transformation of regional and industry structure. The article examines both industry-specific and spatial patterns forming environmental conditions at the regional level.

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

PubMed

Pedruski, Michael T; Arnott, Shelley E

2011-05-01

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

Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

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

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.

Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a 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. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

DOE PAGES

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; ...

2018-02-09

Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a 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. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

Shear-induced orientational dynamics and spatial heterogeneity in suspensions of motile phytoplankton

PubMed Central

Barry, Michael T.; Rusconi, Roberto; Guasto, Jeffrey S.; Stocker, Roman

2015-01-01

Fluid flow, ubiquitous in natural and man-made environments, has the potential to profoundly impact the transport of microorganisms, including phytoplankton in aquatic habitats and bioreactors. Yet, the effect of ambient flow on the swimming behaviour of phytoplankton has remained poorly understood, largely owing to the difficulty of observing cell–flow interactions at the microscale. Here, we present microfluidic experiments where we tracked individual cells for four species of motile phytoplankton exposed to a spatially non-uniform fluid shear rate, characteristic of many flows in natural and artificial environments. We observed that medium-to-high mean shear rates (1–25 s−1) produce heterogeneous cell concentrations in the form of regions of accumulation and regions of depletion. The location of these regions relative to the flow depends on the cells' propulsion mechanism, body shape and flagellar arrangement, as captured by an effective aspect ratio. Species having a large effective aspect ratio accumulated in the high-shear regions, owing to shear-induced alignment of the swimming orientation with the fluid streamlines. Species having an effective aspect ratio close to unity exhibited little preferential accumulation at low-to-moderate flow rates, but strongly accumulated in the low-shear regions under high flow conditions, potentially owing to an active, behavioural response of cells to shear. These observations demonstrate that ambient fluid flow can strongly affect the motility and spatial distribution of phytoplankton and highlight the rich dynamics emerging from the interaction between motility, morphology and flow. PMID:26538558

Watershed Dynamics, with focus on connectivity index and management of water related impacts on road infrastructure

NASA Astrophysics Data System (ADS)

Kalantari, Z.

2015-12-01

In Sweden, spatially explicit approaches have been applied in various disciplines such as landslide modelling based on soil type data and flood risk modelling for large rivers. Regarding flood mapping, most previous studies have focused on complex hydrological modelling on a small scale whereas just a few studies have used a robust GIS-based approach integrating most physical catchment descriptor (PCD) aspects on a larger scale. This study was built on a conceptual framework for looking at SedInConnect model, topography, land use, soil data and other PCDs and climate change in an integrated way to pave the way for more integrated policy making. The aim of the present study was to develop methodology for predicting the spatial probability of flooding on a general large scale. This framework can provide a region with an effective tool to inform a broad range of watershed planning activities within a region. Regional planners, decision-makers, etc. can utilize this tool to identify the most vulnerable points in a watershed and along roads to plan for interventions and actions to alter impacts of high flows and other extreme weather events on roads construction. The application of the model over a large scale can give a realistic spatial characterization of sediment connectivity for the optimal management of debris flow to road structures. The ability of the model to capture flooding probability was determined for different watersheds in central Sweden. Using data from this initial investigation, a method to subtract spatial data for multiple catchments and to produce soft data for statistical analysis was developed. It allowed flood probability to be predicted from spatially sparse data without compromising the significant hydrological features on the landscape. This in turn allowed objective quantification of the probability of floods at the field scale for future model development and watershed management.

Estimating planktonic diversity through spatial dominance patterns in a model ocean.

PubMed

Soccodato, Alice; d'Ovidio, Francesco; Lévy, Marina; Jahn, Oliver; Follows, Michael J; De Monte, Silvia

2016-10-01

In the open ocean, the observation and quantification of biodiversity patterns is challenging. Marine ecosystems are indeed largely composed by microbial planktonic communities whose niches are affected by highly dynamical physico-chemical conditions, and whose observation requires advanced methods for morphological and molecular classification. Optical remote sensing offers an appealing complement to these in-situ techniques. Global-scale coverage at high spatiotemporal resolution is however achieved at the cost of restrained information on the local assemblage. Here, we use a coupled physical and ecological model ocean simulation to explore one possible metrics for comparing measures performed on such different scales. We show that a large part of the local diversity of the virtual plankton ecosystem - corresponding to what accessible by genomic methods - can be inferred from crude, but spatially extended, information - as conveyed by remote sensing. Shannon diversity of the local community is indeed highly correlated to a 'seascape' index, which quantifies the surrounding spatial heterogeneity of the most abundant functional group. The error implied in drastically reducing the resolution of the plankton community is shown to be smaller in frontal regions as well as in regions of intermediate turbulent energy. On the spatial scale of hundreds of kms, patterns of virtual plankton diversity are thus largely sustained by mixing communities that occupy adjacent niches. We provide a proof of principle that in the open ocean information on spatial variability of communities can compensate for limited local knowledge, suggesting the possibility of integrating in-situ and satellite observations to monitor biodiversity distribution at the global scale. Copyright © 2016 Elsevier B.V. All rights reserved.

Ventral-Dorsal Functional Contribution of the Posterior Cingulate Cortex in Human Spatial Orientation: A Meta-Analysis.

PubMed

Burles, Ford; Umiltá, Alberto; McFarlane, Liam H; Potocki, Kendra; Iaria, Giuseppe

2018-01-01

The retrosplenial cortex has long been implicated in human spatial orientation and navigation. However, neural activity peaks labeled "retrosplenial cortex" in human neuroimaging studies investigating spatial orientation often lie significantly outside of the retrosplenial cortex proper. This has led to a large and anatomically heterogenous region being ascribed numerous roles in spatial orientation and navigation. Here, we performed a meta-analysis of functional Magnetic Resonance Imaging (fMRI) investigations of spatial orientation and navigation and have identified a ventral-dorsal functional specialization within the posterior cingulate for spatial encoding vs. spatial recall . Generally, ventral portions of the posterior cingulate cortex were more likely to be activated by spatial encoding , i.e., passive viewing of scenes or active navigation without a demand to respond, perform a spatial computation, or localize oneself in the environment. Conversely, dorsal portions of the posterior cingulate cortex were more likely to be activated by cognitive demands to recall spatial information or to produce judgments of distance or direction to non-visible locations or landmarks. The greatly varying resting-state functional connectivity profiles of the ventral (centroids at MNI -22, -60, 6 and 20, -56, 6) and dorsal (centroid at MNI 4, -60, 28) posterior cingulate regions identified in the meta-analysis supported the conclusion that these regions, which would commonly be labeled as "retrosplenial cortex," should be more appropriately referred to as distinct subregions of the posterior cingulate cortex. We suggest that future studies investigating the role of the retrosplenial and posterior cingulate cortex in spatial tasks carefully localize activity in the context of these identifiable subregions.

Using excess 4He to quantify variability in aquitard leakage

NASA Astrophysics Data System (ADS)

Gardner, W. Payton; Harrington, Glenn A.; Smerdon, Brian D.

2012-10-01

SummaryFluid flux through aquitards controls the rate of recharge, discharge, cross-formational fluid flow and contaminant transport in subsurface systems. In this paper, concentrations of 4He are used to investigate the spatial distribution of vertical fluid flux through the regionally extensive Great Artesian Basin aquitard system in northern South Australia. Two vertical profiles of 4He concentration in aquitard pore water, augmented with regional sampling of aquifers above and below the aquitard were used to estimate fluid flux at multiple locations over a large spatial area. 4He concentrations in the shallow aquifer above the Great Artesian Basin range from atmospheric equilibrium to 1000 times enriched over atmosphere. Fluid flux through the aquitard was estimated by fitting observed helium concentrations at each sampling site with a 1-D model of helium transport through the aquitard. Estimated fluid fluxes through the aquitard vary over three orders of magnitude across the study area. In areas of competent aquitard, fluid fluxes are less than 0.003 mm/yr, and mass transport of helium is dominated by molecular diffusion. Preferential discharge zones are clearly identifiable with fluid fluxes up to 3 mm/yr. Our results show that fluid flux through a regionally extensive aquitard can be highly variable at large spatial scales, and that 4He concentrations in aquifers bounding the aquitard system provide a convenient and sensitive method for investigating aquitard flux at the regional scale.

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

2017-01-01

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

Editorial for Journal of Hydrology: Regional Studies

USGS Publications Warehouse

Willems, Patrick; Batelaan, Okke; Hughes, Denis A.; Swarzenski, Peter W.

2014-01-01

Hydrological regimes and processes show strong regional differences. While some regions are affected by extreme drought and desertification, others are under threat of increased fluvial and/or pluvial floods. Changes to hydrological systems as a consequence of natural variations and human activities are region-specific. Many of these changes have significant interactions with and implications for human life and ecosystems. Amongst others, population growth, improvements in living standards and other demographic and socio-economic trends, related changes in water and energy demands, change in land use, water abstractions and returns to the hydrological system (UNEP, 2008), introduce temporal and spatial changes to the system and cause contamination of surface and ground waters. Hydro-meteorological boundary conditions are also undergoing spatial and temporal changes. Climate change has been shown to increase temporal and spatial variations of rainfall, increase temperature and cause changes to evapotranspiration and other hydro-meteorological variables (IPCC, 2013). However, these changes are also region specific. In addition to these climate trends, (multi)-decadal oscillatory changes in climatic conditions and large variations in meteorological conditions will continue to occur.

Large-scale drivers of malaria and priority areas for prevention and control in the Brazilian Amazon region using a novel multi-pathogen geospatial model.

PubMed

Valle, Denis; Lima, Joanna M Tucker

2014-11-20

Most of the malaria burden in the Americas is concentrated in the Brazilian Amazon but a detailed spatial characterization of malaria risk has yet to be undertaken. Utilizing 2004-2008 malaria incidence data collected from six Brazilian Amazon states, large-scale spatial patterns of malaria risk were characterized with a novel Bayesian multi-pathogen geospatial model. Data included 2.4 million malaria cases spread across 3.6 million sq km. Remotely sensed variables (deforestation rate, forest cover, rainfall, dry season length, and proximity to large water bodies), socio-economic variables (rural population size, income, and literacy rate, mortality rate for children age under five, and migration patterns), and GIS variables (proximity to roads, hydro-electric dams and gold mining operations) were incorporated as covariates. Borrowing information across pathogens allowed for better spatial predictions of malaria caused by Plasmodium falciparum, as evidenced by a ten-fold cross-validation. Malaria incidence for both Plasmodium vivax and P. falciparum tended to be higher in areas with greater forest cover. Proximity to gold mining operations was another important risk factor, corroborated by a positive association between migration rates and malaria incidence. Finally, areas with a longer dry season and areas with higher average rural income tended to have higher malaria risk. Risk maps reveal striking spatial heterogeneity in malaria risk across the region, yet these mean disease risk surface maps can be misleading if uncertainty is ignored. By combining mean spatial predictions with their associated uncertainty, several sites were consistently classified as hotspots, suggesting their importance as priority areas for malaria prevention and control. This article provides several contributions. From a methodological perspective, the benefits of jointly modelling multiple pathogens for spatial predictions were illustrated. In addition, maps of mean disease risk were contrasted with that of statistically significant disease clusters, highlighting the critical importance of uncertainty in determining disease hotspots. From an epidemiological perspective, forest cover and proximity to gold mining operations were important large-scale drivers of disease risk in the region. Finally, the hotspot in Western Acre was identified as the area that should receive highest priority from the Brazilian national malaria prevention and control programme.

Model intra-comparison of transboundary sulfate loadings over springtime east Asia

NASA Astrophysics Data System (ADS)

Goto, D.; Ohara, T.; Nakajima, T.; Takemura, T.; Kajino, M.; Dai, T.; Matsui, H.; Takami, A.; Hatakeyama, S.; Aoki, K.; Sugimoto, N.; Shimizu, A.

2013-12-01

Over east Asia, a spatial gradient of sulfate aerosols from source to outflow regions has not fully evaluated by simulations. In the present study, we executed a global aerosol-transport model (SPRINTARS) during April 2006 to investigate the spatial gradient of sulfate aerosols using multiple measurements including surface mass concentration, aerosol optical thickness, and vertical profiles of extinction coefficients for spherical particles. We also performed sensitivity experiments to estimate possible uncertainties of sulfate mass loadings caused by macrophysical processes; emission inventory, dynamic core, and spatial resolution. Among the experiments, although a difference in the surface sulfate mass concentrations over east Asia was large, none of the simulations in the present study as well as regional models reproduced the spatial gradient of the surface sulfate from the source over China to the outflow regions in Japan. The sensitivity of different macrophysical factors to the surface sulfate differs from that to sulfate loadings in the column especially in the marine boundary layers (MBL). Therefore, to properly simulate the transboundary air pollution over east Asia is required to use multiple measurements in both the source and outflow regions especially in the MBL during the polluted days.

Metacommunity theory as a multispecies, multiscale framework for studying the influence of river network structure on riverine communities and ecosystems

USGS Publications Warehouse

Brown, B.L.; Swan, C.M.; Auerbach, D.A.; Campbell, Grant E.H.; Hitt, N.P.; Maloney, K.O.; Patrick, C.

2011-01-01

Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.

Explaining Spatial Variability in Wellbore Impairment Risk for Pennsylvania Oil and Gas Wells, 2000-2014

NASA Astrophysics Data System (ADS)

Santoro, R.; Ingraffea, A. R.

2015-12-01

Previous modeling (ingraffea et al. PNAS, 2014) indicated roughly two-times higher cumulative risk for wellbore impairment in unconventional wells, relative to conventional wells, and large spatial variation in risk for oil and gas wells drilled in the state of Pennsylvania. Impairment risk for wells in the northeast portion of the state were found to be 8.5-times greater than that of wells drilled in the rest of the state. Here, we set out to explain this apparent regional variability through Boosted Regression Tree (BRT) analysis of geographic, developmental, and general well attributes. We find that regional variability is largely driven by the nature of the development, i.e. whether conventional or unconventional development is dominant. Oil and natural gas market prices and total well depths present as major influences in wellbore impairment, with moderate influences from well densities and geologic factors. The figure depicts influence paths for predictors of impairments for the state (top left), SW region (top right), unconventional/NE region (bottom left) and conventional/NW region (bottom right) models. Influences are scaled to reflect percent contributions in explaining variability in the model.

Effects of region, demography, and protection from fishing on batch fecundity of common coral trout ( Plectropomus leopardus)

NASA Astrophysics Data System (ADS)

Carter, Alex B.; Davies, Campbell R.; Mapstone, Bruce D.; Russ, Garry R.; Tobin, Andrew J.; Williams, Ashley J.

2014-09-01

Batch fecundity of female Plectropomus leopardus, a coral reef fish targeted by commercial and recreational fishing, was compared between reefs open to fishing and reefs within no-take marine reserves within three regions of the Great Barrier Reef (GBR), Australia. Length, weight, and age had positive effects on batch fecundity of spawners from northern and central reefs but negligible effects on spawners from southern reefs. Females were least fecund for a given length, weight, and age in the southern GBR. Batch fecundity of a 500-mm fork length female was 430 % greater on central reefs and 207 % greater on northern reefs than on southern reefs. The effects of length and age on batch fecundity did not differ significantly between reserve and fished reefs in any region, but weight-specific fecundity was 100 % greater for large 2.0 kg females on reserve reefs compared with fished reefs in the central GBR. We hypothesize that regional variation in batch fecundity is likely driven by water temperature and prey availability. Significant regional variation in batch fecundity highlights the need for understanding spatial variation in reproductive output where single conservation or fishery management strategies cover large, potentially diverse, spatial scales.

Large trench-parallel gravity variations predict seismogenic behavior in subduction zones.

PubMed

Song, Teh-Ru Alex; Simons, Mark

2003-08-01

We demonstrate that great earthquakes occur predominantly in regions with a strongly negative trench-parallel gravity anomaly (TPGA), whereas regions with strongly positive TPGA are relatively aseismic. These observations suggest that, over time scales up to at least 1 million years, spatial variations of seismogenic behavior within a given subduction zone are stationary and linked to the geological structure of the fore-arc. The correlations we observe are consistent with a model in which spatial variations in frictional properties on the plate interface control trench-parellel variations in fore-arc topography, gravity, and seismogenic behavior.

Quantifying aggregated uncertainty in Plasmodium falciparum malaria prevalence and populations at risk via efficient space-time geostatistical joint simulation.

PubMed

Gething, Peter W; Patil, Anand P; Hay, Simon I

2010-04-01

Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty--the fidelity of predictions at each mapped pixel--but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.

Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

NASA Technical Reports Server (NTRS)

Liu, Jianbo; Kummerow, Christian D.; Elsaesser, Gregory S.

2016-01-01

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.

A new approach in space-time analysis of multivariate hydrological data: Application to Brazil's Nordeste region rainfall

NASA Astrophysics Data System (ADS)

Sicard, Emeline; Sabatier, Robert; Niel, HéLèNe; Cadier, Eric

2002-12-01

The objective of this paper is to implement an original method for spatial and multivariate data, combining a method of three-way array analysis (STATIS) with geostatistical tools. The variables of interest are the monthly amounts of rainfall in the Nordeste region of Brazil, recorded from 1937 to 1975. The principle of the technique is the calculation of a linear combination of the initial variables, containing a large part of the initial variability and taking into account the spatial dependencies. It is a promising method that is able to analyze triple variability: spatial, seasonal, and interannual. In our case, the first component obtained discriminates a group of rain gauges, corresponding approximately to the Agreste, from all the others. The monthly variables of July and August strongly influence this separation. Furthermore, an annual study brings out the stability of the spatial structure of components calculated for each year.

Biodiversity and ecosystem stability across scales in metacommunities

PubMed Central

Wang, Shaopeng; Loreau, Michel

2016-01-01

Although diversity-stability relationships have been extensively studied in local ecosystems, the global biodiversity crisis calls for an improved understanding of these relationships in a spatial context. Here we use a dynamical model of competitive metacommunities to study the relationships between species diversity and ecosystem variability across scales. We derive analytic relationships under a limiting case; these results are extended to more general cases with numerical simulations. Our model shows that, while alpha diversity decreases local ecosystem variability, beta diversity generally contributes to increasing spatial asynchrony among local ecosystems. Consequently, both alpha and beta diversity provide stabilizing effects for regional ecosystems, through local and spatial insurance effects, respectively. We further show that at the regional scale, the stabilizing effect of biodiversity increases as spatial environmental correlation increases. Our findings have important implications for understanding the interactive effects of global environmental changes (e.g. environmental homogenization) and biodiversity loss on ecosystem sustainability at large scales. PMID:26918536

Spatial Localization in Dissipative Systems

NASA Astrophysics Data System (ADS)

Knobloch, E.

2015-03-01

Spatial localization is a common feature of physical systems, occurring in both conservative and dissipative systems. This article reviews the theoretical foundations of our understanding of spatial localization in forced dissipative systems, from both a mathematical point of view and a physics perspective. It explains the origin of the large multiplicity of simultaneously stable spatially localized states present in a parameter region called the pinning region and its relation to the notion of homoclinic snaking. The localized states are described as bound states of fronts, and the notions of front pinning, self-pinning, and depinning are emphasized. Both one-dimensional and two-dimensional systems are discussed, and the reasons behind the differences in behavior between dissipative systems with conserved and nonconserved dynamics are explained. The insights gained are specific to forced dissipative systems and are illustrated here using examples drawn from fluid mechanics (convection and shear flows) and a simple model of crystallization.

Large Deployable Reflector Science and Technology Workshop. Volume 2: Scientific Rationale and Technology Requirements

NASA Technical Reports Server (NTRS)

Hollenbach, D. (Editor)

1983-01-01

The scientific rationale for the large deployable reflector (LDR) and the overall technological requirements are discussed. The main scientific objectives include studies of the origins of planets, stars and galaxies, and of the ultimate fate of the universe. The envisioned studies require a telescope with a diameter of at least 20 m, diffraction-limited to wavelengths as short as 30-50 micron. In addition, light-bucket operation with 1 arcsec spatial resolution in the 2-4 microns wavelength region would be useful in studies of high-redshifted galaxies. Such a telescope would provide a large increase in spectroscopic sensitivity and spatial resolving power compared with existing or planned infrared telescopes.

Estimation of Global 1km-grid Terrestrial Carbon Exchange Part II: Evaluations and Applications

NASA Astrophysics Data System (ADS)

Murakami, K.; Sasai, T.; Kato, S.; Niwa, Y.; Saito, M.; Takagi, H.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.; Yokota, T.

2015-12-01

Global terrestrial carbon cycle largely depends on a spatial pattern in land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.Global terrestrial carbon cycle largely depends on a spatial pattern of land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.

Decreasing spatial variability in precipitation extremes in southwestern China and the local/large-scale influencing factors

NASA Astrophysics Data System (ADS)

Liu, Meixian; Xu, Xianli; Sun, Alex

2015-07-01

Climate extremes can cause devastating damage to human society and ecosystems. Recent studies have drawn many conclusions about trends in climate extremes, but few have focused on quantitative analysis of their spatial variability and underlying mechanisms. By using the techniques of overlapping moving windows, the Mann-Kendall trend test, correlation, and stepwise regression, this study examined the spatial-temporal variation of precipitation extremes and investigated the potential key factors influencing this variation in southwestern (SW) China, a globally important biodiversity hot spot and climate-sensitive region. Results showed that the changing trends of precipitation extremes were not spatially uniform, but the spatial variability of these precipitation extremes decreased from 1959 to 2012. Further analysis found that atmospheric circulations rather than local factors (land cover, topographic conditions, etc.) were the main cause of such precipitation extremes. This study suggests that droughts or floods may become more homogenously widespread throughout SW China. Hence, region-wide assessments and coordination are needed to help mitigate the economic and ecological impacts.

Biomass and the Climatic Space from historical to future scenarios of a Seasonally Dry Tropical Forest - Caatinga

NASA Astrophysics Data System (ADS)

Castanho, A. D. D. A.; Coe, M. T.; Maia Andrade, E.; Walker, W.; Baccini, A.; Brando, P. M.; Farina, M.

2017-12-01

The Caatinga found in the semiarid region in northeastern Brazil is the largest continuous seasonally dry tropical forest in South America. The region has for centuries been subject to anthropogenic activities of land conversion, abandonment, and regrowth. The region also has a large spatial variability of edaphic-climatic properties. These effects together contribute to a wide variability of plant physiognomies and biomass concentration. In addition to land use change due to anthropogenic activities the region is exposed in the near and long term to dryer conditions. The main goal of this work was to validate a high spatial resolution (30 m) map of above ground biomass, understand the climatic role in the biomass spatial variability in the present, and the potential threat to vegetation for future climatic shifts. Satellite-derived biomass products are advanced tools that can address spatial changes in forest structure for an extended region. Here we combine a compilation of published field phytosociological observations across the region with a new 30-meter spatial resolution satellite biomass product. Climate data used for this analyses were based on the CRU (Climate Research Unit, UEA) for the historical time period and for the future a mean and 25-75% quantiles of the CMIP Global Climate model estimates for the RCP scenarios of 4.5 and 8.5 W/m2. The high heterogeneity in the biomass and physiognomy distribution across the Caatinga region is mostly explained by the climatic space defined by the precipitation and dryness index. The Caatinga region has historically already been exposed to shift in its climatic properties, driving all the physiognomies, to a dryer climatic space within the last decade. Future climate intensify the observed trends. This study provides a clearer understanding of the spatial distribution of Caatinga vegetation, its biomass, and relationships to climate, which are essential for strategic development planning, preservation of the biome functions, human services, and biodiversity, face future climate scenarios.

Some practicable applications of quadtree data structures/representation in astronomy

NASA Technical Reports Server (NTRS)

Pasztor, L.

1992-01-01

Development of quadtree as hierarchical data structuring technique for representing spatial data (like points, regions, surfaces, lines, curves, volumes, etc.) has been motivated to a large extent by storage requirements of images, maps, and other multidimensional (spatially structured) data. For many spatial algorithms, time-efficiency of quadtrees in terms of execution may be as important as their space-efficiency concerning storage conditions. Briefly, the quadtree is a class of hierarchical data structures which is based on the recursive partition of a square region into quadrants and sub-quadrants until a predefined limit. Beyond the wide applicability of quadtrees in image processing, spatial information analysis, and building digital databases (processes becoming ordinary for the astronomical community), there may be numerous further applications in astronomy. Some of these practicable applications based on quadtree representation of astronomical data are presented and suggested for further considerations. Examples are shown for use of point as well as region quadtrees. Statistics of different leaf and non-leaf nodes (homogeneous and heterogeneous sub-quadrants respectively) at different levels may provide useful information on spatial structure of astronomical data in question. By altering the principle guiding the decomposition process, different types of spatial data may be focused on. Finally, a sampling method based on quadtree representation of an image is proposed which may prove to be efficient in the elaboration of sampling strategy in a region where observations were carried out previously either with different resolution or/and in different bands.

EEG source reconstruction reveals frontal-parietal dynamics of spatial conflict processing.

PubMed

Cohen, Michael X; Ridderinkhof, K Richard

2013-01-01

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30-50 Hz), followed by a later alpha-band (8-12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4-8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions.

Silver hake tracks changes in Northwest Atlantic circulation.

PubMed

Nye, Janet A; Joyce, Terrence M; Kwon, Young-Oh; Link, Jason S

2011-08-02

Recent studies documenting shifts in spatial distribution of many organisms in response to a warming climate highlight the need to understand the mechanisms underlying species distribution at large spatial scales. Here we present one noteworthy example of remote oceanographic processes governing the spatial distribution of adult silver hake, Merluccius bilinearis, a commercially important fish in the Northeast US shelf region. Changes in spatial distribution of silver hake over the last 40 years are highly correlated with the position of the Gulf Stream. These changes in distribution are in direct response to local changes in bottom temperature on the continental shelf that are responding to the same large scale circulation change affecting the Gulf Stream path, namely changes in the Atlantic meridional overturning circulation (AMOC). If the AMOC weakens, as is suggested by global climate models, silver hake distribution will remain in a poleward position, the extent to which could be forecast at both decadal and multidecadal scales.

Tidal and atmospheric forcing of the upper ocean in the Gulf of California. I - Sea surface temperature variability

NASA Technical Reports Server (NTRS)

Paden, Cynthia A.; Winant, Clinton D.; Abbott, Mark R.

1991-01-01

SST variability in the northern Gulf of California is examined on the basis of findings of two years of satellite infrared imagery (1984-1986). Empirical orthogonal functions of the temporal and spatial SST variance for 20 monthly mean images show that the dominant SST patterns are generated by spatially varying tidal mixing in the presence of seasonal heating and cooling. Atmospheric forcing of the northern gulf appears to occur over large spatial scales. Area-averaged SSTs for the Guaymas Basin, island region, and northern basin exhibit significant fluctuations which are highly correlated. These fluctuations in SST correspond to similar fluctuations in the air temperature which are related to synoptic weather events over the gulf. A regression analysis of the SST relative to the fortnightly tidal range shows that tidal mixing occurs over the sills in the island region as well as on the shallow northern shelf. Mixing over the sills occurs as a result of large breaking internal waves of internal hydraulic jumps which mix over water in the upper 300-500 m.

Observational evidence of the complementary relationship in regional evaporation lends strong support for Bouchet's hypothesis

Treesearch

Jorge A. Ramirez; Michael T. Hobbins; Thomas C. Brown

2005-01-01

Using independent observations of actual and potential evapotranspiration at a wide range of spatial scales, we provide direct observational evidence of the complementary relationship in regional evapotranspiration hypothesized by Bouchet in 1963. Bouchet proposed that, for large homogeneous surfaces with minimal advection of heat and moisture, potential and actual...

Gradient polymer-disposed liquid crystal single layer of large nematic droplets for modulation of laser light.

PubMed

Hadjichristov, Georgi B; Marinov, Yordan G; Petrov, Alexander G

2011-06-01

The light modulating ability of gradient polymer-disposed liquid crystal (PDLC) single layer of large droplets formed by nematic E7 in UV-cured polymer NOA65 is studied. Operating at relatively low voltages, such PDLC film with a of thickness 10-25 μm and droplet size up to 50 μm exhibits a good contrast ratio and is capable of producing a large phase shift for the propagating coherent light. For a linearly polarized He-Ne laser (λ=633 nm), an electrically commanded phase shift as large as π/2 can be obtained by the large-droplet region of the film. The electrically produced phase shift and its spatial profile controlled by the thickness of the gradient PDLC single layers of large nematic droplets can be useful for tunable spatial light modulators and other devices for active control of laser light.

Assessment of the Suitability of High Resolution Numerical Weather Model Outputs for Hydrological Modelling in Mountainous Cold Regions

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.

2017-12-01

The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.

Exploring spatial-temporal dynamics of fire regime features in mainland Spain

NASA Astrophysics Data System (ADS)

Jiménez-Ruano, Adrián; Rodrigues Mimbrero, Marcos; de la Riva Fernández, Juan

2017-10-01

This paper explores spatial-temporal dynamics in fire regime features, such as fire frequency, burnt area, large fires and natural- and human-caused fires, as an essential part of fire regime characterization. Changes in fire features are analysed at different spatial - regional and provincial/NUTS3 - levels, together with summer and winter temporal scales, using historical fire data from Spain for the period 1974-2013. Temporal shifts in fire features are investigated by means of change point detection procedures - Pettitt test, AMOC (at most one change), PELT (pruned exact linear time) and BinSeg (binary segmentation) - at a regional level to identify changes in the time series of the features. A trend analysis was conducted using the Mann-Kendall and Sen's slope tests at both the regional and NUTS3 level. Finally, we applied a principal component analysis (PCA) and varimax rotation to trend outputs - mainly Sen's slope values - to summarize overall temporal behaviour and to explore potential links in the evolution of fire features. Our results suggest that most fire features show remarkable shifts between the late 1980s and the first half of the 1990s. Mann-Kendall outputs revealed negative trends in the Mediterranean region. Results from Sen's slope suggest high spatial and intra-annual variability across the study area. Fire activity related to human sources seems to be experiencing an overall decrease in the northwestern provinces, particularly pronounced during summer. Similarly, the Hinterland and the Mediterranean coast are gradually becoming less fire affected. Finally, PCA enabled trends to be synthesized into four main components: winter fire frequency (PC1), summer burnt area (PC2), large fires (PC3) and natural fires (PC4).

Spatial structure of plasma density perturbations, induced in the ionosphere modified by powerful HF radio waves: Review of experimental results

NASA Astrophysics Data System (ADS)

Frolov, Vladimir

2015-06-01

In the review, the results of experimental studies of spatial structure of small-, middle-, and large scale plasma density perturbations induced in the ionosphere by its pumping by powerful HF O-mode (ordinary) radio waves, are analyzed. It is shown that the region with induced plasma density perturbations occupied all ionosphere body from its E-region up to the topside ionosphere in the height and it has the horizontal length of about of 300-500 km. Peculiarities of generation of artificial ionosphere irregularities of different scale-lengths in the magnetic zenith region are stated. Experimental results obtained under conditions of ionosphere periodical pumping when the generation of travel ionosphere disturbances is revealed are also discussed.

Producing custom regional climate data sets for impact assessment with xarray

NASA Astrophysics Data System (ADS)

Simcock, J. G.; Delgado, M.; Greenstone, M.; Hsiang, S. M.; Kopp, R. E.; Carleton, T.; Hultgren, A.; Jina, A.; Nath, I.; Rising, J. A.; Rode, A.; Yuan, J.; Chong, T.; Dobbels, G.; Hussain, A.; Song, Y.; Wang, J.; Mohan, S.; Larsen, K.; Houser, T.

2017-12-01

Research in the field of climate impact assessment and valuation frequently requires the pairing of economic observations with historical or projected weather variables. Impact assessments with large geographic scope or spatially aggregated data frequently require climate variables to be prepared for use with administrative/political regions, economic districts such as utility service areas, physical regions such as watersheds, or other larger, non-gridded shapes. Approaches to preparing such data in the literature vary from methods developed out of convenience to more complex measures intended to account for spatial heterogeneity. But more sophisticated methods are difficult to implement, from both a theoretical and a technical standpoint. We present a new python package designed to assist researchers in the preparation of historical and projected climate data for arbitrary spatial definitions. Users specify transformations by providing (a) sets of regions in the form of shapefiles, (b) gridded data to be transformed, and, optionally, (c) gridded weights to use in the transformation. By default, aggregation to regions is conducted such that the resulting regional data draws from each grid cell according to the cell's share of total region area. However, researchers can provide alternative weighting schemes, such that the regional data is weighted by, for example, the population or planted agricultural area within each cell. An advantage of this method is that it enables easy preparation of nonlinear transformations of the climate data before aggregation to regions, allowing aggregated variables to more accurately capture the spatial heterogeneity within a region in the transformed data. At this session, we will allow attendees to view transformed climate projections, examining the effect of various weighting schemes and nonlinear transformations on aggregate regional values, highlighting the implications for climate impact assessment work.

Different regional climatic drivers of Holocene large wildfires in boreal forests of northeastern America

NASA Astrophysics Data System (ADS)

Remy, Cécile C.; Hély, Christelle; Blarquez, Olivier; Magnan, Gabriel; Bergeron, Yves; Lavoie, Martin; Ali, Adam A.

2017-03-01

Global warming could increase climatic instability and large wildfire activity in circumboreal regions, potentially impairing both ecosystem functioning and human health. However, links between large wildfire events and climatic and/or meteorological conditions are still poorly understood, partly because few studies have covered a wide range of past climate-fire interactions. We compared palaeofire and simulated climatic data over the last 7000 years to assess causes of large wildfire events in three coniferous boreal forest regions in north-eastern Canada. These regions span an east-west cline, from a hilly region influenced by the Atlantic Ocean currently dominated by Picea mariana and Abies balsamea to a flatter continental region dominated by Picea mariana and Pinus banksiana. The largest wildfires occurred across the entire study zone between 3000 and 1000 cal. BP. In western and central continental regions these events were triggered by increases in both the fire-season length and summer/spring temperatures, while in the eastern region close to the ocean they were likely responses to hydrological (precipitation/evapotranspiration) variability. The impact of climatic drivers on fire size varied spatially across the study zone, confirming that regional climate dynamics could modulate effects of global climate change on wildfire regimes.

Predicting future spatial distribution of SOC across entire France

NASA Astrophysics Data System (ADS)

Meersmans, Jeroen; Van Rompaey, Anton; Quine, Tim; Martin, Manuel; Pagé, Christian; Arrouays, Dominique

2013-04-01

Soil organic carbon (SOC) is widely recognized as a key factor controlling soil quality and as a crucial and active component of the global C-cycle. Hence, there exists a growing interest in monitoring and modeling the spatial and temporal behavior of this pool. So far, a large attempt has been made to map SOC at national scales for current and/or past situations. Despite some coarse predictions, detailed spatial SOC predictions for the future are still lacking. In this study we aim to predict future spatial evolution of SOC driven by climate and land use change for France up to the year 2100. Therefore, we combined 1) an existing model, predicting SOC as a function of soil type, climate, land use and management (Meersmans et al 2012), with 2) eight different IPCC spatial explicit climate change predictions (conducted by CERFACS) and 3) Land use change scenario predictions. We created business-as-usual land use change scenarios by extrapolating observed trends and calibrating logistic regression models, incorporating a large set of physical and socio-economic factors, at the regional level in combination with a multi-objective land allocation (MOLA) procedure. The resultant detailed projections of future SOC evolution across all regions of France, allow us to identify regions that are most likely to be characterized by a significant gain or loss of SOC and the degree to which land use decisions/outcomes control the scale of loss and gain. Therefore, this methodology and resulting maps can be considered as powerful tools to aid decision making concerning appropriate soil management, in order to enlarge SOC storage possibilities and reduce soil related CO2 fluxes.

Merging Station Observations with Large-Scale Gridded Data to Improve Hydrological Predictions over Chile

NASA Astrophysics Data System (ADS)

Peng, L.; Sheffield, J.; Verbist, K. M. J.

2016-12-01

Hydrological predictions at regional-to-global scales are often hampered by the lack of meteorological forcing data. The use of large-scale gridded meteorological data is able to overcome this limitation, but these data are subject to regional biases and unrealistic values at local scale. This is especially challenging in regions such as Chile, where climate exhibits high spatial heterogeneity as a result of long latitude span and dramatic elevation changes. However, regional station-based observational datasets are not fully exploited and have the potential of constraining biases and spatial patterns. This study aims at adjusting precipitation and temperature estimates from the Princeton University global meteorological forcing (PGF) gridded dataset to improve hydrological simulations over Chile, by assimilating 982 gauges from the Dirección General de Aguas (DGA). To merge station data with the gridded dataset, we use a state-space estimation method to produce optimal gridded estimates, considering both the error of the station measurements and the gridded PGF product. The PGF daily precipitation, maximum and minimum temperature at 0.25° spatial resolution are adjusted for the period of 1979-2010. Precipitation and temperature gauges with long and continuous records (>70% temporal coverage) are selected, while the remaining stations are used for validation. The leave-one-out cross validation verifies the robustness of this data assimilation approach. The merged dataset is then used to force the Variable Infiltration Capacity (VIC) hydrological model over Chile at daily time step which are compared to the observations of streamflow. Our initial results show that the station-merged PGF precipitation effectively captures drizzle and the spatial pattern of storms. Overall the merged dataset has significant improvements compared to the original PGF with reduced biases and stronger inter-annual variability. The invariant spatial pattern of errors between the station data and the gridded product opens up the possibility of merging real-time satellite and intermittent gauge observations to produce more accurate real-time hydrological predictions.

Dynamics of place, boundary and object encoding in rat anterior claustrum

PubMed Central

Jankowski, Maciej M.; O’Mara, Shane M.

2015-01-01

Discrete populations of brain cells signal differing types of spatial information. These “spatial cells” are largely confined to a closely-connected network of sites. We describe here, for the first time, cells in the anterior claustrum of the freely-moving rat encoding place, boundary and object information. This novel claustral spatial signal potentially directly modulates a wide variety of anterior cortical regions. We hypothesize that one of the functions of the claustrum is to provide information about body position, boundaries and landmark information, enabling dynamic control of behavior. PMID:26557060

USING CLASSIFICATION CONSISTENCY IN INTER-SCENE OVERLAP AREAS TO MODEL SPATIAL VARIATIONS IN LAND-COVER ACCURACY OVER LARGE GEOGRAPHIC REGIONS

EPA Science Inventory

During the last decade, a number of initiatives have been undertaken to create systematic national and global data sets of processed satellite imagery. An important application of these data is the derivation of large area (i.e. multi-scene) land cover products. Such products, ho...

Evaluating Site-Specific and Generic Spatial Models of Aboveground Forest Biomass Based on Landsat Time-Series and LiDAR Strip Samples in the Eastern USA

Treesearch

Ram Deo; Matthew Russell; Grant Domke; Hans-Erik Andersen; Warren Cohen; Christopher Woodall

2017-01-01

Large-area assessment of aboveground tree biomass (AGB) to inform regional or national forest monitoring programs can be efficiently carried out by combining remotely sensed data and field sample measurements through a generic statistical model, in contrast to site-specific models. We integrated forest inventory plot data with spatial predictors from Landsat time-...

Using Climate Regionalization to Understand Climate Forecast System Version 2 (CFSv2) Precipitation Performance for the Conterminous United States (CONUS)

NASA Technical Reports Server (NTRS)

Regonda, Satish K.; Zaitchik, Benjamin F.; Badr, Hamada S.; Rodell, Matthew

2016-01-01

Dynamically based seasonal forecasts are prone to systematic spatial biases due to imperfections in the underlying global climate model (GCM). This can result in low-forecast skill when the GCM misplaces teleconnections or fails to resolve geographic barriers, even if the prediction of large-scale dynamics is accurate. To characterize and address this issue, this study applies objective climate regionalization to identify discrepancies between the Climate Forecast SystemVersion 2 (CFSv2) and precipitation observations across the Contiguous United States (CONUS). Regionalization shows that CFSv2 1 month forecasts capture the general spatial character of warm season precipitation variability but that forecast regions systematically differ from observation in some transition zones. CFSv2 predictive skill for these misclassified areas is systematically reduced relative to correctly regionalized areas and CONUS as a whole. In these incorrectly regionalized areas, higher skill can be obtained by using a regional-scale forecast in place of the local grid cell prediction.

Changing patterns of spatial clustering of schistosomiasis in Southwest China between 1999-2001 and 2007-2008: assessing progress toward eradication after the World Bank Loan Project.

PubMed

Hu, Yi; Xiong, Chenglong; Zhang, Zhijie; Luo, Can; Cohen, Ted; Gao, Jie; Zhang, Lijuan; Jiang, Qingwu

2014-01-03

We compared changes in the spatial clustering of schistosomiasis in Southwest China at the conclusion of and six years following the end of the World Bank Loan Project (WBLP), the control strategy of which was focused on the large-scale use of chemotherapy. Parasitological data were obtained through standardized surveys conducted in 1999-2001 and again in 2007-2008. Two alternate spatial cluster methods were used to identify spatial clusters of cases: Anselin's Local Moran's I test and Kulldorff's spatial scan statistic. Substantial reductions in the burden of schistosomiasis were found after the end of the WBLP, but the spatial extent of schistosomiasis was not reduced across the study area. Spatial clusters continued to occur in three regions: Chengdu Plain, Yangtze River Valley, and Lancang River Valley during the two periods, and regularly involved five counties. These findings suggest that despite impressive reductions in burden, the hilly and mountainous regions of Southwest China remain at risk of schistosome re-emergence. Our results help to highlight specific locations where integrated control programs can focus to speed the elimination of schistosomiasis in China.

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.

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

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

ACID RAIN MODELING

EPA Science Inventory

This paper provides an overview of existing statistical methodologies for the estimation of site-specific and regional trends in wet deposition. The interaction of atmospheric processes and emissions tend to produce wet deposition data patterns that show large spatial and tempora...

Spatial scale of similarity as an indicator of metacommunity stability in exploited marine systems.

PubMed

Shackell, Nancy L; Fisher, Jonathan A D; Frank, Kenneth T; Lawton, Peter

2012-01-01

The spatial scale of similarity among fish communities is characteristically large in temperate marine systems: connectivity is enhanced by high rates of dispersal during the larval/juvenile stages and the increased mobility of large-bodied fish. A larger spatial scale of similarity (low beta diversity) is advantageous in heavily exploited systems because locally depleted populations are more likely to be "rescued" by neighboring areas. We explored whether the spatial scale of similarity changed from 1970 to 2006 due to overfishing of dominant, large-bodied groundfish across a 300 000-km2 region of the Northwest Atlantic. Annually, similarities among communities decayed slowly with increasing geographic distance in this open system, but through time the decorrelation distance declined by 33%, concomitant with widespread reductions in biomass, body size, and community evenness. The decline in connectivity stemmed from an erosion of community similarity among local subregions separated by distances as small as 100 km. Larger fish, of the same species, contribute proportionally more viable offspring, so observed body size reductions will have affected maternal output. The cumulative effect of nonlinear maternal influences on egg/larval quality may have compromised the spatial scale of effective larval dispersal, which may account for the delayed recovery of certain member species. Our study adds strong support for using the spatial scale of similarity as an indicator of metacommunity stability both to understand the spatial impacts of exploitation and to refine how spatial structure is used in management plans.

Spatio-Temporal Variability of Groundwater Storage in India

NASA Technical Reports Server (NTRS)

Bhanja, Soumendra; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2016-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Ground water storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent).In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Spatio-temporal variability of groundwater storage in India.

PubMed

Bhanja, Soumendra N; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2017-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Groundwater storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent). In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Right hemisphere dominance during spatial selective attention and target detection occurs outside the dorsal fronto-parietal network

PubMed Central

Shulman, Gordon L.; Pope, Daniel L. W.; Astafiev, Serguei V.; McAvoy, Mark P.; Snyder, Abraham Z.; Corbetta, Maurizio

2010-01-01

Spatial selective attention is widely considered to be right hemisphere dominant. Previous functional magnetic resonance imaging (fMRI) studies, however, have reported bilateral blood-oxygenation-level-dependent (BOLD) responses in dorsal fronto-parietal regions during anticipatory shifts of attention to a location (Kastner et al., 1999; Corbetta et al., 2000; Hopfinger et al., 2000). Right-lateralized activity has mainly been reported in ventral fronto-parietal regions for shifts of attention to an unattended target stimulus (Arrington et al., 2000; Corbetta et al., 2000). However, clear conclusions cannot be drawn from these studies because hemispheric asymmetries were not assessed using direct voxel-wise comparisons of activity in left and right hemispheres. Here, we used this technique to measure hemispheric asymmetries during shifts of spatial attention evoked by a peripheral cue stimulus and during target detection at the cued location. Stimulus-driven shifts of spatial attention in both visual fields evoked right-hemisphere dominant activity in temporo-parietal junction (TPJ). Target detection at the attended location produced a more widespread right hemisphere dominance in frontal, parietal, and temporal cortex, including the TPJ region asymmetrically activated during shifts of spatial attention. However, hemispheric asymmetries were not observed during either shifts of attention or target detection in the dorsal fronto-parietal regions (anterior precuneus, medial intraparietal sulcus, frontal eye fields) that showed the most robust activations for shifts of attention. Therefore, right hemisphere dominance during stimulus-driven shifts of spatial attention and target detection reflects asymmetries in cortical regions that are largely distinct from the dorsal fronto-parietal network involved in the control of selective attention. PMID:20219998

Applying network theory to prioritize multispecies habitat networks that are robust to climate and land-use change.

PubMed

Albert, Cécile H; Rayfield, Bronwyn; Dumitru, Maria; Gonzalez, Andrew

2017-12-01

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land-use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land-use change projections with the latest developments in network-connectivity research and spatial, multipurpose conservation prioritization. We used land-use change simulations to explore robustness of species' habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land-use change. The application of connectivity criteria alongside habitat-quality criteria for protected-area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade-offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low. © 2017 Society for Conservation Biology.

Large-scale spatio-temporal monitoring highlights hotspots of demersal fish diversity in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Granger, Victoria; Fromentin, Jean-Marc; Bez, Nicolas; Relini, Giulio; Meynard, Christine N.; Gaertner, Jean-Claude; Maiorano, Porzia; Garcia Ruiz, Cristina; Follesa, Cristina; Gristina, Michele; Peristeraki, Panagiota; Brind'Amour, Anik; Carbonara, Pierluigi; Charilaou, Charis; Esteban, Antonio; Jadaud, Angélique; Joksimovic, Aleksandar; Kallianiotis, Argyris; Kolitari, Jerina; Manfredi, Chiara; Massuti, Enric; Mifsud, Roberta; Quetglas, Antoni; Refes, Wahid; Sbrana, Mario; Vrgoc, Nedo; Spedicato, Maria Teresa; Mérigot, Bastien

2015-01-01

Increasing human pressures and global environmental change may severely affect the diversity of species assemblages and associated ecosystem services. Despite the recent interest in phylogenetic and functional diversity, our knowledge on large spatio-temporal patterns of demersal fish diversity sampled by trawling remains still incomplete, notably in the Mediterranean Sea, one of the most threatened marine regions of the world. We investigated large spatio-temporal diversity patterns by analysing a dataset of 19,886 hauls from 10 to 800 m depth performed annually during the last two decades by standardised scientific bottom trawl field surveys across the Mediterranean Sea, within the MEDITS program. A multi-component (eight diversity indices) and multi-scale (local assemblages, biogeographic regions to basins) approach indicates that only the two most traditional components (species richness and evenness) were sufficient to reflect patterns in taxonomic, phylogenetic or functional richness and divergence. We also put into question the use of widely computed indices that allow comparing directly taxonomic, phylogenetic and functional diversity within a unique mathematical framework. In addition, demersal fish assemblages sampled by trawl do not follow a continuous decreasing longitudinal/latitudinal diversity gradients (spatial effects explained up to 70.6% of deviance in regression tree and generalised linear models), for any of the indices and spatial scales analysed. Indeed, at both local and regional scales species richness was relatively high in the Iberian region, Malta, the Eastern Ionian and Aegean seas, meanwhile the Adriatic Sea and Cyprus showed a relatively low level. In contrast, evenness as well as taxonomic, phylogenetic and functional divergences did not show regional hotspots. All studied diversity components remained stable over the last two decades. Overall, our results highlight the need to use complementary diversity indices through different spatial scales when developing conservation strategies and defining delimitations for protected areas.

Remote sensing estimation of the total phosphorus concentration in a large lake using band combinations and regional multivariate statistical modeling techniques.

PubMed

Gao, Yongnian; Gao, Junfeng; Yin, Hongbin; Liu, Chuansheng; Xia, Ting; Wang, Jing; Huang, Qi

2015-03-15

Remote sensing has been widely used for ater quality monitoring, but most of these monitoring studies have only focused on a few water quality variables, such as chlorophyll-a, turbidity, and total suspended solids, which have typically been considered optically active variables. Remote sensing presents a challenge in estimating the phosphorus concentration in water. The total phosphorus (TP) in lakes has been estimated from remotely sensed observations, primarily using the simple individual band ratio or their natural logarithm and the statistical regression method based on the field TP data and the spectral reflectance. In this study, we investigated the possibility of establishing a spatial modeling scheme to estimate the TP concentration of a large lake from multi-spectral satellite imagery using band combinations and regional multivariate statistical modeling techniques, and we tested the applicability of the spatial modeling scheme. The results showed that HJ-1A CCD multi-spectral satellite imagery can be used to estimate the TP concentration in a lake. The correlation and regression analysis showed a highly significant positive relationship between the TP concentration and certain remotely sensed combination variables. The proposed modeling scheme had a higher accuracy for the TP concentration estimation in the large lake compared with the traditional individual band ratio method and the whole-lake scale regression-modeling scheme. The TP concentration values showed a clear spatial variability and were high in western Lake Chaohu and relatively low in eastern Lake Chaohu. The northernmost portion, the northeastern coastal zone and the southeastern portion of western Lake Chaohu had the highest TP concentrations, and the other regions had the lowest TP concentration values, except for the coastal zone of eastern Lake Chaohu. These results strongly suggested that the proposed modeling scheme, i.e., the band combinations and the regional multivariate statistical modeling techniques, demonstrated advantages for estimating the TP concentration in a large lake and had a strong potential for universal application for the TP concentration estimation in large lake waters worldwide. Copyright © 2014 Elsevier Ltd. All rights reserved.

The role of spatial organization in preference for color pairs.

PubMed

Schloss, Karen B; Palmer, Stephen E

2011-01-01

We investigated how spatial organization influences color-pair preference asymmetries: differential preference for one color pair over another when the pairs contain the same colors in opposite spatial configurations. Schloss and Palmer (2011, Attention, Perception, & Psychophysics 73 55-571) found weak figure ground preference asymmetries for small squares centered on large squares in aesthetic ratings. Here, we found robust preference asymmetries using a more sensitive forced-choice task: participants strongly prefer pairs with yellower, lighter figures on bluer, darker grounds (experiment 1). We also investigated which spatial factors influence these preference asymmetries. Relative area of the two component regions is clearly important, and perceived 3-D area of the 2-D displays (ie after the ground is amodally completed behind the figure) is more influential than 2-D area (experiment 2). Surroundedness is not required, because yellowness blueness effects were comparable for pairs in which the figure was surrounded by the ground, and for mosaic arrangements in which the regions were adjacent and separated by a gap (experiment 3). Lightness darkness effects, however, were opposite for figure ground versus mosaic organizations: people prefer figure-ground organizations in which smaller regions are lighter, but prefer mosaic organizations in which smaller regions are darker. Physiological, phenomenological, and ecological explanations of the reported results are discussed.

Similarities and differences between the brain networks underlying allocentric and egocentric spatial learning in rat revealed by cytochrome oxidase histochemistry.

PubMed

Rubio, S; Begega, A; Méndez, M; Méndez-López, M; Arias, J L

2012-10-25

The involvement of different brain regions in place- and response-learning was examined using a water cross-maze. Rats were trained to find the goal from the initial arm by turning left at the choice point (egocentric strategy) or by using environmental cues (allocentric strategy). Although different strategies were required, the same maze and learning conditions were used. Using cytochrome oxidase histochemistry as a marker of cellular activity, the function of the 13 diverse cortical and subcortical regions was assessed in rats performing these two tasks. Our results show that allocentric learning depends on the recruitment of a large functional network, which includes the hippocampal CA3, dentate gyrus, medial mammillary nucleus and supramammillary nucleus. Along with the striatum, these last three structures are also related to egocentric spatial learning. The present study provides evidence for the contribution of these regions to spatial navigation and supports a possible functional interaction between the two memory systems, as their structural convergence may facilitate functional cooperation in the behaviours guided by more than one strategy. In summary, it can be argued that spatial learning is based on dynamic functional systems in which the interaction of brain regions is modulated by task requirements. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.

Soil moisture downscaling using a simple thermal based proxy

NASA Astrophysics Data System (ADS)

Peng, Jian; Loew, Alexander; Niesel, Jonathan

2016-04-01

Microwave remote sensing has been largely applied to retrieve soil moisture (SM) from active and passive sensors. The obvious advantage of microwave sensor is that SM can be obtained regardless of atmospheric conditions. However, existing global SM products only provide observations at coarse spatial resolutions, which often hamper their applications in regional hydrological studies. Therefore, various downscaling methods have been proposed to enhance the spatial resolution of satellite soil moisture products. The aim of this study is to investigate the validity and robustness of a simple Vegetation Temperature Condition Index (VTCI) downscaling scheme over different climates and regions. Both polar orbiting (MODIS) and geostationary (MSG SEVIRI) satellite data are used to improve the spatial resolution of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative (ESA CCI) soil moisture, which is a merged product based on both active and passive microwave observations. The results from direct validation against soil moisture in-situ measurements, spatial pattern comparison, as well as seasonal and land use analyses show that the downscaling method can significantly improve the spatial details of CCI soil moisture while maintain the accuracy of CCI soil moisture. The application of the scheme with different satellite platforms and over different regions further demonstrate the robustness and effectiveness of the proposed method. Therefore, the VTCI downscaling method has the potential to facilitate relevant hydrological applications that require high spatial and temporal resolution soil moisture.

Using occupancy estimation to assess the effectiveness of a regional multiple-species conservation plan: bats in the Pacific Northwest

Treesearch

Theodore Weller

2008-01-01

Regional conservation plans are increasingly used to plan for and protect biodiversity at large spatial scales however the means of quantitatively evaluating their effectiveness are rarely specified. Multiple-species approaches, particular those which employ site-occupancy estimation, have been proposed as robust and efficient alternatives for assessing the status of...

Untangling the relationships among regional occupancy, species traits, and niche characteristics in stream invertebrates

PubMed Central

Heino, Jani; Grönroos, Mira

2014-01-01

The regional occupancy and local abundance of species are affected by various species traits, but their relative effects are poorly understood. We studied the relationships between species traits and occupancy (i.e., proportion of sites occupied) or abundance (i.e., mean local abundance at occupied sites) of stream invertebrates using small-grained data (i.e., local stream sites) across a large spatial extent (i.e., three drainage basins). We found a significant, yet rather weak, linear relationship between occupancy and abundance. However, occupancy was strongly related to niche position (NP), but it showed a weaker relationship with niche breadth (NB). Abundance was at best weakly related to these explanatory niche-based variables. Biological traits, including feeding modes, habit traits, dispersal modes and body size classes, were generally less important in accounting for variation in occupancy and abundance. Our findings showed that the regional occupancy of stream invertebrate species is mostly related to niche characteristics, in particular, NP. However, the effects of NB on occupancy were affected by the measure itself. We conclude that niche characteristics determine the regional occupancy of species at relatively large spatial extents, suggesting that species distributions are determined by environmental variation among sites. PMID:24963387

Do spatial patterns of urbanization and land consumption reflect different socioeconomic contexts in Europe?

PubMed

Salvati, Luca; Zambon, Ilaria; Chelli, Francesco Maria; Serra, Pere

2018-06-01

Land-use changes and urban sprawl have transformed European cities, with a direct impact on both metropolitan structures and socioeconomic functions. However, these processes tend to be relatively different across countries, being influenced by place-specific factors associated to socioeconomic, historical, political and cultural factors that influence decisions on the use of land. Considering 155 metropolitan areas in 6 European macro-regions, the present study investigates spatial patterns of land consumption profiling cities according to a large set of territorial variables, with the final objective to identify relevant socioeconomic dimensions characteristic of recent processes of urban growth. Investigating the socioeconomic background underlying land-use changes in metropolitan regions allows identification of place-specific factors improving the design of effective strategies containing land consumption in different European urban typologies. An exhaustive analysis of land-use changes at regional and local spatial scales contributes to find alternative policies for land-use efficiency and long-term environmental sustainability. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatial Variability of accumulation across the Western Greenland Ice Sheet Percolation Zone from ground-penetrating-radar and shallow firn cores

NASA Astrophysics Data System (ADS)

Lewis, G.; Osterberg, E. C.; Hawley, R. L.; Marshall, H. P.; Birkel, S. D.; Meehan, T. G.; Graeter, K.; Overly, T. B.; McCarthy, F.

2017-12-01

The mass balance of the Greenland Ice Sheet (GrIS) in a warming climate is of critical interest to scientists and the general public in the context of future sea-level rise. Increased melting in the GrIS percolation zone over the past several decades has led to increased mass loss at lower elevations due to recent warming. Uncertainties in mass balance are especially large in regions with sparse and/or outdated in situ measurements. This study is the first to calculate in situ accumulation over a large region of western Greenland since the Program for Arctic Regional Climate Assessment campaign during the 1990s. Here we analyze 5000 km of 400 MHz ground penetrating radar data and sixteen 25-33 m-long firn cores in the western GrIS percolation zone to determine snow accumulation over the past 50 years. The cores and radar data were collected as part of the 2016-2017 Greenland Traverse for Accumulation and Climate Studies (GreenTrACS). With the cores and radar profiles we capture spatial accumulation gradients between 1850-2500 m a.s.l and up to Summit Station. We calculate accumulation rates and use them to validate five widely used regional climate models and to compare with IceBridge snow and accumulation radars. Our results indicate that while the models capture most regional spatial climate patterns, they lack the small-scale spatial variability captured by in situ measurements. Additionally, we evaluate temporal trends in accumulation at ice core locations and throughout the traverse. Finally, we use empirical orthogonal function and correlation analyses to investigate the principal drivers of radar-derived accumulation rates across the western GrIS percolation zone, including major North Atlantic climate modes such as the North Atlantic Oscillation, Atlantic Multidecadal Oscillation, and Greenland Blocking Index.

Reconstruction of global gridded monthly sectoral water withdrawals for 1971-2010 and analysis of their spatiotemporal patterns

NASA Astrophysics Data System (ADS)

Huang, Zhongwei; Hejazi, Mohamad; Li, Xinya; Tang, Qiuhong; Vernon, Chris; Leng, Guoyong; Liu, Yaling; Döll, Petra; Eisner, Stephanie; Gerten, Dieter; Hanasaki, Naota; Wada, Yoshihide

2018-04-01

Human water withdrawal has increasingly altered the global water cycle in past decades, yet our understanding of its driving forces and patterns is limited. Reported historical estimates of sectoral water withdrawals are often sparse and incomplete, mainly restricted to water withdrawal estimates available at annual and country scales, due to a lack of observations at seasonal and local scales. In this study, through collecting and consolidating various sources of reported data and developing spatial and temporal statistical downscaling algorithms, we reconstruct a global monthly gridded (0.5°) sectoral water withdrawal dataset for the period 1971-2010, which distinguishes six water use sectors, i.e., irrigation, domestic, electricity generation (cooling of thermal power plants), livestock, mining, and manufacturing. Based on the reconstructed dataset, the spatial and temporal patterns of historical water withdrawal are analyzed. Results show that total global water withdrawal has increased significantly during 1971-2010, mainly driven by the increase in irrigation water withdrawal. Regions with high water withdrawal are those densely populated or with large irrigated cropland production, e.g., the United States (US), eastern China, India, and Europe. Seasonally, irrigation water withdrawal in summer for the major crops contributes a large percentage of total annual irrigation water withdrawal in mid- and high-latitude regions, and the dominant season of irrigation water withdrawal is also different across regions. Domestic water withdrawal is mostly characterized by a summer peak, while water withdrawal for electricity generation has a winter peak in high-latitude regions and a summer peak in low-latitude regions. Despite the overall increasing trend, irrigation in the western US and domestic water withdrawal in western Europe exhibit a decreasing trend. Our results highlight the distinct spatial pattern of human water use by sectors at the seasonal and annual timescales. The reconstructed gridded water withdrawal dataset is open access, and can be used for examining issues related to water withdrawals at fine spatial, temporal, and sectoral scales.

The Atacama Large Millimeter/submillimeter Array (alma): Early Results

NASA Astrophysics Data System (ADS)

Wootten, Alwyn

2012-06-01

New radioastronomical instruments, such as ALMA or the Jansky VLA, have increased spectral throughput by orders of magnitude over previously available capabilities. ALMA brings orders of magnitude increases in spectral sensitivity and spatial resolution over what has previously been available. These increased capabilities open new possibilities for studies of complex molecules in the interstellar medium. Complex interstellar molecules may form on the surfaces of interstellar grains, after which they may be liberated into the gas phase by shocks, radiation, or other external influences. Emission from complex molecules may be diluted owing to the large number of transitions large molecules may undergo, particularly in warm regions of interstellar clouds. High sensitivity and spatial resolution are necessary to explore the distributions and relationships of these molecules. Of particular interest are the distributions of large organic molecules. Observations which establish the relationships between various large molecules are now emerging from these new instruments and will be discussed.

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data.

PubMed

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H

2012-11-06

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the "big data" challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce.

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data

PubMed Central

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H.

2013-01-01

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the “big data” challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce. PMID:24501719

Marine Planning Benefits the Environment

EPA Science Inventory

Coastal and Marine Spatial Planning (CMSP) and Ecosystem-Based Management (EBM) are management approaches that allow sustainable coastal and ocean planning. The basic unit of management under CMSP is a large region, with the United States coastlines and Great Lakes divided into ...

Regional and Temporal Variation in Methamphetamine-Related Incidents: Applications of Spatial and Temporal Scan Statistics

PubMed Central

Sudakin, Daniel L.

2009-01-01

Introduction This investigation utilized spatial scan statistics, geographic information systems and multiple data sources to assess spatial clustering of statewide methamphetamine-related incidents. Temporal and spatial associations with regulatory interventions to reduce access to precursor chemicals (pseudoephedrine) were also explored. Methods Four statewide data sources were utilized including regional poison control center statistics, fatality incidents, methamphetamine laboratory seizures, and hazardous substance releases involving methamphetamine laboratories. Spatial clustering of methamphetamine incidents was assessed using SaTScan™. SaTScan™ was also utilized to assess space-time clustering of methamphetamine laboratory incidents, in relation to the enactment of regulations to reduce access to pseudoephedrine. Results Five counties with a significantly higher relative risk of methamphetamine-related incidents were identified. The county identified as the most likely cluster had a significantly elevated relative risk of methamphetamine laboratories (RR=11.5), hazardous substance releases (RR=8.3), and fatalities relating to methamphetamine (RR=1.4). A significant increase in relative risk of methamphetamine laboratory incidents was apparent in this same geographic area (RR=20.7) during the time period when regulations were enacted in 2004 and 2005, restricting access to pseudoephedrine. Subsequent to the enactment of these regulations, a significantly lower rate of incidents (RR 0.111, p=0.0001) was observed over a large geographic area of the state, including regions that previously had significantly higher rates. Conclusions Spatial and temporal scan statistics can be effectively applied to multiple data sources to assess regional variation in methamphetamine-related incidents, and explore the impact of preventive regulatory interventions. PMID:19225949

Analysis of biophysical and anthropogenic variables and their relation to the regional spatial variation of aboveground biomass illustrated for North and East Kalimantan, Borneo.

PubMed

Van der Laan, Carina; Verweij, Pita A; Quiñones, Marcela J; Faaij, André Pc

2014-12-01

Land use and land cover change occurring in tropical forest landscapes contributes substantially to carbon emissions. Better insights into the spatial variation of aboveground biomass is therefore needed. By means of multiple statistical tests, including geographically weighted regression, we analysed the effects of eight variables on the regional spatial variation of aboveground biomass. North and East Kalimantan were selected as the case study region; the third largest carbon emitting Indonesian provinces. Strong positive relationships were found between aboveground biomass and the tested variables; altitude, slope, land allocation zoning, soil type, and distance to the nearest fire, road, river and city. Furthermore, the results suggest that the regional spatial variation of aboveground biomass can be largely attributed to altitude, distance to nearest fire and land allocation zoning. Our study showed that in this landscape, aboveground biomass could not be explained by one single variable; the variables were interrelated, with altitude as the dominant variable. Spatial analyses should therefore integrate a variety of biophysical and anthropogenic variables to provide a better understanding of spatial variation in aboveground biomass. Efforts to minimise carbon emissions should incorporate the identified factors, by 1) the maintenance of lands with high AGB or carbon stocks, namely in the identified zones at the higher altitudes; and 2) regeneration or sustainable utilisation of lands with low AGB or carbon stocks, dependent on the regeneration capacity of the vegetation. Low aboveground biomass densities can be found in the lowlands in burned areas, and in non-forest zones and production forests.

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.

Stable isotope ratios of tap water in the contiguous United States

NASA Astrophysics Data System (ADS)

Bowen, Gabriel J.; Ehleringer, James R.; Chesson, Lesley A.; Stange, Erik; Cerling, Thure E.

2007-03-01

Understanding links between water consumers and climatological (precipitation) sources is essential for developing strategies to ensure the long-term sustainability of water supplies. In pursing this understanding a need exists for tools to study and monitor complex human-hydrological systems that involve high levels of spatial connectivity and supply problems that are regional, rather than local, in nature. Here we report the first national-level survey of stable isotope ratios in tap water, including spatially and temporally explicit samples from a large number of cities and towns across the contiguous United States. We show that intra-annual ranges of tap water isotope ratios are relatively small (e.g., <10‰ for δ2H) at most sites. In contrast, spatial variation in tap water isotope ratios is very large, spanning ranges of 163‰ for δ2H and 23.6‰ for δ18O. The spatial distribution of tap water isotope ratios at the national level is similar to that of stable isotope ratios of precipitation. At the regional level, however, pervasive differences between tap water and precipitation isotope ratios can be attributed to hydrological factors in the water source to consumer chain. These patterns highlight the potential for monitoring of tap water isotope ratios to contribute to the study of regional water supply stability and provide warning signals for impending water resource changes. We present the first published maps of predicted tap water isotope ratios for the contiguous United States, which will be useful in guiding future research on human-hydrological systems and as a tool for applied forensics and traceability studies.

The cloud imaging and particle size experiment on the aeronomy of ice in the mesosphere mission: Cloud morphology for the northern 2007 season

NASA Astrophysics Data System (ADS)

Rusch, D. W.; Thomas, G. E.; McClintock, W.; Merkel, A. W.; Bailey, S. M.; Russell, J. M., III; Randall, C. E.; Jeppesen, C.; Callan, M.

2009-03-01

The Aeronomy of Ice in the Mesosphere (AIM) mission was launched from Vandenberg Air Force Base in California at 4:26:03 EDT on April 25, 2007, becoming the first satellite mission dedicated to the study of noctilucent clouds (NLCs), also known as polar mesospheric clouds (PMC) when viewed from space. We present the first results from one of the three instruments on board the satellite, the Cloud Imaging and Particle Size (CIPS) instrument. CIPS has produced detailed morphology of the Northern 2007 PMC and Southern 2007/2008 seasons with 5 km horizontal spatial resolution. CIPS, with its very large angular field of view, images cloud structures at multiple scattering angles within a narrow spectral bandpass centered at 265 nm. Spatial coverage is 100% above about 70° latitude, where camera views overlap from orbit to orbit, and terminates at about 82°. Spatial coverage decreases to about 50% at the lowest latitudes where data are collected (35°). Cloud structures have for the first time been mapped out over nearly the entire summertime polar region. These structures include [`]ice rings', spatially small but bright clouds, and large regions ([`]ice-free regions') in the heart of the cloud season essentially devoid of ice particles. The ice rings bear a close resemblance to tropospheric convective outflow events, suggesting a point source of mesospheric convection. These rings (often circular arcs) are most likely Type IV NLC ([`]whirls' in the standard World Meteorological Organization (WMO) nomenclature).

Slow Spatial Recruitment of Neocortex during Secondarily Generalized Seizures and Its Relation to Surgical Outcome

PubMed Central

Martinet, Louis-Emmanuel; Ahmed, Omar J.; Lepage, Kyle Q.; Cash, Sydney S.

2015-01-01

Understanding the spatiotemporal dynamics of brain activity is crucial for inferring the underlying synaptic and nonsynaptic mechanisms of brain dysfunction. Focal seizures with secondary generalization are traditionally considered to begin in a limited spatial region and spread to connected areas, which can include both pathological and normal brain tissue. The mechanisms underlying this spread are important to our understanding of seizures and to improve therapies for surgical intervention. Here we study the properties of seizure recruitment—how electrical brain activity transitions to large voltage fluctuations characteristic of spike-and-wave seizures. We do so using invasive subdural electrode arrays from a population of 16 patients with pharmacoresistant epilepsy. We find an average delay of ∼30 s for a broad area of cortex (8 × 8 cm) to be recruited into the seizure, at an estimated speed of ∼4 mm/s. The spatiotemporal characteristics of recruitment reveal two categories of patients: one in which seizure recruitment of neighboring cortical regions follows a spatially organized pattern consistent from seizure to seizure, and a second group without consistent spatial organization of activity during recruitment. The consistent, organized recruitment correlates with a more regular, compared with small-world, connectivity pattern in simulation and successful surgical treatment of epilepsy. We propose that an improved understanding of how the seizure recruits brain regions into large amplitude voltage fluctuations provides novel information to improve surgical treatment of epilepsy and highlights the slow spread of massive local activity across a vast extent of cortex during seizure. PMID:26109670

Continued warming could transform Greater Yellowstone fire regimes by mid-21st century

Treesearch

Anthony L. Westerling; Monica G. Turner; Erica A. H. Smithwick; William H. Romme; Michael G. Ryan

2011-01-01

Climate change is likely to alter wildfire regimes, but the magnitude and timing of potential climate-driven changes in regional fire regimes are not well understood. We considered how the occurrence, size, and spatial location of large fires might respond to climate projections in the Greater Yellowstone ecosystem (GYE) (Wyoming), a large wildland ecosystem dominated...

Development of a spatially universal framework for classifying stream assemblages with application to conservation planning for Great Lakes lotic fish communities

USGS Publications Warehouse

McKenna, James E.; Schaeffer, Jeffrey S.; Stewart, Jana S.; Slattery, Michael T.

2015-01-01

Classifications are typically specific to particular issues or areas, leading to patchworks of subjectively defined spatial units. Stream conservation is hindered by the lack of a universal habitat classification system and would benefit from an independent hydrology-guided spatial framework of units encompassing all aquatic habitats at multiple spatial scales within large regions. We present a system that explicitly separates the spatial framework from any particular classification developed from the framework. The framework was constructed from landscape variables that are hydrologically and biologically relevant, covered all space within the study area, and was nested hierarchically and spatially related at scales ranging from the stream reach to the entire region; classifications may be developed from any subset of the 9 basins, 107 watersheds, 459 subwatersheds, or 10,000s of valley segments or stream reaches. To illustrate the advantages of this approach, we developed a fish-guided classification generated from a framework for the Great Lakes region that produced a mosaic of habitat units which, when aggregated, formed larger patches of more general conditions at progressively broader spatial scales. We identified greater than 1,200 distinct fish habitat types at the valley segment scale, most of which were rare. Comparisons of biodiversity and species assemblages are easily examined at any scale. This system can identify and quantify habitat types, evaluate habitat quality for conservation and/or restoration, and assist managers and policymakers with prioritization of protection and restoration efforts. Similar spatial frameworks and habitat classifications can be developed for any organism in any riverine ecosystem.

Interannual Variability of OLR as Observed by AIRS and CERES

NASA Technical Reports Server (NTRS)

Susskind, Joel; Molnar, Gyula; Iredell, Lena; Loeb, Norman G.

2012-01-01

This paper compares spatial anomaly time series of OLR (Outgoing Longwave Radiation) and OLR(sub CLR) (Clear Sky OLR) as determined using observations from CERES Terra and AIRS over the time period September 2002 through June 2011. Both AIRS and CERES show a significant decrease in global mean and tropical mean OLR over this time period. We find excellent agreement of the anomaly time-series of the two OLR data sets in almost every detail, down to 1 deg X 1 deg spatial grid point level. The extremely close agreement of OLR anomaly time series derived from observations by two different instruments implies that both sets of results must be highly stable. This agreement also validates to some extent the anomaly time series of the AIRS derived products used in the computation of the AIRS OLR product. The paper also examines the correlations of anomaly time series of AIRS and CERES OLR, on different spatial scales, as well as those of other AIRS derived products, with that of the NOAA Sea Surface Temperature (SST) product averaged over the NOAA Nino-4 spatial region. We refer to these SST anomalies as the El Nino Index. Large spatially coherent positive and negative correlations of OLR anomaly time series with that of the El Nino Index are found in different spatial regions. Anomalies of global mean, and especially tropical mean, OLR are highly positively correlated with the El Nino Index. These correlations explain that the recent global and tropical mean decreases in OLR over the period September 2002 through June 2011, as observed by both AIRS and CERES, are primarily the result of a transition from an El Nino condition at the beginning of the data record to La Nina conditions toward the end of the data period. We show that the close correlation of global mean, and especially tropical mean, OLR anomalies with the El Nino Index can be well accounted for by temporal changes of OLR within two spatial regions which lie outside the NOAA Nino-4 region, in which anomalies of cloud cover and mid-tropospheric water vapor are both highly negatively correlated with the El Nino Index. Agreement of the AIRS and CERES OLR(sub CLR) anomaly time series is less good, which may be a result of the large sampling differences in the ensemble of cases included in each OLR(sub CLR) data set.

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.

Spatial scaling of net primary productivity using subpixel landcover information

NASA Astrophysics Data System (ADS)

Chen, X. F.; Chen, Jing M.; Ju, Wei M.; Ren, L. L.

2008-10-01

Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. These biases result from overlooking subpixel variability of land surface characteristics. Vegetation heterogeneity is an important factor introducing biases in regional ecological modeling, especially when the modeling is made on large grids. This study suggests a simple algorithm that uses subpixel information on the spatial variability of land cover type to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. The algorithm operates in such a way that NPP obtained from calculations made at coarse spatial resolutions are multiplied by simple functions that attempt to reproduce the effects of subpixel variability of land cover type on NPP. Its application to a carbon-hydrology coupled model(BEPS-TerrainLab model) estimates made at a 1-km resolution over a watershed (named Baohe River Basin) located in the southwestern part of Qinling Mountains, Shaanxi Province, China, improved estimates of average NPP as well as its spatial variability.

Spatial patterns of fish standing biomass across Brazilian reefs.

PubMed

Morais, R A; Ferreira, C E L; Floeter, S R

2017-12-01

A large fish-count dataset from the Brazilian province was used to describe spatial patterns in standing biomass and test if total biomass, taxonomic and functional trophic structure vary across nested spatial scales. Taxonomic and functional structure varied more among localities and sites than among regions. Total biomass was generally higher at oceanic islands and remote or protected localities along the coast. Lower level carnivores comprised a large part of the biomass at almost all localities (mean of 44%), zooplanktivores never attained more than 14% and omnivores were more representative of subtropical reefs and oceanic islands (up to 66% of total biomass). Small and large herbivores and detritivores varied greatly in their contribution to total biomass, with no clear geographical patterns. Macrocarnivores comprised less than 12% of the biomass anywhere, except for two remote localities. Top predators, such as sharks and very large groupers, were rare and restricted to a few reefs, suggesting that their ecological function might have already been lost in many Brazilian reefs. © 2017 The Fisheries Society of the British Isles.

Distinct representations for shifts of spatial attention and changes of reward contingencies in the human brain

PubMed Central

Tosoni, Annalisa; Shulman, Gordon L.; Pope, Anna L. W.; McAvoy, Mark P.; Corbetta, Maurizio

2012-01-01

Success in a dynamically changing world requires both rapid shifts of attention to the location of important objects and the detection of changes in motivational contingencies that may alter future behavior. Here we addressed the relationship between these two processes by measuring the blood-oxygenation-level-dependent (BOLD) signal during a visual search task in which the location and the color of a salient cue respectively indicated where a rewarded target would appear and the monetary gain (large or small) associated with its detection. While cues that either shifted or maintained attention were presented every 4 to 8 seconds, the reward magnitude indicated by the cue changed roughly every 30 seconds, allowing us to distinguish a change in expected reward magnitude from a maintained state of expected reward magnitude. Posterior cingulate cortex was modulated by cues signaling an increase in expected reward magnitude, but not by cues for shifting versus maintaining spatial attention. Dorsal fronto-parietal regions in precuneus and FEF also showed increased BOLD activity for changes in expected reward magnitude from low to high, but in addition showed large independent modulations for shifting versus maintaining attention. In particular, the differential activation for shifting versus maintaining attention was not affected by expected reward magnitude. These results indicate that BOLD activations for shifts of attention and increases in expected reward magnitude are largely separate. Finally, visual cortex showed sustained spatially selective signals that were significantly enhanced when greater reward magnitude was expected, but this reward-related modulation was not observed in spatially selective regions of dorsal fronto-parietal cortex. PMID:22578709

North Atlantic Tropical Cyclone Precipitation and Climate Interactions Using a High-Resolution Dataset for the Eastern United States, 1948-2015.

NASA Astrophysics Data System (ADS)

Bregy, J. C.; Maxwell, J. T.; Robeson, S. M.

2017-12-01

Tropical cyclone (TC) impacts are typically concentrated along the coast, yet some TC hazards have wider spatial distributions and affect inland regions. For example, large volumes of TC precipitation (TCP) can cause severe inland flooding, initiate slope failure, and create large sinkholes. Previous studies show that TCP contributes substantially to seasonal precipitation budgets in the eastern United States. However, present knowledge of TCP climatology in the US is limited by the spatial coverage of weather stations. Here we develop a new high resolution (0.25°x0.25°) TCP climatology using HURDAT2 and CPC US Unified Precipitation data (1948-2015). From June to November (JJASON), maximum total TCP for the study period ranges from 2200 to 3800 mm along much of the coast and decreases inland. Likewise, spatial patterns of TCP contribution to total JJASON precipitation largely mirror those of total TCP, with maxima (6-8%) located in coastal Texas and North Carolina. Similar spatial patterns are seen in the mean JJASON TCP and mean TCP contribution over the study period, with maxima extending beyond coastal Texas and North Carolina. JJASON TCP (total, mean, and contribution) was correlated with mean annual JJASON values for the Bermuda High Index (BHI), El Niño-Southern Oscillation combined Niño3.4/Southern Oscillation Index (ENSO-BEST), and North Atlantic Oscillation (NAO). Correlations between climate indices and JJASON TCP show the degree to which BHI, ENSO-BEST, and NAO influence spatiotemporal changes in TCP. Of the three indices, the BHI had the strongest and most spatially consistent correlation with TCP, with significant correlations in the interior of the southeast. These results indicate a strong regional relationship between the North Atlantic Subtropical High (NASH; represented by the BHI) and regional TCP distribution. TCP distribution depends on TC track direction, and is therefore connected to the NASH, which acts as a steering mechanism for TCs. Our derived high resolution TCP climatology further aids our understanding of TC-climate interactions. Moreover, it can be used to understand hazards associated with TCs, serving as an invaluable tool in hazard mitigation efforts.

Biodiversity and ecosystem stability across scales in metacommunities.

PubMed

Wang, Shaopeng; Loreau, Michel

2016-05-01

Although diversity-stability relationships have been extensively studied in local ecosystems, the global biodiversity crisis calls for an improved understanding of these relationships in a spatial context. Here, we use a dynamical model of competitive metacommunities to study the relationships between species diversity and ecosystem variability across scales. We derive analytic relationships under a limiting case; these results are extended to more general cases with numerical simulations. Our model shows that, while alpha diversity decreases local ecosystem variability, beta diversity generally contributes to increasing spatial asynchrony among local ecosystems. Consequently, both alpha and beta diversity provide stabilising effects for regional ecosystems, through local and spatial insurance effects respectively. We further show that at the regional scale, the stabilising effect of biodiversity increases as spatial environmental correlation increases. Our findings have important implications for understanding the interactive effects of global environmental changes (e.g. environmental homogenisation) and biodiversity loss on ecosystem sustainability at large scales. © 2016 John Wiley & Sons Ltd/CNRS.

Land use and carbon dynamics in the southeastern United States from 1992 to 2050

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Sohl, Terry L.; Young, Claudia; Werner, Jeremy M.

2013-01-01

Land use and land cover change (LUCC) plays an important role in determining the spatial distribution, magnitude, and temporal change of terrestrial carbon sources and sinks. However, the impacts of LUCC are not well understood and quantified over large areas. The goal of this study was to quantify the spatial and temporal patterns of carbon dynamics in various terrestrial ecosystems in the southeastern United States from 1992 to 2050 using a process-based modeling system and then to investigate the impacts of LUCC. Spatial LUCC information was reconstructed and projected using the FOREcasting SCEnarios of future land cover (FORE-SCE) model according to information derived from Landsat observations and other sources. Results indicated that urban expansion (from 3.7% in 1992 to 9.2% in 2050) was expected to be the primary driver for other land cover changes in the region, leading to various declines in forest, cropland, and hay/pasture. The region was projected to be a carbon sink of 60.4 gC m−2 yr−1 on average during the study period, primarily due to the legacy impacts of large-scale conversion of cropland to forest that happened since the 1950s. Nevertheless, the regional carbon sequestration rate was expected to decline because of the slowing down of carbon accumulation in aging forests and the decline of forest area.

A spatial data handling system for retrieval of images by unrestricted regions of user interest

NASA Technical Reports Server (NTRS)

Dorfman, Erik; Cromp, Robert F.

1992-01-01

The Intelligent Data Management (IDM) project at NASA/Goddard Space Flight Center has prototyped an Intelligent Information Fusion System (IIFS), which automatically ingests metadata from remote sensor observations into a large catalog which is directly queryable by end-users. The greatest challenge in the implementation of this catalog was supporting spatially-driven searches, where the user has a possible complex region of interest and wishes to recover those images that overlap all or simply a part of that region. A spatial data management system is described, which is capable of storing and retrieving records of image data regardless of their source. This system was designed and implemented as part of the IIFS catalog. A new data structure, called a hypercylinder, is central to the design. The hypercylinder is specifically tailored for data distributed over the surface of a sphere, such as satellite observations of the Earth or space. Operations on the hypercylinder are regulated by two expert systems. The first governs the ingest of new metadata records, and maintains the efficiency of the data structure as it grows. The second translates, plans, and executes users' spatial queries, performing incremental optimization as partial query results are returned.

Guidance of spatial attention by incidental learning and endogenous cuing

PubMed Central

Jiang, Yuhong V.; Swallow, Khena M.; Rosenbaum, Gail M.

2012-01-01

Our visual system is highly sensitive to regularities in the environment. Locations that were important in one’s previous experience are often prioritized during search, even though observers may not be aware of the learning. In this study we characterized the guidance of spatial attention by incidental learning of a target’s spatial probability, and examined the interaction between endogenous cuing and probability cuing. Participants searched for a target (T) among distractors (L’s). The target was more often located in one region of the screen than in others. We found that search RT was faster when the target appeared in the high-frequency region rather than the low-frequency regions. This difference increased when there were more items on the display, suggesting that probability cuing guides spatial attention. Additional data indicated that on their own, probability cuing and endogenous cuing (e.g., a central arrow that predicted a target’s location) were similarly effective at guiding attention. However, when both cues were presented at once, probability cuing was largely eliminated. Thus, although both incidental learning and endogenous cuing can effectively guide attention, endogenous cuing takes precedence over incidental learning. PMID:22506784

Spatially and seasonally asymmetric responses of Amazon forests to El Niño

NASA Astrophysics Data System (ADS)

Mao, J.; Yan, B.; Dickinson, R. E.; Shi, X.; Ricciuto, D. M.; Norby, R. J.; Dai, Y.; Zhang, X.; McDowell, N.; Wu, J.

2017-12-01

El Niño Southern Oscillation (ENSO) events impose strong inter-annual signals on local climate changes and terrestrial ecosystem dynamics in many regions on the Earth especially tropical forests in the Amazon basin. However, much is still unknown regarding the vulnerability of tropical forests to ENSO effects, especially in a spatially-explicit context. Here, using satellite and ground observations with reanalysis data of climate variables, we analyzed the spatial and temporal patterns of plant growth in response to the warm phase of ENSO (i.e., El Niño), which resulted in precipitation anomaly (or drought) over a large area across the Amazon. We found that the influence of El Niño events on vegetation growth varied spatially and seasonally. During each season (dry or wet), the forests were divided into two sub-regions that were either controlled by precipitation or radiation. The boundaries between the two sub-regions were determined, which were distributed from northwest to southeast in the dry season and from northeast to southwest in the wet season. This result improves our understanding of the water and energy availability co-modulating the vegetation growth in Amazonia and the magnitude and direction of Amazon forests responding to drought.

Evidence for hubs in human functional brain networks

PubMed Central

Power, Jonathan D; Schlaggar, Bradley L; Lessov-Schlaggar, Christina N; Petersen, Steven E

2013-01-01

Summary Hubs integrate and distribute information in powerful ways due to the number and positioning of their contacts in a network. Several resting state functional connectivity MRI reports have implicated regions of the default mode system as brain hubs; we demonstrate that previous degree-based approaches to hub identification may have identified portions of large brain systems rather than critical nodes of brain networks. We utilize two methods to identify hub-like brain regions: 1) finding network nodes that participate in multiple sub-networks of the brain, and 2) finding spatial locations where several systems are represented within a small volume. These methods converge on a distributed set of regions that differ from previous reports on hubs. This work identifies regions that support multiple systems, leading to spatially constrained predictions about brain function that may be tested in terms of lesions, evoked responses, and dynamic patterns of activity. PMID:23972601

Adapting populations in space: clonal interference and genetic diversity

NASA Astrophysics Data System (ADS)

Weissman, Daniel; Barton, Nick

Most species inhabit ranges much larger than the scales over which individuals interact. How does this spatial structure interact with adaptive evolution? We consider a simple model of a spatially-extended, adapting population and show that, while clonal interference severely limits the adaptation of purely asexual populations, even rare recombination is enough to allow adaptation at rates approaching those of well-mixed populations. We also find that the genetic hitchhiking produced by the adaptive alleles sweeping through the population has strange effects on the patterns of genetic diversity. In large spatial ranges, even low rates of adaptation cause all individuals in the population to rapidly trace their ancestry back to individuals living in a small region in the center of the range. The probability of fixation of an allele is thus strongly dependent on the allele's spatial location, with alleles from the center favored. Surprisingly, these effects are seen genome-wide (instead of being localized to the regions of the genome undergoing the sweeps). The spatial concentration of ancestry produces a power-law dependence of relatedness on distance, so that even individuals sampled far apart are likely to be fairly closely related, masking the underlying spatial structure.

EEG Source Reconstruction Reveals Frontal-Parietal Dynamics of Spatial Conflict Processing

PubMed Central

Cohen, Michael X; Ridderinkhof, K. Richard

2013-01-01

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30–50 Hz), followed by a later alpha-band (8–12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4–8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions. PMID:23451201

Exploring the spatially varying innovation capacity of the US counties in the framework of Griliches' knowledge production function: a mixed GWR approach

NASA Astrophysics Data System (ADS)

Kang, Dongwoo; Dall'erba, Sandy

2016-04-01

Griliches' knowledge production function has been increasingly adopted at the regional level where location-specific conditions drive the spatial differences in knowledge creation dynamics. However, the large majority of such studies rely on a traditional regression approach that assumes spatially homogenous marginal effects of knowledge input factors. This paper extends the authors' previous work (Kang and Dall'erba in Int Reg Sci Rev, 2015. doi: 10.1177/0160017615572888) to investigate the spatial heterogeneity in the marginal effects by using nonparametric local modeling approaches such as geographically weighted regression (GWR) and mixed GWR with two distinct samples of the US Metropolitan Statistical Area (MSA) and non-MSA counties. The results indicate a high degree of spatial heterogeneity in the marginal effects of the knowledge input variables, more specifically for the local and distant spillovers of private knowledge measured across MSA counties. On the other hand, local academic knowledge spillovers are found to display spatially homogenous elasticities in both MSA and non-MSA counties. Our results highlight the strengths and weaknesses of each county's innovation capacity and suggest policy implications for regional innovation strategies.

Regional reanalysis without local data: Exploiting the downscaling paradigm

NASA Astrophysics Data System (ADS)

von Storch, Hans; Feser, Frauke; Geyer, Beate; Klehmet, Katharina; Li, Delei; Rockel, Burkhardt; Schubert-Frisius, Martina; Tim, Nele; Zorita, Eduardo

2017-08-01

This paper demonstrates two important aspects of regional dynamical downscaling of multidecadal atmospheric reanalysis. First, that in this way skillful regional descriptions of multidecadal climate variability may be constructed in regions with little or no local data. Second, that the concept of large-scale constraining allows global downscaling, so that global reanalyses may be completed by additions of consistent detail in all regions of the world. Global reanalyses suffer from inhomogeneities. However, their large-scale componenst are mostly homogeneous; Therefore, the concept of downscaling may be applied to homogeneously complement the large-scale state of the reanalyses with regional detail—wherever the condition of homogeneity of the description of large scales is fulfilled. Technically, this can be done by dynamical downscaling using a regional or global climate model, which's large scales are constrained by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional weather risks—in particular marine risks—was identified. We have run this system in regions with reduced or absent local data coverage, such as Central Siberia, the Bohai and Yellow Sea, Southwestern Africa, and the South Atlantic. Also, a global simulation was computed, which adds regional features to prescribed global dynamics. Our cases demonstrate that spatially detailed reconstructions of the climate state and its change in the recent three to six decades add useful supplementary information to existing observational data for midlatitude and subtropical regions of the world.

Mapping the distribution of the denitrifier community at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Bru, D.; Ramette, A.; 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 740 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.

Lung cancer mortality clusters in Shandong Province, China: how do they change over 40 years?

PubMed Central

Fu, Zhentao; Li, Yingmei; Lu, Zilong; Chu, Jie; Sun, Jiandong; Zhang, Jiyu; Zhang, Gaohui; Xue, Fuzhong; Guo, Xiaolei; Xu, Aiqiang

2017-01-01

Lung cancer has long been a major health problem in China. This study aimed to examine the temporal trend and spatial pattern of lung cancer mortality in Shandong Province from 1970 to 2013. Lung cancer mortality data were obtained from Shandong Death Registration System and three nationwide retrospective cause-of-death surveys. A Purely Spatial Scan Statistics method with Discrete Poisson models was used to detect possible high-risk spatial clusters. The results show that lung cancer mortality rate in Shandong Province increased markedly from 1970-1974 (7.22 per 100,000 person-years) to 2011-2013 (56.37/100, 000). This increase was associated with both demographic and non-demographic factors. Several significant spatial clusters with high lung cancer mortality were identified. The most likely cluster was located in the northern region of Shandong Province during both 1970-1974 and 2011-2013. It appears the spatial pattern remained largely consistent over the last 40 years despite the absolute increase in the mortality rates. These findings will help develop intervention strategies to reduce lung cancer mortality in this large Chinese population. PMID:29179474

The consequences of landscape change on ecological resources: An assessment of the United States Mid-Atlantic region, 1973-1993

Treesearch

K. Bruce Jones; Anne C. Neale; Timothy G. Wade; James D. Wickham; Chad L. Cross; Curtis M. Edmonds; Thomas R. Loveland; Maliha S. Nash; Kurt H. Riitters; Elizabeth R. Smith

2001-01-01

Spatially explicit identification of changes in ecological conditions over large areas is key to targeting and prioitizing areas for environmental protection and restoration by managers at watershed, basin, and regional scales. A critical limitation to this point has been the development of methods to conduct such broad-scale assessments. Field-based methods have...

Atomic-level spatial distributions of dopants on silicon surfaces: toward a microscopic understanding of surface chemical reactivity

NASA Astrophysics Data System (ADS)

Hamers, Robert J.; Wang, Yajun; Shan, Jun

1996-11-01

We have investigated the interaction of phosphine (PH 3) and diborane (B 2H 6) with the Si(001) surface using scanning tunneling microscopy, infrared spectroscopy, and ab initio molecular orbital calculations. Experiment and theory show that the formation of PSi heterodimers is energetically favorable compared with formation of PP dimers. The stability of the heterodimers arises from a large strain energy associated with formation of PP dimers. At moderate P coverages, the formation of PSi heterodimers leaves the surface with few locations where there are two adjacent reactive sites. This in turn modifies the chemical reactivity toward species such as PH 3, which require only one site to adsorb but require two adjacent sites to dissociate. Boron on Si(001) strongly segregates into localized regions of high boron concentration, separated by large regions of clean Si. This leads to a spatially-modulated chemical reactivity which during subsequent growth by chemical vapor deposition (CVD) leads to formation of a rough surface. The implications of the atomic-level spatial distribution of dopants on the rates and mechanisms of CVD growth processes are discussed.

Small-Area Estimation of Spatial Access to Care and Its Implications for Policy.

PubMed

Gentili, Monica; Isett, Kim; Serban, Nicoleta; Swann, Julie

2015-10-01

Local or small-area estimates to capture emerging trends across large geographic regions are critical in identifying and addressing community-level health interventions. However, they are often unavailable due to lack of analytic capabilities in compiling and integrating extensive datasets and complementing them with the knowledge about variations in state-level health policies. This study introduces a modeling approach for small-area estimation of spatial access to pediatric primary care that is data "rich" and mathematically rigorous, integrating data and health policy in a systematic way. We illustrate the sensitivity of the model to policy decision making across large geographic regions by performing a systematic comparison of the estimates at the census tract and county levels for Georgia and California. Our results show the proposed approach is able to overcome limitations of other existing models by capturing patient and provider preferences and by incorporating possible changes in health policies. The primary finding is systematic underestimation of spatial access, and inaccurate estimates of disparities across population and across geography at the county level with respect to those at the census tract level with implications on where to focus and which type of interventions to consider.

Demographic mechanisms underpinning genetic assimilation of remnant groups of a large carnivore

USGS Publications Warehouse

Mikle, Nathaniel; Graves, Tabitha A.; Kovach, Ryan P.; Kendall, Katherine C.; Macleod, Amy C.

2016-01-01

Current range expansions of large terrestrial carnivores are occurring following human-induced range contraction. Contractions are often incomplete, leaving small remnant groups in refugia throughout the former range. Little is known about the underlying ecological and evolutionary processes that influence how remnant groups are affected during range expansion. We used data from a spatially explicit, long-term genetic sampling effort of grizzly bears (Ursus arctos) in the Northern Continental Divide Ecosystem (NCDE), USA, to identify the demographic processes underlying spatial and temporal patterns of genetic diversity. We conducted parentage analysis to evaluate how reproductive success and dispersal contribute to spatio-temporal patterns of genetic diversity in remnant groups of grizzly bears existing in the southwestern (SW), southeastern (SE) and east-central (EC) regions of the NCDE. A few reproductively dominant individuals and local inbreeding caused low genetic diversity in peripheral regions that may have persisted for multiple generations before eroding rapidly (approx. one generation) during population expansion. Our results highlight that individual-level genetic and reproductive dynamics play critical roles during genetic assimilation, and show that spatial patterns of genetic diversity on the leading edge of an expansion may result from historical demographic patterns that are highly ephemeral.

Demographic mechanisms underpinning genetic assimilation of remnant groups of a large carnivore

PubMed Central

Kovach, Ryan; Kendall, Katherine C.; Macleod, Amy C.

2016-01-01

Current range expansions of large terrestrial carnivores are occurring following human-induced range contraction. Contractions are often incomplete, leaving small remnant groups in refugia throughout the former range. Little is known about the underlying ecological and evolutionary processes that influence how remnant groups are affected during range expansion. We used data from a spatially explicit, long-term genetic sampling effort of grizzly bears (Ursus arctos) in the Northern Continental Divide Ecosystem (NCDE), USA, to identify the demographic processes underlying spatial and temporal patterns of genetic diversity. We conducted parentage analysis to evaluate how reproductive success and dispersal contribute to spatio-temporal patterns of genetic diversity in remnant groups of grizzly bears existing in the southwestern (SW), southeastern (SE) and east-central (EC) regions of the NCDE. A few reproductively dominant individuals and local inbreeding caused low genetic diversity in peripheral regions that may have persisted for multiple generations before eroding rapidly (approx. one generation) during population expansion. Our results highlight that individual-level genetic and reproductive dynamics play critical roles during genetic assimilation, and show that spatial patterns of genetic diversity on the leading edge of an expansion may result from historical demographic patterns that are highly ephemeral. PMID:27655768

Characterizing spatiotemporal dynamics of methane emissions from rice paddies in Northeast China from 1990 to 2010.

PubMed

Zhang, Yuan; Su, Shiliang; Zhang, Feng; Shi, Runhe; Gao, Wei

2012-01-01

Rice paddies have been identified as major methane (CH(4)) source induced by human activities. As a major rice production region in Northern China, the rice paddies in the Three-Rivers Plain (TRP) have experienced large changes in spatial distribution over the recent 20 years (from 1990 to 2010). Consequently, accurate estimation and characterization of spatiotemporal patterns of CH₄ emissions from rice paddies has become an pressing issue for assessing the environmental impacts of agroecosystems, and further making GHG mitigation strategies at regional or global levels. Integrating remote sensing mapping with a process-based biogeochemistry model, Denitrification and Decomposition (DNDC), was utilized to quantify the regional CH(4) emissions from the entire rice paddies in study region. Based on site validation and sensitivity tests, geographic information system (GIS) databases with the spatially differentiated input information were constructed to drive DNDC upscaling for its regional simulations. Results showed that (1) The large change in total methane emission that occurred in 2000 and 2010 compared to 1990 is distributed to the explosive growth in amounts of rice planted; (2) the spatial variations in CH₄ fluxes in this study are mainly attributed to the most sensitive factor soil properties, i.e., soil clay fraction and soil organic carbon (SOC) content, and (3) the warming climate could enhance CH₄ emission in the cool paddies. The study concluded that the introduction of remote sensing analysis into the DNDC upscaling has a great capability in timely quantifying the methane emissions from cool paddies with fast land use and cover changes. And also, it confirmed that the northern wetland agroecosystems made great contributions to global greenhouse gas inventory.

Characterizing Spatiotemporal Dynamics of Methane Emissions from Rice Paddies in Northeast China from 1990 to 2010

PubMed Central

Zhang, Yuan; Su, Shiliang; Zhang, Feng; Shi, Runhe; Gao, Wei

2012-01-01

Background Rice paddies have been identified as major methane (CH4) source induced by human activities. As a major rice production region in Northern China, the rice paddies in the Three-Rivers Plain (TRP) have experienced large changes in spatial distribution over the recent 20 years (from 1990 to 2010). Consequently, accurate estimation and characterization of spatiotemporal patterns of CH4 emissions from rice paddies has become an pressing issue for assessing the environmental impacts of agroecosystems, and further making GHG mitigation strategies at regional or global levels. Methodology/Principal Findings Integrating remote sensing mapping with a process-based biogeochemistry model, Denitrification and Decomposition (DNDC), was utilized to quantify the regional CH4 emissions from the entire rice paddies in study region. Based on site validation and sensitivity tests, geographic information system (GIS) databases with the spatially differentiated input information were constructed to drive DNDC upscaling for its regional simulations. Results showed that (1) The large change in total methane emission that occurred in 2000 and 2010 compared to 1990 is distributed to the explosive growth in amounts of rice planted; (2) the spatial variations in CH4 fluxes in this study are mainly attributed to the most sensitive factor soil properties, i.e., soil clay fraction and soil organic carbon (SOC) content, and (3) the warming climate could enhance CH4 emission in the cool paddies. Conclusions/Significance The study concluded that the introduction of remote sensing analysis into the DNDC upscaling has a great capability in timely quantifying the methane emissions from cool paddies with fast land use and cover changes. And also, it confirmed that the northern wetland agroecosystems made great contributions to global greenhouse gas inventory. PMID:22235268

Spatial and temporal patterns of Amazon rainfall. Consequences for the planning of agricultural occupation and the protection of primary forests.

PubMed

Sombroek, W

2001-11-01

The spatial and temporal pattern of annual rainfall and the strength of the dry season within the Amazon region are poorly known. Existing rainfall maps are based on the data from full-scale, long-term meteorological stations, operated by national organizations linked to the World Meteorological Organisation, such as INMET in Brazil. Stations with 30 or more years of uninterrupted and reliable recordings are very few, considering the size of the region, and most of them are located along the major rivers. It has been suggested that rainfall conditions away from these rivers are substantially different. An analysis has been made of the records of a network of simple pluviometric sites in the Brazilian part of the region as maintained by the National Agency for Electric Energy (ANEEL) since 1970. The latter data sets were used to draw more detailed maps on annual rainfall, and on the strength of the dry season in particular; average number of consecutive months with less than 100 mm, 50 mm, and 10 mm, respectively. Also, some data were obtained on the spatial expression of El Niño events within the region. Subregional differences are large, and it is argued that they are important for the success or failure of agricultural settlements; for the hazard of large-scale fire damage of the still existing primary forest vegetation; for the functioning of this land cover as stock and sink of CO2, and for the likelihood that secondary forests on abandoned agricultural lands will have less biomass. The effects of past El Niño rainfall anomalies on the biodiversity of the natural savannahs within the forest region are discussed.

Spatially resolved spectroscopy analysis of the XMM-Newton large program on SN1006

NASA Astrophysics Data System (ADS)

Li, Jiang-Tao; Decourchelle, Anne; Miceli, Marco; Vink, Jacco; Bocchino, Fabrizio

2016-04-01

We perform analysis of the XMM-Newton large program on SN1006 based on our newly developed methods of spatially resolved spectroscopy analysis. We extract spectra from low and high resolution meshes. The former (3596 meshes) is used to roughly decompose the thermal and non-thermal components and characterize the spatial distributions of different parameters, such as temperature, abundances of different elements, ionization age, and electron density of the thermal component, as well as photon index and cutoff frequency of the non-thermal component. On the other hand, the low resolution meshes (583 meshes) focus on the interior region dominated by the thermal emission and have enough counts to well characterize the Si lines. We fit the spectra from the low resolution meshes with different models, in order to decompose the multiple plasma components at different thermal and ionization states and compare their spatial distributions. In this poster, we will present the initial results of this project.

Relations between nature-based solutions of green-blue area accessibility and socio-economic-ethnic patterns in the urban Stockholm region

NASA Astrophysics Data System (ADS)

Goldenberg, Romain; Kalantari, Zahra; Destouni, Georgia

2017-04-01

More than half of the world's population lives in cities, a proportion expected to increase to two thirds by 2050 (United Nations (UN), 2015). In this study, we investigate the spatial relationships that may exist between income and/or nationality homogeneity/heterogeneity levels of urban populations and their accessibility to local green-blue areas as possible nature-based solutions for sustainable urban design. For this investigation, we consider as a concrete case study the urban region of Stockholm, Sweden, for which we compile and use available land-cover and vegetation density data (the latter in terms of Normalised Difference Vegetation Index, NDVI) in order to identify and assess the spatial distributions of various green-blue area types and aspects. We further combine this data with spatial distribution data for population density, income and nationality, as well as with road-network data for assessing population travel times to nearby green-blue areas within the region. The present study results converge with those of other recent studies in showing large socio-economic-ethnic segregation in the Stockholm region. Moreover, the present data combination and analysis also show large spatial differences in and important socio-economic-ethnic correlations with accessibility to local green areas and nearby water bodies. Specifically, population income and share of Swedish nationals are well correlated in this region, with increases in both of these variables implying greater possibility to choose where to live within the region. The living choices of richer and more homogeneous (primarily Swedish) population parts are then found to be areas with greater local vegetation density (local green areas as identified by high-resolution NDVI data) and greater area extent of nearby water bodies (blue areas). For comparison, no such correlation is found between increased income or Swedish nationality homogeneity and accessibility to nearby forest areas (overall green area extent) or built facilities for recreation and sports. The found living choice correlations point at the importance of green-blue area parts as possible nature-based solutions in urban design and planning, with potential to improve wellbeing and social sustainability for the whole urban population and not just its rich component.

Classification of Large-Scale Remote Sensing Images for Automatic Identification of Health Hazards: Smoke Detection Using an Autologistic Regression Classifier.

PubMed

Wolters, Mark A; Dean, C B

2017-01-01

Remote sensing images from Earth-orbiting satellites are a potentially rich data source for monitoring and cataloguing atmospheric health hazards that cover large geographic regions. A method is proposed for classifying such images into hazard and nonhazard regions using the autologistic regression model, which may be viewed as a spatial extension of logistic regression. The method includes a novel and simple approach to parameter estimation that makes it well suited to handling the large and high-dimensional datasets arising from satellite-borne instruments. The methodology is demonstrated on both simulated images and a real application to the identification of forest fire smoke.

Climate and Edaphic Controls on Humid Tropical Forest Tree Height

NASA Astrophysics Data System (ADS)

Yang, Y.; Saatchi, S. S.; Xu, L.

2014-12-01

Uncertainty in the magnitude and spatial variations of forest carbon density in tropical regions is due to under sampling of forest structure from inventory plots and the lack of regional allometry to estimate the carbon density from structure. Here we quantify the variation of tropical forest structure by using more than 2.5 million measurements of canopy height from systematic sampling of Geoscience Laser Altimeter System (GLAS) satellite observations between 2004 to 2008 and examine the climate and edaphic variables influencing the variations. We used top canopy height of GLAS footprints (~ 0.25 ha) to grid the statistical mean and 90 percentile of samples at 0.5 degrees to capture the regional variability of large trees in tropics. GLAS heights were also aggregated based on a stratification of tropical regions using soil, elevation, and forest types. Both approaches provided consistent patterns of statistically dominant large trees and the least heterogeneity, both as strong drivers of distribution of high biomass forests. Statistical models accounting for spatial autocorrelation suggest that climate, soil and spatial features together can explain more than 60% of the variations in observed tree height information, while climate-only variables explains about one third of the first-order changes in tree height. Soil basics, including physical compositions such as clay and sand contents, chemical properties such as PH values and cation-exchange capacity, as well as biological variables such as organic matters, all present independent but statistically significant relationships to tree height variations. The results confirm other landscape and regional studies that soil fertility, geology and climate may jointly control a majority of the regional variations of forest structure in pan-tropics and influencing both biomass stocks and dynamics. Consequently, other factors such as biotic and disturbance regimes, not included in this study, may have less influence on regional variations but strongly mediate landscape and small-scale forest structure and dynamics.

Beyond precipitation: physiographic gradients dictate the relative importance of environmental drivers on Savanna vegetation.

PubMed

Campo-Bescós, Miguel A; Muñoz-Carpena, Rafael; Kaplan, David A; Southworth, Jane; Zhu, Likai; Waylen, Peter R

2013-01-01

Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving vegetation change in southern African savanna, and how they vary across physiographic gradients. We applied Dynamic Factor Analysis (DFA), a multivariate times series dimension reduction technique to ten years of monthly remote sensing data (MODIS-derived normalized difference vegetation index, NDVI) and a suite of environmental covariates: precipitation, mean and maximum temperature, soil moisture, relative humidity, fire and potential evapotranspiration. Monthly NDVI was described by cyclic seasonal variation with distinct spatiotemporal patterns in different physiographic regions. Results support existing work emphasizing the importance of precipitation, soil moisture and fire on NDVI, but also reveal overlooked effects of temperature and evapotranspiration, particularly in regions with higher mean annual precipitation. Critically, spatial distributions of the weights of environmental covariates point to a transition in the importance of precipitation and soil moisture (strongest in grass-dominated regions with precipitation<750 mm) to fire, potential evapotranspiration, and temperature (strongest in tree-dominated regions with precipitation>950 mm). We quantified the combined spatiotemporal effects of an available suite of environmental drivers on NDVI across a large and diverse savanna region. The analysis supports known drivers of savanna vegetation but also uncovers important roles of temperature and evapotranspiration. Results highlight the utility of applying the DFA approach to remote sensing products for regional analyses of landscape change in the context of global environmental change. With the dramatic increase in global change research, this methodology augurs well for further development and application of spatially explicit time series modeling to studies at the intersection of ecology and remote sensing.

Beyond Precipitation: Physiographic Gradients Dictate the Relative Importance of Environmental Drivers on Savanna Vegetation

PubMed Central

Campo-Bescós, Miguel A.; Muñoz-Carpena, Rafael; Kaplan, David A.; Southworth, Jane; Zhu, Likai; Waylen, Peter R.

2013-01-01

Background Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving vegetation change in southern African savanna, and how they vary across physiographic gradients. Methodology/Principal Findings We applied Dynamic Factor Analysis (DFA), a multivariate times series dimension reduction technique to ten years of monthly remote sensing data (MODIS-derived normalized difference vegetation index, NDVI) and a suite of environmental covariates: precipitation, mean and maximum temperature, soil moisture, relative humidity, fire and potential evapotranspiration. Monthly NDVI was described by cyclic seasonal variation with distinct spatiotemporal patterns in different physiographic regions. Results support existing work emphasizing the importance of precipitation, soil moisture and fire on NDVI, but also reveal overlooked effects of temperature and evapotranspiration, particularly in regions with higher mean annual precipitation. Critically, spatial distributions of the weights of environmental covariates point to a transition in the importance of precipitation and soil moisture (strongest in grass-dominated regions with precipitation<750 mm) to fire, potential evapotranspiration, and temperature (strongest in tree-dominated regions with precipitation>950 mm). Conclusions/Significance We quantified the combined spatiotemporal effects of an available suite of environmental drivers on NDVI across a large and diverse savanna region. The analysis supports known drivers of savanna vegetation but also uncovers important roles of temperature and evapotranspiration. Results highlight the utility of applying the DFA approach to remote sensing products for regional analyses of landscape change in the context of global environmental change. With the dramatic increase in global change research, this methodology augurs well for further development and application of spatially explicit time series modeling to studies at the intersection of ecology and remote sensing. PMID:24023616

Mapping mHealth (mobile health) and mobile penetrations in sub-Saharan Africa for strategic regional collaboration in mHealth scale-up: an application of exploratory spatial data analysis.

PubMed

Lee, Seohyun; Cho, Yoon-Min; Kim, Sun-Young

2017-08-22

Mobile health (mHealth), a term used for healthcare delivery via mobile devices, has gained attention as an innovative technology for better access to healthcare and support for performance of health workers in the global health context. Despite large expansion of mHealth across sub-Saharan Africa, regional collaboration for scale-up has not made progress since last decade. As a groundwork for strategic planning for regional collaboration, the study attempted to identify spatial patterns of mHealth implementation in sub-Saharan Africa using an exploratory spatial data analysis. In order to obtain comprehensive data on the total number of mHelath programs implemented between 2006 and 2016 in each of the 48 sub-Saharan Africa countries, we performed a systematic data collection from various sources, including: the WHO eHealth Database, the World Bank Projects & Operations Database, and the USAID mHealth Database. Additional spatial analysis was performed for mobile cellular subscriptions per 100 people to suggest strategic regional collaboration for improving mobile penetration rates along with the mHealth initiative. Global Moran's I and Local Indicator of Spatial Association (LISA) were calculated for mHealth programs and mobile subscriptions per 100 population to investigate spatial autocorrelation, which indicates the presence of local clustering and spatial disparities. From our systematic data collection, the total number of mHealth programs implemented in sub-Saharan Africa between 2006 and 2016 was 487 (same programs implemented in multiple countries were counted separately). Of these, the eastern region with 17 countries and the western region with 16 countries had 287 and 145 mHealth programs, respectively. Despite low levels of global autocorrelation, LISA enabled us to detect meaningful local clusters. Overall, the eastern part of sub-Saharan Africa shows high-high association for mHealth programs. As for mobile subscription rates per 100 population, the northern area shows extensive low-low association. This study aimed to shed some light on the potential for strategic regional collaboration for scale-up of mHealth and mobile penetration. Firstly, countries in the eastern area with much experience can take the lead role in pursuing regional collaboration for mHealth programs in sub-Saharan Africa. Secondly, collective effort in improving mobile penetration rates for the northern area is recommended.

Modeling very large-fire occurrences over the continental United States from weather and climate forcing

Treesearch

R Barbero; J T Abatzoglou; E A Steel

2014-01-01

Very large-fires (VLFs) have widespread impacts on ecosystems, air quality, fire suppression resources, and in many regions account for a majority of total area burned. Empirical generalized linear models of the largest fires (>5000 ha) across the contiguous United States (US) were developed at ¡­60 km spatial and weekly temporal resolutions using solely atmospheric...

Modeling Trends in Tropospheric Aerosol Burden & Its Radiative Effects

EPA Science Inventory

Large changes in emissions of aerosol precursors have occurred across the southeast U.S., North America, as well as the northern hemisphere. The spatial heterogeneity and contrasting trends in the aerosol burden is resulting in differing effects on regional radiative balance. Mul...

Frequency–specific network connectivity increases underlie accurate spatiotemporal memory retrieval

PubMed Central

Watrous, Andrew J.; Tandon, Nitin; Connor, Chris; Pieters, Thomas; Ekstrom, Arne D.

2013-01-01

The medial temporal lobes, prefrontal cortex, and parts of parietal cortex form the neural underpinnings of episodic memory, which includes remembering both where and when an event occurred. Yet how these three key regions interact during retrieval of spatial and temporal context remains largely untested. Here, we employed simultaneous electrocorticographical recordings across multiple lobular regions, employing phase synchronization as a measure of network functional connectivity, while patients retrieved spatial and temporal context associated with an episode. Successful memory retrieval was characterized by greater global connectivity compared to incorrect retrieval, with the MTL acting as a convergence hub for these interactions. Spatial vs. temporal context retrieval resulted in prominent differences in both the spectral and temporal patterns of network interactions. These results emphasize dynamic network interactions as central to episodic memory retrieval, providing novel insight into how multiple contexts underlying a single event can be recreated within the same network. PMID:23354333

Spatial variation in extreme winds predicts large wildfire locations in chaparral ecosystems

NASA Astrophysics Data System (ADS)

Moritz, Max A.; Moody, Tadashi J.; Krawchuk, Meg A.; Hughes, Mimi; Hall, Alex

2010-02-01

Fire plays a crucial role in many ecosystems, and a better understanding of different controls on fire activity is needed. Here we analyze spatial variation in fire danger during episodic wind events in coastal southern California, a densely populated Mediterranean-climate region. By reconstructing almost a decade of fire weather patterns through detailed simulations of Santa Ana winds, we produced the first high-resolution map of where these hot, dry winds are consistently most severe and which areas are relatively sheltered. We also analyzed over half a century of mapped fire history in chaparral ecosystems of the region, finding that our models successfully predict where the largest wildfires are most likely to occur. There is a surprising lack of information about extreme wind patterns worldwide, and more quantitative analyses of their spatial variation will be important for effective fire management and sustainable long-term urban development on fire-prone landscapes.

Outer satellite atmospheres: Their nature and planetary interactions

NASA Technical Reports Server (NTRS)

Smyth, W. H.; Combi, M. R.

1982-01-01

Significant progress is reported in early modeling analysis of observed sodium cloud images with our new model which includes the oscillating Io plasma torus ionization sink. Both the general w-D morphology of the region B cloud as well as the large spatial gradient seen between the region A and B clouds are found to be consistent with an isotropic flux of sodium atoms from Io. Model analysis of the spatially extended high velocity directional features provided substantial evidence for a magnetospheric wind driven gas escape mechanism from Io. In our efforts to define the source(s) of hydrogen atoms in the Saturn system, major steps were taken in order to understand the role of Titan. We have completed the comparison of the Voyager UVS data with previous Titan model results, as well as the update of the old model computer code to handle the spatially varying ionization sink for H atoms.

Spatially patterned matrix elasticity directs stem cell fate

NASA Astrophysics Data System (ADS)

Yang, Chun; DelRio, Frank W.; Ma, Hao; Killaars, Anouk R.; Basta, Lena P.; Kyburz, Kyle A.; Anseth, Kristi S.

2016-08-01

There is a growing appreciation for the functional role of matrix mechanics in regulating stem cell self-renewal and differentiation processes. However, it is largely unknown how subcellular, spatial mechanical variations in the local extracellular environment mediate intracellular signal transduction and direct cell fate. Here, the effect of spatial distribution, magnitude, and organization of subcellular matrix mechanical properties on human mesenchymal stem cell (hMSCs) function was investigated. Exploiting a photodegradation reaction, a hydrogel cell culture substrate was fabricated with regions of spatially varied and distinct mechanical properties, which were subsequently mapped and quantified by atomic force microscopy (AFM). The variations in the underlying matrix mechanics were found to regulate cellular adhesion and transcriptional events. Highly spread, elongated morphologies and higher Yes-associated protein (YAP) activation were observed in hMSCs seeded on hydrogels with higher concentrations of stiff regions in a dose-dependent manner. However, when the spatial organization of the mechanically stiff regions was altered from a regular to randomized pattern, lower levels of YAP activation with smaller and more rounded cell morphologies were induced in hMSCs. We infer from these results that irregular, disorganized variations in matrix mechanics, compared with regular patterns, appear to disrupt actin organization, and lead to different cell fates; this was verified by observations of lower alkaline phosphatase (ALP) activity and higher expression of CD105, a stem cell marker, in hMSCs in random versus regular patterns of mechanical properties. Collectively, this material platform has allowed innovative experiments to elucidate a novel spatial mechanical dosing mechanism that correlates to both the magnitude and organization of spatial stiffness.

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

PubMed Central

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

2016-01-01

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

Navigating the currents of seascape genomics: how spatial analyses can augment population genomic studies

PubMed Central

Crandall, Eric D.; Liggins, Libby; Bongaerts, Pim; Treml, Eric A.

2016-01-01

Population genomic approaches are making rapid inroads in the study of non-model organisms, including marine taxa. To date, these marine studies have predominantly focused on rudimentary metrics describing the spatial and environmental context of their study region (e.g., geographical distance, average sea surface temperature, average salinity). We contend that a more nuanced and considered approach to quantifying seascape dynamics and patterns can strengthen population genomic investigations and help identify spatial, temporal, and environmental factors associated with differing selective regimes or demographic histories. Nevertheless, approaches for quantifying marine landscapes are complicated. Characteristic features of the marine environment, including pelagic living in flowing water (experienced by most marine taxa at some point in their life cycle), require a well-designed spatial-temporal sampling strategy and analysis. Many genetic summary statistics used to describe populations may be inappropriate for marine species with large population sizes, large species ranges, stochastic recruitment, and asymmetrical gene flow. Finally, statistical approaches for testing associations between seascapes and population genomic patterns are still maturing with no single approach able to capture all relevant considerations. None of these issues are completely unique to marine systems and therefore similar issues and solutions will be shared for many organisms regardless of habitat. Here, we outline goals and spatial approaches for landscape genomics with an emphasis on marine systems and review the growing empirical literature on seascape genomics. We review established tools and approaches and highlight promising new strategies to overcome select issues including a strategy to spatially optimize sampling. Despite the many challenges, we argue that marine systems may be especially well suited for identifying candidate genomic regions under environmentally mediated selection and that seascape genomic approaches are especially useful for identifying robust locus-by-environment associations. PMID:29491947

Navigating the currents of seascape genomics: how spatial analyses can augment population genomic studies.

PubMed

Riginos, Cynthia; Crandall, Eric D; Liggins, Libby; Bongaerts, Pim; Treml, Eric A

2016-12-01

Population genomic approaches are making rapid inroads in the study of non-model organisms, including marine taxa. To date, these marine studies have predominantly focused on rudimentary metrics describing the spatial and environmental context of their study region (e.g., geographical distance, average sea surface temperature, average salinity). We contend that a more nuanced and considered approach to quantifying seascape dynamics and patterns can strengthen population genomic investigations and help identify spatial, temporal, and environmental factors associated with differing selective regimes or demographic histories. Nevertheless, approaches for quantifying marine landscapes are complicated. Characteristic features of the marine environment, including pelagic living in flowing water (experienced by most marine taxa at some point in their life cycle), require a well-designed spatial-temporal sampling strategy and analysis. Many genetic summary statistics used to describe populations may be inappropriate for marine species with large population sizes, large species ranges, stochastic recruitment, and asymmetrical gene flow. Finally, statistical approaches for testing associations between seascapes and population genomic patterns are still maturing with no single approach able to capture all relevant considerations. None of these issues are completely unique to marine systems and therefore similar issues and solutions will be shared for many organisms regardless of habitat. Here, we outline goals and spatial approaches for landscape genomics with an emphasis on marine systems and review the growing empirical literature on seascape genomics. We review established tools and approaches and highlight promising new strategies to overcome select issues including a strategy to spatially optimize sampling. Despite the many challenges, we argue that marine systems may be especially well suited for identifying candidate genomic regions under environmentally mediated selection and that seascape genomic approaches are especially useful for identifying robust locus-by-environment associations.

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

PubMed

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

2016-01-01

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

Hemispheric lateralization in top-down attention during spatial relation processing: a Granger causal model approach.

PubMed

Falasca, N W; D'Ascenzo, S; Di Domenico, A; Onofrj, M; Tommasi, L; Laeng, B; Franciotti, R

2015-04-01

Magnetoencephalography was recorded during a matching-to-sample plus cueing paradigm, in which participants judged the occurrence of changes in either categorical (CAT) or coordinate (COO) spatial relations. Previously, parietal and frontal lobes were identified as key areas in processing spatial relations and it was shown that each hemisphere was differently involved and modulated by the scope of the attention window (e.g. a large and small cue). In this study, Granger analysis highlighted the patterns of causality among involved brain areas--the direction of information transfer ran from the frontal to the visual cortex in the right hemisphere, whereas it ran in the opposite direction in the left side. Thus, the right frontal area seems to exert top-down influence, supporting the idea that, in this task, top-down signals are selectively related to the right side. Additionally, for CAT change preceded by a small cue, the right frontal gyrus was not involved in the information transfer, indicating a selective specialization of the left hemisphere for this condition. The present findings strengthen the conclusion of the presence of a remarkable hemispheric specialization for spatial relation processing and illustrate the complex interactions between the lateralized parts of the neural network. Moreover, they illustrate how focusing attention over large or small regions of the visual field engages these lateralized networks differently, particularly in the frontal regions of each hemisphere, consistent with the theory that spatial relation judgements require a fronto-parietal network in the left hemisphere for categorical relations and on the right hemisphere for coordinate spatial processing. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Characterizing permafrost active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

NASA Astrophysics Data System (ADS)

Yi, Yonghong; Kimball, John S.; Chen, Richard H.; Moghaddam, Mahta; Reichle, Rolf H.; Mishra, Umakant; Zona, Donatella; Oechel, Walter C.

2018-01-01

An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models and can lead to large uncertainties in predicting regional ecosystem responses and climate feedbacks. In this study, we developed a spatially integrated modeling and analysis framework combining field observations, local-scale ( ˜ 50 m resolution) active layer thickness (ALT) and soil moisture maps derived from low-frequency (L + P-band) airborne radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Modeled ALT results show good correspondence with in situ measurements in higher-permafrost-probability (PP ≥ 70 %) areas (n = 33; R = 0.60; mean bias = 1.58 cm; RMSE = 20.32 cm), but with larger uncertainty in sporadic and discontinuous permafrost areas. The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32±1.18 cm yr-1) and much larger increases (> 3 cm yr-1) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60 ± 0.32). A spatially integrated analysis of the radar retrievals and model sensitivity simulations demonstrated that uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was the largest factor affecting modeled ALT accuracy, while soil moisture played a secondary role. Potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of active layer conditions and refinement of the modeling framework across a larger domain.

Climatic Redistribution of Canada's Water Resources (CROCWR): An analysis of spatial and temporal hydrological trends and patterns in western Canada

NASA Astrophysics Data System (ADS)

Bawden, A. J.; Burn, D. H.; Prowse, T. D.

2012-12-01

Climate variability and change can have profound impacts on the hydrologic regime of a watershed. These effects are likely to be especially severe in regions particularly sensitive to changes in climate, such as the Canadian north, or when there are other stresses on the hydrologic regime, such as may occur when there are large withdrawals from, or land-use changes within, a watershed. A recent report of the Intergovernmental Panel on Climate Change (IPCC) stressed that future climate is likely to accelerate the hydrologic cycle and hence may affect water security in certain locations. For some regions, this will mean enhanced access to water resources, but because the effects will not be spatially uniform, other regions will experience reduced access. Understanding these patterns is critical for water managers and government agencies in western Canada - an area of highly contrasting hydroclimatic regimes and overlapping water-use and jurisdictional borders - as adapting to climate change may require reconsideration of inter-regional transfers and revised allocation of water resources to competing industrial sectors, including agriculture, hydroelectric production, and oil and gas. This research involves the detection and examination of spatial and temporal streamflow trends in western Canadian rivers as a response to changing climatic factors, including temperature, precipitation, snowmelt, and the synoptic patterns controlling these drivers. The study area, known as the CROCWR region, extends from the Pacific coast of British Columbia as far east as the Saskatchewan-Manitoba border and from the Canada-United States international border through a large portion of the Northwest Territories. This analysis examines hydrologic trends in monthly and annual streamflow for a collection of 34 hydrometric gauging stations believed to adequately represent the overall effects of climate variability and change on flows in western Canada by means of the Mann-Kendall non-parametric trend test. Large-scale spatial patterns are determined through examination of trends and contrasts between upper and lower reaches of individual sub-basins, as well as via analysis of streamflow redistributions within the CROCWR region as an entirety (i.e. north, south, east and/or west-moving patterns). Results are used to predict future implications of hydroclimatic variability and change on western Canada's water resources and recommend measures to be taken by water managers in response to these changes. This research is part of a larger hydroclimatic study that includes an analysis of the climatic drivers contributing to shifting flow regimes in western Canada as well as a study of the controlling synoptic patterns and teleconnections associated with changes in these driving forces.

A Generalized Subsurface Flow Parameterization Considering Subgrid Spatial Variability of Recharge and Topography

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

Huang, Maoyi; Liang, Xu; Leung, Lai R.

2008-12-05

Subsurface flow is an important hydrologic process and a key component of the water budget, especially in humid regions. In this study, a new subsurface flow formulation is developed that incorporates spatial variability of both topography and recharge. It is shown through theoretical derivation and case studies that the power law and exponential subsurface flow parameterizations and the parameterization proposed by Woods et al.[1997] are all special cases of the new formulation. The subsurface flows calculated using the new formulation compare well with values derived from observations at the Tulpehocken Creek and Walnut Creek watersheds. Sensitivity studies show that whenmore » the spatial variability of topography or recharge, or both is increased, the subsurface flows increase at the two aforementioned sites and the Maimai hillslope. This is likely due to enhancement of interactions between the groundwater table and the land surface that reduce the flow path. An important conclusion of this study is that the spatial variability of recharge alone, and/or in combination with the spatial variability of topography can substantially alter the behaviors of subsurface flows. This suggests that in macroscale hydrologic models or land surface models, subgrid variations of recharge and topography can make significant contributions to the grid mean subsurface flow and must be accounted for in regions with large surface heterogeneity. This is particularly true for regions with humid climate and relatively shallow groundwater table where the combined impacts of spatial variability of recharge and topography are shown to be more important. For regions with arid climate and relatively deep groundwater table, simpler formulations, especially the power law, for subsurface flow can work well, and the impacts of subgrid variations of recharge and topography may be ignored.« less

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities

PubMed Central

Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks implicated during divided attention across spatial locations and sensory modalities, pointing out the importance of investigating effective connectivity of large-scale brain networks supporting complex behavior. PMID:29535614

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities.

PubMed

Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks implicated during divided attention across spatial locations and sensory modalities, pointing out the importance of investigating effective connectivity of large-scale brain networks supporting complex behavior.

A critical look at spatial scale choices in satellite-based aerosol indirect effect studies

NASA Astrophysics Data System (ADS)

Grandey, B. S.; Stier, P.

2010-06-01

Analysing satellite datasets over large regions may introduce spurious relationships between aerosol and cloud properties due to spatial variations in aerosol type, cloud regime and synoptic regime climatologies. Using MODerate resolution Imaging Spectroradiometer data, we calculate relationships between aerosol optical depth τa, derived liquid cloud droplet effective number concentration Ne and liquid cloud droplet effective radius re at different spatial scales. Generally, positive values of dlnNe dlnτa are found for ocean regions, whilst negative values occur for many land regions. The spatial distribution of dlnre dlnτa shows approximately the opposite pattern, with generally postive values for land regions and negative values for ocean regions. We find that for region sizes larger than 4°×4°, spurious spatial variations in retrieved cloud and aerosol properties can introduce widespread significant errors to calculations of dlnNe dlnτa and dlnre dlnτa . For regions on the scale of 60°×60°, these methodological errors may lead to an overestimate in global cloud albedo effect radiative forcing of order 80%.

Spatial and kinematic structure of Monoceros star-forming region

NASA Astrophysics Data System (ADS)

Costado, M. T.; Alfaro, E. J.

2018-05-01

The principal aim of this work is to study the velocity field in the Monoceros star-forming region using the radial velocity data available in the literature, as well as astrometric data from the Gaia first release. This region is a large star-forming complex formed by two associations named Monoceros OB1 and OB2. We have collected radial velocity data for more than 400 stars in the area of 8 × 12 deg2 and distance for more than 200 objects. We apply a clustering analysis in the subspace of the phase space formed by angular coordinates and radial velocity or distance data using the Spectrum of Kinematic Grouping methodology. We found four and three spatial groupings in radial velocity and distance variables, respectively, corresponding to the Local arm, the central clusters forming the associations and the Perseus arm, respectively.

One map policy (OMP) implementation strategy to accelerate mapping of regional spatial planing (RTRW) in Indonesia

NASA Astrophysics Data System (ADS)

Hasyim, Fuad; Subagio, Habib; Darmawan, Mulyanto

2016-06-01

A preparation of spatial planning documents require basic geospatial information and thematic accuracies. Recently these issues become important because spatial planning maps are impartial attachment of the regional act draft on spatial planning (PERDA). The needs of geospatial information in the preparation of spatial planning maps preparation can be divided into two major groups: (i). basic geospatial information (IGD), consist of of Indonesia Topographic maps (RBI), coastal and marine environmental maps (LPI), and geodetic control network and (ii). Thematic Geospatial Information (IGT). Currently, mostly local goverment in Indonesia have not finished their regulation draft on spatial planning due to some constrain including technical aspect. Some constrain in mapping of spatial planning are as follows: the availability of large scale ofbasic geospatial information, the availability of mapping guidelines, and human resources. Ideal conditions to be achieved for spatial planning maps are: (i) the availability of updated geospatial information in accordance with the scale needed for spatial planning maps, (ii) the guideline of mapping for spatial planning to support local government in completion their PERDA, and (iii) capacity building of local goverment human resources to completed spatial planning maps. The OMP strategies formulated to achieve these conditions are: (i) accelerating of IGD at scale of 1:50,000, 1: 25,000 and 1: 5,000, (ii) to accelerate mapping and integration of Thematic Geospatial Information (IGT) through stocktaking availability and mapping guidelines, (iii) the development of mapping guidelines and dissemination of spatial utilization and (iv) training of human resource on mapping technology.

Canopies to Continents: What spatial scales are needed to represent landcover distributions in earth system models?

NASA Astrophysics Data System (ADS)

Guenther, A. B.; Duhl, T.

2011-12-01

Increasing computational resources have enabled a steady improvement in the spatial resolution used for earth system models. Land surface models and landcover distributions have kept ahead by providing higher spatial resolution than typically used in these models. Satellite observations have played a major role in providing high resolution landcover distributions over large regions or the entire earth surface but ground observations are needed to calibrate these data and provide accurate inputs for models. As our ability to resolve individual landscape components improves, it is important to consider what scale is sufficient for providing inputs to earth system models. The required spatial scale is dependent on the processes being represented and the scientific questions being addressed. This presentation will describe the development a contiguous U.S. landcover database using high resolution imagery (1 to 1000 meters) and surface observations of species composition and other landcover characteristics. The database includes plant functional types and species composition and is suitable for driving land surface models (CLM and MEGAN) that predict land surface exchange of carbon, water, energy and biogenic reactive gases (e.g., isoprene, sesquiterpenes, and NO). We investigate the sensitivity of model results to landcover distributions with spatial scales ranging over six orders of magnitude (1 meter to 1000000 meters). The implications for predictions of regional climate and air quality will be discussed along with recommendations for regional and global earth system modeling.

Characterizing China's energy consumption with selective economic factors and energy-resource endowment: a spatial econometric approach

NASA Astrophysics Data System (ADS)

Jiang, Lei; Ji, Minhe; Bai, Ling

2015-06-01

Coupled with intricate regional interactions, the provincial disparity of energy-resource endowment and other economic conditions in China have created spatially complex energy consumption patterns that require analyses beyond the traditional ones. To distill the spatial effect out of the resource and economic factors on China's energy consumption, this study recast the traditional econometric model in a spatial context. Several analytic steps were taken to reveal different aspects of the issue. Per capita energy consumption (AVEC) at the provincial level was first mapped to reveal spatial clusters of high energy consumption being located in either well developed or energy resourceful regions. This visual spatial autocorrelation pattern of AVEC was quantitatively tested to confirm its existence among Chinese provinces. A Moran scatterplot was employed to further display a relatively centralized trend occurring in those provinces that had parallel AVEC, revealing a spatial structure with attraction among high-high or low-low regions and repellency among high-low or low-high regions. By a comparison between the ordinary least square (OLS) model and its spatial econometric counterparts, a spatial error model (SEM) was selected to analyze the impact of major economic determinants on AVEC. While the analytic results revealed a significant positive correlation between AVEC and economic development, other determinants showed some intricate influential patterns. The provinces endowed with rich energy reserves were inclined to consume much more energy than those otherwise, whereas changing the economic structure by increasing the proportion of secondary and tertiary industries also tended to consume more energy. Both situations seem to underpin the fact that these provinces were largely trapped in the economies that were supported by technologies of low energy efficiency during the period, while other parts of the country were rapidly modernized by adopting advanced technologies and more efficient industries. On the other hand, institutional change (i.e., marketization) and innovation (i.e., technological progress) exerted positive impacts on AVEC improvement, as always expected in this and other studies. Finally, the model comparison indicated that SEM was capable of separating spatial effect from the error term of OLS, so as to improve goodness-of-fit and the significance level of individual determinants.

Effects of land use on lake nutrients: The importance of scale, hydrologic connectivity, and region

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Wagner, Tyler; Webster, Katherine E.; Bremigan, Mary Tate

2015-01-01

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales.

Effects of Land Use on Lake Nutrients: The Importance of Scale, Hydrologic Connectivity, and Region

PubMed Central

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Wagner, Tyler; Webster, Katherine E.; Bremigan, Mary Tate

2015-01-01

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales. PMID:26267813

Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

NASA Astrophysics Data System (ADS)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as "field" or "global" significance. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Monthly temperature climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.

When Local Extinction and Colonization of River Fishes Can Be Predicted by Regional Occupancy: the Role of Spatial Scales

PubMed Central

Bergerot, Benjamin; Hugueny, Bernard; Belliard, Jérôme

2013-01-01

Background Predicting which species are likely to go extinct is perhaps one of the most fundamental yet challenging tasks for conservation biologists. This is particularly relevant for freshwater ecosystems which tend to have the highest proportion of species threatened with extinction. According to metapopulation theories, local extinction and colonization rates of freshwater subpopulations can depend on the degree of regional occupancy, notably due to rescue effects. However, relationships between extinction, colonization, regional occupancy and the spatial scales at which they operate are currently poorly known. Methods And Findings: We used a large dataset of freshwater fish annual censuses in 325 stream reaches to analyse how annual extinction/colonization rates of subpopulations depend on the regional occupancy of species. For this purpose, we modelled the regional occupancy of 34 fish species over the whole French river network and we tested how extinction/colonization rates could be predicted by regional occupancy described at five nested spatial scales. Results show that extinction and colonization rates depend on regional occupancy, revealing existence a rescue effect. We also find that these effects are scale dependent and their absolute contribution to colonization and extinction tends to decrease from river section to larger basin scales. Conclusions In terms of management, we show that regional occupancy quantification allows the evaluation of local species extinction/colonization dynamics and reduction of local extinction risks for freshwater fish species implies the preservation of suitable habitats at both local and drainage basin scales. PMID:24367636

When local extinction and colonization of river fishes can be predicted by regional occupancy: the role of spatial scales.

PubMed

Bergerot, Benjamin; Hugueny, Bernard; Belliard, Jérôme

2013-01-01

Predicting which species are likely to go extinct is perhaps one of the most fundamental yet challenging tasks for conservation biologists. This is particularly relevant for freshwater ecosystems which tend to have the highest proportion of species threatened with extinction. According to metapopulation theories, local extinction and colonization rates of freshwater subpopulations can depend on the degree of regional occupancy, notably due to rescue effects. However, relationships between extinction, colonization, regional occupancy and the spatial scales at which they operate are currently poorly known. And Findings: We used a large dataset of freshwater fish annual censuses in 325 stream reaches to analyse how annual extinction/colonization rates of subpopulations depend on the regional occupancy of species. For this purpose, we modelled the regional occupancy of 34 fish species over the whole French river network and we tested how extinction/colonization rates could be predicted by regional occupancy described at five nested spatial scales. Results show that extinction and colonization rates depend on regional occupancy, revealing existence a rescue effect. We also find that these effects are scale dependent and their absolute contribution to colonization and extinction tends to decrease from river section to larger basin scales. In terms of management, we show that regional occupancy quantification allows the evaluation of local species extinction/colonization dynamics and reduction of local extinction risks for freshwater fish species implies the preservation of suitable habitats at both local and drainage basin scales.

Bilateral parietal contributions to spatial language.

PubMed

Conder, Julie; Fridriksson, Julius; Baylis, Gordon C; Smith, Cameron M; Boiteau, Timothy W; Almor, Amit

2017-01-01

It is commonly held that language is largely lateralized to the left hemisphere in most individuals, whereas spatial processing is associated with right hemisphere regions. In recent years, a number of neuroimaging studies have yielded conflicting results regarding the role of language and spatial processing areas in processing language about space (e.g., Carpenter, Just, Keller, Eddy, & Thulborn, 1999; Damasio et al., 2001). In the present study, we used sparse scanning event-related functional magnetic resonance imaging (fMRI) to investigate the neural correlates of spatial language, that is; language used to communicate the spatial relationship of one object to another. During scanning, participants listened to sentences about object relationships that were either spatial or non-spatial in nature (color or size relationships). Sentences describing spatial relationships elicited more activation in the superior parietal lobule and precuneus bilaterally in comparison to sentences describing size or color relationships. Activation of the precuneus suggests that spatial sentences elicit spatial-mental imagery, while the activation of the SPL suggests sentences containing spatial language involve integration of two distinct sets of information - linguistic and spatial. Copyright © 2016 Elsevier Inc. All rights reserved.

Upscaling Ameriflux observations to assess drought impacts on gross primary productivity across the Southwest

NASA Astrophysics Data System (ADS)

Barnes, M.; Moore, D. J.; Scott, R. L.; MacBean, N.; Ponce-Campos, G. E.; Breshears, D. D.

2017-12-01

Both satellite observations and eddy covariance estimates provide crucial information about the Earth's carbon, water and energy cycles. Continuous measurements from flux towers facilitate exploration of the exchange of carbon dioxide, water and energy between the land surface and the atmosphere at fine temporal and spatial scales, while satellite observations can fill in the large spatial gaps of in-situ measurements and provide long-term temporal continuity. The Southwest (Southwest United States and Northwest Mexico) and other semi-arid regions represent a key uncertainty in interannual variability in carbon uptake. Comparisons of existing global upscaled gross primary production (GPP) products with flux tower data at sites across the Southwest show widespread mischaracterization of seasonality in vegetation carbon uptake, resulting in large (up to 200%) errors in annual carbon uptake estimates. Here, remotely sensed and distributed meteorological inputs are used to upscale GPP estimates from 25 Ameriflux towers across the Southwest to the regional scale using a machine learning approach. Our random forest model incorporates two novel features that improve the spatial and temporal variability in GPP. First, we incorporate a multi-scalar drought index at multiple timescales to account for differential seasonality between ecosystem types. Second, our machine learning algorithm was trained on twenty five ecologically diverse sites to optimize both the monthly variability in and the seasonal cycle of GPP. The product and its components will be used to examine drought impacts on terrestrial carbon cycling across the Southwest including the effects of drought seasonality and on carbon uptake. Our spatially and temporally continuous upscaled GPP product drawing from both ground and satellite data over the Southwest region helps us understand linkages between the carbon and water cycles in semi-arid ecosystems and informs predictions of vegetation response to future climate conditions.

Analysis of dose heterogeneity using a subvolume-DVH

NASA Astrophysics Data System (ADS)

Said, M.; Nilsson, P.; Ceberg, C.

2017-11-01

The dose-volume histogram (DVH) is universally used in radiation therapy for its highly efficient way of summarizing three-dimensional dose distributions. An apparent limitation that is inherent to standard histograms is the loss of spatial information, e.g. it is no longer possible to tell where low- and high-dose regions are, and whether they are connected or disjoint. Two methods for overcoming the spatial fragmentation of low- and high-dose regions are presented, both based on the gray-level size zone matrix, which is a two-dimensional histogram describing the frequencies of connected regions of similar intensities. The first approach is a quantitative metric which can be likened to a homogeneity index. The large cold spot metric (LCS) is here defined to emphasize large contiguous regions receiving too low a dose; emphasis is put on both size, and deviation from the prescribed dose. In contrast, the subvolume-DVH (sDVH) is an extension to the standard DVH and allows for a qualitative evaluation of the degree of dose heterogeneity. The information retained from the two-dimensional histogram is overlaid on top of the DVH and the two are presented simultaneously. Both methods gauge the underlying heterogeneity in ways that the DVH alone cannot, and both have their own merits—the sDVH being more intuitive and the LCS being quantitative.

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

USGS Publications Warehouse

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

2017-01-01

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

Spatial and 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.

Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

NASA Astrophysics Data System (ADS)

Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

2018-04-01

A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is distribution-free, robust to spatial dependence, and accounts for time series structure.

Region-specific patterns and drivers of macroscale forest plant invasions

Treesearch

Basil V. Iannone; Christopher M. Oswalt; Andrew M. Liebhold; Qinfeng Guo; Kevin M. Potter; Gabriela C. Nunez-Mir; Sonja N. Oswalt; Bryan C. Pijanowski; Songlin Fei; Bethany Bradley

2015-01-01

Aim Stronger inferences about biological invasions may be obtained when accounting for multiple invasion measures and the spatial heterogeneity occurring across large geographic areas. We pursued this enquiry by utilizing a multimeasure, multiregional framework to investigate forest plant invasions at a subcontinental scale. ...

Urban water - a new frontier in isotope hydrology.

PubMed

Ehleringer, James R; Barnette, Janet E; Jameel, Yusuf; Tipple, Brett J; Bowen, Gabriel J

2016-01-01

Isotope hydrology has focused largely on landscapes away from densely inhabited regions. In coming decades, it will become increasingly more important to focus on water supplies and dynamics within urban systems. Stable isotope analyses provide important information to water managers within large cities, particularly in arid regions where evaporative histories of water sources, vulnerabilities, and reliabilities of the water supplies can be major issues. Here the spatial and vertical understanding of water supporting urban systems that comes from stable isotope analyses can serve as a useful management tool. We explore this research frontier using the coupled natural-human landscape of the Salt Lake Valley, USA, with its greater than one million inhabitants. We first provide data on the stable isotope ratios of the hydrologic system's primary components: precipitation, incoming surface waters, and terminus waters in this closed basin. We then explore the spatial and temporal patterns of drinking waters within the urban landscape and the new opportunities to better link isotope ratio data with short- and long-term management interests of water managers.

Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions.

PubMed

Kallus, Zsófia; Barankai, Norbert; Szüle, János; Vattay, Gábor

2015-01-01

Human interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap between the redrawn and the administrative borders. Here we present a similar analysis based on one of the most popular online social networks represented by the ties between more than 5.8 million of its geo-located users. The worldwide coverage of their measured activity allowed us to analyze the large-scale regional subgraphs of entire continents and an extensive set of examples for single countries. We present results for North and South America, Europe and Asia. In our analysis we used the well-established method of modularity clustering after an aggregation of the individual links into a weighted graph connecting equal-area geographical pixels. Our results show fingerprints of both of the opposing forces of dividing local conflicts and of uniting cross-cultural trends of globalization.

Large-region acoustic source mapping using a movable array and sparse covariance fitting.

PubMed

Zhao, Shengkui; Tuna, Cagdas; Nguyen, Thi Ngoc Tho; Jones, Douglas L

2017-01-01

Large-region acoustic source mapping is important for city-scale noise monitoring. Approaches using a single-position measurement scheme to scan large regions using small arrays cannot provide clean acoustic source maps, while deploying large arrays spanning the entire region of interest is prohibitively expensive. A multiple-position measurement scheme is applied to scan large regions at multiple spatial positions using a movable array of small size. Based on the multiple-position measurement scheme, a sparse-constrained multiple-position vectorized covariance matrix fitting approach is presented. In the proposed approach, the overall sample covariance matrix of the incoherent virtual array is first estimated using the multiple-position array data and then vectorized using the Khatri-Rao (KR) product. A linear model is then constructed for fitting the vectorized covariance matrix and a sparse-constrained reconstruction algorithm is proposed for recovering source powers from the model. The user parameter settings are discussed. The proposed approach is tested on a 30 m × 40 m region and a 60 m × 40 m region using simulated and measured data. Much cleaner acoustic source maps and lower sound pressure level errors are obtained compared to the beamforming approaches and the previous sparse approach [Zhao, Tuna, Nguyen, and Jones, Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP) (2016)].

Functional Geometry Alignment and Localization of Brain Areas.

PubMed

Langs, Georg; Golland, Polina; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J

2010-01-01

Matching functional brain regions across individuals is a challenging task, largely due to the variability in their location and extent. It is particularly difficult, but highly relevant, for patients with pathologies such as brain tumors, which can cause substantial reorganization of functional systems. In such cases spatial registration based on anatomical data is only of limited value if the goal is to establish correspondences of functional areas among different individuals, or to localize potentially displaced active regions. Rather than rely on spatial alignment, we propose to perform registration in an alternative space whose geometry is governed by the functional interaction patterns in the brain. We first embed each brain into a functional map that reflects connectivity patterns during a fMRI experiment. The resulting functional maps are then registered, and the obtained correspondences are propagated back to the two brains. In application to a language fMRI experiment, our preliminary results suggest that the proposed method yields improved functional correspondences across subjects. This advantage is pronounced for subjects with tumors that affect the language areas and thus cause spatial reorganization of the functional regions.

Distinct representations for shifts of spatial attention and changes of reward contingencies in the human brain.

PubMed

Tosoni, Annalisa; Shulman, Gordon L; Pope, Anna L W; McAvoy, Mark P; Corbetta, Maurizio

2013-06-01

Success in a dynamically changing world requires both rapid shifts of attention to the location of important objects and the detection of changes in motivational contingencies that may alter future behavior. Here we addressed the relationship between these two processes by measuring the blood-oxygenation-level-dependent (BOLD) signal during a visual search task in which the location and the color of a salient cue respectively indicated where a rewarded target would appear and the monetary gain (large or small) associated with its detection. While cues that either shifted or maintained attention were presented every 4 to 8 sec, the reward magnitude indicated by the cue changed roughly every 30 sec, allowing us to distinguish a change in expected reward magnitude from a maintained state of expected reward magnitude. Posterior cingulate cortex was modulated by cues signaling an increase in expected reward magnitude, but not by cues for shifting versus maintaining spatial attention. Dorsal fronto-parietal regions in precuneus and frontal eye field (FEF) also showed increased BOLD activity for changes in expected reward magnitude from low to high, but in addition showed large independent modulations for shifting versus maintaining attention. In particular, the differential activation for shifting versus maintaining attention was not affected by expected reward magnitude. These results indicate that BOLD activations for shifts of attention and increases in expected reward magnitude are largely separate. Finally, visual cortex showed sustained spatially selective signals that were significantly enhanced when greater reward magnitude was expected, but this reward-related modulation was not observed in spatially selective regions of dorsal fronto-parietal cortex. Copyright © 2012 Elsevier Ltd. All rights reserved.

Projecting future impacts of hurricanes on the carbon balance of eastern U.S. forests

NASA Astrophysics Data System (ADS)

Fisk, J. P.; Hurtt, G. C.; Chambers, J. Q.; Zeng, H.; Dolan, K.; Flanagan, S.; Rourke, O.; Negron Juarez, R. I.

2011-12-01

In U.S. Atlantic coastal areas, hurricanes are a principal agent of catastrophic wind damage, with dramatic impacts on the structure and functioning of forests. Substantial recent progress has been made to estimate the biomass loss and resulting carbon emissions caused by hurricanes impacting the U.S. Additionally, efforts to evaluate the net effects of hurricanes on the regional carbon balance have demonstrated the importance of viewing large disturbance events in the broader context of recovery from a mosaic of past events. Viewed over sufficiently long time scales and large spatial scales, regrowth from previous storms may largely offset new emissions; however, changes in number, strength or spatial distribution of extreme disturbance events will result in changes to the equilibrium state of the ecosystem and have the potential to result in a lasting carbon source or sink. Many recent studies have linked climate change to changes in the frequency and intensity of hurricanes. In this study, we use a mechanistic ecosystem model, the Ecosystem Demography (ED) model, driven by scenarios of future hurricane activity based on historic activity and future climate projections, to evaluate how changes in hurricane frequency, intensity and spatial distribution could affect regional carbon storage and flux over the coming century. We find a non-linear response where increased storm activity reduces standing biomass stocks reducing the impacts of future events. This effect is highly dependent on the spatial pattern and repeat interval of future hurricane activity. Developing this kind of predictive modeling capability that tracks disturbance events and recovery is key to our understanding and ability to predict the carbon balance of forests.

Spectral Radiance of a Large-Area Integrating Sphere Source

PubMed Central

Walker, James H.; Thompson, Ambler

1995-01-01

The radiance and irradiance calibration of large field-of-view scanning and imaging radiometers for remote sensing and surveillance applications has resulted in the development of novel calibration techniques. One of these techniques is the employment of large-area integrating sphere sources as radiance or irradiance secondary standards. To assist the National Aeronautical and Space Administration’s space based ozone measurement program, a commercially available large-area internally illuminated integrating sphere source’s spectral radiance was characterized in the wavelength region from 230 nm to 400 nm at the National Institute of Standards and Technology. Spectral radiance determinations and spatial mappings of the source indicate that carefully designed large-area integrating sphere sources can be measured with a 1 % to 2 % expanded uncertainty (two standard deviation estimate) in the near ultraviolet with spatial nonuniformities of 0.6 % or smaller across a 20 cm diameter exit aperture. A method is proposed for the calculation of the final radiance uncertainties of the source which includes the field of view of the instrument being calibrated. PMID:29151725

Life-history strategies associated with local population variability confer regional stability.

PubMed

Pribil, Stanislav; Houlahan, Jeff E

2003-07-07

A widely held ecological tenet is that, at the local scale, populations of K-selected species (i.e. low fecundity, long lifespan and large body size) will be less variable than populations of r-selected species (i.e. high fecundity, short lifespan and small body size). We examined the relationship between long-term population trends and life-history attributes for 185 bird species in the Czech Republic and found that, at regional spatial scales and over moderate temporal scales (100-120 years), K-selected bird species were more likely to show both large increases and decreases in population size than r-selected species. We conclude that life-history attributes commonly associated with variable populations at the local scale, confer stability at the regional scale.

Forest fire spatial pattern analysis in Galicia (NW Spain).

PubMed

Fuentes-Santos, I; Marey-Pérez, M F; González-Manteiga, W

2013-10-15

Knowledge of fire behaviour is of key importance in forest management. In the present study, we analysed the spatial structure of forest fire with spatial point pattern analysis and inference techniques recently developed in the Spatstat package of R. Wildfires have been the primary threat to Galician forests in recent years. The district of Fonsagrada-Ancares is one of the most seriously affected by fire in the region and, therefore, the central focus of the study. Our main goal was to determine the spatial distribution of ignition points to model and predict fire occurrence. These data are of great value in establishing enhanced fire prevention and fire fighting plans. We found that the spatial distribution of wildfires is not random and that fire occurrence may depend on ownership conflicts. We also found positive interaction between small and large fires and spatial independence between wildfires in consecutive years. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Temporal and Region-Specific Requirements of αCaMKII in Spatial and Contextual Learning

PubMed Central

Achterberg, Katharina G.; Buitendijk, Gabriëlle H.S.; Kool, Martijn J.; Goorden, Susanna M.I.; Post, Laura; Slump, Denise E.; Silva, Alcino J.; van Woerden, Geeske M.

2014-01-01

The α isoform of the calcium/calmodulin-dependent protein kinase II (αCaMKII) has been implicated extensively in molecular and cellular mechanisms underlying spatial and contextual learning in a wide variety of species. Germline deletion of Camk2a leads to severe deficits in spatial and contextual learning in mice. However, the temporal and region-specific requirements for αCaMKII have remained largely unexplored. Here, we generated conditional Camk2a mutants to examine the influence of spatially restricted and temporally controlled expression of αCaMKII. Forebrain-specific deletion of the Camk2a gene resulted in severe deficits in water maze and contextual fear learning, whereas mice with deletion restricted to the cerebellum learned normally. Furthermore, we found that temporally controlled deletion of the Camk2a gene in adult mice is as detrimental as germline deletion for learning and synaptic plasticity. Together, we confirm the requirement for αCaMKII in the forebrain, but not the cerebellum, in spatial and contextual learning. Moreover, we highlight the absolute requirement for intact αCaMKII expression at the time of learning. PMID:25143599

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

PubMed

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

2017-10-01

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

Collective Interaction of a Compressible Periodic Parallel Jet Flow

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

1997-01-01

A linear instability model for multiple spatially periodic supersonic rectangular jets is solved using Floquet-Bloch theory. The disturbance environment is investigated using a two dimensional perturbation of a mean flow. For all cases large temporal growth rates are found. This work is motivated by an increase in mixing found in experimental measurements of spatially periodic supersonic rectangular jets with phase-locked screech. The results obtained in this paper suggests that phase-locked screech or edge tones may produce correlated spatially periodic jet flow downstream of the nozzles which creates a large span wise multi-nozzle region where a disturbance can propagate. The large temporal growth rates for eddies obtained by model calculation herein are related to the increased mixing since eddies are the primary mechanism that transfer energy from the mean flow to the large turbulent structures. Calculations of growth rates are presented for a range of Mach numbers and nozzle spacings corresponding to experimental test conditions where screech synchronized phase locking was observed. The model may be of significant scientific and engineering value in the quest to understand and construct supersonic mixer-ejector nozzles which provide increased mixing and reduced noise.

Using High-Resolution Forward Model Simulations of Ideal Atmospheric Tracers to Assess the Spatial Information Content of Inverse CO2 Flux Estimates

NASA Technical Reports Server (NTRS)

Pawson, Steven; Nielsen, J. Eric

2011-01-01

Attribution of observed atmospheric carbon concentrations to emissions on the country, state or city level is often inferred using "inversion" techniques. Such computations are often performed using advanced mathematical techniques, such as synthesis inversion or four-dimensional variational analysis, that invoke tracing observed atmospheric concentrations backwards through a transport model to a source region. It is, to date, not well understood how well such techniques can represent fine spatial (and temporal) structure in the inverted flux fields. This question is addressed using forward-model computations with idealized tracers emitted at the surface in a large number of grid boxes over selected regions and examining how distinctly these emitted tracers can be detected downstream. Initial results show that tracers emitted in half-degree grid boxes over a large region of the Eastern USA cannot be distinguished from each other, even at short distances over the Atlantic Ocean, when they are emitted in grid boxes separated by less than five degrees of latitude - especially when only total-column observations are available. A large number of forward model simulations, with varying meteorological conditions, are used to assess how distinctly three types observations (total column, upper tropospheric column, and surface mixing ratio) can separate emissions from different sources. Inferences inverse modeling and source attribution will be drawn.

Antarctic Surface Temperatures Using Satellite Infrared Data from 1979 Through 1995

NASA Technical Reports Server (NTRS)

Comiso, Josefino C.; Stock, Larry

1997-01-01

The large scale spatial and temporal variations of surface ice temperature over the Antarctic region are studied using infrared data derived from the Nimbus-7 Temperature Humidity Infrared Radiometer (THIR) from 1979 through 1985 and from the NOAA Advanced Very High Resolution Radiometer (AVHRR) from 1984 through 1995. Enhanced techniques suitable for the polar regions for cloud masking and atmospheric correction were used before converting radiances to surface temperatures. The observed spatial distribution of surface temperature is highly correlated with surface ice sheet topography and agrees well with ice station temperatures with 2K to 4K standard deviations. The average surface ice temperature over the entire continent fluctuates by about 30K from summer to winter while that over the Antarctic Plateau varies by about 45K. Interannual fluctuations of the coldest interannual variations in surface temperature are highest at the Antarctic Plateau and the ice shelves (e.g., Ross and Ronne) with a periodic cycle of about 5 years and standard deviations of about 11K and 9K, respectively. Despite large temporal variability, however, especially in some regions, a regression analysis that includes removal of the seasonal cycle shows no apparent trend in temperature during the period 1979 through 1995.

Quantifying Spatial and Seasonal Variability in Atmospheric Ammonia with In Situ and Space-Based Observations

NASA Technical Reports Server (NTRS)

Pinder, Robert W.; Walker, John T.; Bash, Jesse O.; Cady-Pereira, Karen E.; Henze, Daven K.; Luo, Mingzhao; Osterman, Gregory B.; Shepard, Mark W.

2011-01-01

Ammonia plays an important role in many biogeochemical processes, yet atmospheric mixing ratios are not well known. Recently, methods have been developed for retrieving NH3 from space-based observations, but they have not been compared to in situ measurements. We have conducted a field campaign combining co-located surface measurements and satellite special observations from the Tropospheric Emission Spectrometer (TES). Our study includes 25 surface monitoring sites spanning 350 km across eastern North Carolina, a region with large seasonal and spatial variability in NH3. From the TES spectra, we retrieve a NH3 representative volume mixing ratio (RVMR), and we restrict our analysis to times when the region of the atmosphere observed by TES is representative of the surface measurement. We find that the TES NH3 RVMR qualitatively captures the seasonal and spatial variability found in eastern North Carolina. Both surface measurements and TES NH3 show a strong correspondence with the number of livestock facilities within 10 km of the observation. Furthermore, we find that TES H3 RVMR captures the month-to-month variability present in the surface observations. The high correspondence with in situ measurements and vast spatial coverage make TES NH3 RVMR a valuable tool for understanding regional and global NH3 fluxes.

Wide-Band Spatially Tunable Photonic Bandgap in Visible Spectral Range and Laser based on a Polymer Stabilized Blue Phase

PubMed Central

Lin, Jia-De; Wang, Tsai-Yen; Mo, Ting-Shan; Huang, Shuan-Yu; Lee, Chia-Rong

2016-01-01

This work successfully develops a largely-gradient-pitched polymer-stabilized blue phase (PSBP) photonic bandgap (PBG) device with a wide-band spatial tunability in nearly entire visible region within a wide blue phase (BP) temperature range including room temperature. The device is fabricated based on the reverse diffusion of two injected BP-monomer mixtures with a low and a high chiral concentrations and afterwards through UV-curing. This gradient-pitched PSBP can show a rainbow-like reflection appearance in which the peak wavelength of the PBG can be spatially tuned from the blue to the red regions at room temperature. The total tuning spectral range for the cell is as broad as 165 nm and covers almost the entire visible region. Based on the gradient-pitched PSBP, a spatially tunable laser is also demonstrated in this work. The temperature sensitivity of the lasing wavelength for the laser is negatively linear and approximately −0.26 nm/°C. The two devices have a great potential for use in applications of photonic devices and displays because of their multiple advantages, such as wide-band tunability, wide operated temperature range, high stability and reliability, no issue of hysteresis, no need of external controlling sources, and not slow tuning speed (mechanically). PMID:27456475

Optimal Scaling of Aftershock Zones using Ground Motion Forecasts

NASA Astrophysics Data System (ADS)

Wilson, John Max; Yoder, Mark R.; Rundle, John B.

2018-02-01

The spatial distribution of aftershocks following major earthquakes has received significant attention due to the shaking hazard these events pose for structures and populations in the affected region. Forecasting the spatial distribution of aftershock events is an important part of the estimation of future seismic hazard. A simple spatial shape for the zone of activity has often been assumed in the form of an ellipse having semimajor axis to semiminor axis ratio of 2.0. However, since an important application of these calculations is the estimation of ground shaking hazard, an effective criterion for forecasting future aftershock impacts is to use ground motion prediction equations (GMPEs) in addition to the more usual approach of using epicentral or hypocentral locations. Based on these ideas, we present an aftershock model that uses self-similarity and scaling relations to constrain parameters as an option for such hazard assessment. We fit the spatial aspect ratio to previous earthquake sequences in the studied regions, and demonstrate the effect of the fitting on the likelihood of post-disaster ground motion forecasts for eighteen recent large earthquakes. We find that the forecasts in most geographic regions studied benefit from this optimization technique, while some are better suited to the use of the a priori aspect ratio.

Electrical Resistivity Imaging of Saltwater and Freshwater Along the Coast of Monterey Bay

NASA Astrophysics Data System (ADS)

Knight, R. J.; Pidlisecky, A.; Moran, T.; Goebel, M.

2014-12-01

A coastal region represents a dynamic interface where the processes of saltwater intrusion and freshwater flow create complex spatial and temporal changes in water chemistry. These changes in water chemistry affect both human use of coastal groundwater aquifers and the functioning of coastal ecosystems. Mapping out the subsurface distribution of saltwater and freshwater is a critical step in predicting, and managing, changes in water chemistry in coastal regions. Our research is focused on California's Monterey Bay region where agriculturally-intensive land meets the sensitive marine environment of the Monterey Bay National Marine Sanctuary. Along the coast of Monterey Bay extensive groundwater extraction (groundwater provides more than 80% of the area's water supply) has led to saltwater intrusion into aquifers at various locations. To date, the mapping of saltwater intrusion has relied on measurements of changing water chemistry in monitoring wells. But it is challenging with wells to capture the spatially complex hydrostratigraphy resulting from changing depositional environments and numerous faulting events. We suggest that geophysical methods be used to map and monitor the distribution of saltwater and freshwater by acquiring non-invasive, high-resolution continuous images of the subsurface. In a pilot study conducted over the past four years, we used electrical resistivity imaging to successfully identify regions of saltwater and freshwater 150 m below sea level along a 7 km stretch of the southern Monterey Bay coast. We employed large-offset electrical resistance tomography using a 96-electrode system with an overall array length of 860 m. The results showed excellent agreement with measurements in nearby monitoring wells. The large-scale image provided by the geophysical measurements revealed the hydrostratigraphic controls on the spatial distribution of the saltwater/freshwater interface. In October 2014 we will expand this study, using large-offset electrical resistance tomography to image to a depth of 300 m along a 40 km stretch of the Monterey Bay coast. The acquisition of this continuous dataset will provide an improved understanding of the biophysical and human factors controlling the processes of saltwater intrusion and freshwater flow in this coastal region.

Determining switchgrass biomass supplies for cellulosic biorefineries

USDA-ARS?s Scientific Manuscript database

Switchgrass (Panicum virgatum L.) is being developed into a bioenergy crop for use in temperate regions of the USA. Information on spatial and temporial variation for stands and biomass yield among and within fields in large agroecoregions is not available. A reliable feedstock supply will be essent...

ESTIMATING REGIONAL SPECIES RICHNESS USING A LIMITED NUMBER OF SURVEY UNITS

EPA Science Inventory

The accurate and precise estimation of species richness at large spatial scales using a limited number of survey units is of great significance for ecology and biodiversity conservation. We used the distribution data of native fish and resident breeding bird species compiled for ...

INVENTORY AND CLASSIFICATION OF GREAT LAKES COASTAL WETLANDS FOR MONITORING AND ASSESSMENT AT LARGE SPATIAL SCALES

EPA Science Inventory

Monitoring aquatic resources for regional assessments requires an accurate and comprehensive inventory of the resource and useful classification of exosystem similarities. Our research effort to create an electronic database and work with various ways to classify coastal wetlands...

Terrestrial ecosystems and their change

Treesearch

Anatoly Z. Shvidenko; Eric Gustafson; A. David McGuire; Vjacheslav I. Kharuk; Dmitry G. Schepaschenko; Herman H. Shugart; Nadezhda M. Tchebakova; Natalia N. Vygodskaya; Alexander A. Onuchin; Daniel J. Hayes; Ian McCallum; Shamil Maksyutov; Ludmila V. Mukhortova; Amber J. Soja; Luca Belelli-Marchesini; Julia A. Kurbatova; Alexander V. Oltchev; Elena I. Parfenova; Jacquelyn K. Shuman

2012-01-01

This chapter considers the current state of Siberian terrestrial ecosystems, their spatial distribution, and major biometric characteristics. Ongoing climate change and the dramatic increase of accompanying anthropogenic pressure provide different but mostly negative impacts on Siberian ecosystems. Future climates of the region may lead to substantial drying on large...

Reconstruction of global gridded monthly sectoral water withdrawals for 1971–2010 and analysis of their spatiotemporal patterns

DOE PAGES

Huang, Zhongwei; Hejazi, Mohamad; Li, Xinya; ...

2018-04-06

Human water withdrawal has increasingly altered the global water cycle in past decades, yet our understanding of its driving forces and patterns is limited. Reported historical estimates of sectoral water withdrawals are often sparse and incomplete, mainly restricted to water withdrawal estimates available at annual and country scales, due to a lack of observations at seasonal and local scales. In this study, through collecting and consolidating various sources of reported data and developing spatial and temporal statistical downscaling algorithms, we reconstruct a global monthly gridded (0.5°) sectoral water withdrawal dataset for the period 1971–2010, which distinguishes six water use sectors, i.e., irrigation,more » domestic, electricity generation (cooling of thermal power plants), livestock, mining, and manufacturing. Based on the reconstructed dataset, the spatial and temporal patterns of historical water withdrawal are analyzed. Results show that total global water withdrawal has increased significantly during 1971–2010, mainly driven by the increase in irrigation water withdrawal. Regions with high water withdrawal are those densely populated or with large irrigated cropland production, e.g., the United States (US), eastern China, India, and Europe. Seasonally, irrigation water withdrawal in summer for the major crops contributes a large percentage of total annual irrigation water withdrawal in mid- and high-latitude regions, and the dominant season of irrigation water withdrawal is also different across regions. Domestic water withdrawal is mostly characterized by a summer peak, while water withdrawal for electricity generation has a winter peak in high-latitude regions and a summer peak in low-latitude regions. Despite the overall increasing trend, irrigation in the western US and domestic water withdrawal in western Europe exhibit a decreasing trend. Our results highlight the distinct spatial pattern of human water use by sectors at the seasonal and annual timescales. Here, the reconstructed gridded water withdrawal dataset is open access, and can be used for examining issues related to water withdrawals at fine spatial, temporal, and sectoral scales.« less

Reconstruction of global gridded monthly sectoral water withdrawals for 1971–2010 and analysis of their spatiotemporal patterns

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

Huang, Zhongwei; Hejazi, Mohamad; Li, Xinya

Human water withdrawal has increasingly altered the global water cycle in past decades, yet our understanding of its driving forces and patterns is limited. Reported historical estimates of sectoral water withdrawals are often sparse and incomplete, mainly restricted to water withdrawal estimates available at annual and country scales, due to a lack of observations at seasonal and local scales. In this study, through collecting and consolidating various sources of reported data and developing spatial and temporal statistical downscaling algorithms, we reconstruct a global monthly gridded (0.5°) sectoral water withdrawal dataset for the period 1971–2010, which distinguishes six water use sectors, i.e., irrigation,more » domestic, electricity generation (cooling of thermal power plants), livestock, mining, and manufacturing. Based on the reconstructed dataset, the spatial and temporal patterns of historical water withdrawal are analyzed. Results show that total global water withdrawal has increased significantly during 1971–2010, mainly driven by the increase in irrigation water withdrawal. Regions with high water withdrawal are those densely populated or with large irrigated cropland production, e.g., the United States (US), eastern China, India, and Europe. Seasonally, irrigation water withdrawal in summer for the major crops contributes a large percentage of total annual irrigation water withdrawal in mid- and high-latitude regions, and the dominant season of irrigation water withdrawal is also different across regions. Domestic water withdrawal is mostly characterized by a summer peak, while water withdrawal for electricity generation has a winter peak in high-latitude regions and a summer peak in low-latitude regions. Despite the overall increasing trend, irrigation in the western US and domestic water withdrawal in western Europe exhibit a decreasing trend. Our results highlight the distinct spatial pattern of human water use by sectors at the seasonal and annual timescales. Here, the reconstructed gridded water withdrawal dataset is open access, and can be used for examining issues related to water withdrawals at fine spatial, temporal, and sectoral scales.« less

Reconstruction of global gridded monthly sectoral water withdrawals for 1971–2010 and analysis of their spatiotemporal patterns

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

Huang, Zhongwei; Hejazi, Mohamad; Li, Xinya

Human water withdrawal has increasingly altered the global water cycle in past decades, yet our understanding of its driving forces and patterns is limited. Reported historical estimates of sectoral water withdrawals are often sparse and incomplete, mainly restricted to water withdrawal estimates available at annual and country scales, due to a lack of observations at seasonal and local scales. In this study, through collecting and consolidating various sources of reported data and developing spatial and temporal statistical downscaling algorithms, we reconstruct a global monthly gridded (0.5°) sectoral water withdrawal dataset for the period 1971–2010, which distinguishes six water use sectors, i.e., irrigation,more » domestic, electricity generation (cooling of thermal power plants), livestock, mining, and manufacturing. Based on the reconstructed dataset, the spatial and temporal patterns of historical water withdrawal are analyzed. Results show that total global water withdrawal has increased significantly during 1971–2010, mainly driven by the increase in irrigation water withdrawal. Regions with high water withdrawal are those densely populated or with large irrigated cropland production, e.g., the United States (US), eastern China, India, and Europe. Seasonally, irrigation water withdrawal in summer for the major crops contributes a large percentage of total annual irrigation water withdrawal in mid- and high-latitude regions, and the dominant season of irrigation water withdrawal is also different across regions. Domestic water withdrawal is mostly characterized by a summer peak, while water withdrawal for electricity generation has a winter peak in high-latitude regions and a summer peak in low-latitude regions. Despite the overall increasing trend, irrigation in the western US and domestic water withdrawal in western Europe exhibit a decreasing trend. Our results highlight the distinct spatial pattern of human water use by sectors at the seasonal and annual timescales. The reconstructed gridded water withdrawal dataset is open access, and can be used for examining issues related to water withdrawals at fine spatial, temporal, and sectoral scales.« less

Exploring the role of movement in determining the global distribution of marine biomass using a coupled hydrodynamic - Size-based ecosystem model

NASA Astrophysics Data System (ADS)

Watson, James R.; Stock, Charles A.; Sarmiento, Jorge L.

2015-11-01

Modeling the dynamics of marine populations at a global scale - from phytoplankton to fish - is necessary if we are to quantify how climate change and other broad-scale anthropogenic actions affect the supply of marine-based food. Here, we estimate the abundance and distribution of fish biomass using a simple size-based food web model coupled to simulations of global ocean physics and biogeochemistry. We focus on the spatial distribution of biomass, identifying highly productive regions - shelf seas, western boundary currents and major upwelling zones. In the absence of fishing, we estimate the total ocean fish biomass to be ∼ 2.84 ×109 tonnes, similar to previous estimates. However, this value is sensitive to the choice of parameters, and further, allowing fish to move had a profound impact on the spatial distribution of fish biomass and the structure of marine communities. In particular, when movement is implemented the viable range of large predators is greatly increased, and stunted biomass spectra characterizing large ocean regions in simulations without movement, are replaced with expanded spectra that include large predators. These results highlight the importance of considering movement in global-scale ecological models.

Large-scale estimates of gross primary production on the Qinghai-Tibet plateau based on remote sensing data

NASA Astrophysics Data System (ADS)

Ma, M., II; Yuan, W.; Dong, J.; Zhang, F.; Cai, W.; Li, H.

2017-12-01

Vegetation gross primary production (GPP) is an important variable for the carbon cycle on the Qinghai-Tibetan Plateau (QTP). Based on the measurements from twelve eddy covariance (EC) sites, we validated a light use efficiency model (i.e. EC-LUE) to evaluate the spatial-temporal patterns of GPP and the effect of environmental variables on QTP. The EC-LUE model explained 85.4% of the daily observed GPP variations through all of the twelve EC sites, and characterized very well the seasonal changes of GPP. Annual GPP over the entire QTP ranged from 575 to 703 Tg C, and showed a significantly increasing trend from 1982 to 2013. However, there were large spatial heterogeneities in long-term trends of GPP. Throughout the entire QTP, air temperature TA increase had a greater influence than solar radiation and PREC changes on productivity. Moreover, our results highlight the large uncertainties of previous GPP estimates due to insufficient parameterization and validations. When compared with GPP estimates of the EC-LUE model, most Coupled Model Intercomparison Project (CMIP5) GPP products overestimate the magnitude and increasing trends of regional GPP, which potentially impact the feedback of ecosystems to regional climate changes.

ESRI applications of GIS technology: Mineral resource development

NASA Technical Reports Server (NTRS)

Derrenbacher, W.

1981-01-01

The application of geographic information systems technology to large scale regional assessment related to mineral resource development, identifying candidate sites for related industry, and evaluating sites for waste disposal is discussed. Efforts to develop data bases were conducted at scales ranging from 1:3,000,000 to 1:25,000. In several instances, broad screening was conducted for large areas at a very general scale with more detailed studies subsequently undertaken in promising areas windowed out of the generalized data base. Increasingly, the systems which are developed are structured as the spatial framework for the long-term collection, storage, referencing, and retrieval of vast amounts of data about large regions. Typically, the reconnaissance data base for a large region is structured at 1:250,000 scale, data bases for smaller areas being structured at 1:25,000, 1:50,000 or 1:63,360. An integrated data base for the coterminous US was implemented at a scale of 1:3,000,000 for two separate efforts.

The surface urban heat island response to urban expansion: A panel analysis for the conterminous United States

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

Li, Xiaoma; Zhou, Yuyu; Asrar, Ghassem R.

Abstract: Urban heat island (UHI), a major concern worldwide, affects human health and energy use. With current and anticipated rapid urbanization, improved understanding of the response of UHI to urbanization is important for impact analysis and developing effective adaptation measures and mitigation strategies. Current studies mainly focus on a single or a few big cities and knowledge on the response of UHI to urbanization for large areas is very limited. Modelling UHI caused by urbanization for large areas that encompass multiple metropolitans remains a major scientific challenge/opportunity. As a major indicator of urbanization, urban area size lends itself well formore » representation in prognostic models to investigate the impacts of urbanization on UHI and the related socioeconomic and environmental effects. However, we have little knowledge on how UHI responds to the increase of urban area size, namely urban expansion, and its spatial and temporal variation over large areas. In this study, we investigated the relationship between surface UHI (SUHI) and urban area size in the climate and ecological context, and its spatial and temporal variations, based on a panel analysis of about 5000 urban areas of 10 km2 or larger, in the conterminous U.S. We found statistically significant positive relationship between SUHI and urban area size, and doubling the urban area size led to a SUHI increase of higher than 0.7 °C. The response of SUHI to the increase of urban area size shows spatial and temporal variations, with stronger SUHI increase in the Northern region of U.S., and during daytime and summer. Urban area size alone can explain as much as 87% of the variance of SUHI among cities studied, but with large spatial and temporal variations. Urban area size shows higher association with SUHI in regions where the thermal characteristics of land cover surrounding the urban are more homogeneous, such as in Eastern U.S., and in the summer months. This study provides a practical approach for large-scale assessment and modeling of the impact of urbanization on SUHI, both spatially and temporally, for developing mitigation/adaptation measures, especially in anticipated warmer climate conditions for the rest of this century.« less

Spatial Holmboe Instability

NASA Astrophysics Data System (ADS)

Sabine, Ortiz; Marc, Chomaz Jean; Thomas, Loiseleux

2001-11-01

In mixing layers between two parallel streams of different densities, shear and gravity effects interplay. When the Roosby number, which compares the nonlinear acceleration terms to the Coriolis forces, is large enough, buoyancy acts as a restoring force, the Kelvin-Helmholtz mode is known to be stabilized by the stratification. If the density interface is sharp enough, two new instability modes, known as Holmboe modes, propagating in opposite directions appear. This mechanism has been study in the temporal instability framework. We analyze the associated spatial instability problem, in the Boussinesq approximation, for two immiscible inviscid fluids with broken-line velocity profile. We show how the classical scenario for transition between absolute and convective instability should be modified due to the presence of propagating waves. In convective region, the spatial theory is relevant and the slowest propagative wave is shown to be the most spatially amplified, as suggested by the intuition. Spatial theory is compared with mixing layer experiments (C.G. Koop and Browand J. Fluid Mech. 93, part 1, 135 (1979)), and wedge flows (G. Pawlak and L. Armi J. Fluid Mech. 376, 1 (1999)). Physical mechanism for the Holmboe mode destabilization is analyzed via an asymptotic expansion that explains precisely the absolute instability domain at large Richardson number.

Impact of Primary Spherical Aberration, Spatial Frequency and Stiles Crawford Apodization on Wavefront determined Refractive Error: A Computational Study

PubMed Central

Xu, Renfeng; Bradley, Arthur; Thibos, Larry N.

2013-01-01

Purpose We tested the hypothesis that pupil apodization is the basis for central pupil bias of spherical refractions in eyes with spherical aberration. Methods We employed Fourier computational optics in which we vary spherical aberration levels, pupil size, and pupil apodization (Stiles Crawford Effect) within the pupil function, from which point spread functions and optical transfer functions were computed. Through-focus analysis determined the refractive correction that optimized retinal image quality. Results For a large pupil (7 mm), as spherical aberration levels increase, refractions that optimize the visual Strehl ratio mirror refractions that maximize high spatial frequency modulation in the image and both focus a near paraxial region of the pupil. These refractions are not affected by Stiles Crawford Effect apodization. Refractions that optimize low spatial frequency modulation come close to minimizing wavefront RMS, and vary with level of spherical aberration and Stiles Crawford Effect. In the presence of significant levels of spherical aberration (e.g. C40 = 0.4 µm, 7mm pupil), low spatial frequency refractions can induce −0.7D myopic shift compared to high SF refraction, and refractions that maximize image contrast of a 3 cycle per degree square-wave grating can cause −0.75D myopic drift relative to refractions that maximize image sharpness. Discussion Because of small depth of focus associated with high spatial frequency stimuli, the large change in dioptric power across the pupil caused by spherical aberration limits the effective aperture contributing to the image of high spatial frequencies. Thus, when imaging high spatial frequencies, spherical aberration effectively induces an annular aperture defining that portion of the pupil contributing to a well-focused image. As spherical focus is manipulated during the refraction procedure, the dimensions of the annular aperture change. Image quality is maximized when the inner radius of the induced annulus falls to zero, thus defining a circular near paraxial region of the pupil that determines refraction outcome. PMID:23683093

Enhanced groundwater recharge rates and altered recharge sensitivity to climate variability through subsurface heterogeneity

PubMed Central

Hartmann, Andreas; Gleeson, Tom; Wagener, Thorsten

2017-01-01

Our environment is heterogeneous. In hydrological sciences, the heterogeneity of subsurface properties, such as hydraulic conductivities or porosities, exerts an important control on water balance. This notably includes groundwater recharge, which is an important variable for efficient and sustainable groundwater resources management. Current large-scale hydrological models do not adequately consider this subsurface heterogeneity. Here we show that regions with strong subsurface heterogeneity have enhanced present and future recharge rates due to a different sensitivity of recharge to climate variability compared with regions with homogeneous subsurface properties. Our study domain comprises the carbonate rock regions of Europe, Northern Africa, and the Middle East, which cover ∼25% of the total land area. We compare the simulations of two large-scale hydrological models, one of them accounting for subsurface heterogeneity. Carbonate rock regions strongly exhibit “karstification,” which is known to produce particularly strong subsurface heterogeneity. Aquifers from these regions contribute up to half of the drinking water supply for some European countries. Our results suggest that water management for these regions cannot rely on most of the presently available projections of groundwater recharge because spatially variable storages and spatial concentration of recharge result in actual recharge rates that are up to four times larger for present conditions and changes up to five times larger for potential future conditions than previously estimated. These differences in recharge rates for strongly heterogeneous regions suggest a need for groundwater management strategies that are adapted to the fast transit of water from the surface to the aquifers. PMID:28242703

Enhanced Groundwater Recharge Rates and Altered Recharge Sensitivity to Climate Variability Through Subsurface Heterogeneity

NASA Technical Reports Server (NTRS)

Hartmann, Andreas; Gleeson, Tom; Wada, Yoshihide; Wagener, Thorsten

2017-01-01

Our environment is heterogeneous. In hydrological sciences, the heterogeneity of subsurface properties, such as hydraulic conductivities or porosities, exerts an important control on water balance. This notably includes groundwater recharge, which is an important variable for efficient and sustainable groundwater resources management. Current large-scale hydrological models do not adequately consider this subsurface heterogeneity. Here we show that regions with strong subsurface heterogeneity have enhanced present and future recharge rates due to a different sensitivity of recharge to climate variability compared with regions with homogeneous subsurface properties. Our study domain comprises the carbonate rock regions of Europe, Northern Africa, and the Middle East, which cover 25 of the total land area. We compare the simulations of two large-scale hydrological models, one of them accounting for subsurface heterogeneity. Carbonate rock regions strongly exhibit karstification, which is known to produce particularly strong subsurface heterogeneity. Aquifers from these regions contribute up to half of the drinking water supply for some European countries. Our results suggest that water management for these regions cannot rely on most of the presently available projections of groundwater recharge because spatially variable storages and spatial concentration of recharge result in actual recharge rates that are up to four times larger for present conditions and changes up to five times larger for potential future conditions than previously estimated. These differences in recharge rates for strongly heterogeneous regions suggest a need for groundwater management strategies that are adapted to the fast transit of water from the surface to the aquifers.

Distribution of late Pleistocene ice-rich syngenetic permafrost of the Yedoma Suite in east and central Siberia, Russia

USGS Publications Warehouse

Grosse, Guido; Robinson, Joel E.; Bryant, Robin; Taylor, Maxwell D.; Harper, William; DeMasi, Amy; Kyker-Snowman, Emily; Veremeeva, Alexandra; Schirrmeister, Lutz; Harden, Jennifer

2013-01-01

This digital database is the product of collaboration between the U.S. Geological Survey, the Geophysical Institute at the University of Alaska, Fairbanks; the Los Altos Hills Foothill College GeoSpatial Technology Certificate Program; the Alfred Wegener Institute for Polar and Marine Research, Potsdam, Germany; and the Institute of Physical Chemical and Biological Problems in Soil Science of the Russian Academy of Sciences. The primary goal for creating this digital database is to enhance current estimates of soil organic carbon stored in deep permafrost, in particular the late Pleistocene syngenetic ice-rich permafrost deposits of the Yedoma Suite. Previous studies estimated that Yedoma deposits cover about 1 million square kilometers of a large region in central and eastern Siberia, but these estimates generally are based on maps with scales smaller than 1:10,000,000. Taking into account this large area, it was estimated that Yedoma may store as much as 500 petagrams of soil organic carbon, a large part of which is vulnerable to thaw and mobilization from thermokarst and erosion. To refine assessments of the spatial distribution of Yedoma deposits, we digitized 11 Russian Quaternary geologic maps. Our study focused on extracting geologic units interpreted by us as late Pleistocene ice-rich syngenetic Yedoma deposits based on lithology, ground ice conditions, stratigraphy, and geomorphological and spatial association. These Yedoma units then were merged into a single data layer across map tiles. The spatial database provides a useful update of the spatial distribution of this deposit for an approximately 2.32 million square kilometers land area in Siberia that will (1) serve as a core database for future refinements of Yedoma distribution in additional regions, and (2) provide a starting point to revise the size of deep but thaw-vulnerable permafrost carbon pools in the Arctic based on surface geology and the distribution of cryolithofacies types at high spatial resolution. However, we recognize that the extent of Yedoma deposits presented in this database is not complete for a global assessment, because Yedoma deposits also occur in the Taymyr lowlands and Chukotka, and in parts of Alaska and northwestern Canada.

Spatial patterns of mixing in the Solomon Sea

NASA Astrophysics Data System (ADS)

Alberty, M. S.; Sprintall, J.; MacKinnon, J.; Ganachaud, A.; Cravatte, S.; Eldin, G.; Germineaud, C.; Melet, A.

2017-05-01

The Solomon Sea is a marginal sea in the southwest Pacific that connects subtropical and equatorial circulation, constricting transport of South Pacific Subtropical Mode Water and Antarctic Intermediate Water through its deep, narrow channels. Marginal sea topography inhibits internal waves from propagating out and into the open ocean, making these regions hot spots for energy dissipation and mixing. Data from two hydrographic cruises and from Argo profiles are employed to indirectly infer mixing from observations for the first time in the Solomon Sea. Thorpe and finescale methods indirectly estimate the rate of dissipation of kinetic energy (ɛ) and indicate that it is maximum in the surface and thermocline layers and decreases by 2-3 orders of magnitude by 2000 m depth. Estimates of diapycnal diffusivity from the observations and a simple diffusive model agree in magnitude but have different depth structures, likely reflecting the combined influence of both diapycnal mixing and isopycnal stirring. Spatial variability of ɛ is large, spanning at least 2 orders of magnitude within isopycnal layers. Seasonal variability of ɛ reflects regional monsoonal changes in large-scale oceanic and atmospheric conditions with ɛ increased in July and decreased in March. Finally, tide power input and topographic roughness are well correlated with mean spatial patterns of mixing within intermediate and deep isopycnals but are not clearly correlated with thermocline mixing patterns.

Evidence for fish dispersal from spatial analysis of stream network topology

USGS Publications Warehouse

Hitt, N.P.; Angermeier, P.L.

2008-01-01

Developing spatially explicit conservation strategies for stream fishes requires an understanding of the spatial structure of dispersal within stream networks. We explored spatial patterns of stream fish dispersal by evaluating how the size and proximity of connected streams (i.e., stream network topology) explained variation in fish assemblage structure and how this relationship varied with local stream size. We used data from the US Environmental Protection Agency's Environmental Monitoring and Assessment Program in wadeable streams of the Mid-Atlantic Highlands region (n = 308 sites). We quantified stream network topology with a continuous analysis based on the rate of downstream flow accumulation from sites and with a discrete analysis based on the presence of mainstem river confluences (i.e., basin area >250 km2) within 20 fluvial km (fkm) from sites. Continuous variation in stream network topology was related to local species richness within a distance of ???10 fkm, suggesting an influence of fish dispersal within this spatial grain. This effect was explained largely by catostomid species, cyprinid species, and riverine species, but was not explained by zoogeographic regions, ecoregions, sampling period, or spatial autocorrelation. Sites near mainstem river confluences supported greater species richness and abundance of catostomid, cyprinid, and ictalurid fishes than did sites >20 fkm from such confluences. Assemblages at sites on the smallest streams were not related to stream network topology, consistent with the hypothesis that local stream size regulates the influence of regional dispersal. These results demonstrate that the size and proximity of connected streams influence the spatial distribution of fish and suggest that these influences can be incorporated into the designs of stream bioassessments and reserves to enhance management efficacy. ?? 2008 by The North American Benthological Society.

Support vector machine in crash prediction at the level of traffic analysis zones: Assessing the spatial proximity effects.

PubMed

Dong, Ni; Huang, Helai; Zheng, Liang

2015-09-01

In zone-level crash prediction, accounting for spatial dependence has become an extensively studied topic. This study proposes Support Vector Machine (SVM) model to address complex, large and multi-dimensional spatial data in crash prediction. Correlation-based Feature Selector (CFS) was applied to evaluate candidate factors possibly related to zonal crash frequency in handling high-dimension spatial data. To demonstrate the proposed approaches and to compare them with the Bayesian spatial model with conditional autoregressive prior (i.e., CAR), a dataset in Hillsborough county of Florida was employed. The results showed that SVM models accounting for spatial proximity outperform the non-spatial model in terms of model fitting and predictive performance, which indicates the reasonableness of considering cross-zonal spatial correlations. The best model predictive capability, relatively, is associated with the model considering proximity of the centroid distance by choosing the RBF kernel and setting the 10% of the whole dataset as the testing data, which further exhibits SVM models' capacity for addressing comparatively complex spatial data in regional crash prediction modeling. Moreover, SVM models exhibit the better goodness-of-fit compared with CAR models when utilizing the whole dataset as the samples. A sensitivity analysis of the centroid-distance-based spatial SVM models was conducted to capture the impacts of explanatory variables on the mean predicted probabilities for crash occurrence. While the results conform to the coefficient estimation in the CAR models, which supports the employment of the SVM model as an alternative in regional safety modeling. Copyright © 2015 Elsevier Ltd. All rights reserved.

Seismicity Pattern Changes before the M = 4.8 Aeolian Archipelago (Italy) Earthquake of August 16, 2010

PubMed Central

2014-01-01

We investigated the seismicity patterns associated with an M = 4.8 earthquake recorded in the Aeolian Archipelago on 16, August, 2010, by means of the region-time-length (RTL) algorithm. This earthquake triggered landslides at Lipari; a rock fall on the flanks of the Vulcano, Lipari, and Salina islands, and some damages to the village of Lipari. The RTL algorithm is widely used for investigating precursory seismicity changes before large and moderate earthquakes. We examined both the spatial and temporal characteristics of seismicity changes in the Aeolian Archipelago region before the M = 4.8 earthquake. The results obtained reveal 6-7 months of seismic quiescence which started about 15 months before the earthquake. The spatial distribution shows an extensive area characterized by seismic quiescence that suggests a relationship between quiescence and the Aeolian Archipelago regional tectonics. PMID:24511288

Multi-scale integration and predictability in resting state brain activity

PubMed Central

Kolchinsky, Artemy; van den Heuvel, Martijn P.; Griffa, Alessandra; Hagmann, Patric; Rocha, Luis M.; Sporns, Olaf; Goñi, Joaquín

2014-01-01

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales. PMID:25104933

A critical look at spatial scale choices in satellite-based aerosol indirect effect studies

NASA Astrophysics Data System (ADS)

Grandey, B. S.; Stier, P.

2010-12-01

Analysing satellite datasets over large regions may introduce spurious relationships between aerosol and cloud properties due to spatial variations in aerosol type, cloud regime and synoptic regime climatologies. Using MODerate resolution Imaging Spectroradiometer data, we calculate relationships between aerosol optical depth τa derived liquid cloud droplet effective number concentration Ne and liquid cloud droplet effective radius re at different spatial scales. Generally, positive values of dlnNedlnτa are found for ocean regions, whilst negative values occur for many land regions. The spatial distribution of dlnredlnτa shows approximately the opposite pattern, with generally postive values for land regions and negative values for ocean regions. We find that for region sizes larger than 4° × 4°, spurious spatial variations in retrieved cloud and aerosol properties can introduce widespread significant errors to calculations of dlnNedlnτa and dlnredlnτa. For regions on the scale of 60° × 60°, these methodological errors may lead to an overestimate in global cloud albedo effect radiative forcing of order 80% relative to that calculated for regions on the scale of 1° × 1°.

Combining MODIS, MISR, CALIOP, OMI, AERONET, and Models to Identify the Spatial and Temporal Distribution, Characterization, and Magnitude of Missing Urban and Wildfire Emissions Sources throughout Asia.

NASA Astrophysics Data System (ADS)

Cohen, J. B.

2016-12-01

Due to intense and changing levels of emissions as well as highly non-linear chemical processing, the concentrations of aerosols and thus their impacts are not well known. Urban areas consist of the majority of the emissions of these species and their precursors over large periods of time, while wildfires contribute very large spikes, concentrated in space and over a period of weeks to months. Yet due to urban and economic expansion, as well as clouds amd low intensity burning, the spatial and temporal profiles of these species are changing, with both new sources appearing and old sources decreasing. New work incorporates measurements at different spatial andboptical resolutions from MODIS, MISR, and OMI, coupled with new sampling approaches with CALIOP and AERONET to search for, characterize, and spatially and temporally constrain aerosols. An advanced modeling system including aerosol chemistry, physics, optics, and transport, using a multi-modal and both externally mixed and core-shell mixing is used to quantify the magnitudes of these missing sources. Comparisons between the model and additional dozens of ground stations show extreme improvement when these new sources are included. This new approach is shown to identify new source regions of emissions, many of which were previously non-urbanized or were not found to contain any fire hotspots. In addition, the use of new models run under conditions including both missing local sources from regions such as the expanded urban areas in Southeast and East Asia and advanced chemical and aerosol routines, allow for a comprehensive analysis to be performed. The impacts of insitu chemistry, horizontal, and vertical transport of species, both on the Regional and Continental scale are also included. It is shown that for proper identification, especially on intra-annual and inter-annual variations, this approach is a large improvement throughout Asia, ranging from India, to Indonesia, to China and Japan. Results specific to Southern China and Southeast East Asia demonstrate the additional importance of the climate, as additional variations are identified. Such knowledge can allow us to better understand the consequences and impacts of the rapid ongoing changes occurring in these regions.

Image Location Estimation by Salient Region Matching.

PubMed

Qian, Xueming; Zhao, Yisi; Han, Junwei

2015-11-01

Nowadays, locations of images have been widely used in many application scenarios for large geo-tagged image corpora. As to images which are not geographically tagged, we estimate their locations with the help of the large geo-tagged image set by content-based image retrieval. In this paper, we exploit spatial information of useful visual words to improve image location estimation (or content-based image retrieval performances). We proposed to generate visual word groups by mean-shift clustering. To improve the retrieval performance, spatial constraint is utilized to code the relative position of visual words. We proposed to generate a position descriptor for each visual word and build fast indexing structure for visual word groups. Experiments show the effectiveness of our proposed approach.

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions.

PubMed

Pavlacky, David C; Lukacs, Paul M; Blakesley, Jennifer A; Skorkowsky, Robert C; Klute, David S; Hahn, Beth A; Dreitz, Victoria J; George, T Luke; Hanni, David J

2017-01-01

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer's sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer's sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical design and analyses ensures reliable knowledge about bird populations that is relevant and integral to bird conservation at multiple scales.

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions

PubMed Central

Hahn, Beth A.; Dreitz, Victoria J.; George, T. Luke

2017-01-01

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer’s sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer’s sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical design and analyses ensures reliable knowledge about bird populations that is relevant and integral to bird conservation at multiple scales. PMID:29065128

Regional climate model sensitivity to domain size

NASA Astrophysics Data System (ADS)

Leduc, Martin; Laprise, René

2009-05-01

Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions (LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving data, unless large scale nudging is applied. The issue of domain size is studied here by using the “perfect model” approach. This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC. The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 × 100 grid points). The permanent “spatial spin-up” corresponds to the characteristic distance that the large-scale flow needs to travel before developing small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere.

Spatial forecasting of switchgrass productivity under current and future climate change scenarios

USDA-ARS?s Scientific Manuscript database

Evaluating the potential of alternative energy crops across large geographic regions and over time is necessary to determine if feedstock production is feasible and sustainable in the face of growing production demands and climatic change. Panicum virgatum L., a perennial herbaceous grass, is a prom...

Effects of image spatial and radiometric resolutions on the detection of cotton plants

USDA-ARS?s Scientific Manuscript database

Accurate and timely detection of volunteer and regrowth cotton plants is important for the eradication of boll weevils in south Texas. Airborne remote sensing imagery has the potential to identify volunteer and regrowth cotton plants over large geographic regions. The objective of this study was to ...

: “Developing Regional Modeling Techniques Applicable for Simulating Future Climate Conditions in the Carolinas”

EPA Science Inventory

Global climate models (GCMs) are currently used to obtain information about future changes in the large-scale climate. However, such simulations are typically done at coarse spatial resolutions, with model grid boxes on the order of 100 km on a horizontal side. Therefore, techniq...

Invasion complexity at large spatial scales is an emergent property of interactions among landscape characteristics and invader traits

USDA-ARS?s Scientific Manuscript database

Understanding the potential for invasive spread is an important consideration for novel agricultural species that may be translocated or introduced into new regions. However, estimating invasion risks remains a challenging problem, particularly in the context of real, complex landscapes. There is ...

Landscape Assessment (LA)

Treesearch

Carl H. Key; Nathan C. Benson

2006-01-01

Landscape Assessment primarily addresses the need to identify and quantify fire effects over large areas, at times involving many burns. In contrast to individual case studies, the ability to compare results is emphasized along with the capacity to aggregate information across broad regions and over time. Results show the spatial heterogeneity of burns and how fire...

Accuracy assessment of NOAA's daily reference evapotranspiration maps for the Texas High Plains

USDA-ARS?s Scientific Manuscript database

The National Oceanic and Atmospheric Administration (NOAA) provides daily reference ET for the continental U.S. using climatic data from North American Land Data Assimilation System (NLDAS). This data provides large scale spatial representation for reference ET, which is essential for regional scal...

Spatial and numerical relationships of arthropod communities associated with key pests of maize

USDA-ARS?s Scientific Manuscript database

Pest management largely focuses on managing individual pest species with little concern for the diverse communities that co-occur with key pests and potentially shape their population dynamics. During anthesis, we described the foliar arthropod communities on 53 maize farms throughout the region of ...

Estimating occupancy probability of moose using hunter survey data

USGS Publications Warehouse

Crum, Nathan J.; Fuller, Angela K.; Sutherland, Christopher S.; Cooch, Evan G.; Hurst, Jeremy E.

2017-01-01

Monitoring rare species can be difficult, especially across large spatial extents, making conventional methods of population monitoring costly and logistically challenging. Citizen science has the potential to produce observational data across large areas that can be used to monitor wildlife distributions using occupancy models. We used citizen science (i.e., hunter surveys) to facilitate monitoring of moose (Alces alces) populations, an especially important endeavor because of their recent apparent declines in the northeastern and upper midwestern regions of the United States. To better understand patterns of occurrence of moose in New York, we used data collected through an annual survey of approximately 11,000 hunters between 2012 and 2014 that recorded detection–non-detection data of moose and other species. We estimated patterns of occurrence of moose in relation to land cover characteristics, climate effects, and interspecific interactions using occupancy models to analyze spatially referenced moose observations. Coniferous and deciduous forest with low prevalence of white-tailed deer (Odocoileus virginianus) had the highest probability of moose occurrence. This study highlights the potential of data collected using citizen science for understanding the spatial distribution of low-density species across large spatial extents and providing key information regarding where and when future research and management activities should be focused.

High-Resolution Subtropical Summer Precipitation Derived from Dynamical Downscaling of the NCEP-DOE Reanalysis: How Much Small-Scale Information Is Added by a Regional Model?

NASA Technical Reports Server (NTRS)

Lim, Young-Kwon; Stefanova, Lydia B.; Chan, Steven C.; Schubert, Siegfried D.; OBrien, James J.

2010-01-01

This study assesses the regional-scale summer precipitation produced by the dynamical downscaling of analyzed large-scale fields. The main goal of this study is to investigate how much the regional model adds smaller scale precipitation information that the large-scale fields do not resolve. The modeling region for this study covers the southeastern United States (Florida, Georgia, Alabama, South Carolina, and North Carolina) where the summer climate is subtropical in nature, with a heavy influence of regional-scale convection. The coarse resolution (2.5deg latitude/longitude) large-scale atmospheric variables from the National Center for Environmental Prediction (NCEP)/DOE reanalysis (R2) are downscaled using the NCEP Environmental Climate Prediction Center regional spectral model (RSM) to produce precipitation at 20 km resolution for 16 summer seasons (19902005). The RSM produces realistic details in the regional summer precipitation at 20 km resolution. Compared to R2, the RSM-produced monthly precipitation shows better agreement with observations. There is a reduced wet bias and a more realistic spatial pattern of the precipitation climatology compared with the interpolated R2 values. The root mean square errors of the monthly R2 precipitation are reduced over 93 (1,697) of all the grid points in the five states (1,821). The temporal correlation also improves over 92 (1,675) of all grid points such that the domain-averaged correlation increases from 0.38 (R2) to 0.55 (RSM). The RSM accurately reproduces the first two observed eigenmodes, compared with the R2 product for which the second mode is not properly reproduced. The spatial patterns for wet versus dry summer years are also successfully simulated in RSM. For shorter time scales, the RSM resolves heavy rainfall events and their frequency better than R2. Correlation and categorical classification (above/near/below average) for the monthly frequency of heavy precipitation days is also significantly improved by the RSM.

Boreal spring precipitation variability in the cold arid western Himalaya during the last millennium, regional linkages, and socio-economic implications

NASA Astrophysics Data System (ADS)

Yadava, Akhilesh K.; Bräuning, Achim; Singh, Jayendra; Yadav, Ram R.

2016-07-01

Precipitation in the monsoon shadow zone of the western Himalayan region, largely under the influence of mid-latitude westerlies, is the dominant regional socioeconomic driver. Current knowledge of long-term regional precipitation variability is scarce due to spatially and temporally limited weather and high-resolution proxy climate records. We developed the first boreal spring precipitation reconstruction for the western Himalaya covering the last millennium (1030-2011 C.E.). The annually resolved reconstruction is based on a large tree-ring data set of Himalayan cedar (Cedrus deodara) and neoza pine (Pinus gerardiana) from 16 ecologically homogeneous moisture stressed settings in Kinnaur, western Indian Himalaya. The precipitation reconstruction revealed persistent long-term spring droughts from the 12th to early 16th century C.E. and pluvial from the late 16th century C.E. to recent decades. The late 15th and early 16th centuries (1490-1514 C.E.) displayed the driest episode, with precipitation being ∼15% lower than the long-term mean. The early 19th century (1820-1844 C.E.) was the wettest period of the past millennium, with mean precipitation ∼13% above the long-term mean. The reconstructed boreal spring precipitation from the western Himalaya revealed large-scale consistency with hydrological records from westerly dominated regions in Central Asia, indicating synoptic-scale changes in atmospheric circulation during the major part of the Medieval and Little Ice Age periods. Protracted droughts in Central Asia could have caused severe contraction of the regional economy, as indicated by striking coherence of reconstructed drought periods and historic social upheavals and invasions of India from Central and Western Asian invaders. Vulnerability to climatic extremes underpins the need to develop a better understanding of the temporal and spatial variability in regional hydroclimate in order to devise viable water resource management plans.

Ghost reefs: Nautical charts document large spatial scale of coral reef loss over 240 years

PubMed Central

McClenachan, Loren; O’Connor, Grace; Neal, Benjamin P.; Pandolfi, John M.; Jackson, Jeremy B. C.

2017-01-01

Massive declines in population abundances of marine animals have been documented over century-long time scales. However, analogous loss of spatial extent of habitat-forming organisms is less well known because georeferenced data are rare over long time scales, particularly in subtidal, tropical marine regions. We use high-resolution historical nautical charts to quantify changes to benthic structure over 240 years in the Florida Keys, finding an overall loss of 52% (SE, 6.4%) of the area of the seafloor occupied by corals. We find a strong spatial dimension to this decline; the spatial extent of coral in Florida Bay and nearshore declined by 87.5% (SE, 7.2%) and 68.8% (SE, 7.5%), respectively, whereas that of offshore areas of coral remained largely intact. These estimates add to finer-scale loss in live coral cover exceeding 90% in some locations in recent decades. The near-complete elimination of the spatial coverage of nearshore coral represents an underappreciated spatial component of the shifting baseline syndrome, with important lessons for other species and ecosystems. That is, modern surveys are typically designed to assess change only within the species’ known, extant range. For species ranging from corals to sea turtles, this approach may overlook spatial loss over longer time frames, resulting in both overly optimistic views of their current conservation status and underestimates of their restoration potential. PMID:28913420

[Soil and forest structure in the Colombian Amazon].

PubMed

Calle-Rendón, Bayron R; Moreno, Flavio; Cárdenas López, Dairon

2011-09-01

Forests structural differences could result of environmental variations at different scales. Because soils are an important component of plant's environment, it is possible that edaphic and structural variables are associated and that, in consequence, spatial autocorrelation occurs. This paper aims to answer two questions: (1) are structural and edaphic variables associated at local scale in a terra firme forest of Colombian Amazonia? and (2) are these variables regionalized at the scale of work? To answer these questions we analyzed the data of a 6ha plot established in a terra firme forest of the Amacayacu National Park. Structural variables included basal area and density of large trees (diameter > or = 10cm) (Gdos and Ndos), basal area and density of understory individuals (diameter < 10cm) (Gsot and Nsot) and number of species of large trees (sp). Edaphic variables included were pH, organic matter, P, Mg, Ca, K, Al, sand, silt and clay. Structural and edaphic variables were reduced through a principal component analysis (PCA); then, the association between edaphic and structural components from PCA was evaluated by multiple regressions. The existence of regionalization of these variables was studied through isotropic variograms, and autocorrelated variables were spatially mapped. PCA found two significant components for structure, corresponding to the structure of large trees (G, Gdos, Ndos and sp) and of small trees (N, Nsot and Gsot), which explained 43.9% and 36.2% of total variance, respectively. Four components were identified for edaphic variables, which globally explained 81.9% of total variance and basically represent drainage and soil fertility. Regression analyses were significant (p < 0.05) and showed that the structure of both large and small trees is associated with greater sand contents and low soil fertility, though they explained a low proportion of total variability (R2 was 4.9% and 16.5% for the structure of large trees and small tress, respectively). Variables with spatial autocorrelation were the structure of small trees, Al, silt, and sand. Among them, Nsot and sand content showed similar patterns of spatial distribution inside the plot.

High-Resolution Climate Data Visualization through GIS- and Web-based Data Portals

NASA Astrophysics Data System (ADS)

WANG, X.; Huang, G.

2017-12-01

Sound decisions on climate change adaptation rely on an in-depth assessment of potential climate change impacts at regional and local scales, which usually requires finer resolution climate projections at both spatial and temporal scales. However, effective downscaling of global climate projections is practically difficult due to the lack of computational resources and/or long-term reference data. Although a large volume of downscaled climate data has been make available to the public, how to understand and interpret the large-volume climate data and how to make use of the data to drive impact assessment and adaptation studies are still challenging for both impact researchers and decision makers. Such difficulties have become major barriers preventing informed climate change adaptation planning at regional scales. Therefore, this research will explore new GIS- and web-based technologies to help visualize the large-volume regional climate data with high spatiotemporal resolutions. A user-friendly public data portal, named Climate Change Data Portal (CCDP, http://ccdp.network), will be established to allow intuitive and open access to high-resolution regional climate projections at local scales. The CCDP offers functions of visual representation through geospatial maps and data downloading for a variety of climate variables (e.g., temperature, precipitation, relative humidity, solar radiation, and wind) at multiple spatial resolutions (i.e., 25 - 50 km) and temporal resolutions (i.e., annual, seasonal, monthly, daily, and hourly). The vast amount of information the CCDP encompasses can provide a crucial basis for assessing impacts of climate change on local communities and ecosystems and for supporting better decision making under a changing climate.

Three Dimensional High-Resolution Reconstruction of the Ionosphere Over the Very Large Array

DTIC Science & Technology

2010-12-15

Watts Progress Report, Dec 10; 1 Final Report: Three Dimensional High-Resolution Reconstruction of the Ionosphere over the Very Large Array...proposed research is reconstruct the three-dimensional regional electron density profile of Earth’s ionosphere with spatial resolution of better than 10 km...10x better sensitivity to total electron content (TEC, or chord integrated density) in the ionosphere that does GPS. The proposal funds the

Spatial Patterns in Biogeochemical Processes During Peak Growing Season in Oiled and Unoiled Louisiana Salt Marshes: A Multi-Year Analysis

NASA Astrophysics Data System (ADS)

Chelsky, A.; Marton, J. M.; Bernhard, A. E.; Giblin, A. E.; Setta, S. P.; Hill, T. D.; Roberts, B. J.

2016-02-01

Louisiana salt marshes are important sites for carbon and nitrogen cycling because they can mitigate fluxes of nutrients and carbon to the Gulf of Mexico where a large hypoxic zone develops annually. The aim of this study was to investigate spatial and temporal patterns of biogeochemical processes in Louisiana coastal wetlands during peak growing season, and to investigate whether the Deepwater Horizon oil spill resulted in persistent changes to these rates. We measured nitrification potential and sediment characteristics at two pairs of oiled/unoiled marshes in three regions across the Louisiana coast (Terrebonne and east and west Barataria Bay) in July from 2012 to 2015, with plots along a gradient from the salt marsh edge to the interior. Rates of nitrification potential across the coast (overall mean of 901 ± 115 nmol gdw-1 d-1 from 2012-2014) were high compared to other published rates for salt marshes but displayed high variability at the plot level (4 orders of magnitude). Within each region interannual means varied by factors of 2-5. Nitrification potential did not differ with oiling history, but did display consistent spatial patterns within each region that corresponded to changes in relative elevation and inundation, which influence patterns of soil properties and microbial communities. In 2015, we also measured greenhouse gas (CO2, N2O and CH4) production and denitrification enzyme activity rates in addition to nitrification potential across the region to investigate spatial relationships between these processes.

Regional zooplankton dispersal provides spatial insurance for ecosystem function.

PubMed

Symons, Celia C; Arnott, Shelley E

2013-05-01

Changing environmental conditions are affecting diversity and ecosystem function globally. Theory suggests that dispersal from a regional species pool may buffer against changes in local community diversity and ecosystem function after a disturbance through the establishment of functionally redundant tolerant species. The spatial insurance provided by dispersal may decrease through time after environmental change as the local community monopolizes resources and reduces community invasibility. To test for evidence of the spatial insurance hypothesis and to determine the role dispersal timing plays in this response we conducted a field experiment using crustacean zooplankton communities in a subarctic region that is expected to be highly impacted by climate change - Churchill, Canada. Three experiments were conducted where nutrients, salt, and dispersal were manipulated. The three experiments differed in time-since-disturbance that the dispersers were added. We found that coarse measures of diversity (i.e. species richness, evenness, and Shannon-Weiner diversity) were generally resistant to large magnitude disturbances, and that dispersal had the most impact on diversity when dispersers were added shortly after disturbance. Ecosystem functioning (chl-a) was degraded in disturbed communities, but dispersal recovered ecosystem function to undisturbed levels. This spatial insurance for ecosystem function was mediated through changes in community composition and the relative abundance of functional groups. Results suggest that regional diversity and habitat connectivity will be important in the future to maintain ecosystem function by introducing functionally redundant species to promote compensatory dynamics. © 2012 Blackwell Publishing Ltd.

A refined regional modeling approach for the Corn Belt - Experiences and recommendations for large-scale integrated modeling

NASA Astrophysics Data System (ADS)

Panagopoulos, Yiannis; Gassman, Philip W.; Jha, Manoj K.; Kling, Catherine L.; Campbell, Todd; Srinivasan, Raghavan; White, Michael; Arnold, Jeffrey G.

2015-05-01

Nonpoint source pollution from agriculture is the main source of nitrogen and phosphorus in the stream systems of the Corn Belt region in the Midwestern US. This region is comprised of two large river basins, the intensely row-cropped Upper Mississippi River Basin (UMRB) and Ohio-Tennessee River Basin (OTRB), which are considered the key contributing areas for the Northern Gulf of Mexico hypoxic zone according to the US Environmental Protection Agency. Thus, in this area it is of utmost importance to ensure that intensive agriculture for food, feed and biofuel production can coexist with a healthy water environment. To address these objectives within a river basin management context, an integrated modeling system has been constructed with the hydrologic Soil and Water Assessment Tool (SWAT) model, capable of estimating river basin responses to alternative cropping and/or management strategies. To improve modeling performance compared to previous studies and provide a spatially detailed basis for scenario development, this SWAT Corn Belt application incorporates a greatly refined subwatershed structure based on 12-digit hydrologic units or 'subwatersheds' as defined by the US Geological Service. The model setup, calibration and validation are time-demanding and challenging tasks for these large systems, given the scale intensive data requirements, and the need to ensure the reliability of flow and pollutant load predictions at multiple locations. Thus, the objectives of this study are both to comprehensively describe this large-scale modeling approach, providing estimates of pollution and crop production in the region as well as to present strengths and weaknesses of integrated modeling at such a large scale along with how it can be improved on the basis of the current modeling structure and results. The predictions were based on a semi-automatic hydrologic calibration approach for large-scale and spatially detailed modeling studies, with the use of the Sequential Uncertainty Fitting algorithm (SUFI-2) and the SWAT-CUP interface, followed by a manual water quality calibration on a monthly basis. The refined modeling approach developed in this study led to successful predictions across most parts of the Corn Belt region and can be used for testing pollution mitigation measures and agricultural economic scenarios, providing useful information to policy makers and recommendations on similar efforts at the regional scale.

Parameterizing a Large-scale Water Balance Model in Regions with Sparse Data: The Tigris-Euphrates River Basins as an Example

NASA Astrophysics Data System (ADS)

Flint, A. L.; Flint, L. E.

2010-12-01

The characterization of hydrologic response to current and future climates is of increasing importance to many countries around the world that rely heavily on changing and uncertain water supplies. Large-scale models that can calculate a spatially distributed water balance and elucidate groundwater recharge and surface water flows for large river basins provide a basis of estimates of changes due to future climate projections. Unfortunately many regions in the world have very sparse data for parameterization or calibration of hydrologic models. For this study, the Tigris and Euphrates River basins were used for the development of a regional water balance model at 180-m spatial scale, using the Basin Characterization Model, to estimate historical changes in groundwater recharge and surface water flows in the countries of Turkey, Syria, Iraq, Iran, and Saudi Arabia. Necessary input parameters include precipitation, air temperature, potential evapotranspiration (PET), soil properties and thickness, and estimates of bulk permeability from geologic units. Data necessary for calibration includes snow cover, reservoir volumes (from satellite data and historic, pre-reservoir elevation data) and streamflow measurements. Global datasets for precipitation, air temperature, and PET were available at very large spatial scales (50 km) through the world scale databases, finer scale WorldClim climate data, and required downscaling to fine scales for model input. Soils data were available through world scale soil maps but required parameterization on the basis of textural data to estimate soil hydrologic properties. Soil depth was interpreted from geomorphologic interpretation and maps of quaternary deposits, and geologic materials were categorized from generalized geologic maps of each country. Estimates of bedrock permeability were made on the basis of literature and data on driller’s logs and adjusted during calibration of the model to streamflow measurements where available. Results of historical water balance calculations throughout the Tigris and Euphrates River basins will be shown along with details of processing input data to provide spatial continuity and downscaling. Basic water availability analysis for recharge and runoff is readily available from a determinisitic solar radiation energy balance model and a global potential evapotranspiration model and global estimates of precipitation and air temperature. Future climate estimates can be readily applied to the same water and energy balance models to evaluate future water availability for countries around the globe.

Spatio-temporal variation of methane over Indian region: Seasonal and inter-annual variation .

NASA Astrophysics Data System (ADS)

M, K.; Nair, P. R.

2015-12-01

Methane (CH4) has an important role in the radiation budget and chemistry in the lower and middle atmosphere as a greenhouse and reactive trace gas. The rapid developments in the agriculture and industry over India have lead to the emission of many pollutants like CO, O3, CH4, CO2, SO2 etc into the atmosphere. However, their sources, sinks and concentration levels are poorly understood because of the lack of systematic sampling and monitoring. The advent of satellite remote sensing has helped to analyze the chemical composition of atmosphere with good spatial coverage especially over tropical region which was poorly sampled with the existing surface network. This work attempts an analysis of spatial distribution, seasonal cycle and inter annual variation of CH4 over Indian region during 2003-2009 using SCIAMACHY data onboard ENVISAT. Column CH4 varies from 1740-1890 ppbv over Indian region with distinct spatial and temporal features. We observed a dependence of seasonal CH4 variation on rice cultivation, convective activities and changes in boundary layer characteristics. The comparative study using satellite, aircraft and surface measurement shown CH4 has non-homogeneity in its distribution and seasonal variation in different layers of atmosphere. A comparative study of CH4 at different hot spot regions over the globe was carried out which showed prominent hemispherical variations. Large spread in column CH4 was observed at India and Chinese region compared to other regions with a significant seasonal variability. This study points to the blending of satellite, aircraft and surface measurements for the realization of regional distribution of CH4.

Extended-range high-resolution dynamical downscaling over a continental-scale spatial domain with atmospheric and surface nudging

NASA Astrophysics Data System (ADS)

Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.

2014-12-01

Extended-range high-resolution mesoscale simulations with limited-area atmospheric models when applied to downscale regional analysis fields over large spatial domains can provide valuable information for many applications including the weather-dependent renewable energy industry. Long-term simulations over a continental-scale spatial domain, however, require mechanisms to control the large-scale deviations in the high-resolution simulated fields from the coarse-resolution driving fields. As enforcement of the lateral boundary conditions is insufficient to restrict such deviations, large scales in the simulated high-resolution meteorological fields are therefore spectrally nudged toward the driving fields. Different spectral nudging approaches, including the appropriate nudging length scales as well as the vertical profiles and temporal relaxations for nudging, have been investigated to propose an optimal nudging strategy. Impacts of time-varying nudging and generation of hourly analysis estimates are explored to circumvent problems arising from the coarse temporal resolution of the regional analysis fields. Although controlling the evolution of the atmospheric large scales generally improves the outputs of high-resolution mesoscale simulations within the surface layer, the prognostically evolving surface fields can nevertheless deviate from their expected values leading to significant inaccuracies in the predicted surface layer meteorology. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil moisture, and snow conditions, toward their expected values obtained from a high-resolution offline surface scheme is therefore proposed to limit any considerable deviation. Finally, wind speed and temperature at wind turbine hub height predicted by different spectrally nudged extended-range simulations are compared against observations to demonstrate possible improvements achievable using higher spatiotemporal resolution.

Spatial Access to Primary Care Providers in Appalachia

PubMed Central

Donohoe, Joseph; Marshall, Vince; Tan, Xi; Camacho, Fabian T.; Anderson, Roger T.; Balkrishnan, Rajesh

2016-01-01

Purpose: The goal of this research was to examine spatial access to primary care physicians in Appalachia using both traditional access measures and the 2-step floating catchment area (2SFCA) method. Spatial access to care was compared between urban and rural regions of Appalachia. Methods: The study region included Appalachia counties of Pennsylvania, Ohio, Kentucky, and North Carolina. Primary care physicians during 2008 and total census block group populations were geocoded into GIS software. Ratios of county physicians to population, driving time to nearest primary care physician, and various 2SFCA approaches were compared. Results: Urban areas of the study region had shorter travel times to their closest primary care physician. Provider to population ratios produced results that varied widely from one county to another because of strict geographic boundaries. The 2SFCA method produced varied results depending on the distance decay weight and variable catchment size techniques chose. 2SFCA scores showed greater access to care in urban areas of Pennsylvania, Ohio, and North Carolina. Conclusion: The different parameters of the 2SFCA method—distance decay weights and variable catchment sizes—have a large impact on the resulting spatial access to primary care scores. The findings of this study suggest that using a relative 2SFCA approach, the spatial access ratio method, when detailed patient travel data are unavailable. The 2SFCA method shows promise for measuring access to care in Appalachia, but more research on patient travel preferences is needed to inform implementation. PMID:26906524

RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

NASA Astrophysics Data System (ADS)

Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

2005-10-01

Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and spatial statistics. The tool also includes some fundamental spatial and non-spatial database in regional population and environment, which can be updated by external database via CD or network. Utilizing this data mining and exploratory analytical tool, the users can easily and quickly analyse the huge mount of the interrelated regional data, and better understand the spatial patterns and trends of the regional development, so as to make a credible and scientific decision. Moreover, it can be used as an educational tool for spatial data analysis and environmental studies. In this paper, we also present a case study on Poyang Lake Basin as an application of the tool and spatial data mining in complex environmental studies. At last, several concluding remarks are discussed.

Spatial Analysis of Large Woody Debris Arrangement in a Midwestern U.S. River System: Geomorphic Implications and Influences

NASA Astrophysics Data System (ADS)

Martin, D. J.

2013-12-01

Large woody debris (LWD) is universally recognized as a key component of the geomorphological and ecological function of fluvial systems and has been increasingly incorporated into stream restoration and watershed management projects. However, 'natural' processes of recruitment and the subsequent arrangement of LWD within the river network are poorly understood and are thus, rarely a management consideration. Additionally, LWD research tends to be regionally biased toward mountainous regions, and scale biased toward the micro-scale. In many locations, the lack of understanding has led to the failure of restoration/rehabilitation projects that involved the use of LWD. This research uses geographic information systems and spatial analysis techniques to investigate longitudinal arrangement patterns of LWD in a low-gradient, Midwestern river. A large-scale GPS inventory of LWD was performed on the Big River, located in the eastern Missouri Ozarks resulting in over 5,000 logged positions of LWD along seven river segments covering nearly 100 km of the 237 km river system. A time series analysis framework was used to statistically identify longitudinal spatial patterns of LWD arrangement along the main stem of the river, and correlation analyses were performed to help identify physical controls of those patterns. Results indicate that upstream segments have slightly lower densities than downstream segments, with the exception of the farthest upstream segment. Results also show lack of an overall longitudinal trend in LWD density; however, periodogram analysis revealed an inherent periodicity in LWD arrangement. Periodicities were most evident in the downstream segments with frequencies ranging from 3 km to 7 km. Additionally, Pearson correlation analysis, performed within the segment displaying the strongest periodic behavior, show that LWD densities are correlated with channel sinuosity (r=0.25). Ongoing research is investigating further relationships between arrangement patterns and geomorphic and riparian variables. Understanding these spatial patterns and relationships will provide valuable insight into the application of LWD-related stream and watershed management practices, and fill a necessary regional knowledge gap in our understanding of LWD's role in fluvial processes.

Tau, amyloid, and cascading network failure across the Alzheimer's disease spectrum.

PubMed

Jones, David T; Graff-Radford, Jonathan; Lowe, Val J; Wiste, Heather J; Gunter, Jeffrey L; Senjem, Matthew L; Botha, Hugo; Kantarci, Kejal; Boeve, Bradley F; Knopman, David S; Petersen, Ronald C; Jack, Clifford R

2017-12-01

Functionally related brain regions are selectively vulnerable to Alzheimer's disease pathophysiology. However, molecular markers of this pathophysiology (i.e., beta-amyloid and tau aggregates) have discrepant spatial and temporal patterns of progression within these selectively vulnerable brain regions. Existing reductionist pathophysiologic models cannot account for these large-scale spatiotemporal inconsistencies. Within the framework of the recently proposed cascading network failure model of Alzheimer's disease, however, these large-scale patterns are to be expected. This model postulates the following: 1) a tau-associated, circumscribed network disruption occurs in brain regions specific to a given phenotype in clinically normal individuals; 2) this disruption can trigger phenotype independent, stereotypic, and amyloid-associated compensatory brain network changes indexed by changes in the default mode network; 3) amyloid deposition marks a saturation of functional compensation and portends an acceleration of the inciting phenotype specific, and tau-associated, network failure. With the advent of in vivo molecular imaging of tau pathology, combined with amyloid and functional network imaging, it is now possible to investigate the relationship between functional brain networks, tau, and amyloid across the disease spectrum within these selectively vulnerable brain regions. In a large cohort (n = 218) spanning the Alzheimer's disease spectrum from young, amyloid negative, cognitively normal subjects to Alzheimer's disease dementia, we found several distinct spatial patterns of tau deposition, including 'Braak-like' and 'non-Braak-like', across functionally related brain regions. Rather than arising focally and spreading sequentially, elevated tau signal seems to occur system-wide based on inferences made from multiple cross-sectional analyses we conducted looking at regional patterns of tau signal. Younger age-of-disease-onset was associated with 'non-Braak-like' patterns of tau, suggesting an association with atypical clinical phenotypes. As predicted by the cascading network failure model of Alzheimer's disease, we found that amyloid is a partial mediator of the relationship between functional network failure and tau deposition in functionally connected brain regions. This study implicates large-scale brain networks in the pathophysiology of tau deposition and offers support to models incorporating large-scale network physiology into disease models linking tau and amyloid, such as the cascading network failure model of Alzheimer's disease. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach?

USGS Publications Warehouse

Archfield, Stacey A.; Pugliese, Alessio; Castellarin, Attilio; Skøien, Jon O.; Kiang, Julie E.

2013-01-01

In the United States, estimation of flood frequency quantiles at ungauged locations has been largely based on regional regression techniques that relate measurable catchment descriptors to flood quantiles. More recently, spatial interpolation techniques of point data have been shown to be effective for predicting streamflow statistics (i.e., flood flows and low-flow indices) in ungauged catchments. Literature reports successful applications of two techniques, canonical kriging, CK (or physiographical-space-based interpolation, PSBI), and topological kriging, TK (or top-kriging). CK performs the spatial interpolation of the streamflow statistic of interest in the two-dimensional space of catchment descriptors. TK predicts the streamflow statistic along river networks taking both the catchment area and nested nature of catchments into account. It is of interest to understand how these spatial interpolation methods compare with generalized least squares (GLS) regression, one of the most common approaches to estimate flood quantiles at ungauged locations. By means of a leave-one-out cross-validation procedure, the performance of CK and TK was compared to GLS regression equations developed for the prediction of 10, 50, 100 and 500 yr floods for 61 streamgauges in the southeast United States. TK substantially outperforms GLS and CK for the study area, particularly for large catchments. The performance of TK over GLS highlights an important distinction between the treatments of spatial correlation when using regression-based or spatial interpolation methods to estimate flood quantiles at ungauged locations. The analysis also shows that coupling TK with CK slightly improves the performance of TK; however, the improvement is marginal when compared to the improvement in performance over GLS.

Determining the spatial variability of wetland soil bulk density, organic matter, and the conversion factor between organic matter and organic carbon across coastal Louisiana, U.S.A.

USGS Publications Warehouse

Wang, Hongqing; Piazza, Sarai C.; Sharp, Leigh A.; Stagg, Camille L.; Couvillion, Brady R.; Steyer, Gregory D.; McGinnis, Thomas E.

2016-01-01

Soil bulk density (BD), soil organic matter (SOM) content, and a conversion factor between SOM and soil organic carbon (SOC) are often used in estimating SOC sequestration and storage. Spatial variability in BD, SOM, and the SOM–SOC conversion factor affects the ability to accurately estimate SOC sequestration, storage, and the benefits (e.g., land building area and vertical accretion) associated with wetland restoration efforts, such as marsh creation and sediment diversions. There are, however, only a few studies that have examined large-scale spatial variability in BD, SOM, and SOM–SOC conversion factors in coastal wetlands. In this study, soil cores, distributed across the entire coastal Louisiana (approximately 14,667 km2) were used to examine the regional-scale spatial variability in BD, SOM, and the SOM–SOC conversion factor. Soil cores for BD and SOM analyses were collected during 2006–09 from 331 spatially well-distributed sites in the Coastwide Reference Monitoring System network. Soil cores for the SOM–SOC conversion factor analysis were collected from 15 sites across coastal Louisiana during 2006–07. Results of a split-plot analysis of variance with incomplete block design indicated that BD and SOM varied significantly at a landscape level, defined by both hydrologic basins and vegetation types. Vertically, BD and SOM varied significantly among different vegetation types. The SOM–SOC conversion factor also varied significantly at the landscape level. This study provides critical information for the assessment of the role of coastal wetlands in large regional carbon budgets and the estimation of carbon credits from coastal restoration.

Estimating Long Term Surface Soil Moisture in the GCIP Area From Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Vrije; VandeGriend, Adriaan A.

2000-01-01

Soil moisture is an important component of the water and energy balances of the Earth's surface. Furthermore, it has been identified as a parameter of significant potential for improving the accuracy of large-scale land surface-atmosphere interaction models. However, accurate estimates of surface soil moisture are often difficult to make, especially at large spatial scales. Soil moisture is a highly variable land surface parameter, and while point measurements are usually accurate, they are representative only of the immediate site which was sampled. Simple averaging of point values to obtain spatial means often leads to substantial errors. Since remotely sensed observations are already a spatially averaged or areally integrated value, they are ideally suited for measuring land surface parameters, and as such, are a logical input to regional or larger scale land process models. A nine-year database of surface soil moisture is being developed for the Central United States from satellite microwave observations. This region forms much of the GCIP study area, and contains most of the Mississippi, Rio Grande, and Red River drainages. Daytime and nighttime microwave brightness temperatures were observed at a frequency of 6.6 GHz, by the Scanning Multichannel Microwave Radiometer (SMMR), onboard the Nimbus 7 satellite. The life of the SMMR instrument spanned from Nov. 1978 to Aug. 1987. At 6.6 GHz, the instrument provided a spatial resolution of approximately 150 km, and an orbital frequency over any pixel-sized area of about 2 daytime and 2 nighttime passes per week. Ground measurements of surface soil moisture from various locations throughout the study area are used to calibrate the microwave observations. Because ground measurements are usually only single point values, and since the time of satellite coverage does not always coincide with the ground measurements, the soil moisture data were used to calibrate a regional water balance for the top 1, 5, and 10 cm surface layers in order to interpolate daily surface moisture values. Such a climate-based approach is often more appropriate for estimating large-area spatially averaged soil moisture because meteorological data are generally more spatially representative than isolated point measurements of soil moisture. Vegetation radiative transfer characteristics, such as the canopy transmissivity, were estimated from vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the 37 GHz Microwave Polarization Difference Index (MPDI). Passive microwave remote sensing presents the greatest potential for providing regular spatially representative estimates of surface soil moisture at global scales. Real time estimates should improve weather and climate modelling efforts, while the development of historical data sets will provide necessary information for simulation and validation of long-term climate and global change studies.

Global Mapping of Provisioning Ecosystem Services

NASA Astrophysics Data System (ADS)

Bingham, Lisa; Straatsma, Menno; Karssenberg, Derek

2016-04-01

Attributing monetary value to ecosystem services for decision-making has become more relevant as a basis for decision-making. There are a number of problematic aspects of the calculations, including consistency of economy represented (e.g., purchasing price, production price) and determining which ecosystem subservices to include in a valuation. While several authors have proposed methods for calculating ecosystem services and calculations are presented for global and regional studies, the calculations are mostly broken down into biomes and regions without showing spatially explicit results. The key to decision-making for governments is to be able to make spatial-based decisions because a large spatial variation may exist within a biome or region. Our objective was to compute the spatial distribution of global ecosystem services based on 89 subservices. Initially, only the provisioning ecosystem service category is presented. The provisioning ecosystem service category was calculated using 6 ecosystem services (food, water, raw materials, genetic resources, medical resources, and ornaments) divided into 41 subservices. Global data sets were obtained from a variety of governmental and research agencies for the year 2005 because this is the most data complete and recent year available. All data originated either in tabular or grid formats and were disaggregated to 10 km cell length grids. A lookup table with production values by subservice by country were disaggregated over the economic zone (either marine, land, or combination) based on the spatial existence of the subservice (e.g. forest cover, crop land, non-arable land). Values express the production price in international dollars per hectare. The ecosystem services and the ecosystem service category(ies) maps may be used to show spatial variation of a service within and between countries as well as to specifically show the values within specific regions (e.g. countries, continents), biomes (e.g. coastal, forest), or hazardous regions (e.g. landslides, flood plains, war zones). A preliminary example of the provisioning ecosystem service category illustrates the valuation of deltaic regions and a second example illustrates the valuation of the subservice category of food production prices in flood zones. Future work of this research will spatially represent the calculations of the remaining three ecosystem service categories (regulating, habitat, cultural) and investigate the propagation of uncertainty of the input data to ecosystem service maps.

Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach

USGS Publications Warehouse

Bled, Florent; Sauer, John R.; Pardieck, Keith L.; Doherty, Paul; Royle, J. Andy

2013-01-01

Population trends, defined as interval-specific proportional changes in population size, are often used to help identify species of conservation interest. Efficient modeling of such trends depends on the consideration of the correlation of population changes with key spatial and environmental covariates. This can provide insights into causal mechanisms and allow spatially explicit summaries at scales that are of interest to management agencies. We expand the hierarchical modeling framework used in the North American Breeding Bird Survey (BBS) by developing a spatially explicit model of temporal trend using a conditional autoregressive (CAR) model. By adopting a formal spatial model for abundance, we produce spatially explicit abundance and trend estimates. Analyses based on large-scale geographic strata such as Bird Conservation Regions (BCR) can suffer from basic imbalances in spatial sampling. Our approach addresses this issue by providing an explicit weighting based on the fundamental sample allocation unit of the BBS. We applied the spatial model to three species from the BBS. Species have been chosen based upon their well-known population change patterns, which allows us to evaluate the quality of our model and the biological meaning of our estimates. We also compare our results with the ones obtained for BCRs using a nonspatial hierarchical model (Sauer and Link 2011). Globally, estimates for mean trends are consistent between the two approaches but spatial estimates provide much more precise trend estimates in regions on the edges of species ranges that were poorly estimated in non-spatial analyses. Incorporating a spatial component in the analysis not only allows us to obtain relevant and biologically meaningful estimates for population trends, but also enables us to provide a flexible framework in order to obtain trend estimates for any area.

Spatial distribution of random velocity inhomogeneities in the western part of Nankai subduction zone

NASA Astrophysics Data System (ADS)

Takahashi, T.; Obana, K.; Yamamoto, Y.; Nakanishi, A.; Kodaira, S.; Kaneda, Y.

2011-12-01

In the Nankai trough, there are three seismogenic zones of megathrust earthquakes (Tokai, Tonankai and Nankai earthquakes). Lithospheric structures in and around these seismogenic zones are important for the studies on mutual interactions and synchronization of their fault ruptures. Recent studies on seismic wave scattering at high frequencies (>1Hz) make it possible to estimate 3D distributions of random inhomogeneities (or scattering coefficient) in the lithosphere, and clarified that random inhomogeneity is one of the important medium properties related to microseismicity and damaged structure near the fault zone [Asano & Hasegawa, 2004; Takahashi et al. 2009]. This study estimates the spatial distribution of the power spectral density function (PSDF) of random inhomogeneities the western part of Nankai subduction zone, and examines the relations with crustal velocity structure and seismic activity. Seismic waveform data used in this study are those recorded at seismic stations of Hi-net & F-net operated by NIED, and 160 ocean bottom seismographs (OBSs) deployed at Hyuga-nada region from Dec. 2008 to Jan. 2009. This OBS observation was conducted by JAMSTEC as a part of "Research concerning Interaction Between the Tokai, Tonankai and Nankai Earthquakes" funded by Ministry of Education, Culture, Sports, Science and Technology, Japan. Spatial distribution of random inhomogeneities is estimated by the inversion analysis of the peak delay time of small earthquakes [Takahashi et al. 2009], where the peak delay time is defined as the time lag from the S-wave onset to its maximal amplitude arrival. We assumed the von Karman type functional form for the PSDF. Peak delay times are measured from root mean squared envelopes at 4-8Hz, 8-16Hz and 16-32Hz. Inversion result can be summarized as follows. Random inhomogeneities beneath the Quaternary volcanoes are characterized by strong inhomogeneities at small spatial scale (~ a few hundreds meter) and weak spectral gradient. Those in the Hyuga-nada region are characterized by the strong inhomogeneities at large spatial wavelength and steep spectral gradient. Random inhomogeneities in the Hyuga-nada region are similar with those in the frontal arc high in northern Izu-Bonin arc, which is thought to be a remnant arc that is presently inactive [Takahashi et al. 2011]. This coincidence implies the existence of subducted Kyushu-Palau ridge in this anomaly of random inhomogeneities, which is also suggested by the seismic refraction survey in this region [Nakanishi et al. 2010 AGU Fall Mtg.]. Source rupture areas of large earthquakes (M>6) in Hyuga-nada regions tend to locate around this anomaly of inhomogeneities. We may say that this anomalously inhomogeneous region is a structural factor affecting the seismic activity in Hyuga-nada region.

Phase-dependent outbreak dynamics of geometrid moth linked to host plant phenology.

PubMed

Jepsen, Jane U; Hagen, Snorre B; Karlsen, Stein-Rune; Ims, Rolf A

2009-12-07

Climatically driven Moran effects have often been invoked as the most likely cause of regionally synchronized outbreaks of insect herbivores without identifying the exact mechanism. However, the degree of match between host plant and larval phenology is crucial for the growth and survival of many spring-feeding pest insects, suggesting that a phenological match/mismatch-driven Moran effect may act as a synchronizing agent. We analyse the phase-dependent spatial dynamics of defoliation caused by cyclically outbreaking geometrid moths in northern boreal birch forest in Fennoscandia through the most recent massive outbreak (2000-2008). We use satellite-derived time series of the prevalence of moth defoliation and the onset of the growing season for the entire region to investigate the link between the patterns of defoliation and outbreak spread. In addition, we examine whether a phase-dependent coherence in the pattern of spatial synchrony exists between defoliation and onset of the growing season, in order to evaluate if the degree of matching phenology between the moth and their host plant could be the mechanism behind a Moran effect. The strength of regional spatial synchrony in defoliation and the pattern of defoliation spread were both highly phase-dependent. The incipient phase of the outbreak was characterized by high regional synchrony in defoliation and long spread distances, compared with the epidemic and crash phase. Defoliation spread was best described using a two-scale stratified spread model, suggesting that defoliation spread is governed by two processes operating at different spatial scale. The pattern of phase-dependent spatial synchrony was coherent in both defoliation and onset of the growing season. This suggests that the timing of spring phenology plays a role in the large-scale synchronization of birch forest moth outbreaks.

Phase-dependent outbreak dynamics of geometrid moth linked to host plant phenology

PubMed Central

Jepsen, Jane U.; Hagen, Snorre B.; Karlsen, Stein-Rune; Ims, Rolf A.

2009-01-01

Climatically driven Moran effects have often been invoked as the most likely cause of regionally synchronized outbreaks of insect herbivores without identifying the exact mechanism. However, the degree of match between host plant and larval phenology is crucial for the growth and survival of many spring-feeding pest insects, suggesting that a phenological match/mismatch-driven Moran effect may act as a synchronizing agent. We analyse the phase-dependent spatial dynamics of defoliation caused by cyclically outbreaking geometrid moths in northern boreal birch forest in Fennoscandia through the most recent massive outbreak (2000–2008). We use satellite-derived time series of the prevalence of moth defoliation and the onset of the growing season for the entire region to investigate the link between the patterns of defoliation and outbreak spread. In addition, we examine whether a phase-dependent coherence in the pattern of spatial synchrony exists between defoliation and onset of the growing season, in order to evaluate if the degree of matching phenology between the moth and their host plant could be the mechanism behind a Moran effect. The strength of regional spatial synchrony in defoliation and the pattern of defoliation spread were both highly phase-dependent. The incipient phase of the outbreak was characterized by high regional synchrony in defoliation and long spread distances, compared with the epidemic and crash phase. Defoliation spread was best described using a two-scale stratified spread model, suggesting that defoliation spread is governed by two processes operating at different spatial scale. The pattern of phase-dependent spatial synchrony was coherent in both defoliation and onset of the growing season. This suggests that the timing of spring phenology plays a role in the large-scale synchronization of birch forest moth outbreaks. PMID:19740876

Isoscapes of tree-ring carbon-13 perform like meteorological networks in predicting regional precipitation patterns

NASA Astrophysics Data System (ADS)

del Castillo, Jorge; Aguilera, Mònica; Voltas, Jordi; Ferrio, Juan Pedro

2013-03-01

isotopes in tree rings provide climatic information with annual resolution dating back for centuries or even millennia. However, deriving spatially explicit climate models from isotope networks remains challenging. Here we propose a methodology to model regional precipitation from carbon isotope discrimination (Δ13C) in tree rings by (1) building regional spatial models of Δ13C (isoscapes) and (2) deriving precipitation maps from Δ13C-isoscapes, taking advantage of the response of Δ13C to precipitation in seasonally dry climates. As a case study, we modeled the spatial distribution of mean annual precipitation (MAP) in the northeastern Iberian Peninsula, a region with complex topography and climate (MAP = 303-1086 mm). We compiled wood Δ13C data for two Mediterranean species that exhibit complementary responses to seasonal precipitation (Pinus halepensis Mill., N = 38; Quercus ilex L.; N = 44; pooling period: 1975-2008). By combining multiple regression and geostatistical interpolation, we generated one Δ13 C-isoscape for each species. A spatial model of MAP was then built as the sum of two complementary maps of seasonal precipitation, each one derived from the corresponding Δ13C-isoscape (September-November from Q. ilex; December-August from P. halepensis). Our approach showed a predictive power for MAP (RMSE = 84 mm) nearly identical to that obtained by interpolating data directly from a similarly dense network of meteorological stations (RMSE = 80-83 mm, N = 65), being only outperformed when using a much denser meteorological network (RMSE = 56-57 mm, N = 340). This method offers new avenues for modeling spatial variability of past precipitation, exploiting the large amount of information currently available from tree-ring networks.

Observation of spatial and temporal variations in X-ray bright point emergence patterns. [at solar surface

NASA Technical Reports Server (NTRS)

Golub, L.; Krieger, A. S.; Vaiana, G. S.

1976-01-01

Observations of X-ray bright points (XBP) over a six-month interval in 1973 show significant variations in both the number density of XBP as a function of heliographic longitude and in the full-sun average number of XBP from one rotation to the next. The observed increases in XBP emergence are estimated to be equivalent to several large active regions emerging per day for several months. The number of XBP emerging at high latitudes varies in phase with the low-latitude variation and reaches a maximum approximately simultaneous with a major outbreak of active regions. The quantity of magnetic flux emerging in the form of XBP at high latitudes alone is estimated to be as large as the contribution from all active regions.

Assessment of climate change impacts on runoff in China using climate elasticity and multiple CMIP5 GCMs

NASA Astrophysics Data System (ADS)

Wu, C.; Hu, B. X.; Wang, P.; Xu, K.

2017-12-01

The occurrence of climate warming is unequivocal and is expected to alter the temporal-spatial patterns of regional water resources. Based on the long-term (1960-2012) water budget data and climate projections from 28 Global Climate Models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results indicate a large spatial variation in precipitation (P) elasticity (from 1.2 to 3.3) and potential evaporation (PET) elasticity (from -2.3 to -0.2) across China. The P elasticity is larger in northeast and western China than in southern China, while the opposite occurs for PET elasticity. Climate projections suggest that there is large uncertainty involved among the GCM simulations, but most project a consistent change in P (or PET) over China at the mean annual scale. During the future period of 2071-2100, the mean annual P will likely increase in most parts of China particularly the western regions, while the mean annual PET will likely increase in the whole China especially the southern regions due to future increases in temperature. Moreover, larger increases are projected for higher emission scenarios. Compared with the baseline 1971-2000, the arid regions and humid regions of China will likely become wetter and drier in the period 2071-2100, respectively.

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.

Practicability of monitoring soil Cd, Hg, and Pb pollution based on a geochemical survey in China.

PubMed

Xia, Xueqi; Yang, Zhongfang; Li, Guocheng; Yu, Tao; Hou, Qingye; Mutelo, Admire Muchimamui

2017-04-01

Repeated visiting, i.e., sampling and analysis at two or more temporal points, is one of the important ways of monitoring soil heavy metal contamination. However, with the concern about the cost, determination of the number of samples and the temporal interval, and their capability to detect a certain change is a key technical problem to be solved. This depends on the spatial variation of the parameters in the monitoring units. The "National Multi-Purpose Regional Geochemical Survey" (NMPRGS) project in China, acquired the spatial distribution of heavy metals using a high density sampling method in the most arable regions in China. Based on soil Cd, Hg, and Pb data and taking administrative regions as the monitoring units, the number of samples and temporal intervals that may be used for monitoring soil heavy metal contamination were determined. It was found that there is a large variety of spatial variation of the elements in each NMPRGS region. This results in the difficulty in the determination of the minimum detectable changes (MDC), the number of samples, and temporal intervals for revisiting. This paper recommends a suitable set of the number of samples (n r ) for each region under the balance of cost, practicability, and monitoring precision. Under n r , MDC values are acceptable for all the regions, and the minimum temporal intervals are practical with the range of 3.3-13.3 years. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessment of the performance of CORDEX-SA experiments in simulating seasonal mean temperature over the Himalayan region for the present climate: Part I

NASA Astrophysics Data System (ADS)

Nengker, T.; Choudhary, A.; Dimri, A. P.

2018-04-01

The ability of an ensemble of five regional climate models (hereafter RCMs) under Coordinated Regional Climate Downscaling Experiments-South Asia (hereafter, CORDEX-SA) in simulating the key features of present day near surface mean air temperature (Tmean) climatology (1970-2005) over the Himalayan region is studied. The purpose of this paper is to understand the consistency in the performance of models across the ensemble, space and seasons. For this a number of statistical measures like trend, correlation, variance, probability distribution function etc. are applied to evaluate the performance of models against observation and simultaneously the underlying uncertainties between them for four different seasons. The most evident finding from the study is the presence of a large cold bias (-6 to -8 °C) which is systematically seen across all the models and across space and time over the Himalayan region. However, these RCMs with its fine resolution perform extremely well in capturing the spatial distribution of the temperature features as indicated by a consistently high spatial correlation (greater than 0.9) with the observation in all seasons. In spite of underestimation in simulated temperature and general intensification of cold bias with increasing elevation the models show a greater rate of warming than the observation throughout entire altitudinal stretch of study region. During winter, the simulated rate of warming gets even higher at high altitudes. Moreover, a seasonal response of model performance and its spatial variability to elevation is found.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

The Middle Atmosphere Program: Winter In Northern Europe (MAP/WINE)

NASA Technical Reports Server (NTRS)

Vonzahn, U.

1982-01-01

The goals of map/wind (winter in Northern Europe) are to better understand: (1) the interaction of planetary waves of tropospheric origin; (2) the temporal and spatial development of sudden stratospheric warmings; (3) the temporal and spatial development of mesospheric cooling events in conjunction with stratospheric warmings; (4) the vertical and horizontal transport of minor constituents; (5) the effects on the chemistry of neutral and charged species of the large temperature changes occurring during stratospheric warmings and mesospheric cooling; (6) sources of turbulent energy; (7) the temporal and spatial development of turbulent layers; and (8) the contributions of dynamical processes to the heating and cooling of the mesospheric and turbopause region.

The research and development of water resources management information system based on ArcGIS

NASA Astrophysics Data System (ADS)

Cui, Weiqun; Gao, Xiaoli; Li, Yuzhi; Cui, Zhencai

According to that there are large amount of data, complexity of data type and format in the water resources management, we built the water resources calculation model and established the water resources management information system based on the advanced ArcGIS and Visual Studio.NET development platform. The system can integrate the spatial data and attribute data organically, and manage them uniformly. It can analyze spatial data, inquire by map and data bidirectionally, provide various charts and report forms automatically, link multimedia information, manage database etc. . So it can provide spatial and static synthetical information services for study, management and decision of water resources, regional geology and eco-environment etc..

Spatial patterns of multidrug resistant tuberculosis and relationships to socio-economic, demographic and household factors in northwest Ethiopia.

PubMed

Alene, Kefyalew Addis; Viney, Kerri; McBryde, Emma S; Clements, Archie C A

2017-01-01

Understanding the geographical distribution of multidrug-resistant tuberculosis (MDR-TB) in high TB burden countries such as Ethiopia is crucial for effective control of TB epidemics in these countries, and thus globally. We present the first spatial analysis of multidrug resistant tuberculosis, and its relationship to socio-economic, demographic and household factors in northwest Ethiopia. An ecological study was conducted using data on patients diagnosed with MDR-TB at the University of Gondar Hospital MDR-TB treatment centre, for the period 2010 to 2015. District level population data were extracted from the Ethiopia National and Regional Census Report. Spatial autocorrelation was explored using Moran's I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate Poisson regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using a Bayesian Markov chain Monte Carlo (MCMC) simulation approach with Gibbs sampling, in WinBUGS. A total of 264 MDR-TB patients were included in the analysis. The overall crude incidence rate of MDR-TB for the six-year period was 3.0 cases per 100,000 population. The highest incidence rate was observed in Metema (21 cases per 100,000 population) and Humera (18 cases per 100,000 population) districts; whereas nine districts had zero cases. Spatial clustering of MDR-TB was observed in districts located in the Ethiopia-Sudan and Ethiopia-Eritrea border regions, where large numbers of seasonal migrants live. Spatial clustering of MDR-TB was positively associated with urbanization (RR: 1.02; 95%CI: 1.01, 1.04) and the percentage of men (RR: 1.58; 95% CI: 1.26, 1.99) in the districts; after accounting for these factors there was no residual spatial clustering. Spatial clustering of MDR-TB, fully explained by demographic factors (urbanization and percent male), was detected in the border regions of northwest Ethiopia, in locations where seasonal migrants live and work. Cross-border initiatives including options for mobile TB treatment and follow up are important for the effective control of MDR-TB in the region.

Spatial heterogeneity of the structure and stress field in Hyuga-nada region, southwest Japan, deduced from onshore and offshore seismic observations

NASA Astrophysics Data System (ADS)

Uehira, K.; Yakiwara, H.; Yamada, T.; Umakoshi, K.; Nakao, S.; Kobayashi, R.; Goto, K.; Miyamachi, H.; Mochizuki, K.; Nakahigashi, K.; Shinohara, M.; Kanazawa, T.; Hino, R.; Goda, M.; Shimizu, H.

2010-12-01

In Hyuga-nada region, the Philippine Sea (PHS) plate is subducting beneath the Eurasian (EU) plate (the southwest Japan arc) along the Nankai trough at a rate of about 5 cm per year. The seismic activity in the boundary between the PHS and the Eurasian (EU) plates varies spatially along the Nankai trough. Especially the region from off coast of Shikoku to the Bungo channel and Hyuga-nada has large variation of seismicity. Although usual microearthquake activity is active in Hyuga-nada, it is inactive near Shikoku. On the other hand, although the great earthquake (M>8) has occurred repeatedly in near Shikoku at intervals of about 100 years, in Hyuga-nada, smaller earthquakes (M7 class) has occurred at intervals of about dozens of years, and so plate coupling varies dozens of kilometers specially. Big earthquakes (M7 class) have occurred in the north region from latitude 31.6 degrees north, but it has not occurred in the south region from latitude 31.6 degrees north. The largest earthquake ever recorded in Hyuga-nada region is the 1968 Hyuga-nada earthquake (Mw 7.5). And microseismicity varies spatially. It is important to understand seismic activity, stress field, and structure in such region in order to understand seismic cycle. We performed extraordinary seismic observation in and around Hyuga-nada region. More than 20 pop-up type OBSs were deployed above hypocentral region of Hyuga-nada using Nagasaki-maru and several data loggers were deployed in order to compensate a regular seismic network on land. We detected earthquakes more than 2 times of JMA. Seismic activity in source region of the 1961 Hyuga-nada Earthquake (M7.0) is low, but around its source region, seismic activity is very high. In order to obtain a 3D seismic velocity structure and precise hypocenter distribution and focal mechanisms around the Hyuga-nada region, we used Double-Difference (DD) Tomography method developed by Zhang and Thurber (2003). We could detect the structure of subduction of Kyushu-Palau Ridge at low seismicity area. We estimated the stress filed using a stress tensor inversion method by polarity of first arrivals from earthquakes [Horiuchi et al. (1995)], and we found that there is a good correlation between the slip distribution at large earthquakes and the angle between maximum principal axis and the plate boundary in northern part of Hyuga-nada region [Uehira et al. (2007)]. Because the shear stress of plate boundary is large on the subducted Kyushu-Palau Ridge, we suspected that it might be caused the strong interplate coupling. We also found a subducted seamount in the southwest margin of source region of the 1968 Hyuga-nada earthquake (Mw 7.5). This may acts as a barrier.

Spatial Patterns of Snow Cover in North Carolina: Surface and Satellite Perspectives

NASA Technical Reports Server (NTRS)

Fuhrmann, Christopher M.; Hall, Dorothy K.; Perry, L. Baker; Riggs, George A.

2010-01-01

Snow mapping is a common practice in regions that receive large amounts of snowfall annually, have seasonally-continuous snow cover, and where snowmelt contributes significantly to the hydrologic cycle. Although higher elevations in the southern Appalachian Mountains average upwards of 100 inches of snow annually, much of the remainder of the Southeast U.S. receives comparatively little snowfall (< 10 inches). Recent snowy winters in the region have provided an opportunity to assess the fine-grained spatial distribution of snow cover and the physical processes that act to limit or improve its detection across the Southeast. In the present work, both in situ and remote sensing data are utilized to assess the spatial distribution of snow cover for a sample of recent snowfall events in North Carolina. Specifically, this work seeks to determine how well ground measurements characterize the fine-grained patterns of snow cover in relation to Moderate- Resolution Imaging Spectroradiometer (MODIS) snow cover products (in this case, the MODIS Fractional Snow Cover product).

Study of diffusion and local structure of sodium-silicate liquid: the molecular dynamic simulation

NASA Astrophysics Data System (ADS)

Hung, Pham Khac; Noritake, Fumiya; San, Luyen Thi; Van, To Ba; Vinh, Le The

2017-10-01

A systematic analysis on sodium-silicate melt with various silica contents was carried out. The simulation revealed two diffusion mechanisms occurred in the melt: the bond-breaking and hopping between sites. The local structure was analyzed through T-simplexes. It was revealed that T-clusters have a non-spherical shape and represent the diffusion channel, in which Na atoms are dominant, but no any O atoms are located. The SiO2-poor melt acquires a long channel. In contrast, the SiO2-rich melt consists of unconnected short channels. The simulation also revealed the immobile and mobile regions which differ in local structure and constituent composition. We propose a new CL-function to characterizing the spatial distribution of different atom component. The spatial distribution of mobile and immobile atoms is found quite different. In particular, the immobile atoms are concentrated in high-density regions possessing very large density of immobile atoms. The spatial distribution of mobile atoms in contrast is more homogeneous.

Helicity patterns on the Sun

NASA Astrophysics Data System (ADS)

Pevtsov, A.

Solar magnetic fields exhibit hemispheric preference for negative (pos- itive) helicity in northern (southern) hemisphere. The hemispheric he- licity rule, however, is not very strong, - the patterns of opposite sign helicity were observed on different spatial scales in each hemisphere. For instance, many individual sunspots exhibit patches of opposite he- licity inside the single polarity field. There are also helicity patterns on scales larger than the size of typical active region. Such patterns were observed in distribution of active regions with abnormal (for a give hemisphere) helicity, in large-scale photospheric magnetic fields and coronal flux systems. We will review the observations of large-scale pat- terns of helicity in solar atmosphere and their possible relationship with (sub-)photospheric processes. The emphasis will be on large-scale pho- tospheric magnetic field and solar corona.

Ecosystem CO2 Exchange Across Semiarid Southwestern North America: A Synthesis of Multi-Year Flux Site Observations and its Comparison with Estimates from Terrestrial Biome Models and Remote Sensing

NASA Astrophysics Data System (ADS)

Biederman, J. A.; Scott, R. L.; Goulden, M.; Litvak, M. E.; Kolb, T.; Yepez, E. A.; Garatuza, J.; Oechel, W. C.; Krofcheck, D. J.; Ponce-Campos, G. E.; Bowling, D. R.; Meyers, T. P.; Maurer, G.

2016-12-01

Global carbon cycle studies reveal that semiarid ecosystems dominate the increasing trend and interannual variability of the land CO2 sink. However, the regional terrestrial biome models (TBM) and remote sensing products (RSP) used in large-scale analyses are poorly constrained by ecosystem flux measurements in semiarid regions, which are under-represented in global flux datasets. Here we present eddy covariance measurements from 25 diverse ecosystems in semiarid southwestern North America with ranges in annual precipitation of 100 - 1000 mm, annual temperatures of 2 - 25 °C, and records of 3 - 10 years each (150 site-years in total). We identified seven subregions with unique seasonal dynamics in climate and ecosystem-atmosphere exchange, including net and gross CO2 exchange (photosynthesis and respiration) and evapotranspiration (ET), and we evaluated how well measured dynamics were captured by satellite-based greenness observations of the Enhanced Vegetation Index (EVI). Annual flux integrals were calculated based on site-appropriate ecohydrologic years. Net ecosystem production (NEP) varied between -550 and + 420 g C m-2, highlighting the wide range of regional sink/source function. Annual photosynthesis and respiration were positively related to water availability but were suppressed in warmer years at a given site and at climatically warmer sites, in contrast to positive temperature responses at wetter sites. When precipitation anomalies were spatially coherent across sites (e.g. related to El Niño Southern Oscillation), we found large regional annual anomalies in net and gross CO2 uptake. TBM and RSP were less effective in capturing spatial gradients in mean ET and CO2 exchange across this semiarid region as compared to wetter regions. Measured interannual variability of ET and gross CO2 exchange was 3 - 5 times larger than estimates from TBM or RSP. These results suggest that semiarid regions play an even larger role in regulating interannual variability of the global carbon cycle than currently estimated by models and remote sensing. In on-going work, we expand this spatial-temporal analysis across a broader gradient of water availability using the Fluxnet 2015 dataset.

Surface melt dominates Alaska glacier mass balance

USGS Publications Warehouse

Larsen Chris F,; Burgess, E; Arendt, A.A.; O'Neel, Shad; Johnson, A.J.; Kienholz, C.

2015-01-01

Mountain glaciers comprise a small and widely distributed fraction of the world's terrestrial ice, yet their rapid losses presently drive a large percentage of the cryosphere's contribution to sea level rise. Regional mass balance assessments are challenging over large glacier populations due to remote and rugged geography, variable response of individual glaciers to climate change, and episodic calving losses from tidewater glaciers. In Alaska, we use airborne altimetry from 116 glaciers to estimate a regional mass balance of −75 ± 11 Gt yr−1 (1994–2013). Our glacier sample is spatially well distributed, yet pervasive variability in mass balances obscures geospatial and climatic relationships. However, for the first time, these data allow the partitioning of regional mass balance by glacier type. We find that tidewater glaciers are losing mass at substantially slower rates than other glaciers in Alaska and collectively contribute to only 6% of the regional mass loss.

Large-scale CO J = 1-0 observations of the giant molecular cloud associated with the infrared ring N35 with the Nobeyama 45 m telescope

NASA Astrophysics Data System (ADS)

Torii, Kazufumi; Fujita, Shinji; Matsuo, Mitsuhiro; Nishimura, Atsushi; Kohno, Mikito; Kuriki, Mika; Tsuda, Yuya; Minamidani, Tetsuhiro; Umemoto, Tomofumi; Kuno, Nario; Hattori, Yusuke; Yoshiike, Satoshi; Ohama, Akio; Tachihara, Kengo; Shima, Kazuhiro; Habe, Asao; Fukui, Yasuo

2018-05-01

We report an observational study of the giant molecular cloud (GMC) associated with the Galactic infrared ring-like structure N35 and two nearby H II regions G024.392+00.072 (H II region A) and G024.510-00.060 (H II region B), using the new CO J = 1-0 data obtained as a part of the FOREST Unbiased Galactic Plane Imaging survey with the Nobeyama 45 m telescope (FUGIN) project at a spatial resolution of 21″. Our CO data reveals that the GMC, with a total molecular mass of 2.1 × 106 M⊙, has two velocity components of over ˜10-15 km s-1. The majority of molecular gas in the GMC is included in the lower-velocity component (LVC) at ˜110-114 km s-1, while the higher-velocity components (HVCs) at ˜118-126 km s-1 consist of three smaller molecular clouds which are located near the three H II regions. The LVC and HVCs show spatially complementary distributions along the line-of-sight, despite large velocity separations of ˜5-15 km s-1, and are connected in velocity by the CO emission with intermediate intensities. By comparing the observations with simulations, we discuss a scenario where collisions of the three HVCs with the LVC at velocities of ˜10-15 km s-1 can provide an interpretation of these two observational signatures. The intermediate-velocity features between the LVC and HVCs can be understood as broad bridge features, which indicate the turbulent motion of the gas at the collision interfaces, while the spatially complementary distributions represent the cavities created in the LVC by the HVCs through the collisions. Our model indicates that the three H II regions were formed after the onset of the collisions, and it is therefore suggested that the high-mass star formation in the GMC was triggered by the collisions.

Large-scale changes in network interactions as a physiological signature of spatial neglect

PubMed Central

Baldassarre, Antonello; Ramsey, Lenny; Hacker, Carl L.; Callejas, Alicia; Astafiev, Serguei V.; Metcalf, Nicholas V.; Zinn, Kristi; Rengachary, Jennifer; Snyder, Abraham Z.; Carter, Alex R.; Shulman, Gordon L.

2014-01-01

The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n = 84) heterogeneous sample of first-ever stroke patients (within 1–2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. PMID:25367028

Earthquake precursors: spatial-temporal gravity changes before the great earthquakes in the Sichuan-Yunnan area

NASA Astrophysics Data System (ADS)

Zhu, Yi-Qing; Liang, Wei-Feng; Zhang, Song

2018-01-01

Using multiple-scale mobile gravity data in the Sichuan-Yunnan area, we systematically analyzed the relationships between spatial-temporal gravity changes and the 2014 Ludian, Yunnan Province Ms6.5 earthquake and the 2014 Kangding Ms6.3, 2013 Lushan Ms7.0, and 2008 Wenchuan Ms8.0 earthquakes in Sichuan Province. Our main results are as follows. (1) Before the occurrence of large earthquakes, gravity anomalies occur in a large area around the epicenters. The directions of gravity change gradient belts usually agree roughly with the directions of the main fault zones of the study area. Such gravity changes might reflect the increase of crustal stress, as well as the significant active tectonic movements and surface deformations along fault zones, during the period of gestation of great earthquakes. (2) Continuous significant changes of the multiple-scale gravity fields, as well as greater gravity changes with larger time scales, can be regarded as medium-range precursors of large earthquakes. The subsequent large earthquakes always occur in the area where the gravity changes greatly. (3) The spatial-temporal gravity changes are very useful in determining the epicenter of coming large earthquakes. The large gravity networks are useful to determine the general areas of coming large earthquakes. However, the local gravity networks with high spatial-temporal resolution are suitable for determining the location of epicenters. Therefore, denser gravity observation networks are necessary for better forecasts of the epicenters of large earthquakes. (4) Using gravity changes from mobile observation data, we made medium-range forecasts of the Kangding, Ludian, Lushan, and Wenchuan earthquakes, with especially successful forecasts of the location of their epicenters. Based on the above discussions, we emphasize that medium-/long-term potential for large earthquakes might exist nowadays in some areas with significant gravity anomalies in the study region. Thus, the monitoring should be strengthened.

Entanglement growth after a global quench in free scalar field theory

DOE PAGES

Cotler, Jordan S.; Hertzberg, Mark P.; Mezei, Márk; ...

2016-11-28

We compute the entanglement and Rényi entropy growth after a global quench in various dimensions in free scalar field theory. We study two types of quenches: a boundary state quench and a global mass quench. Both of these quenches are investigated for a strip geometry in 1, 2, and 3 spatial dimensions, and for a spherical geometry in 2 and 3 spatial dimensions. We compare the numerical results for massless free scalars in these geometries with the predictions of the analytical quasiparticle model based on EPR pairs, and find excellent agreement in the limit of large region sizes. As amore » result, at subleading order in the region size, we observe an anomalous logarithmic growth of entanglement coming from the zero mode of the scalar.« less

Entanglement growth after a global quench in free scalar field theory

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

Cotler, Jordan S.; Hertzberg, Mark P.; Mezei, Márk

We compute the entanglement and Rényi entropy growth after a global quench in various dimensions in free scalar field theory. We study two types of quenches: a boundary state quench and a global mass quench. Both of these quenches are investigated for a strip geometry in 1, 2, and 3 spatial dimensions, and for a spherical geometry in 2 and 3 spatial dimensions. We compare the numerical results for massless free scalars in these geometries with the predictions of the analytical quasiparticle model based on EPR pairs, and find excellent agreement in the limit of large region sizes. As amore » result, at subleading order in the region size, we observe an anomalous logarithmic growth of entanglement coming from the zero mode of the scalar.« less

Slitless Solar Spectroscopy

NASA Technical Reports Server (NTRS)

Davila, Joseph M.; Jones, Sahela

2011-01-01

Spectrographs have traditionally suffered from the inability to obtain line intensities, widths, and Doppler shifts over large spatial regions of the Sun quickly because of the narrow instantaneous field of view. This has limited the spectroscopic analysis of rapidly varying solar features like, flares, CME eruptions, coronal jets, and reconnection regions. Imagers have provided high time resolution images of the full Sun with limited spectral resolution. In this paper we present recent advances in deconvolving spectrally dispersed images obtained through broad slits. We use this new theoretical formulation to examine the effectiveness of various potential observing scenarios, spatial and spectral resolutions, signal to noise ratio, and other instrument characteristics. This information will lay the foundation for a new generation of spectral imagers optimized for slitless spectral operation, while retaining the ability to obtain spectral information in transient solar events.

Image Segmentation Analysis for NASA Earth Science Applications

NASA Technical Reports Server (NTRS)

Tilton, James C.

2010-01-01

NASA collects large volumes of imagery data from satellite-based Earth remote sensing sensors. Nearly all of the computerized image analysis of this data is performed pixel-by-pixel, in which an algorithm is applied directly to individual image pixels. While this analysis approach is satisfactory in many cases, it is usually not fully effective in extracting the full information content from the high spatial resolution image data that s now becoming increasingly available from these sensors. The field of object-based image analysis (OBIA) has arisen in recent years to address the need to move beyond pixel-based analysis. The Recursive Hierarchical Segmentation (RHSEG) software developed by the author is being used to facilitate moving from pixel-based image analysis to OBIA. The key unique aspect of RHSEG is that it tightly intertwines region growing segmentation, which produces spatially connected region objects, with region object classification, which groups sets of region objects together into region classes. No other practical, operational image segmentation approach has this tight integration of region growing object finding with region classification This integration is made possible by the recursive, divide-and-conquer implementation utilized by RHSEG, in which the input image data is recursively subdivided until the image data sections are small enough to successfully mitigat the combinatorial explosion caused by the need to compute the dissimilarity between each pair of image pixels. RHSEG's tight integration of region growing object finding and region classification is what enables the high spatial fidelity of the image segmentations produced by RHSEG. This presentation will provide an overview of the RHSEG algorithm and describe how it is currently being used to support OBIA or Earth Science applications such as snow/ice mapping and finding archaeological sites from remotely sensed data.

Application of GIS in exploring spatial dimensions of Efficiency in Competitiveness of Regions

NASA Astrophysics Data System (ADS)

Rahmat, Shahid; Sen, Joy

2017-04-01

Infrastructure is an important component in building competitiveness of a region. Present global scenario of economic slowdown that is led by slump in demand of goods and services and decreasing capacity of government institutions in investing public infrastructure. Strategy of augmenting competitiveness of a region can be built around improving efficient distribution of public infrastructure in the region. This efficiency in the distribution of infrastructure will reduce the burden of government institution and improve the relative output of the region in relative lesser investment. A rigorous literature study followed by an expert opinion survey (RIDIT scores) reveals that Railway, Road, ICTs and Electricity infrastructure is very crucial for better competitiveness of a region. Discussion with Experts in ICTs, Railways and Electricity sectors were conducted to find the issues, hurdles and possible solution for the development of these sectors. In an underdeveloped country like India, there is a large constrain of financial resources, for investment in infrastructure sector. Judicious planning for allocation of resources for infrastructure provisions becomes very important for efficient and sustainable development. Data Envelopment Analysis (DEA) is the mathematical programming optimization tool that measure technical efficiency of the multiple-input and/or multiple-output case by constructing a relative technical efficiency score. This paper tries to utilize DEA to identify the efficiency at which present level of selected components of Infrastructure (Railway, Road, ICTs and Electricity) is utilized in order to build competitiveness of the region. This paper tries to identify a spatial pattern of efficiency of Infrastructure with the help of spatial auto-correlation and Hot-spot analysis in Arc GIS. This analysis leads to policy implications for efficient allocation of financial resources for the provision of infrastructure in the region and building a prerequisite to boost an efficient Regional Competitiveness.

Spatial Analysis of China Province-level Perinatal Mortality

PubMed Central

XIANG, Kun; SONG, Deyong

2016-01-01

Background: Using spatial analysis tools to determine the spatial patterns of China province-level perinatal mortality and using spatial econometric model to examine the impacts of health care resources and different socio-economic factors on perinatal mortality. Methods: The Global Moran’s I index is used to examine whether the spatial autocorrelation exists in selected regions and Moran’s I scatter plot to examine the spatial clustering among regions. Spatial econometric models are used to investigate the spatial relationships between perinatal mortality and contributing factors. Results: The overall Moran’s I index indicates that perinatal mortality displays positive spatial autocorrelation. Moran’s I scatter plot analysis implies that there is a significant clustering of mortality in both high-rate regions and low-rate regions. The spatial econometric models analyses confirm the existence of a direct link between perinatal mortality and health care resources, socio-economic factors. Conclusions: Since a positive spatial autocorrelation has been detected in China province-level perinatal mortality, the upgrading of regional economic development and medical service level will affect the mortality not only in region itself but also its adjacent regions. PMID:27398334

Estimation of regional differences in wind erosion sensitivity in Hungary

NASA Astrophysics Data System (ADS)

Mezősi, G.; Blanka, V.; Bata, T.; Kovács, F.; Meyer, B.

2015-01-01

In Hungary, wind erosion is one of the most serious natural hazards. Spatial and temporal variation in the factors that determine the location and intensity of wind erosion damage are not well known, nor are the regional and local sensitivities to erosion. Because of methodological challenges, no multi-factor, regional wind erosion sensitivity map is available for Hungary. The aim of this study was to develop a method to estimate the regional differences in wind erosion sensitivity and exposure in Hungary. Wind erosion sensitivity was modelled using the key factors of soil sensitivity, vegetation cover and wind erodibility as proxies. These factors were first estimated separately by factor sensitivity maps and later combined by fuzzy logic into a regional-scale wind erosion sensitivity map. Large areas were evaluated by using publicly available data sets of remotely sensed vegetation information, soil maps and meteorological data on wind speed. The resulting estimates were verified by field studies and examining the economic losses from wind erosion as compensated by the state insurance company. The spatial resolution of the resulting sensitivity map is suitable for regional applications, as identifying sensitive areas is the foundation for diverse land development control measures and implementing management activities.

Hybrid Modeling Approach to Estimate Exposures of Hazardous Air Pollutants (HAPs) for the National Air Toxics Assessment (NATA).

PubMed

Scheffe, Richard D; Strum, Madeleine; Phillips, Sharon B; Thurman, James; Eyth, Alison; Fudge, Steve; Morris, Mark; Palma, Ted; Cook, Richard

2016-11-15

A hybrid air quality model has been developed and applied to estimate annual concentrations of 40 hazardous air pollutants (HAPs) across the continental United States (CONUS) to support the 2011 calendar year National Air Toxics Assessment (NATA). By combining a chemical transport model (CTM) with a Gaussian dispersion model, both reactive and nonreactive HAPs are accommodated across local to regional spatial scales, through a multiplicative technique designed to improve mass conservation relative to previous additive methods. The broad scope of multiple pollutants capturing regional to local spatial scale patterns across a vast spatial domain is precedent setting within the air toxics community. The hybrid design exhibits improved performance relative to the stand alone CTM and dispersion model. However, model performance varies widely across pollutant categories and quantifiably definitive performance assessments are hampered by a limited observation base and challenged by the multiple physical and chemical attributes of HAPs. Formaldehyde and acetaldehyde are the dominant HAP concentration and cancer risk drivers, characterized by strong regional signals associated with naturally emitted carbonyl precursors enhanced in urban transport corridors with strong mobile source sector emissions. The multiple pollutant emission characteristics of combustion dominated source sectors creates largely similar concentration patterns across the majority of HAPs. However, reactive carbonyls exhibit significantly less spatial variability relative to nonreactive HAPs across the CONUS.

Using spatial uncertainty to manipulate the size of the attention focus.

PubMed

Huang, Dan; Xue, Linyan; Wang, Xin; Chen, Yao

2016-09-01

Preferentially processing behaviorally relevant information is vital for primate survival. In visuospatial attention studies, manipulating the spatial extent of attention focus is an important question. Although many studies have claimed to successfully adjust attention field size by either varying the uncertainty about the target location (spatial uncertainty) or adjusting the size of the cue orienting the attention focus, no systematic studies have assessed and compared the effectiveness of these methods. We used a multiple cue paradigm with 2.5° and 7.5° rings centered around a target position to measure the cue size effect, while the spatial uncertainty levels were manipulated by changing the number of cueing positions. We found that spatial uncertainty had a significant impact on reaction time during target detection, while the cue size effect was less robust. We also carefully varied the spatial scope of potential target locations within a small or large region and found that this amount of variation in spatial uncertainty can also significantly influence target detection speed. Our results indicate that adjusting spatial uncertainty is more effective than varying cue size when manipulating attention field size.

Assimilation of Satellite Data in Regional Air Quality Models

NASA Technical Reports Server (NTRS)

Mcnider, Richard T.; Norris, William B.; Casey, Daniel; Pleim, Jonathan E.; Roselle, Shawn J.; Lapenta, William M.

1997-01-01

In terms of important uncertainty in regional-scale air-pollution models, probably no other aspect ranks any higher than the current ability to specify clouds and soil moisture on the regional scale. Because clouds in models are highly parameterized, the ability of models to predict the correct spatial and radiative characteristics is highly suspect and subject to large error. The poor representation of cloud fields from point measurements at National Weather Services stations and the almost total absence of surface moisture availability observations has made assimilation of these variables difficult to impossible. Yet, the correct inclusion of clouds and surface moisture are of first-order importance in regional-scale photochemistry.

High Performance Geostatistical Modeling of Biospheric Resources

NASA Astrophysics Data System (ADS)

Pedelty, J. A.; Morisette, J. T.; Smith, J. A.; Schnase, J. L.; Crosier, C. S.; Stohlgren, T. J.

2004-12-01

We are using parallel geostatistical codes to study spatial relationships among biospheric resources in several study areas. For example, spatial statistical models based on large- and small-scale variability have been used to predict species richness of both native and exotic plants (hot spots of diversity) and patterns of exotic plant invasion. However, broader use of geostastics in natural resource modeling, especially at regional and national scales, has been limited due to the large computing requirements of these applications. To address this problem, we implemented parallel versions of the kriging spatial interpolation algorithm. The first uses the Message Passing Interface (MPI) in a master/slave paradigm on an open source Linux Beowulf cluster, while the second is implemented with the new proprietary Xgrid distributed processing system on an Xserve G5 cluster from Apple Computer, Inc. These techniques are proving effective and provide the basis for a national decision support capability for invasive species management that is being jointly developed by NASA and the US Geological Survey.

Solution of the spatial neutral model yields new bounds on the Amazonian species richness

NASA Astrophysics Data System (ADS)

Shem-Tov, Yahav; Danino, Matan; Shnerb, Nadav M.

2017-02-01

Neutral models, in which individual agents with equal fitness undergo a birth-death-mutation process, are very popular in population genetics and community ecology. Usually these models are applied to populations and communities with spatial structure, but the analytic results presented so far are limited to well-mixed or mainland-island scenarios. Here we combine analytic results and numerics to obtain an approximate solution for the species abundance distribution and the species richness for the neutral model on continuous landscape. We show how the regional diversity increases when the recruitment length decreases and the spatial segregation of species grows. Our results are supported by extensive numerical simulations and allow one to probe the numerically inaccessible regime of large-scale systems with extremely small mutation/speciation rates. Model predictions are compared with the findings of recent large-scale surveys of tropical trees across the Amazon basin, yielding new bounds for the species richness (between 13100 and 15000) and the number of singleton species (between 455 and 690).

Projecting Future Urbanization with Prescott College's Spatial Growth Model to Promote Environmental Sustainability and Smart Growth, A Case Study in Atlanta, Georgia

NASA Technical Reports Server (NTRS)

Estes, Maurice G., Jr.; Crosson, William; Limaye, Ashutosh; Johnson, Hoyt; Quattrochi, Dale; Lapenta, William; Khan, Maudood

2006-01-01

Planning is an integral element of good management and necessary to anticipate events not merely respond to them. Projecting the quantity and spatial distribution of urban growth is essential to effectively plan for the delivery of city services and to evaluate potential environmental impacts. The major drivers of growth in large urban areas are increasing population, employment opportunities, and quality of life attractors such as a favorable climate and recreation opportunities. The spatial distribution of urban growth is dictated by the amount and location of developable land, topography, energy and water resources, transportation network, climate change, and the existing land use configuration. The Atlanta region is growing very rapidly both in population and the consumption of forestland or low-density residential development. Air pollution and water availability are significant ongoing environmental issues. The Prescott Spatial Growth Model (SGM) was used to make growth projections for the metropolitan Atlanta region to 2010,2020 and 2030 and results used for environmental assessment in both business as usual and smart growth scenarios. The Prescott SGM is a tool that uses an ESRI ArcView extension and can be applied at the parcel level or more coarse spatial scales and can accommodate a wide range of user inputs to develop any number of growth rules each of which can be weighted depending on growth assumptions. These projections were used in conjunction with meteorological and air quality models to evaluate future environmental impacts. This presentation will focus on the application of the SGM to the 13-County Atlanta Regional Commission planning jurisdiction as a case study. The SGM will be described, including how rule sets are developed and the decision process for allocation of future development to available land use categories. Data inputs required to effectively run the model will be discussed. Spatial growth projections for ten, twenty, and thirty year planning horizons will be presented and results discussed, including regional climate and air quality impacts.

Delineating ecological regions in marine systems: Integrating physical structure and community composition to inform spatial management in the eastern Bering Sea

NASA Astrophysics Data System (ADS)

Baker, Matthew R.; Hollowed, Anne B.

2014-11-01

Characterizing spatial structure and delineating meaningful spatial boundaries have useful applications to understanding regional dynamics in marine systems, and are integral to ecosystem approaches to fisheries management. Physical structure and drivers combine with biological responses and interactions to organize marine systems in unique ways at multiple scales. We apply multivariate statistical methods to define spatially coherent ecological units or ecoregions in the eastern Bering Sea. We also illustrate a practical approach to integrate data on species distribution, habitat structure and physical forcing mechanisms to distinguish areas with distinct biogeography as one means to define management units in large marine ecosystems. We use random forests to quantify the relative importance of habitat and environmental variables to the distribution of individual species, and to quantify shifts in multispecies assemblages or community composition along environmental gradients. Threshold shifts in community composition are used to identify regions with distinct physical and biological attributes, and to evaluate the relative importance of predictor variables to determining regional boundaries. Depth, bottom temperature and frontal boundaries were dominant factors delineating distinct biological communities in this system, with a latitudinal divide at approximately 60°N. Our results indicate that distinct climatic periods will shift habitat gradients and that dynamic physical variables such as temperature and stratification are important to understanding temporal stability of ecoregion boundaries. We note distinct distribution patterns among functional guilds and also evidence for resource partitioning among individual species within each guild. By integrating physical and biological data to determine spatial patterns in community composition, we partition ecosystems along ecologically significant gradients. This may provide a basis for defining spatial management units or serve as a baseline index for analyses of structural shifts in the physical environment, species abundance and distribution, and community dynamics over time.

Spatial application of WEPS for estimating wind erosion in the Pacific Northwest

USDA-ARS?s Scientific Manuscript database

The Wind Erosion Prediction System (WEPS) is used to simulate soil erosion on cropland and was originally designed to run simulations on a field-scale size. This study extended WEPS to run on multiple fields (grids) independently to cover a large region and to conduct an initial investigation to ass...

Remote Control: A Spatial-History of Correspondence Schooling in New South Wales, Australia

ERIC Educational Resources Information Center

Symes, Colin

2012-01-01

In large continental landmasses such as Australia, forms of education, including correspondence schooling, emerged in the early twentieth century that allowed children in remote regions to access education. To make such schooling possible, other "technologies" of state provision were mobilised such as the postal system, rail network, and…

Landscape pattern metrics and regional assessment

Treesearch

Robert V. O' Neill; Kurt H. Riitters; J.D. Wickham; Bruce K. Jones

1999-01-01

The combination of remote imagery data, geographic information systems software, and landscape ecology theory provides a unique basis for monitoring and assessing large-scale ecological systems. The unique feature of the work has been the need to develop interpret quantitative measures of spatial patter-the landscape indices. This article reviews what is known about...

Influence of environment, disturbance, and ownership on forest vegetation of coastal Oregon.

Treesearch

J.L. Ohmann; M.J. Gregory; T.A. Spies

2007-01-01

We used spatial predictions from gradient models to examine the influence of environment, disturbance, and ownership on patterns of forest vegetation biodiversity across a large forested region, the Oregon Coast Range (USA). Gradients in tree species composition were strongly associated with physical environment, especially climate, and insensitive to disturbance. In...

Determination of field-effective soil properties in the tidewater region of North Carolina

Treesearch

J. McFero Grace; R.W. Skaggs

2013-01-01

Soils vary spatially in texture, structure, depth of horizons, and macropores, which can lead to a large variation in soil physical properties. In particular, saturated hydraulic conductivity (Ksat) and drainable porosity are critical properties required to model field hydrology in poorly drained lands. These soil-property values can be measured...

Spatial And Temporal Variability Of Wildland Fire Emissions Over The U.S.

Treesearch

Yongqiang Liu

2003-01-01

Wildland fires release large amounts of particulate matter (PM), CO, S02, NOx,, and Volatile Organic Carbon (VOC), which can cause serious consequence of regional and local air quality (Sandberg et al., 1999). All these components except VOC are the principal pollutants whose emissions are subject to the National Ambient...

Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

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

Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and icemore » core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.« less

Spatial Fingerprints of Community Structure in Human Interaction Network for an Extensive Set of Large-Scale Regions

PubMed Central

Kallus, Zsófia; Barankai, Norbert; Szüle, János; Vattay, Gábor

2015-01-01

Human interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap between the redrawn and the administrative borders. Here we present a similar analysis based on one of the most popular online social networks represented by the ties between more than 5.8 million of its geo-located users. The worldwide coverage of their measured activity allowed us to analyze the large-scale regional subgraphs of entire continents and an extensive set of examples for single countries. We present results for North and South America, Europe and Asia. In our analysis we used the well-established method of modularity clustering after an aggregation of the individual links into a weighted graph connecting equal-area geographical pixels. Our results show fingerprints of both of the opposing forces of dividing local conflicts and of uniting cross-cultural trends of globalization. PMID:25993329

Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

DOE PAGES

Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

2017-11-15

Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and icemore » core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.« less

Spatially resolved mapping of electrical conductivity across individual domain (grain) boundaries in graphene.

PubMed

Clark, Kendal W; Zhang, X-G; Vlassiouk, Ivan V; He, Guowei; Feenstra, Randall M; Li, An-Ping

2013-09-24

All large-scale graphene films contain extended topological defects dividing graphene into domains or grains. Here, we spatially map electronic transport near specific domain and grain boundaries in both epitaxial graphene grown on SiC and CVD graphene on Cu subsequently transferred to a SiO2 substrate, with one-to-one correspondence to boundary structures. Boundaries coinciding with the substrate step on SiC exhibit a significant potential barrier for electron transport of epitaxial graphene due to the reduced charge transfer from the substrate near the step edge. Moreover, monolayer-bilayer boundaries exhibit a high resistance that can change depending on the height of substrate step coinciding at the boundary. In CVD graphene, the resistance of a grain boundary changes with the width of the disordered transition region between adjacent grains. A quantitative modeling of boundary resistance reveals the increased electron Fermi wave vector within the boundary region, possibly due to boundary induced charge density variation. Understanding how resistance change with domain (grain) boundary structure in graphene is a crucial first step for controlled engineering of defects in large-scale graphene films.

Systematic deficiency of aftershocks in areas of high coseismic slip for large subduction zone earthquakes

PubMed Central

Wetzler, Nadav; Lay, Thorne; Brodsky, Emily E.; Kanamori, Hiroo

2018-01-01

Fault slip during plate boundary earthquakes releases a portion of the shear stress accumulated due to frictional resistance to relative plate motions. Investigation of 101 large [moment magnitude (Mw) ≥ 7] subduction zone plate boundary mainshocks with consistently determined coseismic slip distributions establishes that 15 to 55% of all master event–relocated aftershocks with Mw ≥ 5.2 are located within the slip regions of the mainshock ruptures and few are located in peak slip regions, allowing for uncertainty in the slip models. For the preferred models, cumulative deficiency of aftershocks within the central three-quarters of the scaled slip regions ranges from 15 to 45%, increasing with the total number of observed aftershocks. The spatial gradients of the mainshock coseismic slip concentrate residual shear stress near the slip zone margins and increase stress outside the slip zone, driving both interplate and intraplate aftershock occurrence near the periphery of the mainshock slip. The shear stress reduction in large-slip regions during the mainshock is generally sufficient to preclude further significant rupture during the aftershock sequence, consistent with large-slip areas relocking and not rupturing again for a substantial time. PMID:29487902

Remote sensing for studying atmospheric aerosols in Malaysia

NASA Astrophysics Data System (ADS)

Kanniah, Kasturi D.; Kamarul Zaman, Nurul A. F.

2015-10-01

The aerosol system is Southeast Asia is complex and the high concentrations are due to population growth, rapid urbanization and development of SEA countries. Nevertheless, only a few studies have been carried out especially at large spatial extent and on a continuous basis to study atmospheric aerosols in Malaysia. In this review paper we report the use of remote sensing data to study atmospheric aerosols in Malaysia and document gaps and recommend further studies to bridge the gaps. Satellite data have been used to study the spatial and seasonal patterns of aerosol optical depth (AOD) in Malaysia. Satellite data combined with AERONET data were used to delineate different types and sizes of aerosols and to identify the sources of aerosols in Malaysia. Most of the aerosol studies performed in Malaysia was based on station-based PM10 data that have limited spatial coverage. Thus, satellite data have been used to extrapolate and retrieve PM10 data over large areas by correlating remotely sensed AOD with ground-based PM10. Realising the critical role of aerosols on radiative forcing numerous studies have been conducted worldwide to assess the aerosol radiative forcing (ARF). Such studies are yet to be conducted in Malaysia. Although the only source of aerosol data covering large region in Malaysia is remote sensing, satellite observations are limited by cloud cover, orbital gaps of satellite track, etc. In addition, relatively less understanding is achieved on how the atmospheric aerosol interacts with the regional climate system. These gaps can be bridged by conducting more studies using integrated approach of remote sensing, AERONET and ground based measurements.

Regional co-variability of spatial and temporal soil moisture-precipitation coupling in North Africa: an observational perspective

NASA Astrophysics Data System (ADS)

Petrova, Irina Y.; van Heerwaarden, Chiel C.; Hohenegger, Cathy; Guichard, Françoise

2018-06-01

The magnitude and sign of soil moisture-precipitation coupling (SMPC) is investigated using a probability-based approach and 10 years of daily microwave satellite data across North Africa at a 1° horizontal scale. Specifically, the co-existence and co-variability of spatial (i.e. using soil moisture gradients) and temporal (i.e. using soil moisture anomaly) soil moisture effects on afternoon rainfall is explored. The analysis shows that in the semi-arid environment of the Sahel, the negative spatial and the negative temporal coupling relationships do not only co-exist, but are also dependent on one another. Hence, if afternoon rain falls over temporally drier soils, it is likely to be surrounded by a wetter environment. Two regions are identified as SMPC hot spots. These are the south-western part of the domain (7-15° N, 10° W-7° E), with the most robust negative SMPC signal, and the South Sudanese region (5-13° N, 24-34° E). The sign and significance of the coupling in the latter region is found to be largely modulated by the presence of wetlands and is susceptible to the number of long-lived propagating convective systems. The presence of wetlands and an irrigated land area is found to account for about 30 % of strong and significant spatial SMPC in the North African domain. This study provides the first insight into regional variability of SMPC in North Africa, and supports the potential relevance of mechanisms associated with enhanced sensible heat flux and mesoscale variability in surface soil moisture for deep convection development.

"I have often walked down this street before": fMRI studies on the hippocampus and other structures during mental navigation of an old environment.

PubMed

Rosenbaum, R Shayna; Ziegler, Marilyne; Winocur, Gordon; Grady, Cheryl L; Moscovitch, Morris

2004-01-01

The role of the hippocampus in recent spatial memory has been well documented in patients with damage to this structure, but there is now evidence that the hippocampus may not be needed for the storage and recovery of a spatial layout that was experienced long before injury. Such preservation may rely, instead, on a network of dissociable, extra-hippocampal regions implicated in topographical orientation. Using functional magnetic resonance imaging (fMRI), we investigated this hypothesis in healthy individuals with extensive experience navigating in a large-scale urban environment (downtown Toronto). Participants were scanned as they performed mental navigation tasks that emphasized different types of spatial representations. Tasks included proximity judgments, distance judgments, landmark sequencing, and blocked-route problem-solving. The following regions were engaged to varying degrees depending on the processing demands of each task: retrosplenial cortex, believed to be involved in assigning directional significance to locales within a relatively allocentric framework; medial and posterior parietal cortex, concerned with processing space within egocentric coordinates during imagined movement; and regions of prefrontal cortex, present in tasks heavily dependent on working memory. In a second, event-related experiment, a distinct area of inferotemporal cortex was revealed during identification of familiar landmarks relative to unknown buildings in addition to activation of many of those regions identified in the navigation tasks. This result suggests that familiar landmarks are strongly integrated with the spatial context in which they were experienced. Importantly, right medial temporal lobe activity was observed, its magnitude equivalent across all tasks, though the core of the activated region was in the parahippocampal gyrus, barely touching the hippocampus proper. Copyright 2004 Wiley-Liss, Inc.

Clouds across the Arctic: A spatial perspective uniting surface observations of downwelling infrared radiation, reanalyses and education

NASA Astrophysics Data System (ADS)

Cox, Christopher J.

The polar regions serve an important role in the Earth's energy balance by acting as a heat sink for the global climate system. In the Arctic, a complex distribution of continental and oceanic features support large spatial variability in environmental parameters important for climate. Additionally, feedbacks that are unique to the cryosphere cause the region to be very sensitive to climate perturbations. Environmental changes are being observed, including increasing temperatures, reductions in sea ice extent and thickness, melting permafrost, changing atmospheric circulation patterns and changing cloud properties, which may be signaling a shift in climate. Despite these changes, the Arctic remains an understudied region, including with respect to the atmosphere and clouds. A better understanding of cloud properties and their geographical variability is needed to better understand observed changes and to forecast the future state of the system, to support adaptation and mitigation strategies, and understand how Arctic change impacts other regions of the globe. Surface-based observations of the atmosphere are critical measurements in this effort because they are high quality and have high temporal resolution, but there are few atmospheric observatories in the Arctic and the period of record is short. Reanalyses combine assimilated observations with models to fill in spatial and temporal data gaps, and also provide additional model-derived parameters. Reanalyses are spatially comprehensive, but are limited by large uncertainties and biases, in particular with respect to derived parameters. Infrared radiation is a large component of the surface energy budget. Infrared emission from clouds is closely tied to cloud properties, so measurements of the infrared spectrum can be used to retrieve information about clouds and can also be used to investigate the influence clouds have on the surface radiation balance. In this dissertation, spectral infrared radiances and other observations obtained between 2006 and 2012 at three Arctic observatories are used to investigate the spatial and temporal characteristics of cloud properties in the Arctic. The observatory locations are Barrow, Alaska; Eureka, Nunavut, Canada; and Summit Station, Greenland. Additional spatial information is inferred from reanalysis data. Therefore, to establish confidence in analysis results and context for interpretation, the reanalyses are validated using the surface observations in a mutually informative validation-analysis approach. In Chapter 1, a method is developed to convert spectral infrared radiances to downwelling infrared flux. These measurements are used to compare Barrow and Eureka. These sites are then situated in the context of the greater Arctic using the reanalyses. In Chapter 2, spectral infrared radiances are used to obtain a baseline data set of cloud microphysical and optical properties from Eureka. In Chapter 3, downwelling infrared fluxes are obtained from Summit Station using the method from Chapter 1 and are used to develop a new method for reanalysis validation. Comparisons are made between Summit, Barrow and Eureka. Spatial comparisons of cloud infrared influence are made across the Greenland ice sheet using the reanalyses. Chapter 4 reports on an effort to conduct timely and engaging educational programs for high school students in the Arctic, thereby helping to extend the reach of Arctic cloud science beyond research community.

Alpine Grassland Soil Organic Carbon Stock and Its Uncertainty in the Three Rivers Source Region of the Tibetan Plateau

PubMed Central

Chang, Xiaofeng; Wang, Shiping; Cui, Shujuan; Zhu, Xiaoxue; Luo, Caiyun; Zhang, Zhenhua; Wilkes, Andreas

2014-01-01

Alpine grassland of the Tibetan Plateau is an important component of global soil organic carbon (SOC) stocks, but insufficient field observations and large spatial heterogeneity leads to great uncertainty in their estimation. In the Three Rivers Source Region (TRSR), alpine grasslands account for more than 75% of the total area. However, the regional carbon (C) stock estimate and their uncertainty have seldom been tested. Here we quantified the regional SOC stock and its uncertainty using 298 soil profiles surveyed from 35 sites across the TRSR during 2006–2008. We showed that the upper soil (0–30 cm depth) in alpine grasslands of the TRSR stores 2.03 Pg C, with a 95% confidence interval ranging from 1.25 to 2.81 Pg C. Alpine meadow soils comprised 73% (i.e. 1.48 Pg C) of the regional SOC estimate, but had the greatest uncertainty at 51%. The statistical power to detect a deviation of 10% uncertainty in grassland C stock was less than 0.50. The required sample size to detect this deviation at a power of 90% was about 6–7 times more than the number of sample sites surveyed. Comparison of our observed SOC density with the corresponding values from the dataset of Yang et al. indicates that these two datasets are comparable. The combined dataset did not reduce the uncertainty in the estimate of the regional grassland soil C stock. This result could be mainly explained by the underrepresentation of sampling sites in large areas with poor accessibility. Further research to improve the regional SOC stock estimate should optimize sampling strategy by considering the number of samples and their spatial distribution. PMID:24819054

Examination about the Spatial Representation of PM2.5 Obtained from Limited Stations Using a Network Observation

NASA Astrophysics Data System (ADS)

Shi, X.; Zhao, C.

2017-12-01

Haze aerosol pollution has been a focus issue in China, and its characteristics is highly demanded. With limited observation sites, aerosol properties obtained from a single site is frequently used to represent the haze condition over a large domain, such as tens of kilometers. This could result in high uncertainties in the haze characteristics due to their spatial variation. Using a network observation from November 2015 to February 2016 over an urban city in North China with high spatial resolution, this study examines the spatial representation of ground site observations. A method is first developed to determine the representative area of measurements from limited stations. The key idea of this method is to determine the spatial variability of particulate matter with diameters less than 2.5 μm (PM2.5) concentration using a variance function in 2km x 2km grids. Based on the high spatial resolution (0.5km x 0.5km) measurements of PM2.5, the grids in which PM2.5 have high correlations and weak value differences are determined as the representation area of measurements at these grids. Note that the size representation area is not exactly a circle region. It shows that the size representation are for the study region and study period ranges from 0.25 km2 to 16.25 km2. The representation area varies with locations. For the 20 km x 20 km study region, 10 station observations would have a good representation of the PM2.5 observations obtained from current 169 stations at the four-month time scale.

Plasma Properties and Magnetic Field Structure of the Solar Corona, Based on Coordinated Max '91 Observations from SERTS, the VLA, and Magnetographs

NASA Technical Reports Server (NTRS)

Brosius, Jeffrey W. (Principal Investigator)

1996-01-01

The plasma properties and magnetic field structure of the solar corona were determined using coordinated observations obtained with NASA/GSFC's Solar EUV Rocket Telescope and Spectrograph (SERTS), the Very Large Array (VLA), and Kitt Peak photospheric longitudinal magnetograms. A problem was identified with the SERTS calibration as determined from laboratory measurements. A revised calibration curve was derived by requiring that the numerous available measured line intensity ratios agreed with their respective theoretical values. Densities were derived from line intensity ratios, and active region densities were found to typically exceed quiet Sun densities by factors of only about 2. The active region density was found to remain constant across the SERTS slit, despite the fact that the emission line intensities vary significantly. This indicates that the product of the path length and the volume filling factor must vary significantly from the active region outskirts to the central core. Filling factors were derived and found to range from much less than one to nearly unity. Wavelength shifts were examined along the SERTS slit in the spatially resolved spectra, but no evidence was found for significant Doppler shifts in active region 7563 or in the quiet Sun. The numerical procedure developed by Monsignori-Fossi and Landini was used to derive the active region and quiet sun differential emission measure (DEM) from the spatially averaged spectra. A DEM was estimated for each spatial pixel in the two dimensional active region images by scaling the averaged active region DEM based upon corresponding pixel intensities of SERTS Mg IX, Fe XV, and Fe XVI images. These results, along with density measurements, were used in an IDL computer code which calculated the temperature dependence of the coronal magnetic field in each spatial pixel by minimizing the difference between the observed and calculated 20 and 6 cm microwave brightness temperatures.

Developmental and spatial variations in the diet signatures of hyperbenthic shrimp Nauticaris marionis at the Prince Edward Islands based on stable isotope ratios and fatty acid profiles

NASA Astrophysics Data System (ADS)

Richoux, Nicole B.; Allan, E. Louise; Froneman, P. William

2016-04-01

The caridean shrimp Nauticaris marionis is an ecologically important species in the benthic community around the sub-Antarctic Prince Edward Islands (PEI) as it represents a key prey item for a variety of top predators breeding on the islands. We hypothesized that the diet of N. marionis shifts during its development, and that spatial variability in food availability results in differentiation in the diet signatures of specimens collected from various locations of the shelf waters around the PEI. Specimens were collected from nine stations (depth range 70 to 240 m) around the PEI at inter-island shelf (from west to east: upstream, between and downstream) and nearshore regions during austral autumn 2009. Stable isotope and fatty acid data both revealed spatial and developmental variations in the shrimp diet. Nearshore shrimp were more 13C-enriched than those from the inter-island region, suggesting increased kelp detritus entered the food web in the nearshore regions. The shrimp showed increases in δ13C and δ15N signatures (and trophic position) with an increase in body size, resulting in distinctions between size classes that reflected shifts in their trophic niche through development. The fatty acid profiles similarly indicated distinctions in diet with increased shrimp size (in the deep regions), and spatial variability was evident in relation to region and depth. All shrimp contained large proportions of polyunsaturated and essential fatty acids, indicating that the quality of food consumed was similar between regions despite the diet variability. Our results provide new dietary information about a key species operating near the base of the food web at the highly productive PEI, and show that there were no areas of enhanced nutrition available to the shrimp. As such, there was no nutritional advantage to shrimp inhabiting any specific region around the PEI.

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

Stewart, J; Lindsay, P; University of Toronto, Toronto

Purpose: Recent progress in small animal radiotherapy systems has provided the foundation for delivering the heterogeneous, millimeter scale dose distributions demanded by preclinical radiobiology investigations. Despite advances in preclinical dose planning, delivery of highly heterogeneous dose distributions is constrained by the fixed collimation systems and large x-ray focal spot common in small animal radiotherapy systems. This work proposes a dual focal spot dose optimization and delivery method with a large x-ray focal spot used to deliver homogeneous dose regions and a small focal spot to paint spatially heterogeneous dose regions. Methods: Two-dimensional dose kernels were measured for a 1 mmmore » circular collimator with radiochromic film at 10 mm depth in a solid water phantom for the small and large x-ray focal spots on a recently developed small animal microirradiator. These kernels were used in an optimization framework which segmented a desired dose distribution into low- and high-spatial frequency regions for delivery by the large and small focal spot, respectively. For each region, the method determined an optimal set of stage positions and beam-on times. The method was demonstrated by optimizing a bullseye pattern consisting of 0.75 mm radius circular target and 0.5 and 1.0 mm wide rings alternating between 0 and 2 Gy. Results: Compared to a large focal spot technique, the dual focal spot technique improved the optimized dose distribution: 69.2% of the optimized dose was within 0.5 Gy of the intended dose for the large focal spot, compared to 80.6% for the dual focal spot method. The dual focal spot design required 14.0 minutes of optimization, and will require 178.3 minutes for automated delivery. Conclusion: The dual focal spot optimization and delivery framework is a novel option for delivering conformal and heterogeneous dose distributions at the preclinical level and provides a new experimental option for unique radiobiological investigations. Funding Support: this work is supported by funding the National Sciences and Engineering Research Council of Canada, and a Mitacs-accelerate fellowship. Conflict of Interest: Dr. Lindsay and Dr. Jaffray are listed as inventors of the small animal microirradiator described herein. This system has been licensed for commercial development.« less

A wood density and aboveground biomass variability assessment using pre-felling inventory data in Costa Rica.

PubMed

Svob, Sienna; Arroyo-Mora, J Pablo; Kalacska, Margaret

2014-12-01

The high spatio-temporal variability of aboveground biomass (AGB) in tropical forests is a large source of uncertainty in forest carbon stock estimation. Due to their spatial distribution and sampling intensity, pre-felling inventories are a potential source of ground level data that could help reduce this uncertainty at larger spatial scales. Further, exploring the factors known to influence tropical forest biomass, such as wood density and large tree density, will improve our knowledge of biomass distribution across tropical regions. Here, we evaluate (1) the variability of wood density and (2) the variability of AGB across five ecosystems of Costa Rica. Using forest management (pre-felling) inventories we found that, of the regions studied, Huetar Norte had the highest mean wood density of trees with a diameter at breast height (DBH) greater than or equal to 30 cm, 0.623 ± 0.182 g cm -3 (mean ± standard deviation). Although the greatest wood density was observed in Huetar Norte, the highest mean estimated AGB (EAGB) of trees with a DBH greater than or equal to 30 cm was observed in Osa peninsula (173.47 ± 60.23 Mg ha -1 ). The density of large trees explained approximately 50% of EAGB variability across the five ecosystems studied. Comparing our study's EAGB to published estimates reveals that, in the regions of Costa Rica where AGB has been previously sampled, our forest management data produced similar values. This study presents the most spatially rich analysis of ground level AGB data in Costa Rica to date. Using forest management data, we found that EAGB within and among five Costa Rican ecosystems is highly variable. Combining commercial logging inventories with ecological plots will provide a more representative ground level dataset for the calibration of the models and remotely sensed data used to EAGB at regional and national scales. Additionally, because the non-protected areas of the tropics offer the greatest opportunity to reduce rates of deforestation and forest degradation, logging inventories offer a promising source of data to support mechanisms such as the United Nations REDD + (Reducing Emissions from Tropical Deforestation and Degradation) program.

Characteristics of the horizontal and vertical distributions of dimethyl sulfide throughout the Amundsen Sea Polynya.

PubMed

Kim, Intae; Hahm, Doshik; Park, Keyhong; Lee, Youngju; Choi, Jung-Ok; Zhang, Miming; Chen, Liqi; Kim, Hyun-Cheol; Lee, SangHoon

2017-04-15

We investigated horizontal and vertical distributions of DMS in the upper water column of the Amundsen Sea Polynya and Pine Island Polynya during the austral summer (January-February) of 2016 using a membrane inlet mass spectrometer (MIMS) onboard the Korean icebreaker R/V Araon. The surface water concentrations of DMS varied from <1 to 400nM. The highest DMS (up to 300nM) were observed in sea ice-polynya transition zones and near the Getz ice shelf, where both the first local ice melting and high plankton productivity were observed. In other regions, high DMS concentration was generally accompanied by higher chlorophyll and ΔO 2 /Ar. The large spatial variability of DMS and primary productivity in the surface water of the Amundsen Sea seems to be attributed to melting conditions of sea ice, relative dominance of Phaeocystis Antarctica as a DMS producer, and timing differences between bloom and subsequent DMS productions. The depth profiles of DMS and ΔO 2 /Ar were consistent with the horizontal surface data, showing noticeable spatial variability. However, despite the large spatial variability, in contrast to the previous results from 2009, DMS concentrations and ΔO 2 /Ar in the surface water were indistinct between the two major domains: the sea ice zone and polynya region. The discrepancy may be associated with inter-annual variations of phytoplankton assemblages superimposed on differences in sea-ice conditions, blooming period, and spatial coverage along the vast surface area of the Amundsen Sea. Copyright © 2017 Elsevier B.V. All rights reserved.

Regional flood-frequency relations for streams with many years of no flow

USGS Publications Warehouse

Hjalmarson, Hjalmar W.; Thomas, Blakemore E.; ,

1990-01-01

In the southwestern United States, flood-frequency relations for streams that drain small arid basins are difficult to estimate, largely because of the extreme temporal and spatial variability of floods and the many years of no flow. A method is proposed that is based on the station-year method. The new method produces regional flood-frequency relations using all available annual peak-discharge data. The prediction errors for the relations are directly assessed using randomly selected subsamples of the annual peak discharges.

Impact of Satellite Viewing-Swath Width on Global and Regional Aerosol Optical Thickness Statistics and Trends

NASA Technical Reports Server (NTRS)

Colarco, P. R.; Kahn, R. A.; Remer, L. A.; Levy, R. C.

2014-01-01

We use the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite aerosol optical thickness (AOT) product to assess the impact of reduced swath width on global and regional AOT statistics and trends. Alongtrack and across-track sampling strategies are employed, in which the full MODIS data set is sub-sampled with various narrow-swath (approximately 400-800 km) and single pixel width (approximately 10 km) configurations. Although view-angle artifacts in the MODIS AOT retrieval confound direct comparisons between averages derived from different sub-samples, careful analysis shows that with many portions of the Earth essentially unobserved, spatial sampling introduces uncertainty in the derived seasonal-regional mean AOT. These AOT spatial sampling artifacts comprise up to 60%of the full-swath AOT value under moderate aerosol loading, and can be as large as 0.1 in some regions under high aerosol loading. Compared to full-swath observations, narrower swath and single pixel width sampling exhibits a reduced ability to detect AOT trends with statistical significance. On the other hand, estimates of the global, annual mean AOT do not vary significantly from the full-swath values as spatial sampling is reduced. Aggregation of the MODIS data at coarse grid scales (10 deg) shows consistency in the aerosol trends across sampling strategies, with increased statistical confidence, but quantitative errors in the derived trends are found even for the full-swath data when compared to high spatial resolution (0.5 deg) aggregations. Using results of a model-derived aerosol reanalysis, we find consistency in our conclusions about a seasonal-regional spatial sampling artifact in AOT Furthermore, the model shows that reduced spatial sampling can amount to uncertainty in computed shortwave top-ofatmosphere aerosol radiative forcing of 2-3 W m(sup-2). These artifacts are lower bounds, as possibly other unconsidered sampling strategies would perform less well. These results suggest that future aerosol satellite missions having significantly less than full-swath viewing are unlikely to sample the true AOT distribution well enough to obtain the statistics needed to reduce uncertainty in aerosol direct forcing of climate.

Seasonal and spatial variations of source and drinking water quality in small municipal systems of two Canadian regions.

PubMed

Scheili, A; Rodriguez, M J; Sadiq, R

2015-03-01

A one-year sampling program covering twenty-five small municipal systems was carried out in two Canadian regions to improve our understanding of the variability of water quality in small systems from water source to the end of the distribution system (DS). The database obtained was used to develop a global portrait of physical, chemical and microbiological water quality parameters. More precisely, the temporal and the spatial variability of these parameters were investigated. We observed that the levels of natural organic matter (NOM) were variable during different seasons, with maxima in the fall for both provinces. In the regions under study, the highest trihalomethane (THM) and haloacetic acid (HAA) levels were achieved in warmer seasons (summer, fall), as observed in previous studies involving large systems. Observed THM and HAA levels were three times higher in systems in the province of Newfoundland & Labrador than in the province of Quebec. Taste and odor indicators were detected during the summer and fall, and higher heterotrophic plate count (HPC) levels were associated with lower free chlorine levels. To determine spatial variations, stepwise statistical analysis was used to identify parameters and locations in the DS that act as indicators of drinking water quality. As observed for medium and large systems, free chlorine consumption, THM and HAA levels were dependent on their location in the DS. We also observed that the degradation of HAAs is more important in small systems than in medium or large DS reported in the literature, and this degradation can occur from the beginning of the DS. The results of this research may contribute to providing precious information on drinking water quality to small system operators and pave the way for several opportunities to improve water quality management. Copyright © 2014 Elsevier B.V. All rights reserved.

Fire activity as a function of fire–weather seasonal severity and antecedent climate across spatial scales in southern Europe and Pacific western USA

USGS Publications Warehouse

Urbieta, Itziar R.; Zavala, Gonzalo; Bedia, Joaquin; Gutierrez, Jose M.; San Miguel-Ayanz, Jesus; Camia, Andrea; Keeley, Jon E.; Moreno, Jose M.

2015-01-01

Climate has a strong influence on fire activity, varying across time and space. We analyzed the relationships between fire–weather conditions during the main fire season and antecedent water-balance conditions and fires in two Mediterranean-type regions with contrasted management histories: five southern countries of the European Union (EUMED)(all fires); the Pacific western coast of the USA (California and Oregon, PWUSA)(national forest fires). Total number of fires (≥1 ha), number of large fires (≥100 ha) and area burned were related to mean seasonal fire weather index (FWI), number of days over the 90th percentile of the FWI, and to the standardized precipitation-evapotranspiration index (SPEI) from the preceding 3 (spring) or 8 (autumn through spring) months. Calculations were made at three spatial aggregations in each area, and models related first-difference (year-to-year change) of fires and FWI/climate variables to minimize autocorrelation. An increase in mean seasonal FWI resulted in increases in the three fire variables across spatial scales in both regions. SPEI contributed little to explain fires, with few exceptions. Negative water-balance (dry) conditions from autumn through spring (SPEI8) were generally more important than positive conditions (moist) in spring (SPEI3), both of which contributed positively to fires. The R2 of the models generally improved with increasing area of aggregation. For total number of fires and area burned, the R2 of the models tended to decrease with increasing mean seasonal FWI. Thus, fires were more susceptible to change with climate variability in areas with less amenable conditions for fires (lower FWI) than in areas with higher mean FWI values. The relationships were similar in both regions, albeit weaker in PWUSA, probably due to the wider latitudinal gradient covered in PWUSA than in EUMED. The large variance explained by some of the models indicates that large-scale seasonal forecast could help anticipating fire activity in the investigated areas.

Fire activity as a function of fire-weather seasonal severity and antecedent climate across spatial scales in southern Europe and Pacific western USA

NASA Astrophysics Data System (ADS)

Urbieta, Itziar R.; Zavala, Gonzalo; Bedia, Joaquín; Gutiérrez, José M.; San Miguel-Ayanz, Jesús; Camia, Andrea; Keeley, Jon E.; Moreno, José M.

2015-11-01

Climate has a strong influence on fire activity, varying across time and space. We analyzed the relationships between fire-weather conditions during the main fire season and antecedent water-balance conditions and fires in two Mediterranean-type regions with contrasted management histories: five southern countries of the European Union (EUMED)(all fires); the Pacific western coast of the USA (California and Oregon, PWUSA)(national forest fires). Total number of fires (≥1 ha), number of large fires (≥100 ha) and area burned were related to mean seasonal fire weather index (FWI), number of days over the 90th percentile of the FWI, and to the standardized precipitation-evapotranspiration index (SPEI) from the preceding 3 (spring) or 8 (autumn through spring) months. Calculations were made at three spatial aggregations in each area, and models related first-difference (year-to-year change) of fires and FWI/climate variables to minimize autocorrelation. An increase in mean seasonal FWI resulted in increases in the three fire variables across spatial scales in both regions. SPEI contributed little to explain fires, with few exceptions. Negative water-balance (dry) conditions from autumn through spring (SPEI8) were generally more important than positive conditions (moist) in spring (SPEI3), both of which contributed positively to fires. The R2 of the models generally improved with increasing area of aggregation. For total number of fires and area burned, the R2 of the models tended to decrease with increasing mean seasonal FWI. Thus, fires were more susceptible to change with climate variability in areas with less amenable conditions for fires (lower FWI) than in areas with higher mean FWI values. The relationships were similar in both regions, albeit weaker in PWUSA, probably due to the wider latitudinal gradient covered in PWUSA than in EUMED. The large variance explained by some of the models indicates that large-scale seasonal forecast could help anticipating fire activity in the investigated areas.

Angular dependent anisotropic terahertz response of vertically aligned multi-walled carbon nanotube arrays with spatial dispersion.

PubMed

Zhou, Yixuan; E, Yiwen; Xu, Xinlong; Li, Weilong; Wang, Huan; Zhu, Lipeng; Bai, Jintao; Ren, Zhaoyu; Wang, Li

2016-12-14

Spatial dispersion effect of aligned carbon nanotubes (CNTs) in the terahertz (THz) region has significance for both theoretical and applied consideration due to the unique intrinsically anisotropic physical properties of CNTs. Herein, we report the angular dependent reflection of p-polarized THz wave from vertically aligned multi-walled CNT arrays in both experiment and theory. The spectra indicate that the reflection depends on the film thickness of vertically aligned CNTs, the incident angle, and the frequency. The calculation model is based on the spatial dispersion effect of aligned CNTs and performed with effective impedance method and the Maxwell-Garnett approximation. The results fit well with the experiment when the thickness of CNT film is thin, which reveals a coherent superposition mechanism of the CNT surface reflection and CNTs/Si interface reflection. For thick CNT films, the CNTs/Si interface response determines the reflection at small incident angles, while the CNTs surface effect dominates at large incident angles. This work investigates the spatial dispersion effect of vertically aligned CNT arrays in the THz region, and paves a way for potential anisotropic THz applications based on CNTs with oblique incidence requirements.

Angular dependent anisotropic terahertz response of vertically aligned multi-walled carbon nanotube arrays with spatial dispersion

NASA Astrophysics Data System (ADS)

Zhou, Yixuan; Yiwen, E.; Xu, Xinlong; Li, Weilong; Wang, Huan; Zhu, Lipeng; Bai, Jintao; Ren, Zhaoyu; Wang, Li

2016-12-01

Spatial dispersion effect of aligned carbon nanotubes (CNTs) in the terahertz (THz) region has significance for both theoretical and applied consideration due to the unique intrinsically anisotropic physical properties of CNTs. Herein, we report the angular dependent reflection of p-polarized THz wave from vertically aligned multi-walled CNT arrays in both experiment and theory. The spectra indicate that the reflection depends on the film thickness of vertically aligned CNTs, the incident angle, and the frequency. The calculation model is based on the spatial dispersion effect of aligned CNTs and performed with effective impedance method and the Maxwell-Garnett approximation. The results fit well with the experiment when the thickness of CNT film is thin, which reveals a coherent superposition mechanism of the CNT surface reflection and CNTs/Si interface reflection. For thick CNT films, the CNTs/Si interface response determines the reflection at small incident angles, while the CNTs surface effect dominates at large incident angles. This work investigates the spatial dispersion effect of vertically aligned CNT arrays in the THz region, and paves a way for potential anisotropic THz applications based on CNTs with oblique incidence requirements.

A model for spatial variations in life expectancy; mortality in Chinese regions in 2000.

PubMed

Congdon, Peter

2007-05-02

Life expectancy in China has been improving markedly but health gains have been uneven and there is inequality in survival chances between regions and in rural as against urban areas. This paper applies a statistical modelling approach to mortality data collected in conjunction with the 2000 Census to formally assess spatial mortality contrasts in China. The modelling approach provides interpretable summary parameters (e.g. the relative mortality risk in rural as against urban areas) and is more parsimonious in terms of parameters than the conventional life table model. Predictive fit is assessed both globally and at the level of individual five year age groups. A proportional model (age and area effects independent) has a worse fit than one allowing age-area interactions following a bilinear form. The best fit is obtained by allowing for child and oldest age mortality rates to vary spatially. There is evidence that age (21 age groups) and area (31 Chinese administrative divisions) are not proportional (i.e. independent) mortality risk factors. In fact, spatial contrasts are greatest at young ages. There is a pronounced rural survival disadvantage, and large differences in life expectancy between provinces.

A GIS-based multi-source and multi-box modeling approach (GMSMB) for air pollution assessment--a North American case study.

PubMed

Wang, Bao-Zhen; Chen, Zhi

2013-01-01

This article presents a GIS-based multi-source and multi-box modeling approach (GMSMB) to predict the spatial concentration distributions of airborne pollutant on local and regional scales. In this method, an extended multi-box model combined with a multi-source and multi-grid Gaussian model are developed within the GIS framework to examine the contributions from both point- and area-source emissions. By using GIS, a large amount of data including emission sources, air quality monitoring, meteorological data, and spatial location information required for air quality modeling are brought into an integrated modeling environment. It helps more details of spatial variation in source distribution and meteorological condition to be quantitatively analyzed. The developed modeling approach has been examined to predict the spatial concentration distribution of four air pollutants (CO, NO(2), SO(2) and PM(2.5)) for the State of California. The modeling results are compared with the monitoring data. Good agreement is acquired which demonstrated that the developed modeling approach could deliver an effective air pollution assessment on both regional and local scales to support air pollution control and management planning.

Late Holocene Drought Variability in Eastern North America: Evidence From the Peatland Archive

NASA Astrophysics Data System (ADS)

Booth, R. K.; Jackson, S. T.

2006-12-01

Tree-ring based drought chronologies from semi-arid regions of western North America have revealed substantial variability in water balance during the past 1000 years, including episodes of persistent drought more severe than any observed during historical times. Delimitation of regional and continental-scale footprints of these past drought events, including their spatial patterning in humid regions where moisture-sensitive paleoclimate records are scarce, is critical to understanding their dynamics and potential causes. Ombrotrophic peatlands are scattered throughout humid regions of North America at mid-latitudes and represent an underutilized source of multidecadal-scale information on past moisture variations. We are developing a spatial network of peatland-derived paleoclimate and paleoecological records in eastern North America, in an effort to 1) determine whether large, decadal to multidecadal droughts of the past several thousand years were spatially and temporally coherent, 2) assess whether the magnitude of past drought events was sufficient to force ecological change in terrestrial ecosystems, and 3) assess the underlying mechanisms and dynamics of widespread drought in North America. We have completed water-level reconstructions based on testate-amoeba assemblages from two ombrotrophic peatlands in mid-continental North America, Hole in the Bog (NC Minnesota) and Minden Bog (SE Michgian). We also have developed reconstructions from three Sphagnum-dominated kettle peatlands, South Rhody Peatland (NC Michigan), Hornet Peatland (NW Wisconsin), and Irwin Smith Peatland (NE Michigan). Although these kettle peatlands are not truly ombrotrophic, high-magnitude water-table fluctuations should still be attributable to climate variability, and we use these records to supplement our interpretation of regional climate history. Our results indicate that all high-magnitude fluctuations in water balance were spatially extensive, affecting bog-surface moisture conditions throughout the western Great Lakes region. These include a large drought event during the late 16th century and a series of widespread drought events between 1900-1600 BP and 1100- 700 BP. The highest magnitude droughts of the last 2000 years occurred during an interval roughly consistent with the Medieval Warm Period (MWP), with individual drought events centered on 1000 BP, 800 BP, and 700 BP. These droughts were associated with major ecological changes, including abrupt changes in vegetation and fire regime. Tree-ring records from the western United States also document a series of extensive and high-magnitude drought events during this time period, suggesting these droughts affected a large portion of mid-latitude North America. Similarly widespread drought during the last 100 years has been linked to sea surface temperature (SST) anomalies in the adjacent ocean basins, particularly an anomalously warm North Atlantic and mid-latitude Pacific, and an anomalously cold Tropical Pacific. We hypothesize that the widespread droughts apparent in our bog records were related to amplification of a similar spatial mode of moisture variability. Comparison with available proxy SST records provides some support for this hypothesis, although a more extensive network of terrestrial hydroclimate records, derived using consistent methods and proxies, needs to be used in conjunction with the developing network of proxy SST records to fully test this hypothesis.

China's land cover and land use change from 1700 to 2005: Estimations from high-resolution satellite data and historical archives

NASA Astrophysics Data System (ADS)

Liu, Mingliang; Tian, Hanqin

2010-09-01

One of the major limitations in assessing the impacts of human activities on global biogeochemical cycles and climate is a shortage of reliable data on historical land cover and land use change (LCLUC). China had extreme discrepancies in estimating contemporary and historical patterns of LCLUC over the last 3 centuries because of its geographical complexity, long history of land use, and limited national surveys. This study aims to characterize the spatial and temporal patterns of China's LCLUC during 1700-2005 by reconstructing historical gridded data sets from high-resolution satellite data and long-term historical survey data. During this 300 year period, the major characteristics of LCLUC in China have been shrinking forest (decreased by 22%) and expanding cropland (increased by 42%) and urban areas (including urban and rural settlements, factories, quarries, mining, and other built-up land). New cropland areas have come almost equally from both forested and nonforested land. This study also revealed that substantial conversion between forest and woodland can be attributed to forest harvest, forest regeneration, and land degradation. During 1980-2005, LCLUC was characterized by shrinking cropland, expanding urban and forest areas, and large decadal variations on a national level. LCLUC in China showed significant spatial variations during different time periods, which were caused by spatial heterogeneity in vegetation, soils, and climate and regional imbalance in economy development. During 1700-2005, forests shrunk rapidly while croplands expanded in the northeast and southwest of China. During 1980-2005, we found a serious loss of cropland and urban sprawl in the eastern plain, north, and southeast regions of China and a large increase in forested area in the southeast and southwest regions. The reconstructed LCLUC data sets from this study could be used to assess the impacts of land use change on biogeochemical cycles, the water cycle, and the regional climate in China. To further eliminate uncertainties in this data set and make reliable projections of LCLUC for the future, we need to improve our understanding of the drivers of LCLUC and work toward developing an advanced, spatially explicit land use model.

Spatially balanced provision of health equipment: a cross-sectional study oriented to the identification of challenges to access promotion.

PubMed

Amaral, Pedro Vasconcelos; Rocha, Thiago Augusto Hernandes; Barbosa, Allan Claudius Queiroz; Lein, Adriana; Vissoci, João Ricardo Nickenig

2017-12-04

Access to health services is in part defined by the spatial distribution of healthcare equipment. To ensure equity in the provision of health services, it is important to examine availability across different health care providers taking into account population demand. Given the importance of the equitable provision of health equipment, we evaluate its spatial distribution in Brazil. This study is classified as cross-sectional with an ecological design. We evaluate Brazilian data on distance to available health equipment considering: dialysis machines (385), magnetic resonance imaging (MRI) (257), hospital beds (3675) and bone densitometers (429). We define two distance thresholds (50 km and 200 km) from a municipality to the center of services provision. The balance between infrastructure capacity and potential demand was evaluated to identify a lack or surplus of health services. The distribution of dialysis equipment and bone densitometers is not balanced across Brazilian states, and unmet demand is high. With respect to MRIs, the large capacity of this equipment results in a large excess of supply. However, this characteristic alone cannot account for excesses of supply of over 700%, as is the case of the Federal District when the range is limited to 50 km. At the same time, four states in the Northeastern region of Brazil show a net excess of demand. Some regions do not meet the standard amount of supply defined by Brazilian Ministry of Health. The quantity and distribution of hospital beds are not sufficient to provide full coverage to the population. Our main focus was to evaluate the network of the provision of health equipment in Brazil, considering both private and public sectors conjointly. We take into account two main aspects of a spatially balanced health system: the regional availability of health equipment and the geographic distance between its demand and supply at the municipality level. Some regions do not meet the minimum requirement defined by the Brazilian Ministry of Health regarding the supply of health services.

Understanding Atmospheric Anomalies Associated With Seasonal Pluvial-Drought Processes Using Southwest China as an Example

NASA Astrophysics Data System (ADS)

Liu, Zhenchen; Lu, Guihua; He, Hai; Wu, Zhiyong; He, Jian

2017-11-01

Seasonal pluvial-drought transition processes are unique natural phenomena. To explore possible mechanisms, we considered Southwest China (SWC) as the study region and comprehensively investigated the temporal evolution or spatial patterns of large-scale and regional atmospheric variables with the simple method of Standardized Anomalies (SA). Some key procedures and results include the following: (1) Because regional atmospheric variables are more directly responsible for the transition processes, we investigate it in detail. The temporal evolution of net vertical integral water vapor flux (net VIWVF) across SWC, together with vertical SA-based patterns of regional horizontal divergence (D) and vertical motion (ω), coincides well with pluvial-drought transition processes. (2) With respect to large-scale circulation patterns, a well-organized Eurasian (EU) Pattern is one important feature during the pluvial-drought transitions over SWC. (3) Based on these large-scale and regional atmospheric anomalous features, relevant SA-based indices were built, to explore the possibility of simulating drought development using previous pluvial anomalies. As a whole, simulated drought development only with SA-based indices of large-scale circulation patterns does not perform well. Further, it can be improved a lot when SA-based indices of regional D and net VIWVF are introduced. (4) In addition, the potential drought prediction using pluvial anomalies, together with the deep understanding of physical mechanisms responsible for pluvial-drought transitions, need to be further explored.

Climate and landscape influence on indicators of lake carbon cycling through spatial patterns in dissolved organic carbon.

PubMed

Lapierre, Jean-Francois; Seekell, David A; Del Giorgio, Paul A

2015-12-01

Freshwater ecosystems are strongly influenced by both climate and the surrounding landscape, yet the specific pathways connecting climatic and landscape drivers to the functioning of lake ecosystems are poorly understood. Here, we hypothesize that the links that exist between spatial patterns in climate and landscape properties and the spatial variation in lake carbon (C) cycling at regional scales are at least partly mediated by the movement of terrestrial dissolved organic carbon (DOC) in the aquatic component of the landscape. We assembled a set of indicators of lake C cycling (bacterial respiration and production, chlorophyll a, production to respiration ratio, and partial pressure of CO2 ), DOC concentration and composition, and landscape and climate characteristics for 239 temperate and boreal lakes spanning large environmental and geographic gradients across seven regions. There were various degrees of spatial structure in climate and landscape features that were coherent with the regionally structured patterns observed in lake DOC and indicators of C cycling. These different regions aligned well, albeit nonlinearly along a mean annual temperature gradient; whereas there was a considerable statistical effect of climate and landscape properties on lake C cycling, the direct effect was small and the overall effect was almost entirely overlapping with that of DOC concentration and composition. Our results suggest that key climatic and landscape signals are conveyed to lakes in part via the movement of terrestrial DOC to lakes and that DOC acts both as a driver of lake C cycling and as a proxy for other external signals. © 2015 John Wiley & Sons Ltd.

Structure identification within a transitioning swept-wing boundary layer

NASA Astrophysics Data System (ADS)

Chapman, Keith Lance

1997-08-01

Extensive measurements are made in a transitioning swept-wing boundary layer using hot-film, hot-wire and cross-wire anemometry. The crossflow-dominated flow contains stationary vortices that breakdown near mid-chord. The most amplified vortex wavelength is forced by the use of artificial roughness elements near the leading edge. Two-component velocity and spanwise surface shear-stress correlation measurements are made at two constant chord locations, before and after transition. Streamwise surface shear stresses are also measured through the entire transition region. Correlation techniques are used to identify stationary structures in the laminar regime and coherent structures in the turbulent regime. Basic techniques include observation of the spatial correlations and the spatially distributed auto-spectra. The primary and secondary instability mechanisms are identified in the spectra in all measured fields. The primary mechanism is seen to grow, cause transition and produce large-scale turbulence. The secondary mechanism grows through the entire transition region and produces the small-scale turbulence. Advanced techniques use linear stochastic estimation (LSE) and proper orthogonal decomposition (POD) to identify the spatio-temporal evolutions of structures in the boundary layer. LSE is used to estimate the instantaneous velocity fields using temporal data from just two spatial locations and the spatial correlations. Reference locations are selected using maximum RMS values to provide the best available estimates. POD is used to objectively determine modes characteristic of the measured flow based on energy. The stationary vortices are identified in the first laminar modes of each velocity component and shear component. Experimental evidence suggests that neighboring vortices interact and produce large coherent structures with spanwise periodicity at double the stationary vortex wavelength. An objective transition region detection method is developed using streamwise spatial POD solutions which isolate the growth of the primary and secondary instability mechanisms in the first and second modes, respectively. Temporal evolutions of dominant POD modes in all measured fields are calculated. These scalar POD coefficients contain the integrated characteristics of the entire field, greatly reducing the amount of data to characterize the instantaneous field. These modes may then be used to train future flow control algorithms based on neural networks.

Structure Identification Within a Transitioning Swept-Wing Boundary Layer

NASA Technical Reports Server (NTRS)

Chapman, Keith; Glauser, Mark

1996-01-01

Extensive measurements are made in a transitioning swept-wing boundary layer using hot-film, hot-wire and cross-wire anemometry. The crossflow-dominated flow contains stationary vortices that breakdown near mid-chord. The most amplified vortex wavelength is forced by the use of artificial roughness elements near the leading edge. Two-component velocity and spanwise surface shear-stress correlation measurements are made at two constant chord locations, before and after transition. Streamwise surface shear stresses are also measured through the entire transition region. Correlation techniques are used to identify stationary structures in the laminar regime and coherent structures in the turbulent regime. Basic techniques include observation of the spatial correlations and the spatially distributed auto-spectra. The primary and secondary instability mechanisms are identified in the spectra in all measured fields. The primary mechanism is seen to grow, cause transition and produce large-scale turbulence. The secondary mechanism grows through the entire transition region and produces the small-scale turbulence. Advanced techniques use Linear Stochastic Estimation (LSE) and Proper Orthogonal Decomposition (POD) to identify the spatio-temporal evolutions of structures in the boundary layer. LSE is used to estimate the instantaneous velocity fields using temporal data from just two spatial locations and the spatial correlations. Reference locations are selected using maximum RMS values to provide the best available estimates. POD is used to objectively determine modes characteristic of the measured flow based on energy. The stationary vortices are identified in the first laminar modes of each velocity component and shear component. Experimental evidence suggests that neighboring vortices interact and produce large coherent structures with spanwise periodicity at double the stationary vortex wavelength. An objective transition region detection method is developed using streamwise spatial POD solutions which isolate the growth of the primary and secondary instability mechanisms in the first and second modes, respectively. Temporal evolutions of dominant POD modes in all measured fields are calculated. These scalar POD coefficients contain the integrated characteristics of the entire field, greatly reducing the amount of data to characterize the instantaneous field. These modes may then be used to train future flow control algorithms based on neural networks.

Temporal and spatial changes in plankton respiration and biomass in the Canary Islands region: the effect of mesoscale variability

NASA Astrophysics Data System (ADS)

Arístegui, Javier; Montero, María F.

2005-02-01

The temporal and spatial variabilities in the abundance and respiratory activity of plankton communities (<200 μm) were studied during three seasonal cruises around Gran Canaria Island (Canary Islands), a region of high mesoscale variability. Marked seasonal changes in respiratory activity, plankton community structure, and the ratio of heterotrophic to autotrophic biomass can be largely explained by hydrographic changes at the mesoscale level. Wind/current shearing at the flanks of the island enhances plankton respiration, presumably as the consequence of an increase in turbulence. Counter-paired cyclonic and anticyclonic eddies generated downstream of the island act as a two-way biological pump, increasing plankton production by nutrient pumping into the euphotic zone and accelerating the transport of organic matter into the aphotic zone, respectively. Coastal upwelling waters invading the Canary region in the form of filaments can transport either water with low plankton respiration and large phytoplankton cells or water with high respiratory rates associated with small cells. Plankton respiration was closely related to the abundance of Synechococcus type cyanobacteria and heterotrophic nanoflagellates during the three periods, but was only correlated with chlorophyll during the most fertile season, suggesting that respiration was mainly linked to microbial food web processes. Size-fractionated studies showed that 51-67% of the respiratory activity was due to picoplankton cells (<2 μm). Respiration rates (average values: 113±18 to 187±87 mmol C m -2 d -1) matched primary production rates during the fertile period, but were up to one order of magnitude higher during the rest of the year. Substantial inputs of organic matter from the coastal upwelling would be necessary to balance the large annual heterotrophic deficit in the region of study.

Modeling spatial patterns of link-based PM2.5 emissions and subsequent human exposure in a large canadian metropolitan area

NASA Astrophysics Data System (ADS)

Requia, Weeberb J.; Dalumpines, Ron; Adams, Matthew D.; Arain, Altaf; Ferguson, Mark; Koutrakis, Petros

2017-06-01

Understanding the relationship between mobile source emissions and subsequent human exposure is crucial for emissions control. Determining this relationship over space is fundamental to improve the accuracy and precision of public policies. In this study, we evaluated the spatial patterns of link-based PM2.5 emissions and subsequent human exposure in a large Canadian metropolitan area - the Greater Toronto and Hamilton Area (GTHA). This study was performed in three stages. First, we estimated vehicle emissions using transportation models and emission simulators. Then we evaluated human exposure to PM2.5 emissions using the Intake fraction (iF) approach. Finally, we applied geostatistical methods to assess spatial patterns of vehicle emissions and subsequent human exposure based on three prospective goals: i) classification of emissions (Global Moran's I test), ii) level of emission exposure (Getis-Ord General G test), and; iii) location of emissions (Anselin Local Moran's I). Our results showed that passenger vehicles accounted for the highest total amount of PM2.5 emissions, representing 57% emissions from all vehicles. Examining only the emissions from passenger vehicles, on average, each person in the GTHA inhales 2.58 × 10-3 ppm per day. Accounting the emissions from buses and trucks, on average each person inhales 0.12 × 10-3 and 1.91 × 10-3 ppm per day, respectively. For both PM2.5 emissions and human exposure using iF approach, our analysis showed Moran's Index greater than 0 for all vehicle categories, suggesting the presence of significant clusters (p-value <0.01) in the region. Our study indicates that air pollution control policy must be developed for the whole region, because of the spatial distribution of housing and businesses centers and inter-connectivity of transportation networks across the region, where a policy cannot simply be based on a municipal or other boundaries.

[Stochastic characteristics of daily precipitation and its spatiotemporal difference over China based on information entropy].

PubMed

Li, Xin Xin; Sang, Yan Fang; Xie, Ping; Liu, Chang Ming

2018-04-01

Daily precipitation process in China showed obvious randomness and spatiotemporal variation. It is important to accurately understand the influence of precipitation changes on control of flood and waterlogging disaster. Using the daily precipitation data measured at 520 stations in China during 1961-2013, we quantified the stochastic characteristics of daily precipitation over China based on the index of information entropy. Results showed that the randomness of daily precipitation in the southeast region were larger than that in the northwest region. Moreover, the spatial distribution of stochastic characteristics of precipitation was different at various grades. Stochastic characteri-stics of P 0 (precipitation at 0.1-10 mm) was large, but the spatial variation was not obvious. The stochastic characteristics of P 10 (precipitation at 10-25 mm) and P 25 (precipitation at 25-50 mm) were the largest and their spatial difference was obvious. P 50 (precipitation ≥50 mm) had the smallest stochastic characteristics and the most obviously spatial difference. Generally, the entropy values of precipitation obviously increased over the last five decades, indicating more significantly stochastic characteristics of precipitation (especially the obvious increase of heavy precipitation events) in most region over China under the scenarios of global climate change. Given that the spatial distribution and long-term trend of entropy values of daily precipitation could reflect thespatial distribution of stochastic characteristics of precipitation, our results could provide scientific basis for the control of flood and waterlogging disaster, the layout of agricultural planning, and the planning of ecological environment.

Farmer data sourcing. The case study of the spatial soil information maps in South Tyrol.

NASA Astrophysics Data System (ADS)

Della Chiesa, Stefano; Niedrist, Georg; Thalheimer, Martin; Hafner, Hansjörg; La Cecilia, Daniele

2017-04-01

Nord-Italian region South Tyrol is Europe's largest apple growing area exporting ca. 15% in Europe and 2% worldwide. Vineyards represent ca. 1% of Italian production. In order to deliver high quality food, most of the farmers in South Tyrol follow sustainable farming practices. One of the key practice is the sustainable soil management, where farmers collect regularly (each 5 years) soil samples and send for analyses to improve cultivation management, yield and finally profitability. However, such data generally remain inaccessible. On this regard, in South Tyrol, private interests and the public administration have established a long tradition of collaboration with the local farming industry. This has granted to the collection of large spatial and temporal database of soil analyses along all the cultivated areas. Thanks to this best practice, information on soil properties are centralized and geocoded. The large dataset consist mainly in soil information of texture, humus content, pH and microelements availability such as, K, Mg, Bor, Mn, Cu Zn. This data was finally spatialized by mean of geostatistical methods and several high-resolution digital maps were created. In this contribution, we present the best practice where farmers data source soil information in South Tyrol. Show the capability of a large spatial-temporal geocoded soil dataset to reproduce detailed digital soil property maps and to assess long-term changes in soil properties. Finally, implication and potential application are discussed.

Cooperativeness of the higher chromatin structure of the beta-globin locus revealed by the deletion mutations of DNase I hypersensitive site 3 of the LCR.

PubMed

Fang, Xiangdong; Xiang, Ping; Yin, Wenxuan; Stamatoyannopoulos, George; Li, Qiliang

2007-01-05

High-level transcription of the globin genes requires the enhancement by a distant element, the locus control region (LCR). Such long-range regulation in vivo involves spatial interaction between transcriptional elements, with intervening chromatin looping out. It has been proposed that the clustering of the HS sites of the LCR, the active globin genes, as well as the remote 5' hypersensitive sites (HSs) (HS-60/-62 in mouse, HS-110 in human) and 3'HS1 forms a specific spatial chromatin structure, termed active chromatin hub (ACH). Here we report the effects of the HS3 deletions of the LCR on the spatial chromatin structure of the beta-globin locus as revealed by the chromatin conformation capture (3C) technology. The small HS3 core deletion (0.23 kb), but not the large HS3 deletion (2.3 kb), disrupted the spatial interactions among all the HS sites of the LCR, the beta-globin gene and 3'HS1. We have previously demonstrated that the large HS3 deletion barely impairs the structure of the LCR holocomplex, while the structure is significantly disrupted by the HS3 core deletion. Taken together, these results suggest that the formation of the ACH is dependent on a largely intact LCR structure. We propose that the ACH indeed is an extension of the LCR holocomplex.

Local biomass burning is a dominant cause of the observed precipitation reduction in southern Africa

PubMed Central

Hodnebrog, Øivind; Myhre, Gunnar; Forster, Piers M.; Sillmann, Jana; Samset, Bjørn H.

2016-01-01

Observations indicate a precipitation decline over large parts of southern Africa since the 1950s. Concurrently, atmospheric concentrations of greenhouse gases and aerosols have increased due to anthropogenic activities. Here we show that local black carbon and organic carbon aerosol emissions from biomass burning activities are a main cause of the observed decline in southern African dry season precipitation over the last century. Near the main biomass burning regions, global and regional modelling indicates precipitation decreases of 20–30%, with large spatial variability. Increasing global CO2 concentrations further contribute to precipitation reductions, somewhat less in magnitude but covering a larger area. Whereas precipitation changes from increased CO2 are driven by large-scale circulation changes, the increase in biomass burning aerosols causes local drying of the atmosphere. This study illustrates that reducing local biomass burning aerosol emissions may be a useful way to mitigate reduced rainfall in the region. PMID:27068129

Large-Scale Spatial Distribution Patterns of Gastropod Assemblages in Rocky Shores

PubMed Central

Miloslavich, Patricia; Cruz-Motta, Juan José; Klein, Eduardo; Iken, Katrin; Weinberger, Vanessa; Konar, Brenda; Trott, Tom; Pohle, Gerhard; Bigatti, Gregorio; Benedetti-Cecchi, Lisandro; Shirayama, Yoshihisa; Mead, Angela; Palomo, Gabriela; Ortiz, Manuel; Gobin, Judith; Sardi, Adriana; Díaz, Juan Manuel; Knowlton, Ann; Wong, Melisa; Peralta, Ana C.

2013-01-01

Gastropod assemblages from nearshore rocky habitats were studied over large spatial scales to (1) describe broad-scale patterns in assemblage composition, including patterns by feeding modes, (2) identify latitudinal pattern of biodiversity, i.e., richness and abundance of gastropods and/or regional hotspots, and (3) identify potential environmental and anthropogenic drivers of these assemblages. Gastropods were sampled from 45 sites distributed within 12 Large Marine Ecosystem regions (LME) following the NaGISA (Natural Geography in Shore Areas) standard protocol (www.nagisa.coml.org). A total of 393 gastropod taxa from 87 families were collected. Eight of these families (9.2%) appeared in four or more different LMEs. Among these, the Littorinidae was the most widely distributed (8 LMEs) followed by the Trochidae and the Columbellidae (6 LMEs). In all regions, assemblages were dominated by few species, the most diverse and abundant of which were herbivores. No latitudinal gradients were evident in relation to species richness or densities among sampling sites. Highest diversity was found in the Mediterranean and in the Gulf of Alaska, while highest densities were found at different latitudes and represented by few species within one genus (e.g. Afrolittorina in the Agulhas Current, Littorina in the Scotian Shelf, and Lacuna in the Gulf of Alaska). No significant correlation was found between species composition and environmental variables (r≤0.355, p>0.05). Contributing variables to this low correlation included invasive species, inorganic pollution, SST anomalies, and chlorophyll-a anomalies. Despite data limitations in this study which restrict conclusions in a global context, this work represents the first effort to sample gastropod biodiversity on rocky shores using a standardized protocol across a wide scale. Our results will generate more work to build global databases allowing for large-scale diversity comparisons of rocky intertidal assemblages. PMID:23967204

High-frequency remote monitoring of large lakes with MODIS 500 m imagery

USGS Publications Warehouse

McCullough, Ian M.; Loftin, Cynthia S.; Sader, Steven A.

2012-01-01

Satellite-based remote monitoring programs of regional lake water quality largely have relied on Landsat Thematic Mapper (TM) owing to its long image archive, moderate spatial resolution (30 m), and wide sensitivity in the visible portion of the electromagnetic spectrum, despite some notable limitations such as temporal resolution (i.e., 16 days), data pre-processing requirements to improve data quality, and aging satellites. Moderate-Resolution Imaging Spectroradiometer (MODIS) sensors on Aqua/Terra platforms compensate for these shortcomings, although at the expense of spatial resolution. We developed and evaluated a remote monitoring protocol for water clarity of large lakes using MODIS 500 m data and compared MODIS utility to Landsat-based methods. MODIS images captured during May–September 2001, 2004 and 2010 were analyzed with linear regression to identify the relationship between lake water clarity and satellite-measured surface reflectance. Correlations were strong (R² = 0.72–0.94) throughout the study period; however, they were the most consistent in August, reflecting seasonally unstable lake conditions and inter-annual differences in algal productivity during the other months. The utility of MODIS data in remote water quality estimation lies in intra-annual monitoring of lake water clarity in inaccessible, large lakes, whereas Landsat is more appropriate for inter-annual, regional trend analyses of lakes ≥ 8 ha. Model accuracy is improved when ancillary variables are included to reflect seasonal lake dynamics and weather patterns that influence lake clarity. The identification of landscape-scale drivers of regional water quality is a useful way to supplement satellite-based remote monitoring programs relying on spectral data alone.

Variation in the macrofaunal community over large temporal and spatial scales in the southern Yellow Sea

NASA Astrophysics Data System (ADS)

Xu, Yong; Sui, Jixing; Yang, Mei; Sun, Yue; Li, Xinzheng; Wang, Hongfa; Zhang, Baolin

2017-09-01

To detect large, temporal- and spatial-scale variations in the macrofaunal community in the southern Yellow Sea, data collected along the western, middle and eastern regions of the southern Yellow Sea from 1958 to 2014 were organized and analyzed. Statistical methods such as cluster analysis, non-metric multidimensional scaling ordination (nMDS), permutational multivariate analysis of variance (PERMANOVA), redundancy analysis (RDA) and canonical correspondence analysis (CCA) were applied. The abundance of polychaetes increased in the western region but decreased in the eastern region from 1958 to 2014, whereas the abundance of echinoderms showed an opposite trend. For the entire macrofaunal community, Margalef's richness (d), the Shannon-Wiener index (H‧) and Pielou's evenness (J‧) were significantly lower in the eastern region when compared with the other two regions. No significant temporal differences were found for d and H‧, but there were significantly lower values of J‧ in 2014. Considerable variation in the macrofaunal community structure over the past several decades and among the geographical regions at the species, genus and family levels were observed. The species, genera and families that contributed to the temporal variation in each region were also identified. The most conspicuous pattern was the increase in the species Ophiura sarsii vadicola in the eastern region. In the western region, five polychaetes (Ninoe palmata, Notomastus latericeus, Paralacydonia paradoxa, Paraprionospio pinnata and Sternaspis scutata) increased consistently from 1958 to 2014. The dominance curves showed that both the species diversity and the dominance patterns were relatively stable in the western and middle regions. Environmental parameters such as depth, temperature and salinity could only partially explain the observed biological variation in the southern Yellow Sea. Anthropogenic activities such as demersal fishing and other unmeasured environmental variables may be more responsible for the long-term changes in the macrofaunal community.

The MSFC large-area imaging multistep proportional counter

NASA Technical Reports Server (NTRS)

Ramsey, B. D.; Weisskopf, M. C.; Joy, M. K.

1989-01-01

A large-area multistep imaging proportional counter that is being currently developed at the Marshall Space Flight Center is described. The device, known as a multistep fluorescence gated detector, consists of a multiwire proportional counter (MWPC) with a preamplification region. The MWCP features superior spatial resolution with a very high degree of background rejection. It is ideally suited for use in X-ray astronomy in 20-100 keV energy range. The paper includes the MWPC schematic and a list of instrument specifications.

Grid-based mapping: A method for rapidly determining the spatial distributions of small features over very large areas

NASA Astrophysics Data System (ADS)

Ramsdale, Jason D.; Balme, Matthew R.; Conway, Susan J.; Gallagher, Colman; van Gasselt, Stephan A.; Hauber, Ernst; Orgel, Csilla; Séjourné, Antoine; Skinner, James A.; Costard, Francois; Johnsson, Andreas; Losiak, Anna; Reiss, Dennis; Swirad, Zuzanna M.; Kereszturi, Akos; Smith, Isaac B.; Platz, Thomas

2017-06-01

The increased volume, spatial resolution, and areal coverage of high-resolution images of Mars over the past 15 years have led to an increased quantity and variety of small-scale landform identifications. Though many such landforms are too small to represent individually on regional-scale maps, determining their presence or absence across large areas helps form the observational basis for developing hypotheses on the geological nature and environmental history of a study area. The combination of improved spatial resolution and near-continuous coverage significantly increases the time required to analyse the data. This becomes problematic when attempting regional or global-scale studies of metre and decametre-scale landforms. Here, we describe an approach for mapping small features (from decimetre to kilometre scale) across large areas, formulated for a project to study the northern plains of Mars, and provide context on how this method was developed and how it can be implemented. Rather than ;mapping; with points and polygons, grid-based mapping uses a ;tick box; approach to efficiently record the locations of specific landforms (we use an example suite of glacial landforms; including viscous flow features, the latitude dependant mantle and polygonised ground). A grid of squares (e.g. 20 km by 20 km) is created over the mapping area. Then the basemap data are systematically examined, grid-square by grid-square at full resolution, in order to identify the landforms while recording the presence or absence of selected landforms in each grid-square to determine spatial distributions. The result is a series of grids recording the distribution of all the mapped landforms across the study area. In some ways, these are equivalent to raster images, as they show a continuous distribution-field of the various landforms across a defined (rectangular, in most cases) area. When overlain on context maps, these form a coarse, digital landform map. We find that grid-based mapping provides an efficient solution to the problems of mapping small landforms over large areas, by providing a consistent and standardised approach to spatial data collection. The simplicity of the grid-based mapping approach makes it extremely scalable and workable for group efforts, requiring minimal user experience and producing consistent and repeatable results. The discrete nature of the datasets, simplicity of approach, and divisibility of tasks, open up the possibility for citizen science in which crowdsourcing large grid-based mapping areas could be applied.

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

PubMed

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

2006-10-01

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

What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?

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

Di Vittorio, Alan V.; Kyle, Page; Collins, William D.

Understanding potential impacts of climate change is complicated by spatially mismatched land representations between gridded datasets and models, and land use models with larger regions defined by geopolitical and/or biophysical criteria. Here in this study, we quantify the sensitivity of Global Change Assessment Model (GCAM) outputs to the delineation of Agro-Ecological Zones (AEZs), which are normally based on historical (1961–1990) climate. We reconstruct GCAM's land regions using projected (2071–2100) climate, and find large differences in estimated future land use that correspond with differences in agricultural commodity prices and production volumes. Importantly, historically delineated AEZs experience spatially heterogeneous climate impacts overmore » time, and do not necessarily provide more homogenous initial land productivity than projected AEZs. Finally, we conclude that non-climatic criteria for land use region delineation are likely preferable for modeling land use change in the context of climate change, and that uncertainty associated with land delineation needs to be quantified.« less

Region-Urbanicity Differences in Locus of Control: Social Disadvantage, Structure, or Cultural Exceptionalism?

PubMed

Shifrer, Dara; Sutton, April

2014-11-01

People with internal rather than external locus of control experience better outcomes in multiple domains. Previous studies on spatial differences in control within America only focused on the South, relied on aggregate level data or historical evidence, or did not account for other confounding regional distinctions (such as variation in urbanicity). Using data from the National Education Longitudinal Study, we find differences in adolescents' loci of control depending on their region and urbanicity are largely attributable to differences in their social background, and only minimally to structural differences (i.e., differences in the qualities of adolescents' schools). Differences that persist net of differences across adolescents and their schools suggest the less internal control of rural Southern adolescents, and the more internal control of rural and urban Northeastern adolescents, may be due to cultural distinctions in those areas. Results indicate region is more closely associated than urbanicity with differences in locus of control, with Western and Northeastern cultures seemingly fostering more internal control than Midwestern and Southern cultures. These findings contribute to research on spatial variation in a variety of psychological traits.

Region-Urbanicity Differences in Locus of Control: Social Disadvantage, Structure, or Cultural Exceptionalism?

PubMed Central

Shifrer, Dara; Sutton, April

2014-01-01

People with internal rather than external locus of control experience better outcomes in multiple domains. Previous studies on spatial differences in control within America only focused on the South, relied on aggregate level data or historical evidence, or did not account for other confounding regional distinctions (such as variation in urbanicity). Using data from the National Education Longitudinal Study, we find differences in adolescents' loci of control depending on their region and urbanicity are largely attributable to differences in their social background, and only minimally to structural differences (i.e., differences in the qualities of adolescents' schools). Differences that persist net of differences across adolescents and their schools suggest the less internal control of rural Southern adolescents, and the more internal control of rural and urban Northeastern adolescents, may be due to cultural distinctions in those areas. Results indicate region is more closely associated than urbanicity with differences in locus of control, with Western and Northeastern cultures seemingly fostering more internal control than Midwestern and Southern cultures. These findings contribute to research on spatial variation in a variety of psychological traits. PMID:25382875

SOFIA/FORCAST Observations of the Arched Filamentary Region in the Galactic Center

NASA Astrophysics Data System (ADS)

Hankins, Matthew; Lau, Ryan M.; Morris, Mark; Herter, Terry L.

2016-06-01

Abstract: We present 19.7, 25.2, 31.5, and 37.1 μm maps of the Thermal Arched Filament region in the Galactic Center taken with the Faint Object Infrared Camera for the SOFIA Telescope (FORCAST) with an angular resolution of 3.2-3.8". We calculate the integrated infrared luminosity of the Arched Filaments and show that they are consistent with being heated by the nearby Arches cluster. Additionally, using our observations, we infer dust temperatures (75 - 90 K) across the Arched Filaments which are remarkably consistent over large spatial scales (˜ 25 pc). We discuss the possible geometric effects needed to recreate this temperature structure. Additionally, we compare the observed morphology of the Arches in the FORCAST maps with the Paschen-α emission in the region to study what fraction of the infrared emission may be coming from dust in the HII region versus the PDR beneath it. Finally, we use Spitzer/IRAC 8 μm data to look for spatial variations in PAH abundance in the rich UV environment of the young (~2-4 Myr) and massive Arches cluster.

Quantification of traumatic meningeal injury using dynamic contrast enhanced (DCE) fluid-attenuated inversion recovery (FLAIR) imaging

NASA Astrophysics Data System (ADS)

Castro, Marcelo A.; Williford, Joshua P.; Cota, Martin R.; MacLaren, Judy M.; Dardzinski, Bernard J.; Latour, Lawrence L.; Pham, Dzung L.; Butman, John A.

2016-03-01

Traumatic meningeal injury is a novel imaging marker of traumatic brain injury, which appears as enhancement of the dura on post-contrast T2-weighted FLAIR images, and is likely associated with inflammation of the meninges. Dynamic Contrast Enhanced MRI provides a better discrimination of abnormally perfused regions. A method to properly identify those regions is presented. Images of seventeen patients scanned within 96 hours of head injury with positive traumatic meningeal injury were normalized and aligned. The difference between the pre- and last post-contrast acquisitions was segmented and voxels in the higher class were spatially clustered. Spatial and morphological descriptors were used to identify the regions of enhancement: a) centroid; b) distance to the brain mask from external voxels; c) distance from internal voxels; d) size; e) shape. The method properly identified thirteen regions among all patients. The method failed in one case due to the presence of a large brain lesion that altered the mask boundaries. Most false detections were correctly rejected resulting in a sensitivity and specificity of 92.9% and 93.6%, respectively.

What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?

DOE PAGES

Di Vittorio, Alan V.; Kyle, Page; Collins, William D.

2016-09-03

Understanding potential impacts of climate change is complicated by spatially mismatched land representations between gridded datasets and models, and land use models with larger regions defined by geopolitical and/or biophysical criteria. Here in this study, we quantify the sensitivity of Global Change Assessment Model (GCAM) outputs to the delineation of Agro-Ecological Zones (AEZs), which are normally based on historical (1961–1990) climate. We reconstruct GCAM's land regions using projected (2071–2100) climate, and find large differences in estimated future land use that correspond with differences in agricultural commodity prices and production volumes. Importantly, historically delineated AEZs experience spatially heterogeneous climate impacts overmore » time, and do not necessarily provide more homogenous initial land productivity than projected AEZs. Finally, we conclude that non-climatic criteria for land use region delineation are likely preferable for modeling land use change in the context of climate change, and that uncertainty associated with land delineation needs to be quantified.« less

High Resolution Temperature Measurement of Liquid Stainless Steel Using Hyperspectral Imaging

PubMed Central

Devesse, Wim; De Baere, Dieter; Guillaume, Patrick

2017-01-01

A contactless temperature measurement system is presented based on a hyperspectral line camera that captures the spectra in the visible and near infrared (VNIR) region of a large set of closely spaced points. The measured spectra are used in a nonlinear least squares optimization routine to calculate a one-dimensional temperature profile with high spatial resolution. Measurements of a liquid melt pool of AISI 316L stainless steel show that the system is able to determine the absolute temperatures with an accuracy of 10%. The measurements are made with a spatial resolution of 12 µm/pixel, justifying its use in applications where high temperature measurements with high spatial detail are desired, such as in the laser material processing and additive manufacturing fields. PMID:28067764

Differences in protein expression among five species of stream stonefly (Plecoptera) along a latitudinal gradient in Japan.

PubMed

Gamboa, Maribet; Tsuchiya, Maria Claret; Matsumoto, Suguru; Iwata, Hisato; Watanabe, Kozo

2017-11-01

Proteome variation among natural populations along an environmental gradient may provide insights into how the biological functions of species are related to their local adaptation. We investigated protein expression in five stream stonefly species from four geographic regions along a latitudinal gradient in Japan with varying climatic conditions. The extracted proteins were separated by two-dimensional gel electrophoresis and identified by matrix-assisted laser desorption/ionization of time-of-flight (MALDI TOF/TOF), yielding 446 proteins. Low interspecies variation in the proteome profiles was observed among five species within geographical regions, presumably due to the co-occurring species sharing the environments. However, large spatial variations in protein expression were found among four geographic regions, suggesting strong regulation of protein expression in heterogeneous environments, where the spatial variations were positively correlated with water temperature. We identified 21 unique proteins expressed specifically in a geographical region and six common proteins expressed throughout all regions. In warmer regions, metabolic proteins were upregulated, whereas proteins related to cold stress, the photoperiod, and mating were downregulated. Oxygen-related and energy-production proteins were upregulated in colder regions with higher altitudes. Thus, our proteomic approach is useful for identifying and understanding important biological functions related to local adaptations by populations of stoneflies. © 2017 Wiley Periodicals, Inc.

Imaging the Seismic Cycle in the Central Andean Subduction Zone from Geodetic Observations

NASA Astrophysics Data System (ADS)

Ortega-Culaciati, F.; Becerra-Carreño, V. C.; Socquet, A.; Jara, J.; Carrizo, D.; Norabuena, E. O.; Simons, M.; Vigny, C.; Bataille, K. D.; Moreno, M.; Baez, J. C.; Comte, D.; Contreras-Reyes, E.; Delorme, A.; Genrich, J. F.; Klein, E.; Ortega, I.; Valderas, M. C.

2015-12-01

We aim to quantify spatial and temporal evolution of fault slip behavior during all stages of the seismic cycle in subduction megathrusts, with the eventual goal of improving our understanding of the mechanical behavior of the subduction system and its implications for earthquake and tsunami hazards. In this work, we analyze the portion of the Nazca-SouthAmerican plates subduction zone affected by the 1868 southern Peru and 1877 northern Chile mega-earthquakes. The 1868 and 1878 events defined a seismic gap that did not experience a large earthquake for over 124 years. Only recently, the 1995 Mw 8.1 Antofagasta, 2001 Mw 8.4 Arequipa, 2007 Mw 7.7 Tocopilla, and 2014 Mw 8.2 Pisagua earthquakes released only a small fraction of the potential slip budget, thereby raising concerns about continued seismic and tsunami hazard. We use over a decade of observations from continuous and campaign GPS networks to analyze inter-seismic strain accumulation, as well as co-seimic deformation associated to the more recent earthquakes in the in the Central Andean region. We obtain inferences of slip (and back-slip) behavior using a consistent and robust inversion framework that accounts for the spatial variability of the constraint provided by the observations on slip across the subduction megathrust. We present an updated inter-seismic coupling model and estimates of pre-, co- and post- seismic slip behavior associated with the most recent 2014 Mw 8.2 Pisagua earthquake. We analyze our results, along with published information on the recent and historical large earthquakes, to characterize the regions of the megathrust that tend to behave aseismically, and those that are capable to accumulate a slip budget (ultimately leading to the generation of large earthquakes), to what extent such regions may overlap, and discuss the potential for large earthquakes in the region.

[Land cover classification of Four Lakes Region in Hubei Province based on MODIS and ENVISAT data].

PubMed

Xue, Lian; Jin, Wei-Bin; Xiong, Qin-Xue; Liu, Zhang-Yong

2010-03-01

Based on the differences of back scattering coefficient in ENVISAT ASAR data, a classification was made on the towns, waters, and vegetation-covered areas in the Four Lakes Region of Hubei Province. According to the local cropping systems and phenological characteristics in the region, and by using the discrepancies of the MODIS-NDVI index from late April to early May, the vegetation-covered areas were classified into croplands and non-croplands. The classification results based on the above-mentioned procedure was verified by the classification results based on the ETM data with high spatial resolution. Based on the DEM data, the non-croplands were categorized into forest land and bottomland; and based on the discrepancies of mean NDVI index per month, the crops were identified as mid rice, late rice, and cotton, and the croplands were identified as paddy field and upland field. The land cover classification based on the MODIS data with low spatial resolution was basically consistent with that based on the ETM data with high spatial resolution, and the total error rate was about 13.15% when the classification results based on ETM data were taken as the standard. The utilization of the above-mentioned procedures for large scale land cover classification and mapping could make the fast tracking of regional land cover classification.

Understanding the Distribution of Marine Megafauna in the English Channel Region: Identifying Key Habitats for Conservation within the Busiest Seaway on Earth

PubMed Central

McClellan, Catherine M.; Brereton, Tom; Dell'Amico, Florence; Johns, David G.; Cucknell, Anna-C.; Patrick, Samantha C.; Penrose, Rod; Ridoux, Vincent; Solandt, Jean-Luc; Stephan, Eric; Votier, Stephen C.; Williams, Ruth; Godley, Brendan J.

2014-01-01

The temperate waters of the North-Eastern Atlantic have a long history of maritime resource richness and, as a result, the European Union is endeavouring to maintain regional productivity and biodiversity. At the intersection of these aims lies potential conflict, signalling the need for integrated, cross-border management approaches. This paper focuses on the marine megafauna of the region. This guild of consumers was formerly abundant, but is now depleted and protected under various national and international legislative structures. We present a meta-analysis of available megafauna datasets using presence-only distribution models to characterise suitable habitat and identify spatially-important regions within the English Channel and southern bight of the North Sea. The integration of studies from dedicated and opportunistic observer programmes in the United Kingdom and France provide a valuable perspective on the spatial and seasonal distribution of various taxonomic groups, including large pelagic fishes and sharks, marine mammals, seabirds and marine turtles. The Western English Channel emerged as a hotspot of biodiversity for megafauna, while species richness was low in the Eastern English Channel. Spatial conservation planning is complicated by the highly mobile nature of marine megafauna, however they are important components of the marine environment and understanding their distribution is a first crucial step toward their inclusion into marine ecosystem management. PMID:24586985

Future summer mega-heatwave and record-breaking temperatures in a warmer France climate

NASA Astrophysics Data System (ADS)

Bador, Margot; Terray, Laurent; Boé, Julien; Somot, Samuel; Alias, Antoinette; Gibelin, Anne-Laure; Dubuisson, Brigitte

2017-07-01

This study focuses on future very hot summers associated with severe heatwaves and record-breaking temperatures in France. Daily temperature observations and a pair of historical and scenario (greenhouse gas radiative concentration pathway 8.5) simulations with the high-resolution (∼12.5 km) ALADIN regional climate model provide a robust framework to examine the spatial distribution of these extreme events and their 21st century evolution. Five regions are identified with an extreme event spatial clustering algorithm applied to observed temperatures. They are used to diagnose the 21st century heatwave spatial patterns. In the 2070s, we find a simulated mega-heatwave as severe as the 2003 observed heatwave relative to its contemporaneous climate. A 20-member initial condition ensemble is used to assess the sensitivity of this future heatwave to the internal variability in the regional climate model and to pre-existing land surface conditions. Even in a much warmer and drier climate in France, late spring dry land conditions may lead to a significant amplification of summer extreme temperatures and heatwave intensity through limitations in evapotranspiration. By 2100, the increase in summer temperature maxima exhibits a range from 6 °C to almost 13 °C in the five regions in France, relative to historical maxima. These projections are comparable with the estimates given by a large number of global climate models.

A new data set for estimating organic carbon storage to 3 m depth in soils of the northern circumpolar permafrost region

USGS Publications Warehouse

Hugelius, G.; Bockheim, James G.; Camill, P.; Elberling, B.; Grosse, G.; Harden, J.W.; Johnson, Kevin; Jorgenson, T.; Koven, C.D.; Kuhry, P.; Michaelson, G.; Mishra, U.; Palmtag, J.; Ping, C.-L.; O'Donnell, J.; Schirrmeister, L.; Schuur, E.A.G.; Sheng, Y.; Smith, L.C.; Strauss, J.; Yu, Z.

2013-01-01

High-latitude terrestrial ecosystems are key components in the global carbon cycle. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify stocks of soil organic carbon (SOC) in the northern circumpolar permafrost region (a total area of 18.7 × 106 km2). The NCSCD is a geographical information system (GIS) data set that has been constructed using harmonized regional soil classification maps together with pedon data from the northern permafrost region. Previously, the NCSCD has been used to calculate SOC storage to the reference depths 0–30 cm and 0–100 cm (based on 1778 pedons). It has been shown that soils of the northern circumpolar permafrost region also contain significant quantities of SOC in the 100–300 cm depth range, but there has been no circumpolar compilation of pedon data to quantify this deeper SOC pool and there are no spatially distributed estimates of SOC storage below 100 cm depth in this region. Here we describe the synthesis of an updated pedon data set for SOC storage (kg C m-2) in deep soils of the northern circumpolar permafrost regions, with separate data sets for the 100–200 cm (524 pedons) and 200–300 cm (356 pedons) depth ranges. These pedons have been grouped into the North American and Eurasian sectors and the mean SOC storage for different soil taxa (subdivided into Gelisols including the sub-orders Histels, Turbels, Orthels, permafrost-free Histosols, and permafrost-free mineral soil orders) has been added to the updated NCSCDv2. The updated version of the data set is freely available online in different file formats and spatial resolutions that enable spatially explicit applications in GIS mapping and terrestrial ecosystem models. While this newly compiled data set adds to our knowledge of SOC in the 100–300 cm depth range, it also reveals that large uncertainties remain. Identified data gaps include spatial coverage of deep (> 100 cm) pedons in many regions as well as the spatial extent of areas with thin soils overlying bedrock and the quantity and distribution of massive ground ice. An open access data-portal for the pedon data set and the GIS-data sets is available online at http://bolin.su.se/data/ncscd/.

A new data set for estimating organic carbon storage to 3 m depth in soils of the northern circumpolar permafrost region

DOE PAGES

Hugelius, Gustaf; Bockheim, J. G.; Camill, P.; ...

2013-12-23

High-latitude terrestrial ecosystems are key components in the global carbon cycle. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify stocks of soil organic carbon (SOC) in the northern circumpolar permafrost region (a total area of 18.7 × 10 6 km 2). The NCSCD is a geographical information system (GIS) data set that has been constructed using harmonized regional soil classification maps together with pedon data from the northern permafrost region. Previously, the NCSCD has been used to calculate SOC storage to the reference depths 0–30 cm and 0–100 cm (based on 1778 pedons). It has been shownmore » that soils of the northern circumpolar permafrost region also contain significant quantities of SOC in the 100–300 cm depth range, but there has been no circumpolar compilation of pedon data to quantify this deeper SOC pool and there are no spatially distributed estimates of SOC storage below 100 cm depth in this region. Here we describe the synthesis of an updated pedon data set for SOC storage (kg C m -2) in deep soils of the northern circumpolar permafrost regions, with separate data sets for the 100–200 cm (524 pedons) and 200–300 cm (356 pedons) depth ranges. These pedons have been grouped into the North American and Eurasian sectors and the mean SOC storage for different soil taxa (subdivided into Gelisols including the sub-orders Histels, Turbels, Orthels, permafrost-free Histosols, and permafrost-free mineral soil orders) has been added to the updated NCSCDv2. The updated version of the data set is freely available online in different file formats and spatial resolutions that enable spatially explicit applications in GIS mapping and terrestrial ecosystem models. While this newly compiled data set adds to our knowledge of SOC in the 100–300 cm depth range, it also reveals that large uncertainties remain. In conclusion, identified data gaps include spatial coverage of deep (> 100 cm) pedons in many regions as well as the spatial extent of areas with thin soils overlying bedrock and the quantity and distribution of massive ground ice.« less

Impacts of wind farms on land surface temperature

NASA Astrophysics Data System (ADS)

Zhou, Liming; Tian, Yuhong; Baidya Roy, Somnath; Thorncroft, Chris; Bosart, Lance F.; Hu, Yuanlong

2012-07-01

The wind industry in the United States has experienced a remarkably rapid expansion of capacity in recent years and this fast growth is expected to continue in the future. While converting wind's kinetic energy into electricity, wind turbines modify surface-atmosphere exchanges and the transfer of energy, momentum, mass and moisture within the atmosphere. These changes, if spatially large enough, may have noticeable impacts on local to regional weather and climate. Here we present observational evidence for such impacts based on analyses of satellite data for the period of 2003-2011 over a region in west-central Texas, where four of the world's largest wind farms are located. Our results show a significant warming trend of up to 0.72°C per decade, particularly at night-time, over wind farms relative to nearby non-wind-farm regions. We attribute this warming primarily to wind farms as its spatial pattern and magnitude couples very well with the geographic distribution of wind turbines.

DYNAMICS OF HIGH ENERGY IONS AT A STRUCTURED COLLISIONLESS SHOCK FRONT

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

Gedalin, M.; Dröge, W.; Kartavykh, Y. Y., E-mail: gedalin@bgu.ac.il

2016-07-10

Ions undergoing first-order Fermi acceleration at a shock are scattered in the upstream and downstream regions by magnetic inhomogeneities. For high energy ions this scattering is efficient at spatial scales substantially larger than the gyroradius of the ions. The transition from one diffusive region to the other occurs via crossing the shock, and the ion dynamics during this crossing is mainly affected by the global magnetic field change between the upstream and downstream region. We study the effects of the fine structure of the shock front, such as the foot-ramp-overshoot profile and the phase-standing upstream and downstream magnetic oscillations. Wemore » also consider time dependent features, including reformation and large amplitude coherent waves. We show that the influence of the spatial and temporal structure of the shock front on the dependence of the transition and reflection on the pitch angle of the ions is already weak at ion speeds five times the speed of the upstream flow.« less

Accumulation patterns around Dome C, East Antarctica, in the last 73 kyr

NASA Astrophysics Data System (ADS)

Cavitte, Marie G. P.; Parrenin, Frédéric; Ritz, Catherine; Young, Duncan A.; Van Liefferinge, Brice; Blankenship, Donald D.; Frezzotti, Massimo; Roberts, Jason L.

2018-04-01

We reconstruct the pattern of surface accumulation in the region around Dome C, East Antarctica, since the last glacial. We use a set of 18 isochrones spanning all observable depths of the ice column, interpreted from various ice-penetrating radar surveys and a 1-D ice flow model to invert for accumulation rates in the region. The shallowest four isochrones are then used to calculate paleoaccumulation rates between isochrone pairs using a 1-D assumption where horizontal advection is negligible in the time interval of each layer. We observe that the large-scale (100s km) surface accumulation gradient is spatially stable through the last 73 kyr, which reflects current modeled and observed precipitation gradients in the region. We also observe small-scale (10 s km) accumulation variations linked to snow redistribution at the surface, due to changes in its slope and curvature in the prevailing wind direction that remain spatially stationary since the last glacial.

Ozone distribution in remote ecologically vulnerable terrain of the southern Sierra Nevada, CA.

PubMed

Panek, Jeanne; Saah, David; Esperanza, Annie; Bytnerowicz, Andrzej; Fraczek, Witold; Cisneros, Ricardo

2013-11-01

Ozone concentration spatial patterns remain largely uncharacterized across the extensive wilderness areas of the Sierra Nevada, CA, despite being downwind of major pollution sources. These natural areas, including four national parks and four national forests, contain forest species that are susceptible to ozone injury. Forests stressed by ozone are also more vulnerable to other agents of mortality, including insects, pathogens, climate change, and ultimately fire. Here we analyze three years of passive ozone monitor data from the southern Sierra Nevada and interpolate landscape-scale spatial and temporal patterns during the summer-through-fall high ozone concentration period. Segmentation analysis revealed three types of ozone exposure sub-regions: high, low, and variable. Consistently high ozone exposure regions are expected to be most vulnerable to forest mortality. One high exposure sub-region has been documented elsewhere as being further vulnerable to increased drought and fire potential. Identifying such hot-spots of forest vulnerability has utility for prioritizing management. Copyright © 2013 Elsevier Ltd. All rights reserved.

Euclidean perspective on the unfolding of azurin: angular correlations

NASA Astrophysics Data System (ADS)

Warren, Jeffrey J.; Gray, Harry B.; Winkler, Jay R.; Kozak, John J.

2013-12-01

The geometrical model introduced previously by the authors has been extended quantitatively to document changes in angular correlations between and among residues as azurin unfolds. In the early stages of denaturation, these changes are found to be more pronounced than changes in the spatial displacement of residues, a result that is also found for residues acting in concert, viz., α-helices, β-sheet residues and residues in 'turning regions.' Our analysis leads to a picture of the large-scale motion of the polypeptide chain as azurin denatures. Flanking a central 'ribbon' of residues whose orientation remains essentially invariant, we find that in the early stages of unfolding, left- and right-hand 'wings' adjacent to this stationary scaffolding pivot counterclockwise, while smaller regions on opposing ends of the β-barrel pivot clockwise. As spatial constraints characterising the native state are further relaxed, our calculations show that some regions reverse their orientational motion, reflecting the enhanced flexibility of the polypeptide chain in the denatured state.

On the modeling of irradiation-induced homogeneous precipitation in proton-bombarded Ni-Si solid solutions

NASA Astrophysics Data System (ADS)

Lam, Nghi Q.; Janghorban, K.; Ardell, A. J.

1981-10-01

Irradiation-induced solute redistribution leading to precipitation of coherent γ' particles in undersaturated Ni-based solid solutions containing 6 and 8 at.% Si during 400-keV proton bombardment was modeled, based on the concept of solute segregation in concentrated alloys under spatially-dependent defect production conditions. The combined effects of (i) an extremely large difference between the defect production rates in the peak-damage and mid-range regions during irradiation and (ii) a preferential coupling between the interstitial and solute fluxes generate a net transient flux of Si atoms into the mid-range region, which is much larger than the solute flux out of this location. As a result, the Si concentration exceeds the solubility limit and homogeneous precipitation of the γ' phase occurs in this particular region of the irradiated samples. The spatial, compositional and temperature dependences of irradiation-induced homogeneous precipitation derived from the present theoretical calculations are in good qualitative agreement with experimental observations

A Place-Oriented, Mixed-Level Regionalization Method for Constructing Geographic Areas in Health Data Dissemination and Analysis

PubMed Central

Mu, Lan; Wang, Fahui; Chen, Vivien W.; Wu, Xiao-Cheng

2015-01-01

Similar geographic areas often have great variations in population size. In health data management and analysis, it is desirable to obtain regions of comparable population by decomposing areas of large population (to gain more spatial variability) and merging areas of small population (to mask privacy of data). Based on the Peano curve algorithm and modified scale-space clustering, this research proposes a mixed-level regionalization (MLR) method to construct geographic areas with comparable population. The method accounts for spatial connectivity and compactness, attributive homogeneity, and exogenous criteria such as minimum (and approximately equal) population or disease counts. A case study using Louisiana cancer data illustrates the MLR method and its strengths and limitations. A major benefit of the method is that most upper level geographic boundaries can be preserved to increase familiarity of constructed areas. Therefore, the MLR method is more human-oriented and place-based than computer-oriented and space-based. PMID:26251551

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

NASA Astrophysics Data System (ADS)

Formetta, Giuseppe; Stewart, Elizabeth; Bell, Victoria

2017-04-01

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

The sense and non-sense of plot-scale, catchment-scale, continental-scale and global-scale hydrological modelling

NASA Astrophysics Data System (ADS)

Bronstert, Axel; Heistermann, Maik; Francke, Till

2017-04-01

Hydrological models aim at quantifying the hydrological cycle and its constituent processes for particular conditions, sites or periods in time. Such models have been developed for a large range of spatial and temporal scales. One must be aware that the question which is the appropriate scale to be applied depends on the overall question under study. Therefore, it is not advisable to give a general applicable guideline on what is "the best" scale for a model. This statement is even more relevant for coupled hydrological, ecological and atmospheric models. Although a general statement about the most appropriate modelling scale is not recommendable, it is worth to have a look on what are the advantages and the shortcomings of micro-, meso- and macro-scale approaches. Such an appraisal is of increasing importance, since increasingly (very) large / global scale approaches and models are under operation and therefore the question arises how far and for what purposes such methods may yield scientifically sound results. It is important to understand that in most hydrological (and ecological, atmospheric and other) studies process scale, measurement scale, and modelling scale differ from each other. In some cases, the differences between theses scales can be of different orders of magnitude (example: runoff formation, measurement and modelling). These differences are a major source of uncertainty in description and modelling of hydrological, ecological and atmospheric processes. Let us now summarize our viewpoint of the strengths (+) and weaknesses (-) of hydrological models of different scales: Micro scale (e.g. extent of a plot, field or hillslope): (+) enables process research, based on controlled experiments (e.g. infiltration; root water uptake; chemical matter transport); (+) data of state conditions (e.g. soil parameter, vegetation properties) and boundary fluxes (e.g. rainfall or evapotranspiration) are directly measurable and reproducible; (+) equations based on first principals, partly pde-type, are available for several processes (but not for all), because measurement and modelling scale are compatible (-) the spatial model domain are hardly representative for larger spatial entities, including regions for which water resources management decisions are to be taken; straightforward upsizing is also limited by data availability and computational requirements. Meso scale (e.g. extent of a small to large catchment or region): (+) the spatial extent of the model domain has approximately the same extent as the regions for which water resources management decisions are to be taken. I.e., such models enable water resources quantification at the scale of most water management decisions; (+) data of some state conditions (e.g. vegetation cover, topography, river network and cross sections) are available; (+) data of some boundary fluxes (in particular surface runoff / channel flow) are directly measurable with mostly sufficient certainty; (+) equations, partly based on simple water budgeting, partly variants of pde-type equations, are available for most hydrological processes. This enables the construction of meso-scale distributed models reflecting the spatial heterogeneity of regions/landscapes; (-) process scale, measurement scale, and modelling scale differ from each other for a number of processes, e.g., such as runoff generation; (-) the process formulation (usually derived from micro-scale studies) cannot directly be transferred to the modelling domain. Upscaling procedures for this purpose are not readily and generally available. Macro scale (e.g. extent of a continent up to global): (+) the spatial extent of the model may cover the whole Earth. This enables an attractive global display of model results; (+) model results might be technically interchangeable or at least comparable with results from other global models, such as global climate models; (-) process scale, measurement scale, and modelling scale differ heavily from each other for all hydrological and associated processes; (-) the model domain and its results are not representative regions for which water resources management decisions are to be taken. (-) both state condition and boundary flux data are hardly available for the whole model domain. Water management data and discharge data from remote regions are particular incomplete / unavailable for this scale. This undermines the model's verifiability; (-) since process formulation and resulting modelling reliability at this scale is very limited, such models can hardly show any explanatory skills or prognostic power; (-) since both the entire model domain and the spatial sub-units cover large areas, model results represent values averaged over at least the spatial sub-unit's extent. In many cases, the applied time scale implies a long-term averaging in time, too. We emphasize the importance to be aware of the above mentioned strengths and weaknesses of those scale-specific models. (Many of the) results of the current global model studies do not reflect such limitations. In particular, we consider the averaging over large model entities in space and/or time inadequate. Many hydrological processes are of a non-linear nature, including threshold-type behaviour. Such features cannot be reflected by such large scale entities. The model results therefore can be of little or no use for water resources decisions and/or even misleading for public debates or decision making. Some rather newly developed sustainability concepts, e.g. "Planetary Boundaries" in which humanity may "continue to develop and thrive for generations to come" are based on such global-scale approaches and models. However, many of the major problems regarding sustainability on Earth, e.g. water scarcity, do not exhibit on a global but on a regional scale. While on a global scale water might look like being available in sufficient quantity and quality, there are many regions where water problems already have very harmful or even devastating effects. Therefore, it is the challenge to derive models and observation programmes for regional scales. In case a global display is desired future efforts should be directed towards the development of a global picture based on a mosaic of regional sound assessments, rather than "zooming into" the results of large-scale simulations. Still, a key question remains to be discussed, i.e. for which purpose models at this (global) scale can be used.

Spatial variations in drainage efficiency in a boreal wetland environment as a function of lidar and radar-derived deviations from the regional hydraulic gradient

NASA Astrophysics Data System (ADS)

Hopkinson, C.; Brisco, B.; Chasmer, L.; Devito, K.; Montgomery, J. S.; Patterson, S.; Petrone, R. M.

2017-12-01

The dense forest cover of the Western Boreal Plains of northern Alberta is underlain by a mix of glacial moraines, sandy outwash sediments and clay plains possessing spatially variable hydraulic conductivities. The region is also characterised by a large number of post-glacial surface depression wetlands that have seasonally and topographically limited surface connectivity. Consequently, drainage along shallow regional hydraulic gradients may be dominated either by variations in surface geology or local variations in Et. Long-term government lake level monitoring is sparse in this region, but over a decade of hydrometeorological monitoring has taken place around the Utikuma Regional Study Area (URSA), a research site led by the University of Alberta. In situ lake and ground water level data are here combined with time series of airborne lidar and RadarSat II synthetic aperture radar (SAR) data to assess the spatial variability of water levels during late summer period characterised by flow recession. Long term Lidar data were collected or obtained by the authors in August of 2002, 2008, 2011 and 2016, while seasonal SAR data were captured approximately every 24 days during the summers of 2015, 2016 and 2017. Water levels for wetlands exceeding 100m2 in area across a north-trending 20km x 5km topographic gradient north of Utikuma Lake were extracted directly from the lidar and indirectly from the SAR. The recent seasonal variability in spatial water levels was extracted from SAR, while the lidar data illustrated more long term trends associated with land use and riparian vegetation succession. All water level data collected in August were combined and averaged at multiple scales using a raster focal statistics function to generate a long term spatial map of the regional hydraulic gradient and scale-dependent variations. Areas of indicated high and low drainage efficiency were overlain onto layers of landcover and surface geology to ascertain causal relationships. Areas associated with high spatial variability in water level illustrate reduced drainage connectivity, while areas of reduced variability indicate high surface connectivity and/or hydraulic conductivity. The hypothesis of surface geology controls on local wetland connectivity and landscape drainage efficiency is supported through this analysis.

Landscape-scale distribution and persistence of genetically modified oilseed rape (Brassica napus) in Manitoba, Canada.

PubMed

Knispel, Alexis L; McLachlan, Stéphane M

2010-01-01

Genetically modified herbicide-tolerant (GMHT) oilseed rape (OSR; Brassica napus L.) was approved for commercial cultivation in Canada in 1995 and currently represents over 95% of the OSR grown in western Canada. After a decade of widespread cultivation, GMHT volunteers represent an increasing management problem in cultivated fields and are ubiquitous in adjacent ruderal habitats, where they contribute to the spread of transgenes. However, few studies have considered escaped GMHT OSR populations in North America, and even fewer have been conducted at large spatial scales (i.e. landscape scales). In particular, the contribution of landscape structure and large-scale anthropogenic dispersal processes to the persistence and spread of escaped GMHT OSR remains poorly understood. We conducted a multi-year survey of the landscape-scale distribution of escaped OSR plants adjacent to roads and cultivated fields. Our objective was to examine the long-term dynamics of escaped OSR at large spatial scales and to assess the relative importance of landscape and localised factors to the persistence and spread of these plants outside of cultivation. From 2005 to 2007, we surveyed escaped OSR plants along roadsides and field edges at 12 locations in three agricultural landscapes in southern Manitoba where GMHT OSR is widely grown. Data were analysed to examine temporal changes at large spatial scales and to determine factors affecting the distribution of escaped OSR plants in roadside and field edge habitats within agricultural landscapes. Additionally, we assessed the potential for seed dispersal between escaped populations by comparing the relative spatial distribution of roadside and field edge OSR. Densities of escaped OSR fluctuated over space and time in both roadside and field edge habitats, though the proportion of GMHT plants was high (93-100%). Escaped OSR was positively affected by agricultural landscape (indicative of cropping intensity) and by the presence of an adjacent field planted to OSR. Within roadside habitats, escaped OSR was also strongly associated with large-scale variables, including road surface (indicative of traffic intensity) and distance to the nearest grain elevator. Conversely, within field edges, OSR density was affected by localised crop management practices such as mowing, soil disturbance and herbicide application. Despite the proximity of roadsides and field edges, there was little evidence of spatial aggregation among escaped OSR populations in these two habitats, especially at very fine spatial scales (i.e. <100 m), suggesting that natural propagule exchange is infrequent. Escaped OSR populations were persistent at large spatial and temporal scales, and low density in a given landscape or year was not indicative of overall extinction. As a result of ongoing cultivation and transport of OSR crops, escaped GMHT traits will likely remain predominant in agricultural landscapes. While escaped OSR in field edge habitats generally results from local seeding and management activities occurring at the field-scale, distribution patterns within roadside habitats are determined in large part by seed transport occurring at the landscape scale and at even larger regional scales. Our findings suggest that these large-scale anthropogenic dispersal processes are sufficient to enable persistence despite limited natural seed dispersal. This widespread dispersal is likely to undermine field-scale management practices aimed at eliminating escaped and in-field GMHT OSR populations. Agricultural transport and landscape-scale cropping patterns are important determinants of the distribution of escaped GM crops. At the regional level, these factors ensure ongoing establishment and spread of escaped GMHT OSR despite limited local seed dispersal. Escaped populations thus play an important role in the spread of transgenes and have substantial implications for the coexistence of GM and non-GM production systems. Given the large-scale factors driving the spread of escaped transgenes, localised co-existence measures may be impracticable where they are not commensurate with regional dispersal mechanisms. To be effective, strategies aimed at reducing contamination from GM crops should be multi-scale in approach and be developed and implemented at both farm and landscape levels of organisation. Multiple stakeholders should thus be consulted, including both GM and non-GM farmers, as well as seed developers, processors, transporters and suppliers. Decisions to adopt GM crops require thoughtful and inclusive consideration of the risks and responsibilities inherent in this new technology.

First results from GeMS/GSAOI for project SUNBIRD: Supernovae UNmasked By Infra-Red Detection

NASA Astrophysics Data System (ADS)

Kool, E. C.; Ryder, S.; Kankare, E.; Mattila, S.; Reynolds, T.; McDermid, R. M.; Pérez-Torres, M. A.; Herrero-Illana, R.; Schirmer, M.; Efstathiou, A.; Bauer, F. E.; Kotilainen, J.; Väisänen, P.; Baldwin, C.; Romero-Cañizales, C.; Alberdi, A.

2018-02-01

Core collapse supernova (CCSN) rates suffer from large uncertainties as many CCSNe exploding in regions of bright background emission and significant dust extinction remain unobserved. Such a shortfall is particularly prominent in luminous infrared galaxies (LIRGs), which have high star formation (and thus CCSN) rates and host bright and crowded nuclear regions, where large extinctions and reduced search detection efficiency likely lead to a significant fraction of CCSNe remaining undiscovered. We present the first results of project SUNBIRD (Supernovae UNmasked By Infra-Red Detection), where we aim to uncover CCSNe that otherwise would remain hidden in the complex nuclear regions of LIRGs, and in this way improve the constraints on the fraction that is missed by optical seeing-limited surveys. We observe in the near-infrared 2.15 μm Ks-band, which is less affected by dust extinction compared to the optical, using the multiconjugate adaptive optics imager GeMS/GSAOI on Gemini South, allowing us to achieve a spatial resolution that lets us probe close in to the nuclear regions. During our pilot program and subsequent first full year we have discovered three CCSNe and one candidate with projected nuclear offsets as small as 200 pc. When compared to the total sample of LIRG CCSNe discovered in the near-IR and optical, we show that our method is singularly effective in uncovering CCSNe in nuclear regions and we conclude that the majority of CCSNe exploding in LIRGs are not detected as a result of dust obscuration and poor spatial resolution.

Solutions for extracting file level spatial metadata from airborne mission data

NASA Astrophysics Data System (ADS)

Schwab, M. J.; Stanley, M.; Pals, J.; Brodzik, M.; Fowler, C.; Icebridge Engineering/Spatial Metadata

2011-12-01

Authors: Michael Stanley Mark Schwab Jon Pals Mary J. Brodzik Cathy Fowler Collaboration: Raytheon EED and NSIDC Raytheon / EED 5700 Rivertech Court Riverdale, MD 20737 NSIDC University of Colorado UCB 449 Boulder, CO 80309-0449 Data sets acquired from satellites and aircraft may differ in many ways. We will focus on the differences in spatial coverage between the two platforms. Satellite data sets over a given period typically cover large geographic regions. These data are collected in a consistent, predictable and well understood manner due to the uniformity of satellite orbits. Since satellite data collection paths are typically smooth and uniform the data from satellite instruments can usually be described with simple spatial metadata. Subsequently, these spatial metadata can be stored and searched easily and efficiently. Conversely, aircraft have significantly more freedom to change paths, circle, overlap, and vary altitude all of which add complexity to the spatial metadata. Aircraft are also subject to wind and other elements that result in even more complicated and unpredictable spatial coverage areas. This unpredictability and complexity makes it more difficult to extract usable spatial metadata from data sets collected on aircraft missions. It is not feasible to use all of the location data from aircraft mission data sets for use as spatial metadata. The number of data points in typical data sets poses serious performance problems for spatial searching. In order to provide efficient spatial searching of the large number of files cataloged in our systems, we need to extract approximate spatial descriptions as geo-polygons from a small number of vertices (fewer than two hundred). We present some of the challenges and solutions for creating airborne mission-derived spatial metadata. We are implementing these methods to create the spatial metadata for insertion of IceBridge mission data into ECS for public access through NSIDC and ECHO but, they are potentially extensible to any aircraft mission data.

An empirical model of the tidal currents in the Gulf of the Farallones

USGS Publications Warehouse

Steger, J.M.; Collins, C.A.; Schwing, F.B.; Noble, M.; Garfield, N.; Steiner, M.T.

1998-01-01

Candela et al. (1990, 1992) showed that tides in an open ocean region can be resolved using velocity data from a ship-mounted ADCP. We use their method to build a spatially varying model of the tidal currents in the Gulf of the Farallones, an area of complicated bathymetry where the tidal velocities in some parts of the region are weak compared to the mean currents. We describe the tidal fields for the M2, S2, K1, and O1 constituents and show that this method is sensitive to the model parameters and the quantity of input data. In areas with complex bathymetry and tidal structures, a large amount of spatial data is needed to resolve the tides. A method of estimating the associated errors inherent in the model is described.

Building generalized tree mass/volume component models for improved estimation of forest stocks and utilization potential

Treesearch

David W. MacFarlane

2015-01-01

Accurately assessing forest biomass potential is contingent upon having accurate tree biomass models to translate data from forest inventories. Building generality into these models is especially important when they are to be applied over large spatial domains, such as regional, national and international scales. Here, new, generalized whole-tree mass / volume...

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...

Chapter 12 - Mapping wildland fuel across large regions for the LANDFIRE Prototype Project

Treesearch

Robert E. Keane; Tracey Frescino; Matthew C. Reeves; Jennifer L. Long

2006-01-01

The Landscape Fire and Resource Management Planning Tools Prototype Project, or LANDFIRE Prototype Project, required that the entire array of wildland fuel characteristics be mapped to provide fire and landscape managers with consistent baseline geo-spatial information to plan projects for hazardous fuel mitigation and to improve public and firefighter safety. Fuel...

Large scale atmospheric waves in the Venus mesosphere as seen by the VeRa Radio Science instrument on Venus Express

NASA Astrophysics Data System (ADS)

Tellmann, S.; Häusler, B.; Hinson, D. P.; Tyler, G. L.; Andert, T. P.; Bird, M. K.; Imamura, T.; Pätzold, M.; Remus, S.

2014-04-01

Atmospheric waves on almost all spatial scales have been observed in the Venus atmosphere in various atmospheric regions. They play a crucial role in the redistribution of energy, momentum, and atmospheric constituent and are thought to be involved in the development and maintenance of the atmospheric superrotation.

The Spatial Distribution of Dead Trees across Arkansas Timberlands

Treesearch

Martin A. Spetich; James M. Guldin

1999-01-01

Abstract -- Dead trees are an important part of the forest ecosystem and their attributes have been studied at the stand scale. However, their distribution over a large region has rarely been examined. In this study, the distribution and dynamics of sound wood in dead trees and the ratio of dead to live trees across the Arkansas landscape were...

The Spatial Distribution of Smoking Violations on a No-Smoking Campus: Implications for Prevention

ERIC Educational Resources Information Center

Pires, Stephen F.; Block, Steven; Belance, Ronald; Marteache, Nerea

2016-01-01

Objective: The present study extends research on campus smoking bans by examining where smokers are violating the policy at a large university in the southeastern region of the United States. Participants: The data collection was conducted by one graduate student from the university in August of 2014. Methods: A global positioning system device…

The CA3 Network as a Memory Store for Spatial Representations

ERIC Educational Resources Information Center

Papp, Gergely; Witter, Menno P.; Treves, Alessandro

2007-01-01

Comparative neuroanatomy suggests that the CA3 region of the mammalian hippocampus is directly homologous with the medio-dorsal pallium in birds and reptiles, with which it largely shares the basic organization of primitive cortex. Autoassociative memory models, which are generically applicable to cortical networks, then help assess how well CA3…

Spatialization of Brazilian pig production: relationship between productive, physical, environmental, and socio-economic variables.

PubMed

da Silva, Isabel C M; Bremm, Bárbara; Teixeira, Jennifer L; Costa, Nathalia S; Barcellos, Júlio O J; Braccini, José; Cesconeto, Robson J; McManus, Concepta

2017-06-01

Brazilian pig production spans over a large territory encompassing regions of different climatic and socio-economic realities. Production, physical, socio-economic, and environmental data were used to characterize pig production in the country. Multivariate analysis evaluated indices including number productivity, production levels, and income from pigs, together with the average area of pig farm and socio-economic variables such as municipal human development index, technical guidance received from agricultural cooperatives and industrial companies, number of family farms, and offtake; and finally, environmental variables: latitude, longitude, annual temperature range, solar radiation index, as well as temperature and humidity index. The Southern region has the largest herd, number of pigs sold/sow, and offtake rate (p < 0.05), followed by the Midwest and Southeast. No significant correlations were seen between production rates and productivity with the socio-economic and environmental variables in the regions of Brazil. Production indexes, productivity, and offtake rate discriminated Northeast and Midwest and Northeast and Southeast regions. The Northern region, with a large area, has few and far-between farms that rear pigs for subsistence. The Northeast region has large herds, but low productivity. Number of slaughtered pigs has been variable over the past three decades, with few states responsible for maintaining high production in Brazil. However, the activity can be effective in any region of the country with technology and technical assistance adapted to regional characteristics.

Improvement in Recursive Hierarchical Segmentation of Data

NASA Technical Reports Server (NTRS)

Tilton, James C.

2006-01-01

A further modification has been made in the algorithm and implementing software reported in Modified Recursive Hierarchical Segmentation of Data (GSC- 14681-1), NASA Tech Briefs, Vol. 30, No. 6 (June 2006), page 51. That software performs recursive hierarchical segmentation of data having spatial characteristics (e.g., spectral-image data). The output of a prior version of the software contained artifacts, including spurious segmentation-image regions bounded by processing-window edges. The modification for suppressing the artifacts, mentioned in the cited article, was addition of a subroutine that analyzes data in the vicinities of seams to find pairs of regions that tend to lie adjacent to each other on opposite sides of the seams. Within each such pair, pixels in one region that are more similar to pixels in the other region are reassigned to the other region. The present modification provides for a parameter ranging from 0 to 1 for controlling the relative priority of merges between spatially adjacent and spatially non-adjacent regions. At 1, spatially-adjacent-/spatially- non-adjacent-region merges have equal priority. At 0, only spatially-adjacent-region merges (no spectral clustering) are allowed. Between 0 and 1, spatially-adjacent- region merges have priority over spatially- non-adjacent ones.

Magnetic Fields in the Galaxy

NASA Astrophysics Data System (ADS)

Mayo, Elizabeth A.

2009-01-01

Interstellar magnetic fields are believed to play a crucial role in the star-formation process, therefore a comprehensive study of magnetic fields is necessary in understanding the origins of stars. These projects use observational data obtained from the Very Large Array (VLA) in Socorro, NM. The data reveal interstellar magnetic field strengths via the Zeeman effect in radio frequency spectral lines. This information provides an estimate of the magnetic energy in star-forming interstellar clouds in the Galaxy, and comparisons can be made with these energies and the energies of self-gravitation and internal motions. From these comparisons, a better understanding of the role of magnetic fields in the origins of stars will emerge. NGC 6334 A is a compact HII region at the center of what is believed to be a large, rotating molecular torus (Kramer et al. (1997)). This is a continuing study based on initial measurements of the HI and OH Zeeman effect (Sarma et al. (2000)). The current study includes OH observations performed by the VLA at a higher spatial resolution than previously published data, and allows for a better analysis of the spatial variations of the magnetic field. A new model of the region is also developed based on OH opacity studies, dust continuum maps, radio spectral lines, and infrared (IR) maps. The VLA has been used to study the Zeeman effect in the 21cm HI line seen in absorption against radio sources in the Cygnus-X region. These sources are mostly galactic nebulae or HII regions, and are bright and compact in this region of the spectrum. HI absorption lines are strong against these regions and the VLA is capable of detecting the weak Zeeman effect within them. Support for this work was provided by the NSF PAARE program to South Carolina State University under award AST-0750814.

High Concentrations of Hydrogen-bearing Volatiles at the Base of Poleward-facing slopes in the Moon's Large Southern Permanently Shadowed Regions.

NASA Astrophysics Data System (ADS)

McClanahan, T. P.; Mitrofanov, I. G.; Boynton, W. V.; Chin, G.; Livengood, T. A.; Litvak, M. L.; Sanin, A. B.; Starr, R. D.

2016-12-01

In this paper we review evidence that indicates that high concentrations of hydrogen-bearing volatiles are biased towards the base of poleward-facing slopes (PFS) in the Moon's large southern permanently shadowed regions (PSR). Results are derived from a correlated study of Lunar Reconnaissance Orbiter instrument maps of: epithermal neutron leakage flux observed by the Lunar Exploration Neutron Detector (LEND), topography derived from the Lunar Observing Laser Altimeter (LOLA) and surface thermal maps derived from the Diviner radiometer. Maximum concentrations of hydrogen-volatiles, likely as water ice, are observed in the Cabeus crater's PSR, 0.62 wght% water-equivalent-hydrogen. Detailed studies show that the occurrence of hydrogen-volatiles at the base of the (PFS) are correlated with the locations of low PSR temperatures of Cabeus, Haworth, Shoemaker and Faustini. LEND observations show no consistent correlation to smaller impact craters and the lowest temperatures within the PSR's. It is not presently known if the high volatile concentrations are due to downslope migration or thermal stability in the PFS breaks in slope. 15-km Full-width at Half-Maximum (FWHM) is shown to be an upper-bounds condition for the LEND collimated sensor's spatial resolution, derived from a cross-sectional profile, through the permanently shadowed region at Cabeus'. LEND's high-resolution spatial response is further illustrated in a 220-km long profile cut through the co-aligned permanently shadowed regions and partially-illuminated ridges of Haworth, Shoemaker, Faustini and Amundsen craters.

An innovative procedure to assess multi-scale temporal trends in groundwater quality: Example of the nitrate in the Seine-Normandy basin, France

NASA Astrophysics Data System (ADS)

Lopez, Benjamin; Baran, Nicole; Bourgine, Bernard

2015-03-01

The European Water Framework Directive (WFD) asks Member States to identify trends in contaminant concentrations in groundwater and to take measures to reach a good chemical status by 2015. In this study, carried out in a large hydrological basin (95,300 km2), an innovative procedure is described for the assessment of recent trends in groundwater nitrate concentrations both at sampling point and regional scales. Temporal variograms of piezometric and nitrate concentration time series are automatically calculated and fitted in order to classify groundwater according to their temporal pattern. These results are then coupled with aquifer lithology to map spatial units within which the modes of diffuse transport of contaminants towards groundwater are assumed to be the same at all points. These spatial units are suitable for evaluating regional trends. The stability over time of the time series is tested based on the cumulative sum principle, to determine the time period during which the trend should be sought. The Mann-Kendall and Regional-Kendall nonparametric tests for monotonic trends, coupled with the Sen-slope test, are applied to the periods following the point breaks thus determined at both the sampling point or regional scales. This novel procedure is robust and enables rapid processing of large databases of raw data. It would therefore be useful for managing groundwater quality in compliance with the aims of the WFD.

AIRS Water Vapor and Cloud Products Validate and Explain Recent Negative Global and Tropical OLR Trends Observed by CERES

NASA Technical Reports Server (NTRS)

Susskind, Joel; Molnar, Gyula; Iredell, Lena

2010-01-01

This paper compares spatial and temporal anomalies and trends of OLR as observed by CERES and computed based on AIRS retrieved surface and atmospheric geophysical parameters over the time period September 2002 February 2010. This time period is marked by a substantial decreasing OLR trend on the order of -0.1 W/m2/yr averaged over the globe. There are very large spatial variations of these trends however, with local values ranging from -2.6 W/m2/yr to +3.0 W/m2/yr in the tropics. The spatial patterns of the AIRS and CERES trends are in essentially perfect agreement with each other, as are the anomaly time series averaged over different spatial regions. This essentially perfect agreement of OLR anomalies and trends derived from observations by two different instruments, in totally independent and different manners, implies that both sets of results must be highly accurate. The agreement of anomalies and trends of OLR as observed by CERES and computed from AIRS derived products also indirectly validates the anomalies and trends of the AIRS derived products as well. We used the anomalies and trends of AIRS derived water vapor and cloud products to explain why global OLR has had a large negative trend over the time period September 2002 through February 2010. Tropical OLR began to decrease significantly at the onset of a strong La Nina in mid-2007. AIRS products show that cloudiness and mid-tropospheric water vapor began to increase in the region 5degN - 20degS latitude extending eastward from 150degW - 30 E longitude at that time, with a corresponding very large drop in OLR in this region. Late 2009 is characterized by a strong El-Nino, with a corresponding change in sign of observed anomalies of mid-tropospheric water vapor, cloud cover, and OLR in this region, as we] l as that of OLR anomalies in the tropics and globally. Monthly mean anomalies of OLR, water vapor and cloud cover over this region are all shown to be highly correlated in time with those of an El Nino anomaly index four months previously. The El Nino index is defined as the SST anomaly averaged over the area 15S to 15N and 160W eastward to 30E. If one excludes the area 5degN - 20degS, 150degW - 30degE from the statistics, the negative area mean tropical OLR trends, as well as OLR trends over the rest of the globe, are substantially

AIRS Water Vapor and Cloud Products Validate and Explain Recent Negative Global and Tropical OLR Trends Observed by CERES

NASA Astrophysics Data System (ADS)

Susskind, J.; Molnar, G. I.; Iredell, L. F.; Sounder Research Team

2010-12-01

Joel Susskind, Gyula Molnar, and Lena Iredell NASA GSFC Sounder Research Team Abstract This paper compares spatial and temporal anomalies and trends of OLR as observed by CERES and computed based on AIRS retrieved surface and atmospheric geophysical parameters over the time period September 2002 - February 2010. This time period is marked by a substantial decreasing OLR trend on the order of -0.1 W/m2/yr averaged over the globe. There are very large spatial variations of these trends however, with local values ranging from -2.6 W/m2/yr to +3.0 W/m2/yr in the tropics. The spatial patterns of the AIRS and CERES trends are in essentially perfect agreement with each other, as are the anomaly time series averaged over different spatial regions. This essentially perfect agreement of OLR anomalies and trends derived from observations by two different instruments, in totally independent and different manners, implies that both sets of results must be highly accurate. The agreement of anomalies and trends of OLR as observed by CERES and computed from AIRS derived products also indirectly validates the anomalies and trends of the AIRS derived products as well. We used the anomalies and trends of AIRS derived water vapor and cloud products to explain why global OLR has had a large negative trend over the time period September 2002 through February 2010. Tropical OLR began to decrease significantly at the onset of a strong La Niña in mid-2007. AIRS products show that cloudiness and mid-tropospheric water vapor began to increase in the region 5°N - 20°S latitude extending eastward from 150°W - 30°E longitude at that time, with a corresponding very large drop in OLR in this region. Late 2009 is characterized by a strong El-Niño, with a corresponding change in sign of observed anomalies of mid-tropospheric water vapor, cloud cover, and OLR in this region, as well as that of OLR anomalies in the tropics and globally. Monthly mean anomalies of OLR, water vapor and cloud cover over this region are all shown to be highly correlated in time with those of an El Nino anomaly index four months previously. The El Nino index is defined as the SST anomaly averaged over the area 15S to 15N and 160W eastward to 30E. If one excludes the area 5°N - 20°S, 150°W - 30°E from the statistics, the negative area mean tropical OLR trends, as well as OLR trends over the rest of the globe, are substantially reduced over the time period under study.

Influences of large-scale convection and moisture source on monthly precipitation isotope ratios observed in Thailand, Southeast Asia

NASA Astrophysics Data System (ADS)

Wei, Zhongwang; Lee, Xuhui; Liu, Zhongfang; Seeboonruang, Uma; Koike, Masahiro; Yoshimura, Kei

2018-04-01

Many paleoclimatic records in Southeast Asia rely on rainfall isotope ratios as proxies for past hydroclimatic variability. However, the physical processes controlling modern rainfall isotopic behaviors in the region is poorly constrained. Here, we combined isotopic measurements at six sites across Thailand with an isotope-incorporated atmospheric circulation model (IsoGSM) and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to investigate the factors that govern the variability of precipitation isotope ratios in this region. Results show that rainfall isotope ratios are both correlated with local rainfall amount and regional outgoing longwave radiation, suggesting that rainfall isotope ratios in this region are controlled not only by local rain amount (amount effect) but also by large-scale convection. As a transition zone between the Indian monsoon and the western North Pacific monsoon, the spatial difference of observed precipitation isotope among different sites are associated with moisture source. These results highlight the importance of regional processes in determining rainfall isotope ratios in the tropics and provide constraints on the interpretation of paleo-precipitation isotope records in the context of regional climate dynamics.

The combined effects of exogenous and endogenous variability on the spatial distribution of ant communities in a forested ecosystem (Hymenoptera: Formicidae).

PubMed

Yitbarek, Senay; Vandermeer, John H; Allen, David

2011-10-01

Spatial patterns observed in ecosystems have traditionally been attributed to exogenous processes. Recently, ecologists have found that endogenous processes also have the potential to create spatial patterns. Yet, relatively few studies have attempted to examine the combined effects of exogenous and endogenous processes on the distribution of organisms across spatial and temporal scales. Here we aim to do this, by investigating whether spatial patterns of under-story tree species at a large spatial scale (18 ha) influences the spatial patterns of ground foraging ant species at a much smaller spatial scale (20 m by 20 m). At the regional scale, exogenous processes (under-story tree community) had a strong effect on the spatial patterns in the ground-foraging ant community. We found significantly more Camponotus noveboracensis, Formica subsericae, and Lasius alienus species in black cherry (Prunis serotine Ehrh.) habitats. In witch-hazel (Hamamelis virginiana L.) habitats, we similarly found significantly more Myrmica americana, Formica fusca, and Formica subsericae. At smaller spatial scales, we observed the emergence of mosaic ant patches changing rapidly in space and time. Our study reveals that spatial patterns are the result of both exogenous and endogenous forces, operating at distinct scales.

Using online database for landslide susceptibility assessment with an example from the Veneto Region (north-eastern Italy).

NASA Astrophysics Data System (ADS)

Floris, Mario; Squarzoni, Cristina; Zorzi, Luca; D'Alpaos, Andrea; Iafelice, Maria

2010-05-01

Landslide susceptibility maps describe landslide-prone areas by the spatial correlation between landslides and related factors, derived from different kinds of datasets: geological, geotechnical and geomechanical maps, hydrogeological maps, landslides maps, vector and raster terrain data, real-time inclinometer and pore pressure data. In the last decade, thanks to the increasing use of web-based tools for management, sharing and communication of territorial information, many Web-based Geographical Information Systems (WebGIS) were created by local governments or nations, University and Research Centres. Nowadays there is a strong proliferation of geological WebGIS or GeoBrowser, allowing free download of spatial information. There are global Cartographical Portals that provide a free download of DTM and other vector data related to the whole planet (http://www.webgis.com). At major scale, there are WebGIS regarding entire nation (http://www.agiweb.org), or specific region of a country (http://www.mrt.tas.gov.au), or single municipality (http://sitn.ne.ch/). Moreover, portals managed by local government and academic government (http://turtle.ags.gov.ab.ca/Peace_River/Site/) or by a private agency (http://www.bbt-se.com) are noteworthy. In Italy, the first national projects for the creation of WebGIS and web-based databases begun during the 1980s, and evolved, through years, to the present number of different WebGIS, which have different territorial extensions: national (Italian National Cartographical Portal, http://www.pcn.minambiente.it; E-GEO Project, http://www.egeo.unisi.it), interregional (River Tiber Basin Authority, www.abtevere.it ), and regional (Veneto Region, www.regione.veneto.it). In this way we investigated most of the Italian WebGIS in order to verify their geographic range and the availability and quality of data useful for landslide hazard analyses. We noticed a large variability of the accessing information among the different browsers. In particular, the Trento and Bolzano Provinces Geobrowsers (http://www.provincia.bz.it; http://www.territorio.provincia.tn.it) provide a large availability of data respect to the other regional and interregional WebGIS, which generally allow only the download of topographic data. Recently, the Italian Institute for Environmental Protection and Research, ISPRA (Istituto Superiore per la Protezione e la ricerca Ambientale), makes available and free usable the Italian Inventory of Landslides (IFFI Project). The inventory contains information derived from the census of all the instability phenomena in Italy, offering a base-cognitive instrument for the landslide hazard evaluation. For the landslide hazard assessment it is essential to evaluate the real effectiveness of the available data. Hence, we test the effectiveness of the web databases to evaluate the landslides susceptibility in the Euganean Hill Regional Park (185.5 km2), located at SE of Padua (Veneto Region, Italy). We used data available from three online spatial databases: Veneto Region Cartographic Portal (http://www.regione.veneto.it), for vector terrain data at 1:5000 scale; the IFFI archive (http://www.sinanet.apat.it), for information concerning landslides; and the National Cartographic Portal of the Italian Ministry of Environment (http://www.pcn.minambiente.it), for the multi-temporal orthophotos. The landslide susceptibility was evaluated using a simple probabilistic analysis considering the relationships between landslides and DEM-derived factors, such as slope, curvature and aspect. For the validation of the analysis, we made a spatial test by subdividing the study area in two sectors: training area and test area. The obtained results show that the actual no-completeness of online available spatial databases related to the Veneto Region allows only regional and medium scale (>1:25,000) susceptibility analysis. Data about lithology, land use, groundwater and others relevant factors are absent. In addition, the lack of data on the temporal evolution of the landslides permits only a spatial analysis, impeding a complete evaluation of the landslide hazard.

A watershed scale spatially-distributed model for streambank erosion rate driven by channel curvature

NASA Astrophysics Data System (ADS)

McMillan, Mitchell; Hu, Zhiyong

2017-10-01

Streambank erosion is a major source of fluvial sediment, but few large-scale, spatially distributed models exist to quantify streambank erosion rates. We introduce a spatially distributed model for streambank erosion applicable to sinuous, single-thread channels. We argue that such a model can adequately characterize streambank erosion rates, measured at the outsides of bends over a 2-year time period, throughout a large region. The model is based on the widely-used excess-velocity equation and comprised three components: a physics-based hydrodynamic model, a large-scale 1-dimensional model of average monthly discharge, and an empirical bank erodibility parameterization. The hydrodynamic submodel requires inputs of channel centerline, slope, width, depth, friction factor, and a scour factor A; the large-scale watershed submodel utilizes watershed-averaged monthly outputs of the Noah-2.8 land surface model; bank erodibility is based on tree cover and bank height as proxies for root density. The model was calibrated with erosion rates measured in sand-bed streams throughout the northern Gulf of Mexico coastal plain. The calibrated model outperforms a purely empirical model, as well as a model based only on excess velocity, illustrating the utility of combining a physics-based hydrodynamic model with an empirical bank erodibility relationship. The model could be improved by incorporating spatial variability in channel roughness and the hydrodynamic scour factor, which are here assumed constant. A reach-scale application of the model is illustrated on ∼1 km of a medium-sized, mixed forest-pasture stream, where the model identifies streambank erosion hotspots on forested and non-forested bends.

Coupling a distributed hydrological model with detailed forest structural information for large-scale global change impact assessment

NASA Astrophysics Data System (ADS)

Eisner, Stephanie; Huang, Shaochun; Majasalmi, Titta; Bright, Ryan; Astrup, Rasmus; Beldring, Stein

2017-04-01

Forests are recognized for their decisive effect on landscape water balance with structural forest characteristics as stand density or species composition determining energy partitioning and dominant flow paths. However, spatial and temporal variability in forest structure is often poorly represented in hydrological modeling frameworks, in particular in regional to large scale hydrological modeling and impact analysis. As a common practice, prescribed land cover classes (including different generic forest types) are linked to parameter values derived from literature, or parameters are determined by calibration. While national forest inventory (NFI) data provide comprehensive, detailed information on hydrologically relevant forest characteristics, their potential to inform hydrological simulation over larger spatial domains is rarely exploited. In this study we present a modeling framework that couples the distributed hydrological model HBV with forest structural information derived from the Norwegian NFI and multi-source remote sensing data. The modeling framework, set up for the entire of continental Norway at 1 km spatial resolution, is explicitly designed to study the combined and isolated impacts of climate change, forest management and land use change on hydrological fluxes. We use a forest classification system based on forest structure rather than biomes which allows to implicitly account for impacts of forest management on forest structural attributes. In the hydrological model, different forest classes are represented by three parameters: leaf area index (LAI), mean tree height and surface albedo. Seasonal cycles of LAI and surface albedo are dynamically simulated to make the framework applicable under climate change conditions. Based on a hindcast for the pilot regions Nord-Trøndelag and Sør-Trøndelag, we show how forest management has affected regional hydrological fluxes during the second half of the 20th century as contrasted to climate variability.

Modern thermokarst lake dynamics in the continuous permafrost zone, northern Seward Peninsula, Alaska

USGS Publications Warehouse

Jones, Benjamin M.; Grosse, G.; Arp, C.D.; Jones, M.C.; Walter, Anthony K.M.; Romanovsky, V.E.

2011-01-01

Quantifying changes in thermokarst lake extent is of importance for understanding the permafrost-related carbon budget, including the potential release of carbon via lake expansion or sequestration as peat in drained lake basins. We used high spatial resolution remotely sensed imagery from 1950/51, 1978, and 2006/07 to quantify changes in thermokarst lakes for a 700 km2 area on the northern Seward Peninsula, Alaska. The number of water bodies larger than 0.1 ha increased over the entire observation period (666 to 737 or +10.7%); however, total surface area decreased (5,066 ha to 4,312 ha or -14.9%). This pattern can largely be explained by the formation of remnant ponds following partial drainage of larger water bodies. Thus, analysis of large lakes (>40 ha) shows a decrease of 24% and 26% in number and area, respectively, differing from lake changes reported from other continuous permafrost regions. Thermokarst lake expansion rates did not change substantially between 1950/51 and 1978 (0.35 m/yr) and 1978 and 2006/07 (0.39 m/yr). However, most lakes that drained did expand as a result of surface permafrost degradation before lateral drainage. Drainage rates over the observation period were stable (2.2 to 2.3 per year). Thus, analysis of decadal-scale, high spatial resolution imagery has shown that lake drainage in this region is triggered by lateral breaching and not subterranean infiltration. Future research should be directed toward better understanding thermokarst lake dynamics at high spatial and temporal resolution as these systems have implications for landscape-scale hydrology and carbon budgets in thermokarst lake-rich regions in the circum-Arctic.

Spatially extended hybrid methods: a review

PubMed Central

2018-01-01

Many biological and physical systems exhibit behaviour at multiple spatial, temporal or population scales. Multiscale processes provide challenges when they are to be simulated using numerical techniques. While coarser methods such as partial differential equations are typically fast to simulate, they lack the individual-level detail that may be required in regions of low concentration or small spatial scale. However, to simulate at such an individual level throughout a domain and in regions where concentrations are high can be computationally expensive. Spatially coupled hybrid methods provide a bridge, allowing for multiple representations of the same species in one spatial domain by partitioning space into distinct modelling subdomains. Over the past 20 years, such hybrid methods have risen to prominence, leading to what is now a very active research area across multiple disciplines including chemistry, physics and mathematics. There are three main motivations for undertaking this review. Firstly, we have collated a large number of spatially extended hybrid methods and presented them in a single coherent document, while comparing and contrasting them, so that anyone who requires a multiscale hybrid method will be able to find the most appropriate one for their need. Secondly, we have provided canonical examples with algorithms and accompanying code, serving to demonstrate how these types of methods work in practice. Finally, we have presented papers that employ these methods on real biological and physical problems, demonstrating their utility. We also consider some open research questions in the area of hybrid method development and the future directions for the field. PMID:29491179

Comparison Study on the Estimation of the Spatial Distribution of Regional Soil Metal(loid)s Pollution Based on Kriging Interpolation and BP Neural Network.

PubMed

Jia, Zhenyi; Zhou, Shenglu; Su, Quanlong; Yi, Haomin; Wang, Junxiao

2017-12-26

Soil pollution by metal(loid)s resulting from rapid economic development is a major concern. Accurately estimating the spatial distribution of soil metal(loid) pollution has great significance in preventing and controlling soil pollution. In this study, 126 topsoil samples were collected in Kunshan City and the geo-accumulation index was selected as a pollution index. We used Kriging interpolation and BP neural network methods to estimate the spatial distribution of arsenic (As) and cadmium (Cd) pollution in the study area. Additionally, we introduced a cross-validation method to measure the errors of the estimation results by the two interpolation methods and discussed the accuracy of the information contained in the estimation results. The conclusions are as follows: data distribution characteristics, spatial variability, and mean square errors (MSE) of the different methods showed large differences. Estimation results from BP neural network models have a higher accuracy, the MSE of As and Cd are 0.0661 and 0.1743, respectively. However, the interpolation results show significant skewed distribution, and spatial autocorrelation is strong. Using Kriging interpolation, the MSE of As and Cd are 0.0804 and 0.2983, respectively. The estimation results have poorer accuracy. Combining the two methods can improve the accuracy of the Kriging interpolation and more comprehensively represent the spatial distribution characteristics of metal(loid)s in regional soil. The study may provide a scientific basis and technical support for the regulation of soil metal(loid) pollution.

Afforestation may have little effect on hydrological cycle over the Three-North region of China

NASA Astrophysics Data System (ADS)

Meng, S.; Xie, X.

2017-12-01

Afforestation or reforestation is generally effective to improve environmental conditions, and it may have substantial impact on hydrological cycle by increasing rainfall interception and transpiration. To combat desertification and to control dust storms, China has implemented a few Large-scale afforestation programs since 1980s, including the world's most ambitious afforestation program, the Three-North Forest Shelterbelt (TNFS) program in the arid and semiarid land areas. This afforestation plan covers about 4 million km2 (> 42%) of the land area of China. Although the TNFS program eased environmental problems in the region to some degree, the consequences of large-scale afforestation on hydrological cycles is still controversial. To identify the impact of the afforestation on hydrological cycle at regional scale, we employed a large-scale hydrological model, i.e., the Variable Infiltration Capacity (VIC) model, and satellite remote sensing data sets, i.e., leaf area index (LAI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Global LAnd Surface satellite (GLASS). The VIC modelling was forced with long-term dynamic LAI and gridded atmospheric data. We focused on the period of 2000-2015 when fewer afforestation activities implemented and the vegetation in steady growth stage in the three-north region. The results show that, despite the spatial heterogeneity, LAI in the growing season exhibits a slight increase across the three-north region, which is the contribution of the vegetation growth due to afforestation program. Evapotranspiration (ET) increased at a rate of 3.93 mm/yr over the whole region from 2000 to 2015. The spatial pattern of ET is consistent with the changes in LAI and precipitation, but this does not mean vegetation growth contributed equally. Based on factor-distinguishing simulations, we found that precipitation change has more significant influence on hydrological cycle than vegetation growth. Therefore, the afforestation practices are influential at small-catchment scale, but at regional scale, they may have little effect on the hydrological cycles. For sustainable water resource management, we should pay special attention on climate change rather than the afforestation efforts.

Stress Drops of Earthquakes on the Subducting Pacific Plate in the South-East off Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Saito, Y.; Yamada, T.

2013-12-01

Large earthquakes have been occurring repeatedly in the South-East of Hokkaido, Japan, where the Pacific Plate subducts beneath the Okhotsk Plate in the north-west direction. For example, the 2003 Tokachi-oki earthquake (Mw8.3 determined by USGS) took place in the region on September 26, 2003. Yamanaka and Kikuchi (2003) analyzed the slip distribution of the earthquake and concluded that the 2003 earthquake had ruptured the deeper half of the fault plane of the 1952 Tokachi-oki earthquake. Miyazaki et al. (2004) reported that a notable afterslip was observed at adjacent areas to the coseismic rupture zone of the 2003 earthquake, which suggests that there would be significant heterogeneities of strength, stress and frictional properties on the surface of the Pacific Plate in the region. In addition, some previous studies suggest that the region with a large slip in large earthquakes permanently have large difference of strength and the dynamic frictional stress level and that it would be able to predict the spatial pattern of slip in the next large earthquake by analyzing the stress drop of small earthquakes (e.g. Allmann and Shearer, 2007 and Yamada et al., 2010). We estimated stress drops of 150 earthquakes (4.2 ≤ M ≤ 5.0), using S-coda waves, or the waveforms from 4.00 to 9.11 seconds after the S wave arrivals, of Hi-net data. The 150 earthquakes were the ones that occurred from June, 2002 to December, 2010 in south-east of Hokkaido, Japan, from 40.5N to 43.5N and from 141.0E to 146.5E. First we selected waveforms of the closest earthquakes with magnitudes between 3.0 and 3.2 to individual 150 earthquakes as empirical Green's functions. We then calculated source spectral ratios of the 150 pairs of interested earthquakes and EGFs by deconvolving the individual S-coda waves. We finally estimated corner frequencies of earthquakes from the spectral ratios by assuming the omega-squared model of Boatwright (1978) and calculated stress drops of the earthquakes by using the model of Madariaga (1976). The estimated values of stress drop range from 1 to 10 MPa with a little number of outliers(Fig.(a)). Fig.(b) shows the spatial distribution of stress drops in south-east off Hokkaido, Japan. We found that earthquakes occurred around 42N 145E had larger stress drops. We are going to analyze smaller earthquakes and investigate the spatial pattern of the stress drop in the future. Fig. (a) Estimated values of stress drop with respect to seismic moments of earthquakes. (b) Spatial distribution of stress drops.

Can global hydrological models reproduce large scale river flood regimes?

NASA Astrophysics Data System (ADS)

Eisner, Stephanie; Flörke, Martina

2013-04-01

River flooding remains one of the most severe natural hazards. On the one hand, major flood events pose a serious threat to human well-being, causing deaths and considerable economic damage. On the other hand, the periodic occurrence of flood pulses is crucial to maintain the functioning of riverine floodplains and wetlands, and to preserve the ecosystem services the latter provide. In many regions, river floods reveal a distinct seasonality, i.e. they occur at a particular time during the year. This seasonality is related to regionally dominant flood generating processes which can be expressed in river flood types. While in data-rich regions (esp. Europe and North America) the analysis of flood regimes can be based on observed river discharge time series, this data is sparse or lacking in many other regions of the world. This gap of knowledge can be filled by global modeling approaches. However, to date most global modeling studies have focused on mean annual or monthly water availability and their change over time while simulating discharge extremes, both floods and droughts, still remains a challenge for large scale hydrological models. This study will explore the ability of the global hydrological model WaterGAP3 to simulate the large scale patterns of river flood regimes, represented by seasonal pattern and the dominant flood type. WaterGAP3 simulates the global terrestrial water balance on a 5 arc minute spatial grid (excluding Greenland and Antarctica) at a daily time step. The model accounts for human interference on river flow, i.e. water abstraction for various purposes, e.g. irrigation, and flow regulation by large dams and reservoirs. Our analysis will provide insight in the general ability of global hydrological models to reproduce river flood regimes and thus will promote the creation of a global map of river flood regimes to provide a spatially inclusive and comprehensive picture. Understanding present-day flood regimes can support both flood risk analysis and the assessment of potential regional impacts of climate change on river flooding.

Quantitative imaging of carbon dimer precursor for nanomaterial synthesis in the carbon arc

DOE PAGES

Vekselman, V.; Khrabry, A.; Kaganovich, I.; ...

2018-02-06

Delineating the dominant processes responsible for nanomaterial synthesis in a plasma environment requires measurements of the precursor species contributing to the growth of nanostructures. Here, we performed comprehensive measurements of spatial and temporal profiles of carbon dimers (C 2) in sub-atmospheric-pressure carbon arc by laser-induced fluorescence. Measured spatial profiles of C 2 coincide with the growth region of carbon nanotubes (Fang et al 2016 Carbon 107 273–80) and vary depending on the arc operation mode, which is determined by the discharge current and the ablation rate of the graphite anode. The C 2 density profile exhibits large spatial and timemore » variations due to motion of the arc core. A comparison of the experimental data with the 2D simulation results of self-consistent arc modeling shows good agreement. The model predicts well the main processes determining spatial profiles of carbon dimers (C 2).« less

Quantitative imaging of carbon dimer precursor for nanomaterial synthesis in the carbon arc

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

Vekselman, V.; Khrabry, A.; Kaganovich, I.

Delineating the dominant processes responsible for nanomaterial synthesis in a plasma environment requires measurements of the precursor species contributing to the growth of nanostructures. Here, we performed comprehensive measurements of spatial and temporal profiles of carbon dimers (C 2) in sub-atmospheric-pressure carbon arc by laser-induced fluorescence. Measured spatial profiles of C 2 coincide with the growth region of carbon nanotubes (Fang et al 2016 Carbon 107 273–80) and vary depending on the arc operation mode, which is determined by the discharge current and the ablation rate of the graphite anode. The C 2 density profile exhibits large spatial and timemore » variations due to motion of the arc core. A comparison of the experimental data with the 2D simulation results of self-consistent arc modeling shows good agreement. The model predicts well the main processes determining spatial profiles of carbon dimers (C 2).« less

Hydrological regions in monsoon Asia

NASA Astrophysics Data System (ADS)

Kondoh, Akihiko; Budi Harto, Agung; Eleonora, Runtunuwu; Kojiri, Toshiharu

2004-11-01

Monsoon Asia is characterized by its diversity of natural and social environments. These environments range from humid tropics to arid regions and there exist associated various hydrological phenomena. This paper attempts to characterize the hydrological regions of monsoon Asia based on the water budget calculated using grid-based global datasets. A map of hydrological regions is created by ranking the value of water surplus and deficit. A humid zone with large water surplus extending from Southeast Asia to the Japanese archipelago, rapid transition from humid to arid environments in eastern China, and an arid region surrounded by a humid region in continental Southeast Asia are the most remarkable features in monsoon Asia. The map reveals that an essential characteristic of monsoon Asia is the proximity of the arid and humid environments. Many water problems and water management practices in a region can be easily understood by plotting them on a map. The boundaries of several large river basins are superimposed on the map, and examined for the water budget and flow regimes. The results are found to explain the regional characteristics of the seasonal runoff regimes satisfactorily. The importance of using a spatial framework for the comparative hydrological study in Monsoon Asia is highlighted.

Space-based observations of nitrogen dioxide: Trends in anthropogenic emissions

NASA Astrophysics Data System (ADS)

Russell, Ashley Ray

Space-based instruments provide routine global observations, offering a unique perspective on the spatial and temporal variation of atmospheric constituents. In this dissertation, trends in regional-scale anthropogenic nitrogen oxide emissions (NO + NO2 ≡ NOx) are investigated using high resolution observations from the Ozone Monitoring Instrument (OMI). By comparing trends in OMI observations with those from ground-based measurements and an emissions inventory, I show that satellite observations are well-suited for capturing changes in emissions over time. The high spatial and temporal resolutions of the observations provide a uniquely complete view of regional-scale changes in the spatial patterns of NO 2. I show that NOx concentrations have decreased significantly in urban regions of the United States between 2005 and 2011, with an average reduction of 32 ± 7%. By examining day-of-week and interannual trends, I show that these reductions can largely be attributed to improved emission control technology in the mobile source fleet; however, I also show that the economic downturn of the late 2000's has impacted emissions. Additionally, I describe the development of a high-resolution retrieval of NO2 from OMI observations known as the Berkeley High Resolution (BEHR) retrieval. The BEHR product uses higher spatial and temporal resolution terrain and profile parameters than the operational retrievals and is shown to provide a more quantitative measure of tropospheric NO2 column density. These results have important implications for future retrievals of NO2 from space-based observations.

A global approach to estimate irrigated areas - a comparison between different data and statistics

NASA Astrophysics Data System (ADS)

Meier, Jonas; Zabel, Florian; Mauser, Wolfram

2018-02-01

Agriculture is the largest global consumer of water. Irrigated areas constitute 40 % of the total area used for agricultural production (FAO, 2014a) Information on their spatial distribution is highly relevant for regional water management and food security. Spatial information on irrigation is highly important for policy and decision makers, who are facing the transition towards more efficient sustainable agriculture. However, the mapping of irrigated areas still represents a challenge for land use classifications, and existing global data sets differ strongly in their results. The following study tests an existing irrigation map based on statistics and extends the irrigated area using ancillary data. The approach processes and analyzes multi-temporal normalized difference vegetation index (NDVI) SPOT-VGT data and agricultural suitability data - both at a spatial resolution of 30 arcsec - incrementally in a multiple decision tree. It covers the period from 1999 to 2012. The results globally show a 18 % larger irrigated area than existing approaches based on statistical data. The largest differences compared to the official national statistics are found in Asia and particularly in China and India. The additional areas are mainly identified within already known irrigated regions where irrigation is more dense than previously estimated. The validation with global and regional products shows the large divergence of existing data sets with respect to size and distribution of irrigated areas caused by spatial resolution, the considered time period and the input data and assumption made.

Detection of the spatial accuracy of an O-arm in the region of surgical interest

NASA Astrophysics Data System (ADS)

Koivukangas, Tapani; Katisko, Jani P. A.; Koivukangsa, John P.

2013-03-01

Medical imaging is an essential component of a wide range of surgical procedures1. For image guided surgical (IGS) procedures, medical images are the main source of information2. The IGS procedures rely largely on obtained image data, so the data needs to provide differentiation between normal and abnormal tissues, especially when other surgical guidance devices are used in the procedures. The image data also needs to provide accurate spatial representation of the patient3. This research has concentrated on the concept of accuracy assessment of IGS devices to meet the needs of quality assurance in the hospital environment. For this purpose, two precision engineered accuracy assessment phantoms have been developed as advanced materials and methods for the community. The phantoms were designed to mimic the volume of a human head as the common region of surgical interest (ROSI). This paper introduces the utilization of the phantoms in spatial accuracy assessment of a commercial surgical 3D CT scanner, the O-Arm. The study presents methods and results of image quality detection of possible geometrical distortions in the region of surgical interest. The results show that in the pre-determined ROSI there are clear image distortion and artefacts using too high imaging parameters when scanning the objects. On the other hand, when using optimal parameters, the O-Arm causes minimal error in IGS accuracy. The detected spatial inaccuracy of the O-Arm with used parameters was in the range of less than 1.00 mm.

Neural mechanisms underlying spatial realignment during adaptation to optical wedge prisms.

PubMed

Chapman, Heidi L; Eramudugolla, Ranmalee; Gavrilescu, Maria; Strudwick, Mark W; Loftus, Andrea; Cunnington, Ross; Mattingley, Jason B

2010-07-01

Visuomotor adaptation to a shift in visual input produced by prismatic lenses is an example of dynamic sensory-motor plasticity within the brain. Prism adaptation is readily induced in healthy individuals, and is thought to reflect the brain's ability to compensate for drifts in spatial calibration between different sensory systems. The neural correlate of this form of functional plasticity is largely unknown, although current models predict the involvement of parieto-cerebellar circuits. Recent studies that have employed event-related functional magnetic resonance imaging (fMRI) to identify brain regions associated with prism adaptation have discovered patterns of parietal and cerebellar modulation as participants corrected their visuomotor errors during the early part of adaptation. However, the role of these regions in the later stage of adaptation, when 'spatial realignment' or true adaptation is predicted to occur, remains unclear. Here, we used fMRI to quantify the distinctive patterns of parieto-cerebellar activity as visuomotor adaptation develops. We directly contrasted activation patterns during the initial error correction phase of visuomotor adaptation with that during the later spatial realignment phase, and found significant recruitment of the parieto-cerebellar network--with activations in the right inferior parietal lobe and the right posterior cerebellum. These findings provide the first evidence of both cerebellar and parietal involvement during the spatial realignment phase of prism adaptation. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

ALMA Discovery of Solar Umbral Brightness Enhancement at λ = 3 mm

NASA Astrophysics Data System (ADS)

Iwai, K.; Loukitcheva, M.; Shimojo, M.; Solanki, S. K.; White, S. M.

2017-12-01

We report the discovery of a brightness enhancement in the center of a large sunspot umbra at a wavelength of 3 mm using the Atacama Large Millimeter/sub-millimeter Array (ALMA). Sunspots are among the most prominent features on the solar surface, but many of their aspects are surprisingly poorly understood. We analyzed a λ = 3 mm (100 GHz) mosaic image obtained by ALMA that includes a large sunspot within the active region AR12470, on 2015 December 16. The 3 mm map has a 300''×300'' field of view and 4.9''×2.2'' spatial resolution, which is the highest spatial resolution map of an entire sunspot in this frequency range. We find a gradient of 3 mm brightness from a high value in the outer penumbra to a low value in the inner penumbra/outer umbra. Within the inner umbra, there is a marked increase in 3 mm brightness temperature, which we call an umbral brightness enhancement. This enhanced emission corresponds to a temperature excess of 800 K relative to the surrounding inner penumbral region and coincides with excess brightness in the 1330 and 1400 Å slit-jaw images of the Interface Region Imaging Spectrograph (IRIS), adjacent to a partial lightbridge. This λ = 3 mm brightness enhancement may be an intrinsic feature of the sunspot umbra at chromospheric heights, such as a manifestation of umbral flashes, or it could be related to a coronal plume, since the brightness enhancement was coincident with the footpoint of a coronal loop observed at 171 Å.

New Possibilities for High-Resolution, Large-Scale Ecosystem Assessment of the World's Semi-Arid Regions

NASA Astrophysics Data System (ADS)

Burney, J. A.; Goldblatt, R.

2016-12-01

Understanding drivers of land use change - and in particular, levels of ecosystem degradation - in semi-arid regions is of critical importance because these agroecosystems (1) are home to the world's poorest populations, almost all of whom depend on agriculture for their livelihoods, (2) play a critical role in the global carbon and climate cycles, and (3) have in many cases seen dramatic changes in temperature and precipitation, relative to global averages, over the past several decades. However, assessing ecosystem health (or, conversely, degradation) presents a difficult measurement problem. Established methods are very labor intensive and rest on detailed questionnaires and field assessments. High-resolution satellite imagery has a unique role semi-arid ecosystem assessment in that it can be used for rapid (or repeated) and very simple measurements of tree and shrub density, an excellent overall indicator for dryland ecosystem health. Because trees and large shrubs are more sparse in semi-arid regions, sub-meter resolution imagery in conjunction with automated image analysis can be used to assess density differences at high spatial resolution without expensive and time-consuming ground-truthing. This could be used down to the farm level, for example, to better assess the larger-scale ecosystem impacts of different management practices, to assess compliance with REDD+ carbon offset protocols, or to evaluate implementation of conservation goals. Here we present results comparing spatial and spectral remote sensing methods for semi-arid ecosystem assessment across new data sources, using the Brazilian Sertão as an example, and the implications for large-scale use in semi-arid ecosystem science.

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

Shao, Huaiyong, E-mail: huaiyongshao@163.com; Center for Global Change and Earth Observations, Michigan State University, East Lansing 48823, MI; Sun, Xiaofei

The Chinese government has conducted the Returning Grazing Land to Grassland Project (RGLGP) across large portions of grasslands from western China since 2003. In order to explore and understand the impact in the grassland's eco-environment during the RGLGP, we utilized Projection Pursuit Model (PPM) and Geographic Information System (GIS) to develop a spatial assessment model to examine the ecological vulnerability of the grassland. Our results include five indications: (1) it is practical to apply the spatial PPM on ecological vulnerability assessment for the grassland. This methodology avoids creating an artificial hypothesis, thereby providing objective results that successfully execute a multi-indexmore » assessment process and analysis under non-linear systems in eco-environments; (2) the spatial PPM is not only capable of evaluating regional eco-environmental vulnerability in a quantitative way, but also can quantitatively demonstrate the degree of effect in each evaluation index for regional eco-environmental vulnerability; (3) the eco-environment of the Xianshui River Basin falls into the medium range level. The normalized difference vegetation index (NDVI) and land use cover and change (LUCC) crucially influence the Xianshui River Basin's eco-environmental vulnerability. Generally, in the Xianshui River Basin, regional eco-environmental conditions improved during 2000 and 2010. The RGLGP positively affected NDVI and LUCC structure, thereby promoting the enhancement of the regional eco-environment; (4) the Xianshui River Basin divides its ecological vulnerability across different levels; therefore our study investigates three ecological regions and proposes specific suggestions for each in order to assist in eco-environmental protection and rehabilitation; and lastly that (5) the spatial PPM established by this study has the potential to be applied on all types of grassland eco-environmental vulnerability assessments under the RGLGP and under the similar conditions in the Returning Agriculture Land to Forest Project (RALFP). However, when establishing an eco-environmental vulnerability assessment model, it is necessary to choose suitable evaluation indexes in accordance with regional eco-environmental characteristics. - Highlights: • We present a method for regional eco-environmental vulnerability assessment. • The method combines Projection Pursuit Model with Geographic Information System. • The Returning Grazing Land to Grassland Project is crucial to environment recovery. • The method is more objective to assess regional eco-environmental vulnerability.« less

Comparison of different wind data interpolation methods for a region with complex terrain in Central Asia

NASA Astrophysics Data System (ADS)

Reinhardt, Katja; Samimi, Cyrus

2018-01-01

While climatological data of high spatial resolution are largely available in most developed countries, the network of climatological stations in many other regions of the world still constitutes large gaps. Especially for those regions, interpolation methods are important tools to fill these gaps and to improve the data base indispensible for climatological research. Over the last years, new hybrid methods of machine learning and geostatistics have been developed which provide innovative prospects in spatial predictive modelling. This study will focus on evaluating the performance of 12 different interpolation methods for the wind components \\overrightarrow{u} and \\overrightarrow{v} in a mountainous region of Central Asia. Thereby, a special focus will be on applying new hybrid methods on spatial interpolation of wind data. This study is the first evaluating and comparing the performance of several of these hybrid methods. The overall aim of this study is to determine whether an optimal interpolation method exists, which can equally be applied for all pressure levels, or whether different interpolation methods have to be used for the different pressure levels. Deterministic (inverse distance weighting) and geostatistical interpolation methods (ordinary kriging) were explored, which take into account only the initial values of \\overrightarrow{u} and \\overrightarrow{v} . In addition, more complex methods (generalized additive model, support vector machine and neural networks as single methods and as hybrid methods as well as regression-kriging) that consider additional variables were applied. The analysis of the error indices revealed that regression-kriging provided the most accurate interpolation results for both wind components and all pressure heights. At 200 and 500 hPa, regression-kriging is followed by the different kinds of neural networks and support vector machines and for 850 hPa it is followed by the different types of support vector machine and ordinary kriging. Overall, explanatory variables improve the interpolation results.

From BASE-ASIA Toward 7-SEAS: A Satellite-Surface Perspective of Boreal Spring Biomass-Burning Aerosols and Clouds in Southeast Asia

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; Hsu, N. Christina; Lau, William K.-M.; Li, Can; Gabriel, Philip M.; Ji, Qiang; Holben, Brent N.; Welton, E. Judd; Nguyen, Anh X.; Janjai, Serm;

Chemical and biological impacts of ocean acidification along the west coast of North America

NASA Astrophysics Data System (ADS)

Feely, Richard A.; Alin, Simone R.; Carter, Brendan; Bednaršek, Nina; Hales, Burke; Chan, Francis; Hill, Tessa M.; Gaylord, Brian; Sanford, Eric; Byrne, Robert H.; Sabine, Christopher L.; Greeley, Dana; Juranek, Lauren

2016-12-01

The continental shelf region off the west coast of North America is seasonally exposed to water with a low aragonite saturation state by coastal upwelling of CO2-rich waters. To date, the spatial and temporal distribution of anthropogenic CO2 (Canth) within the CO2-rich waters is largely unknown. Here we adapt the multiple linear regression approach to utilize the GO-SHIP Repeat Hydrography data from the northeast Pacific to establish an annually updated relationship between Canth and potential density. This relationship was then used with the NOAA Ocean Acidification Program West Coast Ocean Acidification (WCOA) cruise data sets from 2007, 2011, 2012, and 2013 to determine the spatial variations of Canth in the upwelled water. Our results show large spatial differences in Canth in surface waters along the coast, with the lowest values (37-55 μmol kg-1) in strong upwelling regions off southern Oregon and northern California and higher values (51-63 μmol kg-1) to the north and south of this region. Coastal dissolved inorganic carbon concentrations are also elevated due to a natural remineralized component (Cbio), which represents carbon accumulated through net respiration in the seawater that has not yet degassed to the atmosphere. Average surface Canth is almost twice the surface remineralized component. In contrast, Canth is only about one third and one fifth of the remineralized component at 50 m and 100 m depth, respectively. Uptake of Canth has caused the aragonite saturation horizon to shoal by approximately 30-50 m since the preindustrial period so that undersaturated waters are well within the regions of the continental shelf that affect the shell dissolution of living pteropods. Our data show that the most severe biological impacts occur in the nearshore waters, where corrosive waters are closest to the surface. Since the pre-industrial times, pteropod shell dissolution has, on average, increased approximately 19-26% in both nearshore and offshore waters.

Conceptual Design of Optimized Fossil Energy Systems with Capture and Sequestration of Carbon Dioxide

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

Nils Johnson; Joan Ogden

2010-12-31

In this final report, we describe research results from Phase 2 of a technical/economic study of fossil hydrogen energy systems with carbon dioxide (CO{sub 2}) capture and storage (CCS). CO{sub 2} capture and storage, or alternatively, CO{sub 2} capture and sequestration, involves capturing CO{sub 2} from large point sources and then injecting it into deep underground reservoirs for long-term storage. By preventing CO{sub 2} emissions into the atmosphere, this technology has significant potential to reduce greenhouse gas (GHG) emissions from fossil-based facilities in the power and industrial sectors. Furthermore, the application of CCS to power plants and hydrogen production facilitiesmore » can reduce CO{sub 2} emissions associated with electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs) and, thus, can also improve GHG emissions in the transportation sector. This research specifically examines strategies for transitioning to large-scale coal-derived energy systems with CCS for both hydrogen fuel production and electricity generation. A particular emphasis is on the development of spatially-explicit modeling tools for examining how these energy systems might develop in real geographic regions. We employ an integrated modeling approach that addresses all infrastructure components involved in the transition to these energy systems. The overall objective is to better understand the system design issues and economics associated with the widespread deployment of hydrogen and CCS infrastructure in real regions. Specific objectives of this research are to: Develop improved techno-economic models for all components required for the deployment of both hydrogen and CCS infrastructure, Develop novel modeling methods that combine detailed spatial data with optimization tools to explore spatially-explicit transition strategies, Conduct regional case studies to explore how these energy systems might develop in different regions of the United States, and Examine how the design and cost of coal-based H{sub 2} and CCS infrastructure depend on geography and location.« less

Daily air temperature interpolated at high spatial resolution over a large mountainous region

USGS Publications Warehouse

Dodson, R.; Marks, D.

1997-01-01

Two methods are investigated for interpolating daily minimum and maximum air temperatures (Tmin and Tmax) at a 1 km spatial resolution over a large mountainous region (830 000 km2) in the U.S. Pacific Northwest. The methods were selected because of their ability to (1) account for the effect of elevation on temperature and (2) efficiently handle large volumes of data. The first method, the neutral stability algorithm (NSA), used the hydrostatic and potential temperature equations to convert measured temperatures and elevations to sea-level potential temperatures. The potential temperatures were spatially interpolated using an inverse-squared-distance algorithm and then mapped to the elevation surface of a digital elevation model (DEM). The second method, linear lapse rate adjustment (LLRA), involved the same basic procedure as the NSA, but used a constant linear lapse rate instead of the potential temperature equation. Cross-validation analyses were performed using the NSA and LLRA methods to interpolate Tmin and Tmax each day for the 1990 water year, and the methods were evaluated based on mean annual interpolation error (IE). The NSA method showed considerable bias for sites associated with vertical extrapolation. A correction based on climate station/grid cell elevation differences was developed and found to successfully remove the bias. The LLRA method was tested using 3 lapse rates, none of which produced a serious extrapolation bias. The bias-adjusted NSA and the 3 LLRA methods produced almost identical levels of accuracy (mean absolute errors between 1.2 and 1.3??C), and produced very similar temperature surfaces based on image difference statistics. In terms of accuracy, speed, and ease of implementation, LLRA was chosen as the best of the methods tested.

Flexural rigidity of the Basin and Range-Colorado Plateau-Rocky Mountain transition from coherence analysis of gravity and topography

NASA Technical Reports Server (NTRS)

Lowery, Anthony R.; Smith, Robert B.

1994-01-01

Stochastic inversion for flexural loads and flexural rigidity of the continental elastic layer can be accomplished most effectively by using the coherence of gravity and topography. However, the spatial resolution of coherence analysis has been limited by use of two-dimensional periodogram spectra from very large (greater than 10(exp 5)sq km) windows that generally include multiple tectonic features. Using a two-dimensional spectral estimator based on the maximum entropy method, the spatial resolution of flexural proerties can be enhanced by a factor of 4 or more, enabling more detailed analysis at the scale of individual tectonic features. This new approach is used to map the spatial variation of flexural rigidity along the Basin and Range transition to the Colorado Plateau and Middle Rocky Mountains physiographic provinces. Large variations in flexural isostatic responses are found, with rigidities ranging from as low as 8.7 x 10(exp 20) N m (elastic thickness (T(sub e) = 4.6 km) in the Basin and Range to as high as 4.1 x 10(exp 24) N m T(sub e) = 77 km) in the Middle Rocky Mountains. These results compare favorably woith independent determinations of flexural rigidity in the region. Areas of low flexural rigidity correlate strongly with areas of high surface heat flow, as is expected from the contingence of flexural rigidity on a temperature-dependent flow law. Also, late Cenozoic normal faults with large displacements are found primarily in area of low flexural rigidity region. The highest flexural rigidity is found within the Archean Wyoming craton, where evidence suggests that deeply rooted cratonic lithosphere may play a role in determining the distribution of tectonism at the surface.

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

Bosler, Peter A.; Roesler, Erika L.; Taylor, Mark A.

This study discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared: the commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. The Stride Search algorithm is defined independently of the spatial discretization associated with a particular data set. Results from the two algorithms are compared for the application of tropical cyclonemore » detection, and shown to produce similar results for the same set of storm identification criteria. Differences between the two algorithms arise for some storms due to their different definition of search regions in physical space. The physical space associated with each Stride Search region is constant, regardless of data resolution or latitude, and Stride Search is therefore capable of searching all regions of the globe in the same manner. Stride Search's ability to search high latitudes is demonstrated for the case of polar low detection. Wall clock time required for Stride Search is shown to be smaller than a grid point search of the same data, and the relative speed up associated with Stride Search increases as resolution increases.« less

The methane distribution on Titan: high resolution spectroscopy in the near-IR with Keck NIRSPEC/AO

NASA Astrophysics Data System (ADS)

Adamkovics, Mate; Mitchell, Jonathan L.

2014-11-01

The distribution of methane on Titan is a diagnostic of regional scale meteorology and large scale atmospheric circulation. The observed formation of clouds and the transport of heat through the atmosphere both depend on spatial and temporal variations in methane humidity. We have performed observations to measure the the distribution on methane Titan using high spectral resolution near-IR (H-band) observations made with NIRSPEC, with adaptive optics, at Keck Observatory in July 2014. This work builds on previous attempts at this measurement with improvement in the observing protocol and data reduction, together with increased integration times. Radiative transfer models using line-by-line calculation of methane opacities from the HITRAN2012 database are used to retrieve methane abundances. We will describe analysis of the reduced observations, which show latitudinal spatial variation in the region the spectrum that is thought to be sensitive to methane abundance. Quantifying the methane abundance variation requires models that include the spatial variation in surface albedo and meridional haze gradient; we will describe (currently preliminary) analysis of the the methane distribution and uncertainties in the retrieval.

Effect of fertility on secondary sex ratio and twinning rate in Sweden, 1749-1870.

PubMed

Fellman, Johan; Eriksson, Aldur W

2015-02-01

We analyzed the effect of total fertility rate (TFR) and crude birth rate (CBR) on the number of males per 100 females at birth, also called the secondary sex ratio (SR), and on the twinning rate (TWR). Earlier studies have noted regional variations in TWR and racial differences in the SR. Statistical analyses have shown that comparisons between SRs demand large data sets because random fluctuations in moderate data are marked. Consequently, reliable results presuppose national birth data. Here, we analyzed historical demographic data and their regional variations between counties in Sweden. We built spatial models for the TFR in 1860 and the CBR in 1751-1870, and as regressors we used geographical coordinates for the provincial capitals of the counties. For both variables, we obtained significant spatial variations, albeit of different patterns and power. The SR among the live-born in 1749-1869 and the TWR in 1751-1860 showed slight spatial variations. The influence of CBR and TFR on the SR and TWR was examined and statistical significant effects were found.

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.

Identification of the key ecological factors influencing vegetation degradation in semi-arid agro-pastoral ecotone considering spatial scales

NASA Astrophysics Data System (ADS)

Peng, Yu; Wang, Qinghui; Fan, Min

2017-11-01

When assessing re-vegetation project performance and optimizing land management, identification of the key ecological factors inducing vegetation degradation has crucial implications. Rainfall, temperature, elevation, slope, aspect, land use type, and human disturbance are ecological factors affecting the status of vegetation index. However, at different spatial scales, the key factors may vary. Using Helin County, Inner-Mongolia, China as the study site and combining remote sensing image interpretation, field surveying, and mathematical methods, this study assesses key ecological factors affecting vegetation degradation under different spatial scales in a semi-arid agro-pastoral ecotone. It indicates that the key factors are different at various spatial scales. Elevation, rainfall, and temperature are identified as crucial for all spatial extents. Elevation, rainfall and human disturbance are key factors for small-scale quadrats of 300 m × 300 m and 600 m × 600 m, temperature and land use type are key factors for a medium-scale quadrat of 1 km × 1 km, and rainfall, temperature, and land use are key factors for large-scale quadrats of 2 km × 2 km and 5 km × 5 km. For this region, human disturbance is not the key factor for vegetation degradation across spatial scales. It is necessary to consider spatial scale for the identification of key factors determining vegetation characteristics. The eco-restoration programs at various spatial scales should identify key influencing factors according their scales so as to take effective measurements. The new understanding obtained in this study may help to explore the forces which driving vegetation degradation in the degraded regions in the world.

Chlorophyll-a variability in the Seychelles-Chagos Thermocline Ridge: Analysis of a coupled biophysical model

NASA Astrophysics Data System (ADS)

Dilmahamod, A. F.; Hermes, J. C.; Reason, C. J. C.

2016-02-01

The biological variability of the upwelling region of the Seychelles-Chagos Thermocline Ridge (SCTR), both at surface and subsurface levels, is investigated using monthly outputs of a coupled biophysical model from 1958 to 2011. Owing to its large spatial distribution and sensitivity to climate variability, the SCTR is studied as three distinct regions; namely, sub-regions 1 (western; 5°S-12°S, 55°E-65°E), 2 (central; 5°S-12°S, 65°E-75°E) and 3 (eastern; 5°S-12°S, 75°E-90°E). Surface and subsurface chlorophyll-a (Chl-a) exhibit completely different response mechanisms in sub-region 3 compared to sub-regions 1 and 2 during El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events. During the intense 1997/1998 ENSO-IOD event, the high Chl-a tongue observed in the eastern Indian Ocean induces an increase in surface concentration in sub-region 3, whose subsurface variability is also substantially less (more) impacted by downwelling (upwelling) Rossby waves generated by El Niño (La Niña) forcing. After filtering out the annual signal, wavelet analysis of surface Chl-a revealed a significant 6 month periodicity in sub-regions 1 and 2 whereas a 5-year signal dominated in sub-region 3. The latter suggests that sub-region 3 is more prone to different ENSO/IOD influences, due to its proximity to the eastern Indian Ocean. In the unfiltered data, the subsurface Chl-a in sub-region 3 exhibits a strong signal near 1 year, with sub-regions 1 and 2 having a pronounced 6-year and 5-year signals respectively. These analyses show that the SCTR cannot be investigated as a single homogeneous region due to its large spatial distribution and different response mechanisms to climate events. Furthermore, changes in SST, thermocline depth, winds and Chl-a before and after the 1976-1977 climate shift differed across the SCTR, further highlighting the heterogeneity of this sensitive region in the Indian Ocean.

Three-dimensional spectral-spatial EPR imaging of free radicals in the heart: a technique for imaging tissue metabolism and oxygenation.

PubMed Central

Kuppusamy, P; Chzhan, M; Vij, K; Shteynbuk, M; Lefer, D J; Giannella, E; Zweier, J L

1994-01-01

It has been hypothesized that free radical metabolism and oxygenation in living organs and tissues such as the heart may vary over the spatially defined tissue structure. In an effort to study these spatially defined differences, we have developed electron paramagnetic resonance imaging instrumentation enabling the performance of three-dimensional spectral-spatial images of free radicals infused into the heart and large vessels. Using this instrumentation, high-quality three-dimensional spectral-spatial images of isolated perfused rat hearts and rabbit aortas are obtained. In the isolated aorta, it is shown that spatially and spectrally accurate images of the vessel lumen and wall could be obtained in this living vascular tissue. In the isolated rat heart, imaging experiments were performed to determine the kinetics of radical clearance at different spatial locations within the heart during myocardial ischemia. The kinetic data show the existence of regional and transmural differences in myocardial free radical clearance. It is further demonstrated that EPR imaging can be used to noninvasively measure spatially localized oxygen concentrations in the heart. Thus, the technique of spectral-spatial EPR imaging is shown to be a powerful tool in providing spatial information regarding the free radical distribution, metabolism, and tissue oxygenation in living biological organs and tissues. Images PMID:8159757

Satellite-based characterization of climatic conditions before large-scale general flowering events in Peninsular Malaysia

PubMed Central

Azmy, Muna Maryam; Hashim, Mazlan; Numata, Shinya; Hosaka, Tetsuro; Noor, Nur Supardi Md.; Fletcher, Christine

2016-01-01

General flowering (GF) is a unique phenomenon wherein, at irregular intervals, taxonomically diverse trees in Southeast Asian dipterocarp forests synchronize their reproduction at the community level. Triggers of GF, including drought and low minimum temperatures a few months previously has been limitedly observed across large regional scales due to lack of meteorological stations. Here, we aim to identify the climatic conditions that trigger large-scale GF in Peninsular Malaysia using satellite sensors, Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), to evaluate the climatic conditions of focal forests. We observed antecedent drought, low temperature and high photosynthetic radiation conditions before large-scale GF events, suggesting that large-scale GF events could be triggered by these factors. In contrast, we found higher-magnitude GF in forests where lower precipitation preceded large-scale GF events. GF magnitude was also negatively influenced by land surface temperature (LST) for a large-scale GF event. Therefore, we suggest that spatial extent of drought may be related to that of GF forests, and that the spatial pattern of LST may be related to that of GF occurrence. With significant new findings and other results that were consistent with previous research we clarified complicated environmental correlates with the GF phenomenon. PMID:27561887

Satellite-based characterization of climatic conditions before large-scale general flowering events in Peninsular Malaysia.

PubMed

Azmy, Muna Maryam; Hashim, Mazlan; Numata, Shinya; Hosaka, Tetsuro; Noor, Nur Supardi Md; Fletcher, Christine

2016-08-26

General flowering (GF) is a unique phenomenon wherein, at irregular intervals, taxonomically diverse trees in Southeast Asian dipterocarp forests synchronize their reproduction at the community level. Triggers of GF, including drought and low minimum temperatures a few months previously has been limitedly observed across large regional scales due to lack of meteorological stations. Here, we aim to identify the climatic conditions that trigger large-scale GF in Peninsular Malaysia using satellite sensors, Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), to evaluate the climatic conditions of focal forests. We observed antecedent drought, low temperature and high photosynthetic radiation conditions before large-scale GF events, suggesting that large-scale GF events could be triggered by these factors. In contrast, we found higher-magnitude GF in forests where lower precipitation preceded large-scale GF events. GF magnitude was also negatively influenced by land surface temperature (LST) for a large-scale GF event. Therefore, we suggest that spatial extent of drought may be related to that of GF forests, and that the spatial pattern of LST may be related to that of GF occurrence. With significant new findings and other results that were consistent with previous research we clarified complicated environmental correlates with the GF phenomenon.

Large-scale changes in network interactions as a physiological signature of spatial neglect.

PubMed

Baldassarre, Antonello; Ramsey, Lenny; Hacker, Carl L; Callejas, Alicia; Astafiev, Serguei V; Metcalf, Nicholas V; Zinn, Kristi; Rengachary, Jennifer; Snyder, Abraham Z; Carter, Alex R; Shulman, Gordon L; Corbetta, Maurizio

2014-12-01

The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n=84) heterogeneous sample of first-ever stroke patients (within 1-2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

NASA Astrophysics Data System (ADS)

Yang, Lei; Chen, Liding; Wei, Wei

2017-04-01

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

Land use and climate affect Black Tern, Northern Harrier, and Marsh Wren abundance in the Prairie Pothole Region of the United States

USGS Publications Warehouse

Forcey, Greg M.; Thogmartin, Wayne E.; Linz, George M.; McKann, Patrick C.

2014-01-01

Bird populations are influenced by many environmental factors at both large and small scales. Our study evaluated the influences of regional climate and land-use variables on the Northern Harrier (Circus cyaneus), Black Tern (Childonias niger), and Marsh Wren (Cistothorus palustris) in the prairie potholes of the upper Midwest of the United States. These species were chosen because their diverse habitat preference represent the spectrum of habitat conditions present in the Prairie Potholes, ranging from open prairies to dense cattail marshes. We evaluated land-use covariates at three logarithmic spatial scales (1,000 ha, 10,000 ha, and 100,000 ha) and constructed models a priori using information from published habitat associations and climatic influences. The strongest influences on the abundance of each of the three species were the percentage of wetland area across all three spatial scales and precipitation in the year preceding that when bird surveys were conducted. Even among scales ranging over three orders of magnitude the influence of spatial scale was small, as models with the same variables expressed at different scales were often in the best model subset. Examination of the effects of large-scale environmental variables on wetland birds elucidated relationships overlooked in many smaller-scale studies, such as the influences of climate and habitat variables at landscape scales. Given the spatial variation in the abundance of our focal species within the prairie potholes, our model predictions are especially useful for targeting locations, such as northeastern South Dakota and central North Dakota, where management and conservation efforts would be optimally beneficial. This modeling approach can also be applied to other species and geographic areas to focus landscape conservation efforts and subsequent small-scale studies, especially in constrained economic climates.

Region-of-interest image reconstruction in circular cone-beam microCT

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

Cho, Seungryong; Bian, Junguo; Pelizzari, Charles A.

2007-12-15

Cone-beam microcomputed tomography (microCT) is one of the most popular choices for small animal imaging which is becoming an important tool for studying animal models with transplanted diseases. Region-of-interest (ROI) imaging techniques in CT, which can reconstruct an ROI image from the projection data set of the ROI, can be used not only for reducing imaging-radiation exposure to the subject and scatters to the detector but also for potentially increasing spatial resolution of the reconstructed images. Increasing spatial resolution in microCT images can facilitate improved accuracy in many assessment tasks. A method proposed previously for increasing CT image spatial resolutionmore » entails the exploitation of the geometric magnification in cone-beam CT. Due to finite detector size, however, this method can lead to data truncation for a large geometric magnification. The Feldkamp-Davis-Kress (FDK) algorithm yields images with artifacts when truncated data are used, whereas the recently developed backprojection filtration (BPF) algorithm is capable of reconstructing ROI images without truncation artifacts from truncated cone-beam data. We apply the BPF algorithm to reconstructing ROI images from truncated data of three different objects acquired by our circular cone-beam microCT system. Reconstructed images by use of the FDK and BPF algorithms from both truncated and nontruncated cone-beam data are compared. The results of the experimental studies demonstrate that, from certain truncated data, the BPF algorithm can reconstruct ROI images with quality comparable to that reconstructed from nontruncated data. In contrast, the FDK algorithm yields ROI images with truncation artifacts. Therefore, an implication of the studies is that, when truncated data are acquired with a configuration of a large geometric magnification, the BPF algorithm can be used for effective enhancement of the spatial resolution of a ROI image.« less

Large-scale patterns formed by solar active regions during the ascending phase of cycle 21

NASA Astrophysics Data System (ADS)

Gaizauskas, V.; Harvey, K. L.; Harvey, J. W.; Zwaan, C.

1983-02-01

Synoptic maps of photospheric magnetic fields prepared at the Kitt Peak National Observatory are used in investigating large-scale patterns in the spatial and temporal distribution of solar active regions for 27 solar rotations between 1977 and 1979. The active regions are found to be distributed in 'complexes of activity' (Bumba and Howard, 1965). With the working definition of a complex of activity based on continuity and proximity of the constituent active regions, the phenomenology of complexes is explored. It is found that complexes of activity form within one month and that they are typically maintained for 3 to 6 solar rotations by fresh injections of magnetic flux. During the active lifetime of a complex of activity, the total magnetic flux in the complex remains steady to within a factor of 2. The magnetic polarities are closely balanced, and each complex rotates about the sun at its own special, constant rate. In certain cases, the complexes form two diverging branches.

Spatial, seasonal, and source variability in the stable oxygen and hydrogen isotopic composition of tap waters throughout the USA

USGS Publications Warehouse

Landwehr, Jurate M.; Coplen, Tyler B.; Stewart, David W.

2013-01-01

To assess spatial, seasonal, and source variability in stable isotopic composition of human drinking waters throughout the entire USA, we have constructed a database of δ18O and δ2H of US tap waters. An additional purpose was to create a publicly available dataset useful for evaluating the forensic applicability of these isotopes for human tissue source geolocation. Samples were obtained at 349 sites, from diverse population centres, grouped by surface hydrologic units for regional comparisons. Samples were taken concurrently during two contrasting seasons, summer and winter. Source supply (surface, groundwater, mixed, and cistern) and system (public and private) types were noted. The isotopic composition of tap waters exhibits large spatial and regional variation within each season as well as significant at-site differences between seasons at many locations, consistent with patterns found in environmental (river and precipitation) waters deriving from hydrologic processes influenced by geographic factors. However, anthropogenic factors, such as the population of a tap’s surrounding community and local availability from diverse sources, also influence the isotopic composition of tap waters. Even within a locale as small as a single metropolitan area, tap waters with greatly differing isotopic compositions can be found, so that tap water within a region may not exhibit the spatial or temporal coherence predicted for environmental water. Such heterogeneities can be confounding factors when attempting forensic inference of source water location, and they underscore the necessity of measurements, not just predictions, with which to characterize the isotopic composition of regional tap waters. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

Two cis elements collaborate to spatially repress transcription from a sea urchin promoter

NASA Technical Reports Server (NTRS)

Frudakis, T. N.; Wilt, F.

1995-01-01

The expression pattern of many territory-specific genes in metazoan embryos is maintained by an active process of negative spatial regulation. However, the mechanism of this strategy of gene regulation is not well understood in any system. Here we show that reporter constructs containing regulatory sequence for the SM30-alpha gene of Stronglyocentrotus purpuratus are expressed in a pattern congruent with that of the endogenous SM30 gene(s), largely as a result of active transcriptional repression in cell lineages in which the gene is not normally expressed. Chloramphenicol acetyl transferase assays of deletion constructs from the 2600-bp upstream region showed that repressive elements were present in the region from -1628 to -300. In situ hybridization analysis showed that the spatial fidelity of expression was severely compromised when the region from -1628 to -300 was deleted. Two highly repetitive sequence motifs, (G/A/C)CCCCT and (T/C)(T/A/C)CTTTT(T/A/C), are present in the -1628 to -300 region. Representatives of these elements were analyzed by gel mobility shift experiments and were found to interact specifically with protein in crude nuclear extracts. When oligonucleotides containing either sequence element were co-injected with a correctly regulated reporter as potential competitors, the reporter was expressed in inappropriate cells. When composite oligonucleotides, containing both sequence elements, were fused to a misregulated reporter, the expression of the reporter in inappropriate cells was suppressed. Comparison of composite oligonucleotides with oligonucleotides containing single constituent elements show that both sequence elements are required for effective spatial regulation. Thus, both individual elements are required, but only a composite element containing both elements is sufficient to function as a tissue-specific repressive element.

Landscape-scale consequences of differential tree mortality from catastrophic wind disturbance in the Amazon.

PubMed

Rifai, Sami W; Urquiza Muñoz, José D; Negrón-Juárez, Robinson I; Ramírez Arévalo, Fredy R; Tello-Espinoza, Rodil; Vanderwel, Mark C; Lichstein, Jeremy W; Chambers, Jeffrey Q; Bohlman, Stephanie A

2016-10-01

Wind disturbance can create large forest blowdowns, which greatly reduces live biomass and adds uncertainty to the strength of the Amazon carbon sink. Observational studies from within the central Amazon have quantified blowdown size and estimated total mortality but have not determined which trees are most likely to die from a catastrophic wind disturbance. Also, the impact of spatial dependence upon tree mortality from wind disturbance has seldom been quantified, which is important because wind disturbance often kills clusters of trees due to large treefalls killing surrounding neighbors. We examine (1) the causes of differential mortality between adult trees from a 300-ha blowdown event in the Peruvian region of the northwestern Amazon, (2) how accounting for spatial dependence affects mortality predictions, and (3) how incorporating both differential mortality and spatial dependence affect the landscape level estimation of necromass produced from the blowdown. Standard regression and spatial regression models were used to estimate how stem diameter, wood density, elevation, and a satellite-derived disturbance metric influenced the probability of tree death from the blowdown event. The model parameters regarding tree characteristics, topography, and spatial autocorrelation of the field data were then used to determine the consequences of non-random mortality for landscape production of necromass through a simulation model. Tree mortality was highly non-random within the blowdown, where tree mortality rates were highest for trees that were large, had low wood density, and were located at high elevation. Of the differential mortality models, the non-spatial models overpredicted necromass, whereas the spatial model slightly underpredicted necromass. When parameterized from the same field data, the spatial regression model with differential mortality estimated only 7.5% more dead trees across the entire blowdown than the random mortality model, yet it estimated 51% greater necromass. We suggest that predictions of forest carbon loss from wind disturbance are sensitive to not only the underlying spatial dependence of observations, but also the biological differences between individuals that promote differential levels of mortality. © 2016 by the Ecological Society of America.

Spatial-Temporal Heterogeneity in Regional Watershed Phosphorus Cycles Driven by Changes in Human Activity over the Past Century

NASA Astrophysics Data System (ADS)

Hale, R. L.; Grimm, N. B.; Vorosmarty, C. J.

2014-12-01

An ongoing challenge for society is to harness the benefits of phosphorus (P) while minimizing negative effects on downstream ecosystems. To meet this challenge we must understand the controls on the delivery of anthropogenic P from landscapes to downstream ecosystems. We used a model that incorporates P inputs to watersheds, hydrology, and infrastructure (sewers, waste-water treatment plants, and reservoirs) to reconstruct historic P yields for the northeastern U.S. from 1930 to 2002. At the regional scale, increases in P inputs were paralleled by increased fractional retention, thus P loading to the coast did not increase significantly. We found that temporal variation in regional P yield was correlated with P inputs. Spatial patterns of watershed P yields were best predicted by inputs, but the correlation between inputs and yields in space weakened over time, due to infrastructure development. Although the magnitude of infrastructure effect was small, its role changed over time and was important in creating spatial and temporal heterogeneity in input-yield relationships. We then conducted a hierarchical cluster analysis to identify a typology of anthropogenic P cycling, using data on P inputs (fertilizer, livestock feed, and human food), infrastructure (dams, wastewater treatment plants, sewers), and hydrology (runoff coefficient). We identified 6 key types of watersheds that varied significantly in climate, infrastructure, and the types and amounts of P inputs. Annual watershed P yields and retention varied significantly across watershed types. Although land cover varied significantly across typologies, clusters based on land cover alone did not explain P budget patterns, suggesting that this variable is insufficient to understand patterns of P cycling across large spatial scales. Furthermore, clusters varied over time as patterns of climate, P use, and infrastructure changed. Our results demonstrate that the drivers of P cycles are spatially and temporally heterogeneous, yet they also suggest that a relatively simple typology of watersheds can be useful for understanding regional P cycles and may help inform P management approaches.

Isoscapes of tree-ring carbon-13 perform like meteorological networks in predicting regional precipitation patterns

NASA Astrophysics Data System (ADS)

del Castillo, Jorge; Aguilera, Mònica; Voltas, Jordi; Ferrio, Juan Pedro

2013-04-01

Stable isotopes in tree rings provide climatic information with annual resolution dating back for centuries or even millennia. However, deriving spatially explicit climate models from isotope networks remains challenging. Here we propose a methodology to model regional precipitation from carbon isotope discrimination (Δ13C) in tree rings by (1) building regional spatial models of Δ13C (isoscapes), and (2) deriving precipitation maps from 13C-isoscapes, taking advantage of the response of Δ13C to precipitation in seasonally-dry climates. As a case study, we modeled the spatial distribution of mean annual precipitation (MAP) in the northeastern Iberian Peninsula, a region with complex orography and climate (MAP=303-1086 mm). We compiled wood Δ13C data for two Mediterranean species that exhibit complementary responses to seasonal precipitation (Pinus halepensis Mill., N=38; Quercus ilex L.; N=44; pooling period: 1975-2008). By combining multiple regression and geostatistical interpolation, we generated one 13C-isoscape for each species. A spatial model of MAP was then built as the sum of two complementary maps of seasonal precipitation, each one derived from the corresponding 13C-isoscape (September-November from Q. ilex; December-August from P. halepensis). Our approach showed a predictive power for MAP (RMSE=84 mm) nearly identical to that obtained by interpolating data directly from a similarly dense network of meteorological stations (RMSE=80-83 mm, N=65), being only outperformed when using a much denser meteorological network (RMSE=56-57 mm, N=340). This method offers new avenues for modeling spatial variability of past precipitation, exploiting the large amount of information currently available from tree-ring networks. Acknowledgements: This work was funded by MC-ERG-246725 (FP7, EU) and AGL 2012-40039-C02-02 (MINECO, Spain). JdC and JPF are supported by FPI fellowship (MCINN) and Ramón y Cajal programme (RYC-2008-02050, MINECO), respectively.

Spatiotemporal variability of snow depth across the Eurasian continent from 1966 to 2012

NASA Astrophysics Data System (ADS)

Zhong, Xinyue; Zhang, Tingjun; Kang, Shichang; Wang, Kang; Zheng, Lei; Hu, Yuantao; Wang, Huijuan

2018-01-01

Snow depth is one of the key physical parameters for understanding land surface energy balance, soil thermal regime, water cycle, and assessing water resources from local community to regional industrial water supply. Previous studies by using in situ data are mostly site specific; data from satellite remote sensing may cover a large area or global scale, but uncertainties remain large. The primary objective of this study is to investigate spatial variability and temporal change in snow depth across the Eurasian continent. Data used include long-term (1966-2012) ground-based measurements from 1814 stations. Spatially, long-term (1971-2000) mean annual snow depths of >20 cm were recorded in northeastern European Russia, the Yenisei River basin, Kamchatka Peninsula, and Sakhalin. Annual mean and maximum snow depth increased by 0.2 and 0.6 cm decade-1 from 1966 through 2012. Seasonally, monthly mean snow depth decreased in autumn and increased in winter and spring over the study period. Regionally, snow depth significantly increased in areas north of 50° N. Compared with air temperature, snowfall had greater influence on snow depth during November through March across the former Soviet Union. This study provides a baseline for snow depth climatology and changes across the Eurasian continent, which would significantly help to better understanding climate system and climate changes on regional, hemispheric, or even global scales.

Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty.

PubMed

Leedale, Joseph; Tompkins, Adrian M; Caminade, Cyril; Jones, Anne E; Nikulin, Grigory; Morse, Andrew P

2016-03-31

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate- driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

Population Vulnerability to Biannual Cholera Outbreaks and Associated Macro-Scale Drivers in the Bengal Delta

PubMed Central

Akanda, Ali Shafqat; Jutla, Antarpreet S.; Gute, David M.; Sack, R. Bradley; Alam, Munirul; Huq, Anwar; Colwell, Rita R.; Islam, Shafiqul

2013-01-01

The highly populated floodplains of the Bengal Delta have a long history of endemic and epidemic cholera outbreaks, both coastal and inland. Previous studies have not addressed the spatio-temporal dynamics of population vulnerability related to the influence of underlying large-scale processes. We analyzed spatial and temporal variability of cholera incidence across six surveillance sites in the Bengal Delta and their association with regional hydroclimatic and environmental drivers. More specifically, we use salinity and flood inundation modeling across the vulnerable districts of Bangladesh to test earlier proposed hypotheses on the role of these environmental variables. Our results show strong influence of seasonal and interannual variability in estuarine salinity on spring outbreaks and inland flooding on fall outbreaks. A large segment of the population in the Bengal Delta floodplains remain vulnerable to these biannual cholera transmission mechanisms that provide ecologic and environmental conditions for outbreaks over large geographic regions. PMID:24019441

Spatially Explicit Modeling Reveals Cephalopod Distributions Match Contrasting Trophic Pathways in the Western Mediterranean Sea

PubMed Central

Puerta, Patricia; Hunsicker, Mary E.; Quetglas, Antoni; Álvarez-Berastegui, Diego; Esteban, Antonio; González, María; Hidalgo, Manuel

2015-01-01

Populations of the same species can experience different responses to the environment throughout their distributional range as a result of spatial and temporal heterogeneity in habitat conditions. This highlights the importance of understanding the processes governing species distribution at local scales. However, research on species distribution often averages environmental covariates across large geographic areas, missing variability in population-environment interactions within geographically distinct regions. We used spatially explicit models to identify interactions between species and environmental, including chlorophyll a (Chla) and sea surface temperature (SST), and trophic (prey density) conditions, along with processes governing the distribution of two cephalopods with contrasting life-histories (octopus and squid) across the western Mediterranean Sea. This approach is relevant for cephalopods, since their population dynamics are especially sensitive to variations in habitat conditions and rarely stable in abundance and location. The regional distributions of the two cephalopod species matched two different trophic pathways present in the western Mediterranean Sea, associated with the Gulf of Lion upwelling and the Ebro river discharges respectively. The effects of the studied environmental and trophic conditions were spatially variant in both species, with usually stronger effects along their distributional boundaries. We identify areas where prey availability limited the abundance of cephalopod populations as well as contrasting effects of temperature in the warmest regions. Despite distributional patterns matching productive areas, a general negative effect of Chla on cephalopod densities suggests that competition pressure is common in the study area. Additionally, results highlight the importance of trophic interactions, beyond other common environmental factors, in shaping the distribution of cephalopod populations. Our study presents a valuable approach for understanding the spatially variant ecology of cephalopod populations, which is important for fisheries and ecosystem management. PMID:26201075

Effects of anisotropy and spatial curvature on the pre-big-bang scenario

NASA Astrophysics Data System (ADS)

Clancy, Dominic; Lidsey, James E.; Tavakol, Reza

1998-08-01

A class of exact, anisotropic cosmological solutions to the vacuum Brans-Dicke theory of gravity is considered within the context of the pre-big-bang scenario. Included in this class are the Bianchi type III, V and VIh models and the spatially isotropic, negatively curved Friedmann-Robertson-Walker universe. The effects of large anisotropy and spatial curvature are determined. In contrast with a negatively curved Friedmann-Robertson-Walker model, there exist regions of the parameter space in which the combined effects of curvature and anisotropy prevent the occurrence of inflation. When inflation is possible, the necessary and sufficient conditions for successful pre-big-bang inflation are more stringent than in the isotropic models. The initial state for these models is established and corresponds in general to a gravitational plane wave.

Applications of Spatial Technology in Schistosomiasis Control Programme in The People's Republic of China.

PubMed

Wang, X-Y; He, J; Yang, K; Liang, S

2016-01-01

Schistosomiasis, as the important parasitic disease, has caused serious threats to human health globally. The People's Republic of China has acquired significant achievements based on large-scale interventions and innovational technology. The spatial technology was introduced in 1980s and widely used in the study and control of schistosomiasis in The People's Republic of China. This chapter reviews the progress and application of spatial technology in schistosomiasis control by analysing the spatiotemporal pattern of and the impact of ecological changes on schistosomiasis transmission, which have provided the information to design and select the control strategy, and assisted the establishment of the monitoring and early warning system in The People's Republic of China, especially in the marshland and mountainous regions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evolution of Precipitation Extremes in Three Large Ensembles of Climate Simulations - Impact of Spatial and Temporal Resolutions

NASA Astrophysics Data System (ADS)

Martel, J. L.; Brissette, F.; Mailhot, A.; Wood, R. R.; Ludwig, R.; Frigon, A.; Leduc, M.; Turcotte, R.

2017-12-01

Recent studies indicate that the frequency and intensity of extreme precipitation will increase in future climate due to global warming. In this study, we compare annual maxima precipitation series from three large ensembles of climate simulations at various spatial and temporal resolutions. The first two are at the global scale: the Canadian Earth System Model (CanESM2) 50-member large ensemble (CanESM2-LE) at a 2.8° resolution and the Community Earth System Model (CESM1) 40-member large ensemble (CESM1-LE) at a 1° resolution. The third ensemble is at the regional scale over both Eastern North America and Europe: the Canadian Regional Climate Model (CRCM5) 50-member large ensemble (CRCM5-LE) at a 0.11° resolution, driven at its boundaries by the CanESM-LE. The CRCM5-LE is a new ensemble issued from the ClimEx project (http://www.climex-project.org), a Québec-Bavaria collaboration. Using these three large ensembles, change in extreme precipitations over the historical (1980-2010) and future (2070-2100) periods are investigated. This results in 1 500 (30 years x 50 members for CanESM2-LE and CRCM5-LE) and 1200 (30 years x 40 members for CESM1-LE) simulated years over both the historical and future periods. Using these large datasets, the empirical daily (and sub-daily for CRCM5-LE) extreme precipitation quantiles for large return periods ranging from 2 to 100 years are computed. Results indicate that daily extreme precipitations generally will increase over most land grid points of both domains according to the three large ensembles. Regarding the CRCM5-LE, the increase in sub-daily extreme precipitations will be even more important than the one observed for daily extreme precipitations. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety.

Evaluation of methods for delineating riparian zones in a semi-arid montane watershed

Treesearch

Jessica A. Salo; David M. Theobald; Thomas C. Brown

2016-01-01

Riparian zones in semi-arid, mountainous regions provide a disproportionate amount of the available wildlife habitat and ecosystem services. Despite their importance, there is little guidance on the best way to map riparian zones for broad spatial extents (e.g., large watersheds) when detailed maps from field data or high-resolution imagery and terrain data...

New forest vegetation maps facilitate assessment of biodiversity indicators over large, multi-ownership regions.

Treesearch

Janet L. Ohmann

2003-01-01

Natural resource policy analysis and conservation planning are best served by broad-scale information about vegetation that is detailed, spatially complete, and consistent across land ownerships and allocations. In this paper I describe how a new generation of forest vegetation maps can be used to assess the distribution of vegetation biodiversity among land ownerships...

Mapping wildland fuels and forest structure for land management: a comparison of nearest neighbor imputation and other methods

Treesearch

Kenneth B. Pierce; Janet L. Ohmann; Michael C. Wimberly; Matthew J. Gregory; Jeremy S. Fried

2009-01-01

Land managers need consistent information about the geographic distribution of wildland fuels and forest structure over large areas to evaluate fire risk and plan fuel treatments. We compared spatial predictions for 12 fuel and forest structure variables across three regions in the western United States using gradient nearest neighbor (GNN) imputation, linear models (...

Linking an ecosystem model and a landscape model to study forest species response to climate warming

Treesearch

Hong S. He; David J. Mladenoff; Thomas R. Crow

1999-01-01

No single model can address forest change from single tree to regional scales. We discuss a framework linking an ecosystem process model {LINKAGES) with a spatial landscape model (LANDIS) to examine forest species responses to climate warming for a large, heterogeneous landscape in northern Wisconsin, USA. Individual species response at the ecosystem scale was...

Bird Habitat Conservation at Various Scales in the Atlantic Coast Joint Venture

Treesearch

Andrew Milliken; Craig Watson; Chuck Hayes

2005-01-01

The Atlantic Coast Joint Venture is a partnership focused on the conservation of habitats for migratory birds within the Atlantic Flyway/Atlantic Coast Region from Maine south to Puerto Rico. In order to be effective in planning and implementing conservation in this large and diverse area, the joint venture must work at multiple spatial scales, from the largest ?...