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

High-resolution wavefront reconstruction using the frozen flow hypothesis

NASA Astrophysics Data System (ADS)

Liu, Xuewen; Liang, Yonghui; Liu, Jin; Xu, Jieping

2017-10-01

This paper describes an approach to reconstructing wavefronts on finer grid using the frozen flow hypothesis (FFH), which exploits spatial and temporal correlations between consecutive wavefront sensor (WFS) frames. Under the assumption of FFH, slope data from WFS can be connected to a finer, composite slope grid using translation and down sampling, and elements in transformation matrices are determined by wind information. Frames of slopes are then combined and slopes on finer grid are reconstructed by solving a sparse, large-scale, ill-posed least squares problem. By using reconstructed finer slope data and adopting Fried geometry of WFS, high-resolution wavefronts are then reconstructed. The results show that this method is robust even with detector noise and wind information inaccuracy, and under bad seeing conditions, high-frequency information in wavefronts can be recovered more accurately compared with when correlations in WFS frames are ignored.

Influence of resolution in irrigated area mapping and area estimation

USGS Publications Warehouse

Velpuri, N.M.; Thenkabail, P.S.; Gumma, M.K.; Biradar, C.; Dheeravath, V.; Noojipady, P.; Yuanjie, L.

2009-01-01

The overarching goal of this paper was to determine how irrigated areas change with resolution (or scale) of imagery. Specific objectives investigated were to (a) map irrigated areas using four distinct spatial resolutions (or scales), (b) determine how irrigated areas change with resolutions, and (c) establish the causes of differences in resolution-based irrigated areas. The study was conducted in the very large Krishna River basin (India), which has a high degree of formal contiguous, and informal fragmented irrigated areas. The irrigated areas were mapped using satellite sensor data at four distinct resolutions: (a) NOAA AVHRR Pathfinder 10,000 m, (b) Terra MODIS 500 m, (c) Terra MODIS 250 m, and (d) Landsat ETM+ 30 m. The proportion of irrigated areas relative to Landsat 30 m derived irrigated areas (9.36 million hectares for the Krishna basin) were (a) 95 percent using MODIS 250 m, (b) 93 percent using MODIS 500 m, and (c) 86 percent using AVHRR 10,000 m. In this study, it was found that the precise location of the irrigated areas were better established using finer spatial resolution data. A strong relationship (R2 = 0.74 to 0.95) was observed between irrigated areas determined using various resolutions. This study proved the hypotheses that "the finer the spatial resolution of the sensor used, greater was the irrigated area derived," since at finer spatial resolutions, fragmented areas are detected better. Accuracies and errors were established consistently for three classes (surface water irrigated, ground water/conjunctive use irrigated, and nonirrigated) across the four resolutions mentioned above. The results showed that the Landsat data provided significantly higher overall accuracies (84 percent) when compared to MODIS 500 m (77 percent), MODIS 250 m (79 percent), and AVHRR 10,000 m (63 percent). ?? 2009 American Society for Photogrammetry and Remote Sensing.

Field Assessment of the Village Green Project: An Autonomous Community Air Quality Monitoring System

EPA Science Inventory

Recent findings on air pollution levels in communities motivate new technologies to assess air pollution at finer spatial scale. The Village Green Project (VGP) is a novel approach using commercially-available technology for long-term community environments air pollution measure...

Influence of Scale Effect and Model Performance in Downscaling ASTER Land Surface Temperatures to a Very High Spatial Resolution in an Agricultural Area

NASA Astrophysics Data System (ADS)

Zhou, J.; Li, G.; Liu, S.; Zhan, W.; Zhang, X.

2015-12-01

At present land surface temperatures (LSTs) can be generated from thermal infrared remote sensing with spatial resolutions from ~100 m to tens of kilometers. However, LSTs with high spatial resolution, e.g. tens of meters, are still lack. The purpose of LST downscaling is to generate LSTs with finer spatial resolutions than their native spatial resolutions. The statistical linear or nonlinear regression models are most frequently used for LST downscaling. The basic assumption of these models is the scale-invariant relationships between LST and its descriptors, which is questioned but rare researches have been reported. In addition, few researches can be found for downscaling satellite LST or TIR data to a high spatial resolution, i.e. better than 100 m or even finer. The lack of LST with high spatial resolution cannot satisfy the requirements of applications such as evapotranspiration mapping at the field scale. By selecting a dynamically developing agricultural oasis as the study area, the aim of this study is to downscale the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LSTs to 15 m, to satisfy the requirement of evapotranspiration mapping at the field scale. Twelve ASTER images from May to September in 2012, covering the entire growth stage of maize, were selected. Four statistical models were evaluated, including one global model, one piecewise model, and two local models. The influence from scale effect in downscaling LST was quantified. The downscaled LSTs are evaluated from accuracy and image quality. Results demonstrate that the influence from scale effect varies according to models and the maize growth stage. Significant influence about -4 K to 6 K existed at the early stage and weaker influence existed in the middle stage. When compared with the ground measured LSTs, the downscaled LSTs resulted from the global and local models yielded higher accuracies and better image qualities than the local models. In addition to the vegetation indices, the surface albedo is an important descriptor for downscaling LST through explaining its spatial variation induced by soil moisture.

Spatial Downscaling of Alien Species Presences using Machine Learning

NASA Astrophysics Data System (ADS)

Daliakopoulos, Ioannis N.; Katsanevakis, Stelios; Moustakas, Aristides

2017-07-01

Large scale, high-resolution data on alien species distributions are essential for spatially explicit assessments of their environmental and socio-economic impacts, and management interventions for mitigation. However, these data are often unavailable. This paper presents a method that relies on Random Forest (RF) models to distribute alien species presence counts at a finer resolution grid, thus achieving spatial downscaling. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The method is tested with an approximately 8×8 km2 grid containing floral alien species presence and several indices of climatic, habitat, land use covariates for the Mediterranean island of Crete, Greece. Alien species presence is aggregated at 16×16 km2 and used as a predictor of presence at the original resolution, thus simulating spatial downscaling. Potential explanatory variables included habitat types, land cover richness, endemic species richness, soil type, temperature, precipitation, and freshwater availability. Uncertainty assessment of the spatial downscaling of alien species’ occurrences was also performed and true/false presences and absences were quantified. The approach is promising for downscaling alien species datasets of larger spatial scale but coarse resolution, where the underlying environmental information is available at a finer resolution than the alien species data. Furthermore, the RF architecture allows for tuning towards operationally optimal sensitivity and specificity, thus providing a decision support tool for designing a resource efficient alien species census.

Multiscale measurement error models for aggregated small area health data.

PubMed

Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin

2016-08-01

Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. © The Author(s) 2016.

Using multi-scale sampling and spatial cross-correlation to investigate patterns of plant species richness

USGS Publications Warehouse

Kalkhan, M.A.; Stohlgren, T.J.

2000-01-01

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, IYZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m2) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m2 subplots within each of the 1000 m2 plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.

The Kain-Fritsch Scheme: Science Updates & Revisiting Gray-Scale Issues from the NWP & Regional Climatae Perspectives

EPA Science Inventory

It’s just a matter of time before we see global climate models increasing their spatial resolution to that now typical of regional models. This encroachment brings in an urgent need for making regional NWP and climate models applicable at certain finer resolutions. One of the hin...

Climate change, ecosystem impacts, and management for Pacific salmon

Treesearch

D.E. Schindler; X. Augerot; E. Fleishman; N.J. Mantua; B. Riddell; M. Ruckelshaus; J. Seeb; M. Webster

2008-01-01

As climate change intensifies, there is increasing interest in developing models that reduce uncertainties in projections of global climate and refine these projections to finer spatial scales. Forecasts of climate impacts on ecosystems are far more challenging and their uncertainties even larger because of a limited understanding of physical controls on biological...

Adaptation strategies and approaches: Chapter 2

Treesearch

Patricia Butler; Chris Swanston; Maria Janowiak; Linda Parker; Matt St. Pierre; Leslie Brandt

2012-01-01

A wealth of information is available on climate change adaptation, but much of it is very broad and of limited use at the finer spatial scales most relevant to land managers. This chapter contains a "menu" of adaptation actions and provides land managers in northern Wisconsin with a range of options to help forest ecosystems adapt to climate change impacts....

A synchrotron-based local computed tomography combined with data-constrained modelling approach for quantitative analysis of anthracite coal microstructure

PubMed Central

Chen, Wen Hao; Yang, Sam Y. S.; Xiao, Ti Qiao; Mayo, Sherry C.; Wang, Yu Dan; Wang, Hai Peng

2014-01-01

Quantifying three-dimensional spatial distributions of pores and material compositions in samples is a key materials characterization challenge, particularly in samples where compositions are distributed across a range of length scales, and where such compositions have similar X-ray absorption properties, such as in coal. Consequently, obtaining detailed information within sub-regions of a multi-length-scale sample by conventional approaches may not provide the resolution and level of detail one might desire. Herein, an approach for quantitative high-definition determination of material compositions from X-ray local computed tomography combined with a data-constrained modelling method is proposed. The approach is capable of dramatically improving the spatial resolution and enabling finer details within a region of interest of a sample larger than the field of view to be revealed than by using conventional techniques. A coal sample containing distributions of porosity and several mineral compositions is employed to demonstrate the approach. The optimal experimental parameters are pre-analyzed. The quantitative results demonstrated that the approach can reveal significantly finer details of compositional distributions in the sample region of interest. The elevated spatial resolution is crucial for coal-bed methane reservoir evaluation and understanding the transformation of the minerals during coal processing. The method is generic and can be applied for three-dimensional compositional characterization of other materials. PMID:24763649

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

Wang, Jiali; Swati, F. N. U.; Stein, Michael L.

Regional climate models (RCMs) are a standard tool for downscaling climate forecasts to finer spatial scales. The evaluation of RCMs against observational data is an important step in building confidence in the use of RCMs for future prediction. In addition to model performance in climatological means and marginal distributions, a model’s ability to capture spatio-temporal relationships is important. This study develops two approaches: (1) spatial correlation/variogram for a range of spatial lags, with total monthly precipitation and non-seasonal precipitation components used to assess the spatial variations of precipitation; and (2) spatio-temporal correlation for a wide range of distances, directions, andmore » time lags, with daily precipitation occurrence used to detect the dynamic features of precipitation. These measures of spatial and spatio-temporal dependence are applied to a high-resolution RCM run and to the National Center for Environmental Prediction (NCEP)-U.S. Department of Energy (DOE) AMIP II reanalysis data (NCEP-R2), which provides initial and lateral boundary conditions for the RCM. The RCM performs better than NCEP-R2 in capturing both the spatial variations of total and non-seasonal precipitation components and the spatio-temporal correlations of daily precipitation occurrences, which are related to dynamic behaviors of precipitating systems. The improvements are apparent not just at resolutions finer than that of NCEP-R2, but also when the RCM and observational data are aggregated to the resolution of NCEP-R2.« less

Scaling local species-habitat relations to the larger landscape with a hierarchical spatial count model

USGS Publications Warehouse

Thogmartin, W.E.; Knutson, M.G.

2007-01-01

Much of what is known about avian species-habitat relations has been derived from studies of birds at local scales. It is entirely unclear whether the relations observed at these scales translate to the larger landscape in a predictable linear fashion. We derived habitat models and mapped predicted abundances for three forest bird species of eastern North America using bird counts, environmental variables, and hierarchical models applied at three spatial scales. Our purpose was to understand habitat associations at multiple spatial scales and create predictive abundance maps for purposes of conservation planning at a landscape scale given the constraint that the variables used in this exercise were derived from local-level studies. Our models indicated a substantial influence of landscape context for all species, many of which were counter to reported associations at finer spatial extents. We found land cover composition provided the greatest contribution to the relative explained variance in counts for all three species; spatial structure was second in importance. No single spatial scale dominated any model, indicating that these species are responding to factors at multiple spatial scales. For purposes of conservation planning, areas of predicted high abundance should be investigated to evaluate the conservation potential of the landscape in their general vicinity. In addition, the models and spatial patterns of abundance among species suggest locations where conservation actions may benefit more than one species. ?? 2006 Springer Science+Business Media B.V.

Implications of sensor design for coral reef detection: Upscaling ground hyperspectral imagery in spatial and spectral scales

NASA Astrophysics Data System (ADS)

Caras, Tamir; Hedley, John; Karnieli, Arnon

2017-12-01

Remote sensing offers a potential tool for large scale environmental surveying and monitoring. However, remote observations of coral reefs are difficult especially due to the spatial and spectral complexity of the target compared to sensor specifications as well as the environmental implications of the water medium above. The development of sensors is driven by technological advances and the desired products. Currently, spaceborne systems are technologically limited to a choice between high spectral resolution and high spatial resolution, but not both. The current study explores the dilemma of whether future sensor design for marine monitoring should prioritise on improving their spatial or spectral resolution. To address this question, a spatially and spectrally resampled ground-level hyperspectral image was used to test two classification elements: (1) how the tradeoff between spatial and spectral resolutions affects classification; and (2) how a noise reduction by majority filter might improve classification accuracy. The studied reef, in the Gulf of Aqaba (Eilat), Israel, is heterogeneous and complex so the local substrate patches are generally finer than currently available imagery. Therefore, the tested spatial resolution was broadly divided into four scale categories from five millimeters to one meter. Spectral resolution resampling aimed to mimic currently available and forthcoming spaceborne sensors such as (1) Environmental Mapping and Analysis Program (EnMAP) that is characterized by 25 bands of 6.5 nm width; (2) VENμS with 12 narrow bands; and (3) the WorldView series with broadband multispectral resolution. Results suggest that spatial resolution should generally be prioritized for coral reef classification because the finer spatial scale tested (pixel size < 0.1 m) may compensate for some low spectral resolution drawbacks. In this regard, it is shown that the post-classification majority filtering substantially improves the accuracy of all pixel sizes up to the point where the kernel size reaches the average unit size (pixel < 0.25 m). However, careful investigation as to the effect of band distribution and choice could improve the sensor suitability for the marine environment task. This in mind, while the focus in this study was on the technologically limited spaceborne design, aerial sensors may presently provide an opportunity to implement the suggested setup.

On the Representation of Subgrid Microtopography Effects in Process-based Hydrologic Models

NASA Astrophysics Data System (ADS)

Jan, A.; Painter, S. L.; Coon, E. T.

2017-12-01

Increased availability of high-resolution digital elevation are enabling process-based hydrologic modeling on finer and finer scales. However, spatial variability in surface elevation (microtopography) exists below the scale of a typical hyper-resolution grid cell and has the potential to play a significant role in water retention, runoff, and surface/subsurface interactions. Though the concept of microtopographic features (depressions, obstructions) and the associated implications on flow and discharge are well established, representing those effects in watershed-scale integrated surface/subsurface hydrology models remains a challenge. Using the complex and coupled hydrologic environment of the Arctic polygonal tundra as an example, we study the effects of submeter topography and present a subgrid model parameterized by small-scale spatial heterogeneities for use in hyper-resolution models with polygons at a scale of 15-20 meters forming the surface cells. The subgrid model alters the flow and storage terms in the diffusion wave equation for surface flow. We compare our results against sub-meter scale simulations (acts as a benchmark for our simulations) and hyper-resolution models without the subgrid representation. The initiation of runoff in the fine-scale simulations is delayed and the recession curve is slowed relative to simulated runoff using the hyper-resolution model with no subgrid representation. Our subgrid modeling approach improves the representation of runoff and water retention relative to models that ignore subgrid topography. We evaluate different strategies for parameterizing subgrid model and present a classification-based method to efficiently move forward to larger landscapes. This work was supported by the Interoperable Design of Extreme-scale Application Software (IDEAS) project and the Next-Generation Ecosystem Experiments-Arctic (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the DOE Office of Science.

Molecular dynamics modeling of periodic nanostructuring of metals with a short UV laser pulse under spatial confinement by a water layer

NASA Astrophysics Data System (ADS)

Ivanov, D. S.; Blumenstein, A.; Ihlemann, J.; Simon, P.; Garcia, M. E.; Rethfeld, B.

2017-12-01

The possibility of material surfaces restructuring on the nanoscale due to ultrashort laser pulses has recently found a number of practical applications. It was found experimentally that under spatial confinement due to a liquid layer atop the surface, one can achieve even finer and cleaner structures as compared to that in air or in vacuum. The mechanism of the materials restructuring under the liquid confinement, however, is not clear and its experimental study is limited by the extreme conditions realized during the intense and localized laser energy deposition that takes place on nanometer spatial and picosecond time-scales. In this theoretical work, we suggest a molecular dynamics-based approach that is capable of simulating the processes of periodic nanostructuring with ultrashort UV laser pulse on metals. The theoretical results of the simulations are directly compared with the experimental data on the same spatial and temporal scales.

Effect of Variable Spatial Scales on USLE-GIS Computations

NASA Astrophysics Data System (ADS)

Patil, R. J.; Sharma, S. K.

2017-12-01

Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.

Seasonal variability shapes resilience of small-scale fisheries in Baja California Sur, Mexico.

PubMed

Pellowe, Kara E; Leslie, Heather M

2017-01-01

Small-scale fisheries are an important source of food and livelihoods to coastal communities around the world. Understanding the seasonality of fisheries catch and composition is crucial to fisheries management, particularly in the context of changing environmental and socioeconomic conditions. While seasonal variability directly impacts the lives of fishers, most fisheries studies focus on longer-term change. Here we examine seasonal variability in the small-scale fisheries of Baja California Sur, Mexico based on 13 years of government fisheries data. We investigate how four fisheries indicators with direct relevance to ecological resilience-magnitude and variance of landed fish biomass, taxon richness and the proportion of top-trophic-level taxa in total catch-vary within and among years and at multiple spatial scales. We find that these resilience indicators vary both seasonally and spatially. These results highlight the value of finer-scale monitoring and management, particularly for data-poor fisheries.

Seasonal variability shapes resilience of small-scale fisheries in Baja California Sur, Mexico

PubMed Central

Leslie, Heather M.

2017-01-01

Small-scale fisheries are an important source of food and livelihoods to coastal communities around the world. Understanding the seasonality of fisheries catch and composition is crucial to fisheries management, particularly in the context of changing environmental and socioeconomic conditions. While seasonal variability directly impacts the lives of fishers, most fisheries studies focus on longer-term change. Here we examine seasonal variability in the small-scale fisheries of Baja California Sur, Mexico based on 13 years of government fisheries data. We investigate how four fisheries indicators with direct relevance to ecological resilience–magnitude and variance of landed fish biomass, taxon richness and the proportion of top-trophic-level taxa in total catch–vary within and among years and at multiple spatial scales. We find that these resilience indicators vary both seasonally and spatially. These results highlight the value of finer-scale monitoring and management, particularly for data-poor fisheries. PMID:28783740

Land use regression models to assess air pollution exposure in Mexico City using finer spatial and temporal input parameters.

PubMed

Son, Yeongkwon; Osornio-Vargas, Álvaro R; O'Neill, Marie S; Hystad, Perry; Texcalac-Sangrador, José L; Ohman-Strickland, Pamela; Meng, Qingyu; Schwander, Stephan

2018-05-17

The Mexico City Metropolitan Area (MCMA) is one of the largest and most populated urban environments in the world and experiences high air pollution levels. To develop models that estimate pollutant concentrations at fine spatiotemporal scales and provide improved air pollution exposure assessments for health studies in Mexico City. We developed finer spatiotemporal land use regression (LUR) models for PM 2.5 , PM 10 , O 3 , NO 2 , CO and SO 2 using mixed effect models with the Least Absolute Shrinkage and Selection Operator (LASSO). Hourly traffic density was included as a temporal variable besides meteorological and holiday variables. Models of hourly, daily, monthly, 6-monthly and annual averages were developed and evaluated using traditional and novel indices. The developed spatiotemporal LUR models yielded predicted concentrations with good spatial and temporal agreements with measured pollutant levels except for the hourly PM 2.5 , PM 10 and SO 2 . Most of the LUR models met performance goals based on the standardized indices. LUR models with temporal scales greater than one hour were successfully developed using mixed effect models with LASSO and showed superior model performance compared to earlier LUR models, especially for time scales of a day or longer. The newly developed LUR models will be further refined with ongoing Mexico City air pollution sampling campaigns to improve personal exposure assessments. Copyright © 2018. Published by Elsevier B.V.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Sharpening vision by adapting to flicker.

PubMed

Arnold, Derek H; Williams, Jeremy D; Phipps, Natasha E; Goodale, Melvyn A

2016-11-01

Human vision is surprisingly malleable. A static stimulus can seem to move after prolonged exposure to movement (the motion aftereffect), and exposure to tilted lines can make vertical lines seem oppositely tilted (the tilt aftereffect). The paradigm used to induce such distortions (adaptation) can provide powerful insights into the computations underlying human visual experience. Previously spatial form and stimulus dynamics were thought to be encoded independently, but here we show that adaptation to stimulus dynamics can sharpen form perception. We find that fast flicker adaptation (FFAd) shifts the tuning of face perception to higher spatial frequencies, enhances the acuity of spatial vision-allowing people to localize inputs with greater precision and to read finer scaled text, and it selectively reduces sensitivity to coarse-scale form signals. These findings are consistent with two interrelated influences: FFAd reduces the responsiveness of magnocellular neurons (which are important for encoding dynamics, but can have poor spatial resolution), and magnocellular responses contribute coarse spatial scale information when the visual system synthesizes form signals. Consequently, when magnocellular responses are mitigated via FFAd, human form perception is transiently sharpened because "blur" signals are mitigated.

Sharpening vision by adapting to flicker

PubMed Central

Arnold, Derek H.; Williams, Jeremy D.; Phipps, Natasha E.; Goodale, Melvyn A.

2016-01-01

Human vision is surprisingly malleable. A static stimulus can seem to move after prolonged exposure to movement (the motion aftereffect), and exposure to tilted lines can make vertical lines seem oppositely tilted (the tilt aftereffect). The paradigm used to induce such distortions (adaptation) can provide powerful insights into the computations underlying human visual experience. Previously spatial form and stimulus dynamics were thought to be encoded independently, but here we show that adaptation to stimulus dynamics can sharpen form perception. We find that fast flicker adaptation (FFAd) shifts the tuning of face perception to higher spatial frequencies, enhances the acuity of spatial vision—allowing people to localize inputs with greater precision and to read finer scaled text, and it selectively reduces sensitivity to coarse-scale form signals. These findings are consistent with two interrelated influences: FFAd reduces the responsiveness of magnocellular neurons (which are important for encoding dynamics, but can have poor spatial resolution), and magnocellular responses contribute coarse spatial scale information when the visual system synthesizes form signals. Consequently, when magnocellular responses are mitigated via FFAd, human form perception is transiently sharpened because “blur” signals are mitigated. PMID:27791115

What spatial scales are believable for climate model projections of sea surface temperature?

NASA Astrophysics Data System (ADS)

Kwiatkowski, Lester; Halloran, Paul R.; Mumby, Peter J.; Stephenson, David B.

2014-09-01

Earth system models (ESMs) provide high resolution simulations of variables such as sea surface temperature (SST) that are often used in off-line biological impact models. Coral reef modellers have used such model outputs extensively to project both regional and global changes to coral growth and bleaching frequency. We assess model skill at capturing sub-regional climatologies and patterns of historical warming. This study uses an established wavelet-based spatial comparison technique to assess the skill of the coupled model intercomparison project phase 5 models to capture spatial SST patterns in coral regions. We show that models typically have medium to high skill at capturing climatological spatial patterns of SSTs within key coral regions, with model skill typically improving at larger spatial scales (≥4°). However models have much lower skill at modelling historical warming patters and are shown to often perform no better than chance at regional scales (e.g. Southeast Asian) and worse than chance at finer scales (<8°). Our findings suggest that output from current generation ESMs is not yet suitable for making sub-regional projections of change in coral bleaching frequency and other marine processes linked to SST warming.

Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005-2015

NASA Astrophysics Data System (ADS)

Thompson, David R.; Kahn, Brian H.; Green, Robert O.; Chien, Steve A.; Middleton, Elizabeth M.; Tran, Daniel Q.

2018-02-01

The distribution of ice, liquid, and mixed phase clouds is important for Earth's planetary radiation budget, impacting cloud optical properties, evolution, and solar reflectivity. Most remote orbital thermodynamic phase measurements observe kilometer scales and are insensitive to mixed phases. This under-constrains important processes with outsize radiative forcing impact, such as spatial partitioning in mixed phase clouds. To date, the fine spatial structure of cloud phase has not been measured at global scales. Imaging spectroscopy of reflected solar energy from 1.4 to 1.8 µm can address this gap: it directly measures ice and water absorption, a robust indicator of cloud top thermodynamic phase, with spatial resolution of tens to hundreds of meters. We report the first such global high spatial resolution survey based on data from 2005 to 2015 acquired by the Hyperion imaging spectrometer onboard NASA's Earth Observer 1 (EO-1) spacecraft. Seasonal and latitudinal distributions corroborate observations by the Atmospheric Infrared Sounder (AIRS). For extratropical cloud systems, just 25 % of variance observed at GCM grid scales of 100 km was related to irreducible measurement error, while 75 % was explained by spatial correlations possible at finer resolutions.

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

Testing for shared biogeographic history in the lower Central American freshwater fish assemblage using comparative phylogeography: concerted, independent, or multiple evolutionary responses?

PubMed Central

Bagley, Justin C; Johnson, Jerald B

2014-01-01

A central goal of comparative phylogeography is determining whether codistributed species experienced (1) concerted evolutionary responses to past geological and climatic events, indicated by congruent spatial and temporal patterns (“concerted-response hypothesis”); (2) independent responses, indicated by spatial incongruence (“independent-response hypothesis”); or (3) multiple responses (“multiple-response hypothesis”), indicated by spatial congruence but temporal incongruence (“pseudocongruence”) or spatial and temporal incongruence (“pseudoincongruence”). We tested these competing hypotheses using DNA sequence data from three livebearing fish species codistributed in the Nicaraguan depression of Central America (Alfaro cultratus, Poecilia gillii, and Xenophallus umbratilis) that we predicted might display congruent responses due to co-occurrence in identical freshwater drainages. Spatial analyses recovered different subdivisions of genetic structure for each species, despite shared finer-scale breaks in northwestern Costa Rica (also supported by phylogenetic results). Isolation-with-migration models estimated incongruent timelines of among-region divergences, with A. cultratus and Xenophallus populations diverging over Miocene–mid-Pleistocene while P. gillii populations diverged over mid-late Pleistocene. Approximate Bayesian computation also lent substantial support to multiple discrete divergences over a model of simultaneous divergence across shared spatial breaks (e.g., Bayes factor [B10] = 4.303 for Ψ [no. of divergences] > 1 vs. Ψ = 1). Thus, the data support phylogeographic pseudoincongruence consistent with the multiple-response hypothesis. Model comparisons also indicated incongruence in historical demography, for example, support for intraspecific late Pleistocene population growth was unique to P. gillii, despite evidence for finer-scale population expansions in the other taxa. Empirical tests for phylogeographic congruence indicate that multiple evolutionary responses to historical events have shaped the population structure of freshwater species codistributed within the complex landscapes in/around the Nicaraguan depression. Recent community assembly through different routes (i.e., different past distributions or colonization routes), and intrinsic ecological differences among species, has likely contributed to the unique phylogeographical patterns displayed by these Neotropical fishes. PMID:24967085

The spatial and temporal domains of modern ecology.

PubMed

Estes, Lyndon; Elsen, Paul R; Treuer, Timothy; Ahmed, Labeeb; Caylor, Kelly; Chang, Jason; Choi, Jonathan J; Ellis, Erle C

2018-05-01

To understand ecological phenomena, it is necessary to observe their behaviour across multiple spatial and temporal scales. Since this need was first highlighted in the 1980s, technology has opened previously inaccessible scales to observation. To help to determine whether there have been corresponding changes in the scales observed by modern ecologists, we analysed the resolution, extent, interval and duration of observations (excluding experiments) in 348 studies that have been published between 2004 and 2014. We found that observational scales were generally narrow, because ecologists still primarily use conventional field techniques. In the spatial domain, most observations had resolutions ≤1 m 2 and extents ≤10,000 ha. In the temporal domain, most observations were either unreplicated or infrequently repeated (>1 month interval) and ≤1 year in duration. Compared with studies conducted before 2004, observational durations and resolutions appear largely unchanged, but intervals have become finer and extents larger. We also found a large gulf between the scales at which phenomena are actually observed and the scales those observations ostensibly represent, raising concerns about observational comprehensiveness. Furthermore, most studies did not clearly report scale, suggesting that it remains a minor concern. Ecologists can better understand the scales represented by observations by incorporating autocorrelation measures, while journals can promote attentiveness to scale by implementing scale-reporting standards.

Spatial Distribution of Coffee Wilt Disease Under Roguing and Replanting Conditions: A Case Study from Kaweri Estate in Uganda.

PubMed

Pinard, F; Makune, S E; Campagne, P; Mwangi, J

2016-11-01

Based on time and spatial dynamic considerations, this study evaluates the potential role of short- and long-distance dispersal in the spread of coffee wilt disease (CWD) in a large commercial Robusta coffee estate in Uganda (Kaweri, 1,755 ha) over a 4-year period (2008 to 2012). In monthly surveys, total disease incidence, expansion of infection foci, and the occurrence of isolated infected trees were recorded and submitted to spatial analysis. Incidence was higher and disease progression faster in old coffee plantings compared with young plantings, indicating a lack of efficiency of roguing for reducing disease development in old plantings. At large spatial scale (approximately 1 km), Moran indices (both global and local) revealed the existence of clusters characterized by contrasting disease incidences. This suggested that local environmental conditions were heterogeneous or there were spatial interactions among blocks. At finer spatial scale (approximately 200 m), O-ring statistics revealed positive correlation between distant infection sites across distances as great as 60 m. Although these observations indicate the role of short-distance dispersal in foci expansion, dispersal at greater distances (>20 m) appeared to also contribute to both initiation of new foci and disease progression at coarser spatial scales. Therefore, our results suggested the role of aerial dispersal in CWD progression.

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

USGS Publications Warehouse

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

2006-01-01

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

Up, Down, and All Around: Scale-Dependent Spatial Variation in Rocky-Shore Communities of Fildes Peninsula, King George Island, Antarctica

PubMed Central

Valdivia, Nelson; Díaz, María J.; Holtheuer, Jorge; Garrido, Ignacio; Huovinen, Pirjo; Gómez, Iván

2014-01-01

Understanding the variation of biodiversity along environmental gradients and multiple spatial scales is relevant for theoretical and management purposes. Hereby, we analysed the spatial variability in diversity and structure of intertidal and subtidal macrobenthic Antarctic communities along vertical environmental stress gradients and across multiple horizontal spatial scales. Since biotic interactions and local topographic features are likely major factors for coastal assemblages, we tested the hypothesis that fine-scale processes influence the effects of the vertical environmental stress gradients on the macrobenthic diversity and structure. We used nested sampling designs in the intertidal and subtidal habitats, including horizontal spatial scales ranging from few centimetres to 1000s of metres along the rocky shore of Fildes Peninsula, King George Island. In both intertidal and subtidal habitats, univariate and multivariate analyses showed a marked vertical zonation in taxon richness and community structure. These patterns depended on the horizontal spatial scale of observation, as all analyses showed a significant interaction between height (or depth) and the finer spatial scale analysed. Variance and pseudo-variance components supported our prediction for taxon richness, community structure, and the abundance of dominant species such as the filamentous green alga Urospora penicilliformis (intertidal), the herbivore Nacella concinna (intertidal), the large kelp-like Himantothallus grandifolius (subtidal), and the red crustose red alga Lithothamnion spp. (subtidal). We suggest that in coastal ecosystems strongly governed by physical factors, fine-scale processes (e.g. biotic interactions and refugia availability) are still relevant for the structuring and maintenance of the local communities. The spatial patterns found in this study serve as a necessary benchmark to understand the dynamics and adaptation of natural assemblages in response to observed and predicted environmental changes in Antarctica. PMID:24956114

Wavelet-based de-noising algorithm for images acquired with parallel magnetic resonance imaging (MRI).

PubMed

Delakis, Ioannis; Hammad, Omer; Kitney, Richard I

2007-07-07

Wavelet-based de-noising has been shown to improve image signal-to-noise ratio in magnetic resonance imaging (MRI) while maintaining spatial resolution. Wavelet-based de-noising techniques typically implemented in MRI require that noise displays uniform spatial distribution. However, images acquired with parallel MRI have spatially varying noise levels. In this work, a new algorithm for filtering images with parallel MRI is presented. The proposed algorithm extracts the edges from the original image and then generates a noise map from the wavelet coefficients at finer scales. The noise map is zeroed at locations where edges have been detected and directional analysis is also used to calculate noise in regions of low-contrast edges that may not have been detected. The new methodology was applied on phantom and brain images and compared with other applicable de-noising techniques. The performance of the proposed algorithm was shown to be comparable with other techniques in central areas of the images, where noise levels are high. In addition, finer details and edges were maintained in peripheral areas, where noise levels are low. The proposed methodology is fully automated and can be applied on final reconstructed images without requiring sensitivity profiles or noise matrices of the receiver coils, therefore making it suitable for implementation in a clinical MRI setting.

Pore-scale dynamics of salt transport and distribution in drying porous media

NASA Astrophysics Data System (ADS)

Shokri, Nima

2014-01-01

Understanding the physics of water evaporation from saline porous media is important in many natural and engineering applications such as durability of building materials and preservation of monuments, water quality, and mineral-fluid interactions. We applied synchrotron x-ray micro-tomography to investigate the pore-scale dynamics of dissolved salt distribution in a three dimensional drying saline porous media using a cylindrical plastic column (15 mm in height and 8 mm in diameter) packed with sand particles saturated with CaI2 solution (5% concentration by mass) with a spatial and temporal resolution of 12 μm and 30 min, respectively. Every time the drying sand column was set to be imaged, two different images were recorded using distinct synchrotron x-rays energies immediately above and below the K-edge value of Iodine. Taking the difference between pixel gray values enabled us to delineate the spatial and temporal distribution of CaI2 concentration at pore scale. Results indicate that during early stages of evaporation, air preferentially invades large pores at the surface while finer pores remain saturated and connected to the wet zone at bottom via capillary-induced liquid flow acting as evaporating spots. Consequently, the salt concentration increases preferentially in finer pores where evaporation occurs. Higher salt concentration was observed close to the evaporating surface indicating a convection-driven process. The obtained salt profiles were used to evaluate the numerical solution of the convection-diffusion equation (CDE). Results show that the macro-scale CDE could capture the overall trend of the measured salt profiles but fail to produce the exact slope of the profiles. Our results shed new insight on the physics of salt transport and its complex dynamics in drying porous media and establish synchrotron x-ray tomography as an effective tool to investigate the dynamics of salt transport in porous media at high spatial and temporal resolution.

Pore-scale dynamics of salt transport and distribution in drying porous media

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

Shokri, Nima, E-mail: nima.shokri@manchester.ac.uk

2014-01-15

Understanding the physics of water evaporation from saline porous media is important in many natural and engineering applications such as durability of building materials and preservation of monuments, water quality, and mineral-fluid interactions. We applied synchrotron x-ray micro-tomography to investigate the pore-scale dynamics of dissolved salt distribution in a three dimensional drying saline porous media using a cylindrical plastic column (15 mm in height and 8 mm in diameter) packed with sand particles saturated with CaI{sub 2} solution (5% concentration by mass) with a spatial and temporal resolution of 12 μm and 30 min, respectively. Every time the drying sandmore » column was set to be imaged, two different images were recorded using distinct synchrotron x-rays energies immediately above and below the K-edge value of Iodine. Taking the difference between pixel gray values enabled us to delineate the spatial and temporal distribution of CaI{sub 2} concentration at pore scale. Results indicate that during early stages of evaporation, air preferentially invades large pores at the surface while finer pores remain saturated and connected to the wet zone at bottom via capillary-induced liquid flow acting as evaporating spots. Consequently, the salt concentration increases preferentially in finer pores where evaporation occurs. Higher salt concentration was observed close to the evaporating surface indicating a convection-driven process. The obtained salt profiles were used to evaluate the numerical solution of the convection-diffusion equation (CDE). Results show that the macro-scale CDE could capture the overall trend of the measured salt profiles but fail to produce the exact slope of the profiles. Our results shed new insight on the physics of salt transport and its complex dynamics in drying porous media and establish synchrotron x-ray tomography as an effective tool to investigate the dynamics of salt transport in porous media at high spatial and temporal resolution.« less

Evaluation of MODIS Albedo Product (MCD43A) over Grassland, Agriculture and Forest Surface Types During Dormant and Snow-Covered Periods

NASA Technical Reports Server (NTRS)

Wang, Zhousen; Schaaf, Crystal B.; Strahler, Alan H.; Chopping, Mark J.; Roman, Miguel O.; Shuai, Yanmin; Woodcock, Curtis E.; Hollinger, David Y.; Fitzjarrald, David R.

2013-01-01

This study assesses the Moderate-resolution Imaging Spectroradiometer (MODIS) BRDF/albedo 8 day standard product and products from the daily Direct Broadcast BRDF/albedo algorithm, and shows that these products agree well with ground-based albedo measurements during the more difficult periods of vegetation dormancy and snow cover. Cropland, grassland, deciduous and coniferous forests are considered. Using an integrated validation strategy, analyses of the representativeness of the surface heterogeneity under both dormant and snow-covered situations are performed to decide whether direct comparisons between ground measurements and 500-m satellite observations can be made or whether finer spatial resolution airborne or spaceborne data are required to scale the results at each location. Landsat Enhanced Thematic Mapper Plus (ETM +) data are used to generate finer scale representations of albedo at each location to fully link ground data with satellite data. In general, results indicate the root mean square errors (RMSEs) are less than 0.030 over spatially representative sites of agriculture/grassland during the dormant periods and less than 0.050 during the snow-covered periods for MCD43A albedo products. For forest, the RMSEs are less than 0.020 during the dormant period and 0.025 during the snow-covered periods. However, a daily retrieval strategy is necessary to capture ephemeral snow events or rapidly changing situations such as the spring snow melt.

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.

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

NASA Technical Reports Server (NTRS)

Levin, Simon A.; Pacala, Stephen W.

1997-01-01

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

Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics

NASA Astrophysics Data System (ADS)

Xu, Y.; Wang, L.

2017-12-01

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

Prediction of Root Zone Soil Moisture using Remote Sensing Products and In-Situ Observation under Climate Change Scenario

NASA Astrophysics Data System (ADS)

Singh, G.; Panda, R. K.; Mohanty, B.

2015-12-01

Prediction of root zone soil moisture status at field level is vital for developing efficient agricultural water management schemes. In this study, root zone soil moisture was estimated across the Rana watershed in Eastern India, by assimilation of near-surface soil moisture estimate from SMOS satellite into a physically-based Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble Kalman filter (EnKF) technique coupled with SWAP model was used for assimilating the satellite soil moisture observation at different spatial scales. The universal triangle concept and artificial intelligence techniques were applied to disaggregate the SMOS satellite monitored near-surface soil moisture at a 40 km resolution to finer scale (1 km resolution), using higher spatial resolution of MODIS derived vegetation indices (NDVI) and land surface temperature (Ts). The disaggregated surface soil moisture were compared to ground-based measurements in diverse landscape using portable impedance probe and gravimetric samples. Simulated root zone soil moisture were compared with continuous soil moisture profile measurements at three monitoring stations. In addition, the impact of projected climate change on root zone soil moisture were also evaluated. The climate change projections of rainfall were analyzed for the Rana watershed from statistically downscaled Global Circulation Models (GCMs). The long-term root zone soil moisture dynamics were estimated by including a rainfall generator of likely scenarios. The predicted long term root zone soil moisture status at finer scale can help in developing efficient agricultural water management schemes to increase crop production, which lead to enhance the water use efficiency.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

Bayesian Hierarchical Modeling for Big Data Fusion in Soil Hydrology

NASA Astrophysics Data System (ADS)

Mohanty, B.; Kathuria, D.; Katzfuss, M.

2016-12-01

Soil moisture datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors on the other hand provide observations on a finer spatial scale (meter scale or less) but are sparsely available. Soil moisture is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables. Hydrologic processes usually occur at a scale of 1 km or less and therefore spatially ubiquitous and temporally periodic soil moisture products at this scale are required to aid local decision makers in agriculture, weather prediction and reservoir operations. Past literature has largely focused on downscaling RS soil moisture for a small extent of a field or a watershed and hence the applicability of such products has been limited. The present study employs a spatial Bayesian Hierarchical Model (BHM) to derive soil moisture products at a spatial scale of 1 km for the state of Oklahoma by fusing point scale Mesonet data and coarse scale RS data for soil moisture and its auxiliary covariates such as precipitation, topography, soil texture and vegetation. It is seen that the BHM model handles change of support problems easily while performing accurate uncertainty quantification arising from measurement errors and imperfect retrieval algorithms. The computational challenge arising due to the large number of measurements is tackled by utilizing basis function approaches and likelihood approximations. The BHM model can be considered as a complex Bayesian extension of traditional geostatistical prediction methods (such as Kriging) for large datasets in the presence of uncertainties.

Scales of snow depth variability in high elevation rangeland sagebrush

NASA Astrophysics Data System (ADS)

Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.

2017-09-01

In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

Downscaling of Remotely Sensed Land Surface Temperature with multi-sensor based products

NASA Astrophysics Data System (ADS)

Jeong, J.; Baik, J.; Choi, M.

2016-12-01

Remotely sensed satellite data provides a bird's eye view, which allows us to understand spatiotemporal behavior of hydrologic variables at global scale. Especially, geostationary satellite continuously observing specific regions is useful to monitor the fluctuations of hydrologic variables as well as meteorological factors. However, there are still problems regarding spatial resolution whether the fine scale land cover can be represented with the spatial resolution of the satellite sensor, especially in the area of complex topography. To solve these problems, many researchers have been trying to establish the relationship among various hydrological factors and combine images from multi-sensor to downscale land surface products. One of geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS), has Meteorological Imager (MI) and Geostationary Ocean Color Imager (GOCI). MI performing the meteorological mission produce Rainfall Intensity (RI), Land Surface Temperature (LST), and many others every 15 minutes. Even though it has high temporal resolution, low spatial resolution of MI data is treated as major research problem in many studies. This study suggests a methodology to downscale 4 km LST datasets derived from MI in finer resolution (500m) by using GOCI datasets in Northeast Asia. Normalized Difference Vegetation Index (NDVI) recognized as variable which has significant relationship with LST are chosen to estimate LST in finer resolution. Each pixels of NDVI and LST are separated according to land cover provided from MODerate resolution Imaging Spectroradiometer (MODIS) to achieve more accurate relationship. Downscaled LST are compared with LST observed from Automated Synoptic Observing System (ASOS) for assessing its accuracy. The downscaled LST results of this study, coupled with advantage of geostationary satellite, can be applied to observe hydrologic process efficiently.

Soil Moisture fusion across scales using a multiscale nonstationary Spatial Hierarchical Model

NASA Astrophysics Data System (ADS)

Kathuria, D.; Mohanty, B.; Katzfuss, M.

2017-12-01

Soil moisture (SM) datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors, on the other hand, provide observations on a finer spatial scale (meter scale or less) but are sparsely available. SM is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables and these interactions change dynamically with footprint scales. Past literature has largely focused on the scale specific effect of these covariates on soil moisture. The present study proposes a robust Multiscale-Nonstationary Spatial Hierarchical Model (MN-SHM) which can assimilate SM from point to RS footprints. The spatial structure of SM across footprints is modeled by a class of scalable covariance functions whose nonstationary depends on atmospheric forcings (such as precipitation) and surface physical controls (such as topography, soil-texture and vegetation). The proposed model is applied to fuse point and airborne ( 1.5 km) SM data obtained during the SMAPVEX12 campaign in the Red River watershed in Southern Manitoba, Canada with SMOS ( 30km) data. It is observed that precipitation, soil-texture and vegetation are the dominant factors which affect the SM distribution across various footprint scales (750 m, 1.5 km, 3 km, 9 km,15 km and 30 km). We conclude that MN-SHM handles the change of support problems easily while retaining reasonable predictive accuracy across multiple spatial resolutions in the presence of surface heterogeneity. The MN-SHM can be considered as a complex non-stationary extension of traditional geostatistical prediction methods (such as Kriging) for fusing multi-platform multi-scale datasets.

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.

RACORO Extended-Term Aircraft Observations of Boundary-Layer Clouds

NASA Technical Reports Server (NTRS)

Vogelmann, Andrew M.; McFarquhar, Greg M.; Ogren, John A.; Turner, David D.; Comstock, Jennifer M.; Feingold, Graham; Long, Charles N.; Jonsson, Haflidi H.; Bucholtz, Anthony; Collins, Don R.;

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Burke, W.; Tague, C.

2017-12-01

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

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

USGS Publications Warehouse

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

2013-01-01

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

Local topography shapes fine-scale spatial genetic structure in the Arkansas Valley evening primrose, Oenothera harringtonii (Onagraceae).

PubMed

Rhodes, Matthew K; Fant, Jeremie B; Skogen, Krissa A

2014-01-01

Identifying factors that shape the spatial distribution of genetic variation is crucial to understanding many population- and landscape-level processes. In this study, we explore fine-scale spatial genetic structure in Oenothera harringtonii (Onagraceae), an insect-pollinated, gravity-dispersed herb endemic to the grasslands of south-central and southeastern Colorado, USA. We genotyped 315 individuals with 11 microsatellite markers and utilized a combination of spatial autocorrelation analyses and landscape genetic models to relate life history traits and landscape features to dispersal processes. Spatial genetic structure was consistent with theoretical expectations of isolation by distance, but this pattern was weak (Sp = 0.00374). Anisotropic analyses indicated that spatial genetic structure was markedly directional, in this case consistent with increased dispersal along prominent slopes. Landscape genetic models subsequently confirmed that spatial genetic variation was significantly influenced by local topographic heterogeneity, specifically that geographic distance, elevation and aspect were important predictors of spatial genetic structure. Among these variables, geographic distance was ~68% more important than elevation in describing spatial genetic variation, and elevation was ~42% more important than aspect after removing the effect of geographic distance. From these results, we infer a mechanism of hydrochorous seed dispersal along major drainages aided by seasonal monsoon rains. Our findings suggest that landscape features may shape microevolutionary processes at much finer spatial scales than typically considered, and stress the importance of considering how particular dispersal vectors are influenced by their environmental context. © The American Genetic Association 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A new global anthropogenic heat estimation based on high-resolution nighttime light data

PubMed Central

Yang, Wangming; Luan, Yibo; Liu, Xiaolei; Yu, Xiaoyong; Miao, Lijuan; Cui, Xuefeng

2017-01-01

Consumption of fossil fuel resources leads to global warming and climate change. Apart from the negative impact of greenhouse gases on the climate, the increasing emission of anthropogenic heat from energy consumption also brings significant impacts on urban ecosystems and the surface energy balance. The objective of this work is to develop a new method of estimating the global anthropogenic heat budget and validate it on the global scale with a high precision and resolution dataset. A statistical algorithm was applied to estimate the annual mean anthropogenic heat (AH-DMSP) from 1992 to 2010 at 1×1 km2 spatial resolution for the entire planet. AH-DMSP was validated for both provincial and city scales, and results indicate that our dataset performs well at both scales. Compared with other global anthropogenic heat datasets, the AH-DMSP has a higher precision and finer spatial distribution. Although there are some limitations, the AH-DMSP could provide reliable, multi-scale anthropogenic heat information, which could be used for further research on regional or global climate change and urban ecosystems. PMID:28829436

Pore-scale dynamics of salt transport in drying porous media

NASA Astrophysics Data System (ADS)

Shokri, N.

2013-12-01

Understanding the physics of water evaporation from saline porous media is important in many hydrological processes such as land-atmosphere interactions, water management, vegetation, soil salinity, and mineral-fluid interactions. We applied synchrotron x-ray micro-tomography to investigate the pore-scale dynamics of dissolved salt distribution in a three dimensional drying saline porous media using a cylindrical plastic column (15 mm in height and 8 mm in diameter) packed with sand particles saturated with CaI2 solution (5% concentration by mass) with a spatial and temporal resolution of 12 microns and 30 min, respectively. Every time the drying sand column was set to be imaged, two different images were recorded using distinct synchrotron X-rays energies immediately above (33.2690 keV) and below (33.0690 keV) the K-edge value of Iodine (33.1694 keV). Taking the difference between pixel gray values enabled us to delineate the spatial and temporal distribution of CaI2 concentration at pore scale. The experiment was continued for 12 hours. Results indicate that during early stages of evaporation, air preferentially invades large pores at the surface while finer pores remain saturated and connected to the wet zone at bottom via capillary-induced liquid flow. Consequently, the salt concentration increases preferentially in finer pores where evaporation occurs. The Peclet number (describing the competition between convection and diffusion) was greater than one in our experiment resulting in higher salt concentrations closer to the evaporation surface indicating a convection-driven process. The obtained salt profiles were used to evaluate the numerical solution of the convection-diffusion equation (CDE). Results show that the macro-scale CDE could capture the overall trend of the measured salt profiles but fail to produce the exact slope of the profiles. Our results shed new insight on the physics of salt transport and its complex dynamics in drying porous media and establish synchrotron x-ray micro-tomography as an effective tool to investigate the dynamics of dissolved salt transport in porous media with high spatial and temporal resolutions.

Multi Scale Modeling of Continuous Aramid Fiber Reinforced Polymer Matrix Composites Used in Ballistic Protection Applications

DTIC Science & Technology

2014-11-16

related to identification of the type and the extent of data generated at a finer length scale to the adjacent coarser length scale, as well as seamless ...data generated at a finer length scale to the adjacent coarser length scale, as well as seamless integration of different length scales into a unified...composite laminate consisting of 32 laminae and impacted (at a 0° obliquity angle and an incident velocity of 500 m/s) by a 0.30 caliber steel

Species distribution model transferability and model grain size - finer may not always be better.

PubMed

Manzoor, Syed Amir; Griffiths, Geoffrey; Lukac, Martin

2018-05-08

Species distribution models have been used to predict the distribution of invasive species for conservation planning. Understanding spatial transferability of niche predictions is critical to promote species-habitat conservation and forecasting areas vulnerable to invasion. Grain size of predictor variables is an important factor affecting the accuracy and transferability of species distribution models. Choice of grain size is often dependent on the type of predictor variables used and the selection of predictors sometimes rely on data availability. This study employed the MAXENT species distribution model to investigate the effect of the grain size on model transferability for an invasive plant species. We modelled the distribution of Rhododendron ponticum in Wales, U.K. and tested model performance and transferability by varying grain size (50 m, 300 m, and 1 km). MAXENT-based models are sensitive to grain size and selection of variables. We found that over-reliance on the commonly used bioclimatic variables may lead to less accurate models as it often compromises the finer grain size of biophysical variables which may be more important determinants of species distribution at small spatial scales. Model accuracy is likely to increase with decreasing grain size. However, successful model transferability may require optimization of model grain size.

Potential accuracy of translation estimation between radar and optical images

NASA Astrophysics Data System (ADS)

Uss, M.; Vozel, B.; Lukin, V.; Chehdi, K.

2015-10-01

This paper investigates the potential accuracy achievable for optical to radar image registration by area-based approach. The analysis is carried out mainly based on the Cramér-Rao Lower Bound (CRLB) on translation estimation accuracy previously proposed by the authors and called CRLBfBm. This bound is now modified to take into account radar image speckle noise properties: spatial correlation and signal-dependency. The newly derived theoretical bound is fed with noise and texture parameters estimated for the co-registered pair of optical Landsat 8 and radar SIR-C images. It is found that difficulty of optical to radar image registration stems more from speckle noise influence than from dissimilarity of the considered kinds of images. At finer scales (and higher speckle noise level), probability of finding control fragments (CF) suitable for registration is low (1% or less) but overall number of such fragments is high thanks to image size. Conversely, at the coarse scale, where speckle noise level is reduced, probability of finding CFs suitable for registration can be as high as 40%, but overall number of such CFs is lower. Thus, the study confirms and supports area-based multiresolution approach for optical to radar registration where coarse scales are used for fast registration "lock" and finer scales for reaching higher registration accuracy. The CRLBfBm is found inaccurate for the main scale due to intensive speckle noise influence. For other scales, the validity of the CRLBfBm bound is confirmed by calculating statistical efficiency of area-based registration method based on normalized correlation coefficient (NCC) measure that takes high values of about 25%.

Cortical geometry as a determinant of brain activity eigenmodes: Neural field analysis

NASA Astrophysics Data System (ADS)

Gabay, Natasha C.; Robinson, P. A.

2017-09-01

Perturbation analysis of neural field theory is used to derive eigenmodes of neural activity on a cortical hemisphere, which have previously been calculated numerically and found to be close analogs of spherical harmonics, despite heavy cortical folding. The present perturbation method treats cortical folding as a first-order perturbation from a spherical geometry. The first nine spatial eigenmodes on a population-averaged cortical hemisphere are derived and compared with previous numerical solutions. These eigenmodes contribute most to brain activity patterns such as those seen in electroencephalography and functional magnetic resonance imaging. The eigenvalues of these eigenmodes are found to agree with the previous numerical solutions to within their uncertainties. Also in agreement with the previous numerics, all eigenmodes are found to closely resemble spherical harmonics. The first seven eigenmodes exhibit a one-to-one correspondence with their numerical counterparts, with overlaps that are close to unity. The next two eigenmodes overlap the corresponding pair of numerical eigenmodes, having been rotated within the subspace spanned by that pair, likely due to second-order effects. The spatial orientations of the eigenmodes are found to be fixed by gross cortical shape rather than finer-scale cortical properties, which is consistent with the observed intersubject consistency of functional connectivity patterns. However, the eigenvalues depend more sensitively on finer-scale cortical structure, implying that the eigenfrequencies and consequent dynamical properties of functional connectivity depend more strongly on details of individual cortical folding. Overall, these results imply that well-established tools from perturbation theory and spherical harmonic analysis can be used to calculate the main properties and dynamics of low-order brain eigenmodes.

Identifying the scale-dependent motifs in atmospheric surface layer by ordinal pattern analysis

NASA Astrophysics Data System (ADS)

Li, Qinglei; Fu, Zuntao

2018-07-01

Ramp-like structures in various atmospheric surface layer time series have been long studied, but the presence of motifs with the finer scale embedded within larger scale ramp-like structures has largely been overlooked in the reported literature. Here a novel, objective and well-adapted methodology, the ordinal pattern analysis, is adopted to study the finer-scaled motifs in atmospheric boundary-layer (ABL) time series. The studies show that the motifs represented by different ordinal patterns take clustering properties and 6 dominated motifs out of the whole 24 motifs account for about 45% of the time series under particular scales, which indicates the higher contribution of motifs with the finer scale to the series. Further studies indicate that motif statistics are similar for both stable conditions and unstable conditions at larger scales, but large discrepancies are found at smaller scales, and the frequencies of motifs "1234" and/or "4321" are a bit higher under stable conditions than unstable conditions. Under stable conditions, there are great changes for the occurrence frequencies of motifs "1234" and "4321", where the occurrence frequencies of motif "1234" decrease from nearly 24% to 4.5% with the scale factor increasing, and the occurrence frequencies of motif "4321" change nonlinearly with the scale increasing. These great differences of dominated motifs change with scale can be taken as an indicator to quantify the flow structure changes under different stability conditions, and motif entropy can be defined just by only 6 dominated motifs to quantify this time-scale independent property of the motifs. All these results suggest that the defined scale of motifs with the finer scale should be carefully taken into consideration in the interpretation of turbulence coherent structures.

Influence of permeability on nanoscale zero-valent iron particle transport in saturated homogeneous and heterogeneous porous media.

PubMed

Strutz, Tessa J; Hornbruch, Götz; Dahmke, Andreas; Köber, Ralf

2016-09-01

Nanoscale zero-valent iron (NZVI) particles can be used for in situ groundwater remediation. The spatial particle distribution plays a very important role in successful and efficient remediation, especially in heterogeneous systems. Initial sand permeability (k 0) influences on spatial particle distributions were investigated and quantified in homogeneous and heterogeneous systems within the presented study. Four homogeneously filled column experiments and a heterogeneously filled tank experiment, using different median sand grain diameters (d 50), were performed to determine if NZVI particles were transported into finer sand where contaminants could be trapped. More NZVI particle retention, less particle transport, and faster decrease in k were observed in the column studies using finer sands than in those using coarser sands, reflecting a function of k 0. In heterogeneous media, NZVI particles were initially transported and deposited in coarse sand areas. Increasing the retained NZVI mass (decreasing k in particle deposition areas) caused NZVI particles to also be transported into finer sand areas, forming an area with a relatively homogeneous particle distribution and converged k values despite the different grain sizes present. The deposited-particle surface area contribution to the increasing of the matrix surface area (θ) was one to two orders of magnitude higher for finer than coarser sand. The dependency of θ on d 50 presumably affects simulated k changes and NZVI distributions in numerical simulations of NZVI injections into heterogeneous aquifers. The results implied that NZVI can in principle also penetrate finer layers.

A review of potential image fusion methods for remote sensing-based irrigation management: Part II

USDA-ARS?s Scientific Manuscript database

Satellite-based sensors provide data at either greater spectral and coarser spatial resolutions, or lower spectral and finer spatial resolutions due to complementary spectral and spatial characteristics of optical sensor systems. In order to overcome this limitation, image fusion has been suggested ...

Assessment of village-wise groundwater draft for irrigation: a field-based study in hard-rock aquifers of central India

NASA Astrophysics Data System (ADS)

Ray, R. K.; Syed, T. H.; Saha, Dipankar; Sarkar, B. C.; Patre, A. K.

2017-12-01

Extracted groundwater, 90% of which is used for irrigated agriculture, is central to the socio-economic development of India. A lack of regulation or implementation of regulations, alongside unrecorded extraction, often leads to over exploitation of large-scale common-pool resources like groundwater. Inevitably, management of groundwater extraction (draft) for irrigation is critical for sustainability of aquifers and the society at large. However, existing assessments of groundwater draft, which are mostly available at large spatial scales, are inadequate for managing groundwater resources that are primarily exploited by stakeholders at much finer scales. This study presents an estimate, projection and analysis of fine-scale groundwater draft in the Seonath-Kharun interfluve of central India. Using field surveys of instantaneous discharge from irrigation wells and boreholes, annual groundwater draft for irrigation in this area is estimated to be 212 × 106 m3, most of which (89%) is withdrawn during non-monsoon season. However, the density of wells/boreholes, and consequent extraction of groundwater, is controlled by the existing hydrogeological conditions. Based on trends in the number of abstraction structures (1982-2011), groundwater draft for the year 2020 is projected to be approximately 307 × 106 m3; hence, groundwater draft for irrigation in the study area is predicted to increase by ˜44% within a span of 8 years. Central to the work presented here is the approach for estimation and prediction of groundwater draft at finer scales, which can be extended to critical groundwater zones of the country.

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

Tang, Q; Xie, S

This report describes the Atmospheric Radiation Measurement (ARM) Best Estimate (ARMBE) 2-dimensional (2D) gridded surface data (ARMBE2DGRID) value-added product. Spatial variability is critically important to many scientific studies, especially those that involve processes of great spatial variations at high temporal frequency (e.g., precipitation, clouds, radiation, etc.). High-density ARM sites deployed at the Southern Great Plains (SGP) allow us to observe the spatial patterns of variables of scientific interests. The upcoming megasite at SGP with its enhanced spatial density will facilitate the studies at even finer scales. Currently, however, data are reported only at individual site locations at different time resolutionsmore » for different datastreams. It is difficult for users to locate all the data they need and requires extra effort to synchronize the data. To address these problems, the ARMBE2DGRID value-added product merges key surface measurements at the ARM SGP sites and interpolates the data to a regular 2D grid to facilitate the data application.« less

Monthly estimates of carbon dioxide emissions from fossil-fuel consumption in Brazil during the late 1990s and early 2000s

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

Losey, London M; Andres, Robert Joseph; Marland, Gregg

2006-12-01

Detailed understanding of global carbon cycling requires estimates of CO2 emissions on temporal and spatial scales finer than annual and country. This is the first attempt to derive such estimates for a large, developing, Southern Hemisphere country. Though data on energy use are not complete in terms of time and geography, there are enough data available on the sale or consumption of fuels in Brazil to reasonably approximate the temporal and spatial patterns of fuel use and CO2 emissions. Given the available data, a strong annual cycle in emissions from Brazil is not apparent. CO2 emissions are unevenly distributed withinmore » Brazil as the population density and level of development both vary widely.« less

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Semantic classification of urban buildings combining VHR image and GIS data: An improved random forest approach

NASA Astrophysics Data System (ADS)

Du, Shihong; Zhang, Fangli; Zhang, Xiuyuan

2015-07-01

While most existing studies have focused on extracting geometric information on buildings, only a few have concentrated on semantic information. The lack of semantic information cannot satisfy many demands on resolving environmental and social issues. This study presents an approach to semantically classify buildings into much finer categories than those of existing studies by learning random forest (RF) classifier from a large number of imbalanced samples with high-dimensional features. First, a two-level segmentation mechanism combining GIS and VHR image produces single image objects at a large scale and intra-object components at a small scale. Second, a semi-supervised method chooses a large number of unbiased samples by considering the spatial proximity and intra-cluster similarity of buildings. Third, two important improvements in RF classifier are made: a voting-distribution ranked rule for reducing the influences of imbalanced samples on classification accuracy and a feature importance measurement for evaluating each feature's contribution to the recognition of each category. Fourth, the semantic classification of urban buildings is practically conducted in Beijing city, and the results demonstrate that the proposed approach is effective and accurate. The seven categories used in the study are finer than those in existing work and more helpful to studying many environmental and social problems.

Enhanced-Resolution Satellite Microwave Brightness Temperature Records for Mapping Boreal-Arctic Landscape Freeze-Thaw Heterogeneity

NASA Astrophysics Data System (ADS)

Kim, Y.; Du, J.; Kimball, J. S.

2017-12-01

The landscape freeze-thaw (FT) status derived from satellite microwave remote sensing is closely linked to vegetation phenology and productivity, surface energy exchange, evapotranspiration, snow/ice melt dynamics, and trace gas fluxes over land areas affected by seasonally frozen temperatures. A long-term global satellite microwave Earth System Data Record of daily landscape freeze-thaw status (FT-ESDR) was developed using similar calibrated 37GHz, vertically-polarized (V-pol) brightness temperatures (Tb) from SMMR, SSM/I, and SSMIS sensors. The FT-ESDR shows mean annual spatial classification accuracies of 90.3 and 84.3 % for PM and AM overpass retrievals relative surface air temperature (SAT) measurement based FT estimates from global weather stations. However, the coarse FT-ESDR gridding (25-km) is insufficient to distinguish finer scale FT heterogeneity. In this study, we tested alternative finer scale FT estimates derived from two enhanced polar-grid (3.125-km and 6-km resolution), 36.5 GHz V-pol Tb records derived from calibrated AMSR-E and AMSR2 sensor observations. The daily FT estimates are derived using a modified seasonal threshold algorithm that classifies daily Tb variations in relation to grid cell-wise FT thresholds calibrated using ERA-Interim reanalysis based SAT, downscaled using a digital terrain map and estimated temperature lapse rates. The resulting polar-grid FT records for a selected study year (2004) show mean annual spatial classification accuracies of 90.1% (84.2%) and 93.1% (85.8%) for respective PM (AM) 3.125km and 6-km Tb retrievals relative to in situ SAT measurement based FT estimates from regional weather stations. Areas with enhanced FT accuracy include water-land boundaries and mountainous terrain. Differences in FT patterns and relative accuracy obtained from the enhanced grid Tb records were attributed to several factors, including different noise contributions from underlying Tb processing and spatial mismatches between Tb retrievals and SAT calibrated FT thresholds.

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

PubMed

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

2016-08-09

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

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

PubMed Central

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

2016-01-01

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

The Australian National Airborne Field Experiment 2005: Soil Moisture Remote Sensing at 60 Meter Resolution and Up

NASA Technical Reports Server (NTRS)

Kim, E. J.; Walker, J. P.; Panciera, R.; Kalma, J. D.

2006-01-01

Spatially-distributed soil moisture observations have applications spanning a wide range of spatial resolutions from the very local needs of individual farmers to the progressively larger areas of interest to weather forecasters, water resource managers, and global climate modelers. To date, the most promising approach for space-based remote sensing of soil moisture makes use of passive microwave emission radiometers at L-band frequencies (1-2 GHz). Several soil moisture-sensing satellites have been proposed in recent years, with the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission scheduled to be launched first in a couple years. While such a microwave-based approach has the advantage of essentially allweather operation, satellite size limits spatial resolution to 10's of km. Whether used at this native resolution or in conjunction with some type of downscaling technique to generate soil moisture estimates on a finer-scale grid, the effects of subpixel spatial variability play a critical role. The soil moisture variability is typically affected by factors such as vegetation, topography, surface roughness, and soil texture. Understanding and these factors is the key to achieving accurate soil moisture retrievals at any scale. Indeed, the ability to compensate for these factors ultimately limits the achievable spatial resolution and/or accuracy of the retrieval. Over the last 20 years, a series of airborne campaigns in the USA have supported the development of algorithms for spaceborne soil moisture retrieval. The most important observations involved imagery from passive microwave radiometers. The early campaigns proved that the retrieval worked for larger and larger footprints, up to satellite-scale footprints. These provided the solid basis for proposing the satellite missions. More recent campaigns have explored other aspects such as retrieval performance through greater amounts of vegetation. All of these campaigns featured extensive ground truth collection over a range of grid spacings, to provide a basis for examining the effects of subpixel variability. However, the native footprint size of the airborne L-band radiometers was always a few hundred meters. During the recently completed (November, 2005) National Airborne Field Experiment (NAFE) campaign in Australia, a compact L-band radiometer was deployed on a small aircraft. This new combination permitted routine observations at native resolutions as high as 60 meters, substantially finer than in previous airborne soil moisture campaigns, as well as satellite footprint areal coverage. The radiometer, the Polarimetric L-band Microwave Radiometer (PLMR) performed extremely well and operations included extensive calibration-related observations. Thus, along with the extensive fine-scale ground truth, the NAFE dataset includes all the ingredients for the first scaling studies involving very-high-native resolution soil moisture observations and the effects of vegetation, roughness, etc. A brief overview of the NAFE will be presented, then examples of the airborne observations with resolutions from 60 m to 1 km will be shown, and early results from scaling studies will be discussed.

Validation and application of MODIS-derived clean snow albedo and dust radiative forcing

NASA Astrophysics Data System (ADS)

Rittger, K. E.; Bryant, A. C.; Seidel, F. C.; Bair, E. H.; Skiles, M.; Goodale, C. E.; Ramirez, P.; Mattmann, C. A.; Dozier, J.; Painter, T.

2012-12-01

Snow albedo is an important control on snowmelt. Though albedo evolution of aging snow can be roughly modeled from grain growth, dust and other light absorbing impurities are extrinsic and therefore must be measured. Estimates of clean snow albedo and surface radiative forcing from impurities, which can be inferred from MODIS 500 m surface reflectance products, can provide this driving data for snowmelt models. Here we use MODSCAG (MODIS snow covered area and grain size) to estimate the clean snow albedo and MODDRFS (MODIS dust radiative forcing of snow) to estimate the additional absorbed solar radiation from dust and black carbon. With its finer spatial (20 m) and spectral (10 nm) resolutions, AVIRIS provides a way to estimate the accuracy of MODIS products and understand variability of snow albedo at a finer scale that we explore though a range of topography. The AVIRIS database includes images from late in the accumulation season through the melt season when we are most interested in changes in snow albedo. In addition to the spatial validation, we employ the best estimate of albedo from MODIS in an energy balance reconstruction model to estimate the maximum snow water equivalent. MODDRFS calculates radiative forcing only in pixels that are completely snow-covered, so we spatially interpolate the product to estimate the forcing in all pixels where MODSCAG has given us estimates of clean snow albedo. Comparisons with snow pillows and courses show better agreement when the radiative forcing from absorbing impurities is included in the energy balance reconstruction.

What it takes to invade grassland ecosystems: traits, introduction history and filtering processes

PubMed Central

Carboni, Marta; Münkemüller, Tamara; Lavergne, Sébastien; Choler, Philippe; Borgy, Benjamin; Violle, Cyrille; Essl, Franz; Roquet, Cristina; Munoz, François; Consortium, DivGrass; Thuiller, Wilfried

2016-01-01

Whether the success of alien species can be explained by their functional or phylogenetic characteristics remains unresolved because of data limitations, scale issues and weak quantifications of success. Using permanent grasslands across France (50,000 vegetation-plots, 2000 species, 130 aliens) and building on the Rabinowitz’ classification to quantify spread, we showed that phylogenetic and functional similarities to natives were the most important correlates of invasion success compared to intrinsic functional characteristics and introduction history. Results contrasted between spatial scales and components of invasion success. Widespread and common aliens were similar to co-occurring natives at coarse scales (indicating environmental filtering), but dissimilar at finer scales (indicating local competition). In contrast, regionally widespread but locally rare aliens showed patterns of competitive exclusion already at coarse scale. Quantifying trait differences between aliens and natives and distinguishing the components of invasion success improved our ability to understand and potentially predict alien spread at multiple scales. PMID:26689431

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

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

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

2013-04-28

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

A novel multiscale topo-morphometric approach for separating arteries and veins via pulmonary CT imaging

NASA Astrophysics Data System (ADS)

Saha, Punam K.; Gao, Zhiyun; Alford, Sara; Sonka, Milan; Hoffman, Eric

2009-02-01

Distinguishing arterial and venous trees in pulmonary multiple-detector X-ray computed tomography (MDCT) images (contrast-enhanced or unenhanced) is a critical first step in the quantification of vascular geometry for purposes of determining, for instance, pulmonary hypertension, using vascular dimensions as a comparator for assessment of airway size, detection of pulmonary emboli and more. Here, a novel method is reported for separating arteries and veins in MDCT pulmonary images. Arteries and veins are modeled as two iso-intensity objects closely entwined with each other at different locations at various scales. The method starts with two sets of seeds -- one for arteries and another for veins. Initialized with seeds, arteries and veins grow iteratively while maintaining their spatial separation and eventually forming two disjoint objects at convergence. The method combines fuzzy distance transform, a morphologic feature, with a topologic connectivity property to iteratively separate finer and finer details starting at a large scale and progressing towards smaller scales. The method has been validated in mathematically generated tubular objects with different levels of fuzziness, scale and noise. Also, it has been successfully applied to clinical CT pulmonary data. The accuracy of the method has been quantitatively evaluated by comparing its results with manual outlining. For arteries, the method has yielded correctness of 81.7% at the cost of 6.7% false positives and 11.6% false negatives. Our method is very promising for automated separation of arteries and veins in MDCT pulmonary images even when there is no mark of intensity variation at conjoining locations.

Post-Disturbance Stability of Fish Assemblages Measured at Coarse Taxonomic Resolution Masks Change at Finer Scales.

PubMed

Ceccarelli, Daniela M; Emslie, Michael J; Richards, Zoe T

2016-01-01

Quantifying changes to coral reef fish assemblages in the wake of cyclonic disturbances is challenging due to spatial variability of damage inherent in such events. Often, fish abundance appears stable at one spatial scale (e.g. reef-wide), but exhibits substantial change at finer scales (e.g. site-specific decline or increase). Taxonomic resolution also plays a role; overall stability at coarse taxonomic levels (e.g. family) may mask species-level turnover. Here we document changes to reef fish communities after severe Tropical Cyclone Ita crossed Lizard Island, Great Barrier Reef. Coral and reef fish surveys were conducted concurrently before and after the cyclone at four levels of exposure to the prevailing weather. Coral cover declined across all exposures except sheltered sites, with the largest decline at exposed sites. There was no significant overall reduction in the total density, biomass and species richness of reef fishes between 2011 and 2015, but individual fish taxa (families and species) changed in complex and unpredictable ways. For example, more families increased in density and biomass than decreased following Cyclone Ita, particularly at exposed sites whilst more fish families declined at lagoon sites even though coral cover did not decline. All sites lost biomass of several damselfish species, and at most sites there was an increase in macroinvertivores and grazers. Overall, these results suggest that the degree of change measured at coarse taxonomic levels masked high species-level turnover, although other potential explanations include that there was no impact of the storm, fish assemblages were impacted but underwent rapid recovery or that there is a time lag before the full impacts become apparent. This study confirms that in high-complexity, high diversity ecosystems such as coral reefs, species level analyses are essential to adequately capture the consequences of disturbance events.

Post-Disturbance Stability of Fish Assemblages Measured at Coarse Taxonomic Resolution Masks Change at Finer Scales

PubMed Central

Ceccarelli, Daniela M.

2016-01-01

Quantifying changes to coral reef fish assemblages in the wake of cyclonic disturbances is challenging due to spatial variability of damage inherent in such events. Often, fish abundance appears stable at one spatial scale (e.g. reef-wide), but exhibits substantial change at finer scales (e.g. site-specific decline or increase). Taxonomic resolution also plays a role; overall stability at coarse taxonomic levels (e.g. family) may mask species-level turnover. Here we document changes to reef fish communities after severe Tropical Cyclone Ita crossed Lizard Island, Great Barrier Reef. Coral and reef fish surveys were conducted concurrently before and after the cyclone at four levels of exposure to the prevailing weather. Coral cover declined across all exposures except sheltered sites, with the largest decline at exposed sites. There was no significant overall reduction in the total density, biomass and species richness of reef fishes between 2011 and 2015, but individual fish taxa (families and species) changed in complex and unpredictable ways. For example, more families increased in density and biomass than decreased following Cyclone Ita, particularly at exposed sites whilst more fish families declined at lagoon sites even though coral cover did not decline. All sites lost biomass of several damselfish species, and at most sites there was an increase in macroinvertivores and grazers. Overall, these results suggest that the degree of change measured at coarse taxonomic levels masked high species-level turnover, although other potential explanations include that there was no impact of the storm, fish assemblages were impacted but underwent rapid recovery or that there is a time lag before the full impacts become apparent. This study confirms that in high-complexity, high diversity ecosystems such as coral reefs, species level analyses are essential to adequately capture the consequences of disturbance events. PMID:27285160

Impact of temporal upscaling and chemical transport model horizontal resolution on reducing ozone exposure misclassification

NASA Astrophysics Data System (ADS)

Xu, Yadong; Serre, Marc L.; Reyes, Jeanette M.; Vizuete, William

2017-10-01

We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error.

Roles of Spatial Scale and Rarity on the Relationship between Butterfly Species Richness and Human Density in South Africa

PubMed Central

Mecenero, Silvia; Altwegg, Res; Colville, Jonathan F.; Beale, Colin M.

2015-01-01

Wildlife and humans tend to prefer the same productive environments, yet high human densities often lead to reduced biodiversity. Species richness is often positively correlated with human population density at broad scales, but this correlation could also be caused by unequal sampling effort leading to higher species tallies in areas of dense human activity. We examined the relationships between butterfly species richness and human population density at five spatial resolutions ranging from 2' to 60' across South Africa. We used atlas-type data and spatial interpolation techniques aimed at reducing the effect of unequal spatial sampling. Our results confirm the general positive correlation between total species richness and human population density. Contrary to our expectations, the strength of this positive correlation did not weaken at finer spatial resolutions. The patterns observed using total species richness were driven mostly by common species. The richness of threatened and restricted range species was not correlated to human population density. None of the correlations we examined were particularly strong, with much unexplained variance remaining, suggesting that the overlap between butterflies and humans is not strong compared to other factors not accounted for in our analyses. Special consideration needs to be made regarding conservation goals and variables used when investigating the overlap between species and humans for biodiversity conservation. PMID:25915899

Roles of Spatial Scale and Rarity on the Relationship between Butterfly Species Richness and Human Density in South Africa.

PubMed

Mecenero, Silvia; Altwegg, Res; Colville, Jonathan F; Beale, Colin M

2015-01-01

Wildlife and humans tend to prefer the same productive environments, yet high human densities often lead to reduced biodiversity. Species richness is often positively correlated with human population density at broad scales, but this correlation could also be caused by unequal sampling effort leading to higher species tallies in areas of dense human activity. We examined the relationships between butterfly species richness and human population density at five spatial resolutions ranging from 2' to 60' across South Africa. We used atlas-type data and spatial interpolation techniques aimed at reducing the effect of unequal spatial sampling. Our results confirm the general positive correlation between total species richness and human population density. Contrary to our expectations, the strength of this positive correlation did not weaken at finer spatial resolutions. The patterns observed using total species richness were driven mostly by common species. The richness of threatened and restricted range species was not correlated to human population density. None of the correlations we examined were particularly strong, with much unexplained variance remaining, suggesting that the overlap between butterflies and humans is not strong compared to other factors not accounted for in our analyses. Special consideration needs to be made regarding conservation goals and variables used when investigating the overlap between species and humans for biodiversity conservation.

How Much Can Remotely-Sensed Natural Resource Inventories Benefit from Finer Spatial Resolutions?

NASA Astrophysics Data System (ADS)

Hou, Z.; Xu, Q.; McRoberts, R. E.; Ståhl, G.; Greenberg, J. A.

2017-12-01

For remote sensing facilitated natural resource inventories, the effects of spatial resolution in the form of pixel size and the effects of subpixel information on estimates of population parameters were evaluated by comparing results obtained using Landsat 8 and RapidEye auxiliary imagery. The study area was in Burkina Faso, and the variable of interest was the stem volume (m3/ha) convertible to the woodland aboveground biomass. A sample consisting of 160 field plots was selected and measured from the population following a two-stage sampling design. Models were fit using weighted least squares; the population mean, mu, and the variance of the estimator of the population mean, Var(mu.hat), were estimated in two inferential frameworks, model-based and model-assisted, and compared; for each framework, Var(mu.hat) was estimated both analytically and empirically. Empirical variances were estimated with bootstrapping that for resampling takes clustering effects into account. The primary results were twofold. First, for the effects of spatial resolution and subpixel information, four conclusions are relevant: (1) finer spatial resolution imagery indeed contributes to greater precision for estimators of population parameter, but this increase is slight at a maximum rate of 20% considering that RapidEye data are 36 times finer resolution than Landsat 8 data; (2) subpixel information on texture is marginally beneficial when it comes to making inference for population of large areas; (3) cost-effectiveness is more favorable for the free of charge Landsat 8 imagery than RapidEye imagery; and (4) for a given plot size, candidate remote sensing auxiliary datasets are more cost-effective when their spatial resolutions are similar to the plot size than with much finer alternatives. Second, for the comparison between estimators, three conclusions are relevant: (1) model-based variance estimates are consistent with each other and about half as large as stabilized model-assisted estimates, suggesting superior effectiveness of model-based inference to model-assisted inference; (2) bootstrapping is an effective alternative to analytical variance estimators; and (3) prediction accuracy expressed by RMSE is useful for screening candidate models to be used for population inferences.

Mapping Tree Density at the Global Scale

NASA Astrophysics Data System (ADS)

Covey, K. R.; Crowther, T. W.; Glick, H.; Bettigole, C.; Bradford, M.

2015-12-01

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global-scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.39 trillion exist in tropical and subtropical regions, with 0.74, and 0.61 trillion in boreal and temperate regions, respectively. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming impact of humans across most of the world. Based on our projected tree densities, we estimate that deforestation is currently responsible for removing over 15 billion trees each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Mapping tree density at a global scale

NASA Astrophysics Data System (ADS)

Crowther, T. W.; Glick, H. B.; Covey, K. R.; Bettigole, C.; Maynard, D. S.; Thomas, S. M.; Smith, J. R.; Hintler, G.; Duguid, M. C.; Amatulli, G.; Tuanmu, M.-N.; Jetz, W.; Salas, C.; Stam, C.; Piotto, D.; Tavani, R.; Green, S.; Bruce, G.; Williams, S. J.; Wiser, S. K.; Huber, M. O.; Hengeveld, G. M.; Nabuurs, G.-J.; Tikhonova, E.; Borchardt, P.; Li, C.-F.; Powrie, L. W.; Fischer, M.; Hemp, A.; Homeier, J.; Cho, P.; Vibrans, A. C.; Umunay, P. M.; Piao, S. L.; Rowe, C. W.; Ashton, M. S.; Crane, P. R.; Bradford, M. A.

2015-09-01

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.39 trillion exist in tropical and subtropical forests, with 0.74 trillion in boreal regions and 0.61 trillion in temperate regions. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming effect of humans across most of the world. Based on our projected tree densities, we estimate that over 15 billion trees are cut down each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Mapping tree density at a global scale.

PubMed

Crowther, T W; Glick, H B; Covey, K R; Bettigole, C; Maynard, D S; Thomas, S M; Smith, J R; Hintler, G; Duguid, M C; Amatulli, G; Tuanmu, M-N; Jetz, W; Salas, C; Stam, C; Piotto, D; Tavani, R; Green, S; Bruce, G; Williams, S J; Wiser, S K; Huber, M O; Hengeveld, G M; Nabuurs, G-J; Tikhonova, E; Borchardt, P; Li, C-F; Powrie, L W; Fischer, M; Hemp, A; Homeier, J; Cho, P; Vibrans, A C; Umunay, P M; Piao, S L; Rowe, C W; Ashton, M S; Crane, P R; Bradford, M A

2015-09-10

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.39 trillion exist in tropical and subtropical forests, with 0.74 trillion in boreal regions and 0.61 trillion in temperate regions. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming effect of humans across most of the world. Based on our projected tree densities, we estimate that over 15 billion trees are cut down each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Generation of High Resolution Land Surface Parameters in the Community Land Model

NASA Astrophysics Data System (ADS)

Ke, Y.; Coleman, A. M.; Wigmosta, M. S.; Leung, L.; Huang, M.; Li, H.

2010-12-01

The Community Land Model (CLM) is the land surface model used for the Community Atmosphere Model (CAM) and the Community Climate System Model (CCSM). It examines the physical, chemical, and biological processes across a variety of spatial and temporal scales. Currently, efforts are being made to improve the spatial resolution of the CLM, in part, to represent finer scale hydrologic characteristics. Current land surface parameters of CLM4.0, in particular plant functional types (PFT) and leaf area index (LAI), are generated from MODIS and calculated at a 0.05 degree resolution. These MODIS-derived land surface parameters have also been aggregated to coarser resolutions (e.g., 0.5, 1.0 degrees). To evaluate the response of CLM across various spatial scales, higher spatial resolution land surface parameters need to be generated. In this study we examine the use of Landsat TM/ETM+ imagery and data fusion techniques for generating land surface parameters at a 1km resolution within the Pacific Northwest United States. . Land cover types and PFTs are classified based on Landsat multi-season spectral information, DEM, National Land Cover Database (NLCD) and the USDA-NASS Crop Data Layer (CDL). For each PFT, relationships between MOD15A2 high quality LAI values, Landsat-based vegetation indices, climate variables, terrain, and laser-altimeter derived vegetation height are used to generate monthly LAI values at a 30m resolution. The high-resolution PFT and LAI data are aggregated to create a 1km model grid resolution. An evaluation and comparison of CLM land surface response at both fine and moderate scale is presented.

Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling.

PubMed

Stoy, Paul C; Quaife, Tristan

2015-01-01

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.

Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling

PubMed Central

Stoy, Paul C.; Quaife, Tristan

2015-01-01

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes. PMID:26067835

HiPS - Hierarchical Progressive Survey Version 1.0

NASA Astrophysics Data System (ADS)

Fernique, Pierre; Allen, Mark; Boch, Thomas; Donaldson, Tom; Durand, Daniel; Ebisawa, Ken; Michel, Laurent; Salgado, Jesus; Stoehr, Felix; Fernique, Pierre

2017-05-01

This document presents HiPS, a hierarchical scheme for the description, storage and access of sky survey data. The system is based on hierarchical tiling of sky regions at finer and finer spatial resolution which facilitates a progressive view of a survey, and supports multi-resolution zooming and panning. HiPS uses the HEALPix tessellation of the sky as the basis for the scheme and is implemented as a simple file structure with a direct indexing scheme that leads to practical implementations.

Wiener-matrix image restoration beyond the sampling passband

NASA Technical Reports Server (NTRS)

Rahman, Zia-Ur; Alter-Gartenberg, Rachel; Fales, Carl L.; Huck, Friedrich O.

1991-01-01

A finer-than-sampling-lattice resolution image can be obtained using multiresponse image gathering and Wiener-matrix restoration. The multiresponse image gathering weighs the within-passband and aliased signal components differently, allowing the Wiener-matrix restoration filter to unscramble these signal components and restore spatial frequencies beyond the sampling passband of the photodetector array. A multiresponse images can be reassembled into a single minimum mean square error image with a resolution that is sq rt A times finer than the photodetector-array sampling lattice.

Scale problems in assessment of hydrogeological parameters of groundwater flow models

NASA Astrophysics Data System (ADS)

Nawalany, Marek; Sinicyn, Grzegorz

2015-09-01

An overview is presented of scale problems in groundwater flow, with emphasis on upscaling of hydraulic conductivity, being a brief summary of the conventional upscaling approach with some attention paid to recently emerged approaches. The focus is on essential aspects which may be an advantage in comparison to the occasionally extremely extensive summaries presented in the literature. In the present paper the concept of scale is introduced as an indispensable part of system analysis applied to hydrogeology. The concept is illustrated with a simple hydrogeological system for which definitions of four major ingredients of scale are presented: (i) spatial extent and geometry of hydrogeological system, (ii) spatial continuity and granularity of both natural and man-made objects within the system, (iii) duration of the system and (iv) continuity/granularity of natural and man-related variables of groundwater flow system. Scales used in hydrogeology are categorised into five classes: micro-scale - scale of pores, meso-scale - scale of laboratory sample, macro-scale - scale of typical blocks in numerical models of groundwater flow, local-scale - scale of an aquifer/aquitard and regional-scale - scale of series of aquifers and aquitards. Variables, parameters and groundwater flow equations for the three lowest scales, i.e., pore-scale, sample-scale and (numerical) block-scale, are discussed in detail, with the aim to justify physically deterministic procedures of upscaling from finer to coarser scales (stochastic issues of upscaling are not discussed here). Since the procedure of transition from sample-scale to block-scale is physically well based, it is a good candidate for upscaling block-scale models to local-scale models and likewise for upscaling local-scale models to regional-scale models. Also the latest results in downscaling from block-scale to sample scale are briefly referred to.

Sandy beaches: state of the art of nematode ecology.

PubMed

Maria, Tatiana F; Vanaverbeke, Jan; Vanreusel, Ann; Esteves, André M

2016-01-01

In this review, we summarize existing knowledge of the ecology of sandy-beach nematodes, in relation to spatial distribution, food webs, pollution and climate change. We attempt to discuss spatial scale patterns (macro-, meso- and microscale) according to their degree of importance in structuring sandy-beach nematode assemblages. This review will provide a substantial background on current knowledge of sandy-beach nematodes, and can be used as a starting point to delineate further investigations in this field. Over decades, sandy beaches have been the scene of studies focusing on community and population ecology, both related to morphodynamic models. The combination of physical factors (e.g. grain size, tidal exposure) and biological interactions (e.g. trophic relationships) is responsible for the spatial distribution of nematodes. In other words, the physical factors are more important in structuring nematodes communities over large scale of distribution while biological interactions are largely important in finer-scale distributions. It has been accepted that biological interactions are assumed to be of minor importance because physical factors overshadow the biological interactions in sandy beach sediments; however, the most recent results from in-situ and ex-situ experimental investigations on behavior and biological factors on a microscale have shown promise for understanding the mechanisms underlying larger-scale patterns and processes. Besides nematodes are very promising organisms used to understand the effects of pollution and climate changes although these subjects are less studied in sandy beaches than distribution patterns.

Climate Change and Conservation Planning in California: The San Francisco Bay Area Upland Habitat Goals Approach

NASA Astrophysics Data System (ADS)

Branciforte, R.; Weiss, S. B.; Schaefer, N.

2008-12-01

Climate change threatens California's vast and unique biodiversity. The Bay Area Upland Habitat Goals is a comprehensive regional biodiversity assessment of the 9 counties surrounding San Francisco Bay, and is designing conservation land networks that will serve to protect, manage, and restore that biodiversity. Conservation goals for vegetation, rare plants, mammals, birds, fish, amphibians, reptiles, and invertebrates are set, and those goals are met using the optimization algorithm MARXAN. Climate change issues are being considered in the assessment and network design in several ways. The high spatial variability at mesoclimatic and topoclimatic scales in California creates high local biodiversity, and provides some degree of local resiliency to macroclimatic change. Mesoclimatic variability from 800 m scale PRISM climatic norms is used to assess "mesoclimate spaces" in distinct mountain ranges, so that high mesoclimatic variability, especially local extremes that likely support range limits of species and potential climatic refugia, can be captured in the network. Quantitative measures of network resiliency to climate change include the spatial range of key temperature and precipitation variables within planning units. Topoclimatic variability provides a finer-grained spatial patterning. Downscaling to the topoclimatic scale (10-50 m scale) includes modeling solar radiation across DEMs for predicting maximum temperature differentials, and topographic position indices for modeling minimum temperature differentials. PRISM data are also used to differentiate grasslands into distinct warm and cool types. The overall conservation strategy includes local and regional connectivity so that range shifts can be accommodated.

Solutions Network Formulation Report. Visible/Infrared Imager/Radiometer Suite and Landsat Data Continuity Mission Simulated Data Products for the Great Lakes Basin Ecological Team

NASA Technical Reports Server (NTRS)

Estep, Leland

2007-01-01

The proposed solution would simulate VIIRS and LDCM sensor data for use in the USGS/USFWS GLBET DST. The VIIRS sensor possesses a spectral range that provides water-penetrating bands that could be used to assess water clarity on a regional spatial scale. The LDCM sensor possesses suitable spectral bands in a range of wavelengths that could be used to map water quality at finer spatial scales relative to VIIRS. Water quality, alongshore sediment transport and pollutant discharge tracking into the Great Lakes system are targeted as the primary products to be developed. A principal benefit of water quality monitoring via satellite imagery is its economy compared to field-data collection methods. Additionally, higher resolution satellite imagery provides a baseline dataset(s) against which later imagery can be overlaid in GIS-based DST programs. Further, information derived from higher resolution satellite imagery can be used to address public concerns and to confirm environmental compliance. The candidate solution supports the Public Health, Coastal Management, and Water Management National Applications.

Jobs and the resource curse in the sun: The effects of oil production on female labor force participation in California counties from 1980-2010

NASA Astrophysics Data System (ADS)

Zavala, Gabriel

This study aims to evaluate the relationship between oil income and the female labor force participation rate in California for the years of 1980, 1990, 2000 and 2010 using panel linear regression models. This study also aims to visualize the spatial patterns of both variables in California through Hot Spot analysis at the county level for the same years. The regression found no sign of a relationship between oil income and female labor force participation rate but did find evidence of a positive relationship between two income control variables and the female labor force participation rate. The hot spot analysis also found that female labor force participation cold spots are not spatially correlated with oil production hot spots. These findings contribute new methodologies at a finer scale to the very nuanced discussion of the resource curse in the United States.

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

PubMed

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

2011-01-01

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

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

USGS Publications Warehouse

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

2011-01-01

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

Mammalian phylogenetic diversity-area relationships at a continental scale

PubMed Central

Mazel, Florent; Renaud, Julien; Guilhaumon, François; Mouillot, David; Gravel, Dominique; Thuiller, Wilfried

2015-01-01

In analogy to the species-area relationship (SAR), one of the few laws in Ecology, the phylogenetic diversity-area relationship (PDAR) describes the tendency of phylogenetic diversity (PD) to increase with area. Although investigating PDAR has the potential to unravel the underlying processes shaping assemblages across spatial scales and to predict PD loss through habitat reduction, it has been little investigated so far. Focusing on PD has noticeable advantages compared to species richness (SR) since PD also gives insights on processes such as speciation/extinction, assembly rules and ecosystem functioning. Here we investigate the universality and pervasiveness of the PDAR at continental scale using terrestrial mammals as study case. We define the relative robustness of PD (compared to SR) to habitat loss as the area between the standardized PDAR and standardized SAR (i.e. standardized by the diversity of the largest spatial window) divided by the area under the standardized SAR only. This metric quantifies the relative increase of PD robustness compared to SR robustness. We show that PD robustness is higher than SR robustness but that it varies among continents. We further use a null model approach to disentangle the relative effect of phylogenetic tree shape and non random spatial distribution of evolutionary history on the PDAR. We find that for most spatial scales and for all continents except Eurasia, PDARs are not different from expected by a model using only the observed SAR and the shape of the phylogenetic tree at continental scale. Interestingly, we detect a strong phylogenetic structure of the Eurasian PDAR that can be predicted by a model that specifically account for a finer biogeographical delineation of this continent. In conclusion, the relative robustness of PD to habitat loss compared to species richness is determined by the phylogenetic tree shape but also depends on the spatial structure of PD. PMID:26649401

Nonlinear plasma wave models in 3D fluid simulations of laser-plasma interaction

NASA Astrophysics Data System (ADS)

Chapman, Thomas; Berger, Richard; Arrighi, Bill; Langer, Steve; Banks, Jeffrey; Brunner, Stephan

2017-10-01

Simulations of laser-plasma interaction (LPI) in inertial confinement fusion (ICF) conditions require multi-mm spatial scales due to the typical laser beam size and durations of order 100 ps in order for numerical laser reflectivities to converge. To be computationally achievable, these scales necessitate a fluid-like treatment of light and plasma waves with a spatial grid size on the order of the light wave length. Plasma waves experience many nonlinear phenomena not naturally described by a fluid treatment, such as frequency shifts induced by trapping, a nonlinear (typically suppressed) Landau damping, and mode couplings leading to instabilities that can cause the plasma wave to decay rapidly. These processes affect the onset and saturation of stimulated Raman and Brillouin scattering, and are of direct interest to the modeling and prediction of deleterious LPI in ICF. It is not currently computationally feasible to simulate these Debye length-scale phenomena in 3D across experimental scales. Analytically-derived and/or numerically benchmarked models of processes occurring at scales finer than the fluid simulation grid offer a path forward. We demonstrate the impact of a range of kinetic processes on plasma reflectivity via models included in the LPI simulation code pF3D. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Vulnerability of ecosystems to climate change moderated by habitat intactness.

PubMed

Eigenbrod, Felix; Gonzalez, Patrick; Dash, Jadunandan; Steyl, Ilse

2015-01-01

The combined effects of climate change and habitat loss represent a major threat to species and ecosystems around the world. Here, we analyse the vulnerability of ecosystems to climate change based on current levels of habitat intactness and vulnerability to biome shifts, using multiple measures of habitat intactness at two spatial scales. We show that the global extent of refugia depends highly on the definition of habitat intactness and spatial scale of the analysis of intactness. Globally, 28% of terrestrial vegetated area can be considered refugia if all natural vegetated land cover is considered. This, however, drops to 17% if only areas that are at least 50% wilderness at a scale of 48×48 km are considered and to 10% if only areas that are at least 50% wilderness at a scale of 4.8×4.8 km are considered. Our results suggest that, in regions where relatively large, intact wilderness areas remain (e.g. Africa, Australia, boreal regions, South America), conservation of the remaining large-scale refugia is the priority. In human-dominated landscapes, (e.g. most of Europe, much of North America and Southeast Asia), focusing on finer scale refugia is a priority because large-scale wilderness refugia simply no longer exist. Action to conserve such refugia is particularly urgent since only 1 to 2% of global terrestrial vegetated area is classified as refugia and at least 50% covered by the global protected area network. © 2014 John Wiley & Sons Ltd.

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

Wolfram, Phillip J.; Ringler, Todd D.; Maltrud, Mathew E.

Isopycnal diffusivity due to stirring by mesoscale eddies in an idealized, wind-forced, eddying, midlatitude ocean basin is computed using Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT). Simulation is performed via LIGHT within the Model for Prediction across Scales Ocean (MPAS-O). Simulations are performed at 4-, 8-, 16-, and 32-km resolution, where the first Rossby radius of deformation (RRD) is approximately 30 km. Scalar and tensor diffusivities are estimated at each resolution based on 30 ensemble members using particle cluster statistics. Each ensemble member is composed of 303 665 particles distributed across five potential density surfaces. Diffusivity dependence upon modelmore » resolution, velocity spatial scale, and buoyancy surface is quantified and compared with mixing length theory. The spatial structure of diffusivity ranges over approximately two orders of magnitude with values of O(10 5) m 2 s –1 in the region of western boundary current separation to O(10 3) m 2 s –1 in the eastern region of the basin. Dominant mixing occurs at scales twice the size of the first RRD. Model resolution at scales finer than the RRD is necessary to obtain sufficient model fidelity at scales between one and four RRD to accurately represent mixing. Mixing length scaling with eddy kinetic energy and the Lagrangian time scale yield mixing efficiencies that typically range between 0.4 and 0.8. In conclusion, a reduced mixing length in the eastern region of the domain relative to the west suggests there are different mixing regimes outside the baroclinic jet region.« less

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.

Racial segregation in postbellum Southern cities: The case of Washington, D.C.

PubMed Central

Logan, John R.

2018-01-01

BACKGROUND Segregation in Southern cities has been described as a 20th-century development, layered onto an earlier pattern in which whites and blacks (both slaves and free black people) shared the same neighborhoods. Urban historians have pointed out ways in which the Southern postbellum pattern was less benign, but studies relying on census data aggregated by administrative areas – and segregation measures based on this data – have not confirmed their observations. METHODS This study is based mainly on 100% microdata from the 1880 census that has been mapped at the address level in Washington, D.C. This data makes it possible to examine in detail the unique spatial configuration of segregation that is found in this city, especially the pattern of housing in alleys. RESULTS While segregation appears to have been low, as reflected in data by wards and even by much smaller enumeration districts, analyses at a finer spatial scale reveal strongly patterned separation between blacks and whites at this early time. CONTRIBUTION This research provides much new information about segregation in a major Southern city at the end of the 19th century. It also demonstrates the importance of dealing explicitly with issues of both scale and spatial pattern in studies of segregation. PMID:29375269

Indicators of biodiversity and ecosystem services: A synthesis across ecosystems and spatial scales

USGS Publications Warehouse

Feld, C.K.; Da Silva, P.M.; Sousa, J.P.; De Bello, F.; Bugter, R.; Grandin, U.; Hering, D.; Lavorel, S.; Mountford, O.; Pardo, I.; Partel, M.; Rombke, J.; Sandin, Leonard; Jones, K. Bruce; Harrison, P.

2009-01-01

According to the Millennium Ecosystem Assessment, common indicators are needed to monitor the loss of biodiversity and the implications for the sustainable provision of ecosystem services. However, a variety of indicators are already being used resulting in many, mostly incompatible, monitoring systems. In order to synthesise the different indicator approaches and to detect gaps in the development of common indicator systems, we examined 531 indicators that have been reported in 617 peer-reviewed journal articles between 1997 and 2007. Special emphasis was placed on comparing indicators of biodiversity and ecosystem services across ecosystems (forests, grass- and shrublands, wetlands, rivers, lakes, soils and agro-ecosystems) and spatial scales (from patch to global scale). The application of biological indicators was found most often focused on regional and finer spatial scales with few indicators applied across ecosystem types. Abiotic indicators, such as physico-chemical parameters and measures of area and fragmentation, are most frequently used at broader (regional to continental) scales. Despite its multiple dimensions, biodiversity is usually equated with species richness only. The functional, structural and genetic components of biodiversity are poorly addressed despite their potential value across habitats and scales. Ecosystem service indicators are mostly used to estimate regulating and supporting services but generally differ between ecosystem types as they reflect ecosystem-specific services. Despite great effort to develop indicator systems over the past decade, there is still a considerable gap in the widespread use of indicators for many of the multiple components of biodiversity and ecosystem services, and a need to develop common monitoring schemes within and across habitats. Filling these gaps is a prerequisite for linking biodiversity dynamics with ecosystem service delivery and to achieving the goals of global and sub-global initiatives to halt the loss of biodiversity. ?? 2009 Oikos.

Beta-diversity of ectoparasites at two spatial scales: nested hierarchy, geography and habitat type.

PubMed

Warburton, Elizabeth M; van der Mescht, Luther; Stanko, Michal; Vinarski, Maxim V; Korallo-Vinarskaya, Natalia P; Khokhlova, Irina S; Krasnov, Boris R

2017-06-01

Beta-diversity of biological communities can be decomposed into (a) dissimilarity of communities among units of finer scale within units of broader scale and (b) dissimilarity of communities among units of broader scale. We investigated compositional, phylogenetic/taxonomic and functional beta-diversity of compound communities of fleas and gamasid mites parasitic on small Palearctic mammals in a nested hierarchy at two spatial scales: (a) continental scale (across the Palearctic) and (b) regional scale (across sites within Slovakia). At each scale, we analyzed beta-diversity among smaller units within larger units and among larger units with partitioning based on either geography or ecology. We asked (a) whether compositional, phylogenetic/taxonomic and functional dissimilarities of flea and mite assemblages are scale dependent; (b) how geographical (partitioning of sites according to geographic position) or ecological (partitioning of sites according to habitat type) characteristics affect phylogenetic/taxonomic and functional components of dissimilarity of ectoparasite assemblages and (c) whether assemblages of fleas and gamasid mites differ in their degree of dissimilarity, all else being equal. We found that compositional, phylogenetic/taxonomic, or functional beta-diversity was greater on a continental rather than a regional scale. Compositional and phylogenetic/taxonomic components of beta-diversity were greater among larger units than among smaller units within larger units, whereas functional beta-diversity did not exhibit any consistent trend regarding site partitioning. Geographic partitioning resulted in higher values of beta-diversity of ectoparasites than ecological partitioning. Compositional and phylogenetic components of beta-diversity were higher in fleas than mites but the opposite was true for functional beta-diversity in some, but not all, traits.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Aggregating pixel-level basal area predictions derived from LiDAR data to industrial forest stands in North-Central Idaho

Treesearch

Andrew T. Hudak; Jeffrey S. Evans; Nicholas L. Crookston; Michael J. Falkowski; Brant K. Steigers; Rob Taylor; Halli Hemingway

2008-01-01

Stand exams are the principal means by which timber companies monitor and manage their forested lands. Airborne LiDAR surveys sample forest stands at much finer spatial resolution and broader spatial extent than is practical on the ground. In this paper, we developed models that leverage spatially intensive and extensive LiDAR data and a stratified random sample of...

Sample-based synthesis of two-scale structures with anisotropy

DOE PAGES

Liu, Xingchen; Shapiro, Vadim

2017-05-19

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

Sample-based synthesis of two-scale structures with anisotropy

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

Liu, Xingchen; Shapiro, Vadim

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

An Updating System for the Gridded Population Database of China Based on Remote Sensing, GIS and Spatial Database Technologies.

PubMed

Yang, Xiaohuan; Huang, Yaohuan; Dong, Pinliang; Jiang, Dong; Liu, Honghui

2009-01-01

The spatial distribution of population is closely related to land use and land cover (LULC) patterns on both regional and global scales. Population can be redistributed onto geo-referenced square grids according to this relation. In the past decades, various approaches to monitoring LULC using remote sensing and Geographic Information Systems (GIS) have been developed, which makes it possible for efficient updating of geo-referenced population data. A Spatial Population Updating System (SPUS) is developed for updating the gridded population database of China based on remote sensing, GIS and spatial database technologies, with a spatial resolution of 1 km by 1 km. The SPUS can process standard Moderate Resolution Imaging Spectroradiometer (MODIS L1B) data integrated with a Pattern Decomposition Method (PDM) and an LULC-Conversion Model to obtain patterns of land use and land cover, and provide input parameters for a Population Spatialization Model (PSM). The PSM embedded in SPUS is used for generating 1 km by 1 km gridded population data in each population distribution region based on natural and socio-economic variables. Validation results from finer township-level census data of Yishui County suggest that the gridded population database produced by the SPUS is reliable.

Multiscale comparison of GPM radar and passive microwave precipitation fields over oceans and land: effective resolution and global/regional/local diagnostics for improving retrieval algorithms

NASA Astrophysics Data System (ADS)

Guilloteau, C.; Foufoula-Georgiou, E.; Kummerow, C.; Kirstetter, P. E.

2017-12-01

A multiscale approach is used to compare precipitation fields retrieved from GMI using the last version of the GPROF algorithm (GPROF-2017) to the DPR fields all over the globe. Using a wavelet-based spectral analysis, which renders the multi-scale decompositions of the original fields independent of each other spatially and across scales, we quantitatively assess the various scales of variability of the retrieved fields, and thus define the spatially-variable "effective resolution" (ER) of the retrievals. Globally, a strong agreement is found between passive microwave and radar patterns at scales coarser than 80km. Over oceans the patterns match down to the 20km scale. Over land, comparison statistics are spatially heterogeneous. In most areas a strong discrepancy is observed between passive microwave and radar patterns at scales finer than 40-80km. The comparison is also supported by ground-based observations over the continental US derived from the NOAA/NSSL MRMS suite of products. While larger discrepancies over land than over oceans are classically explained by land complex surface emissivity perturbing the passive microwave retrieval, other factors are investigated here, such as intricate differences in the storm structure over oceans and land. Differences in term of statistical properties (PDF of intensities and spatial organization) of precipitation fields over land and oceans are assessed from radar data, as well as differences in the relation between the 89GHz brightness temperature and precipitation. Moreover, the multiscale approach allows quantifying the part of discrepancies caused by miss-match of the location of intense cells and instrument-related geometric effects. The objective is to diagnose shortcomings of current retrieval algorithms such that targeted improvements can be made to achieve over land the same retrieval performance as over oceans.

A multi-scale evaluation of pack stock effects on subalpine meadow plant communities in the Sierra Nevada

USGS Publications Warehouse

Lee, Steven R.; Berlow, Eric L.; Ostoja, Steven M.; Brooks, Matthew L.; Génin, Alexandre; Matchett, John R.; Hart, Stephen C.

2017-01-01

We evaluated the influence of pack stock (i.e., horse and mule) use on meadow plant communities in Sequoia and Yosemite National Parks in the Sierra Nevada of California. Meadows were sampled to account for inherent variability across multiple scales by: 1) controlling for among-meadow variability by using remotely sensed hydro-climatic and geospatial data to pair stock use meadows with similar non-stock (reference) sites, 2) accounting for within-meadow variation in the local hydrology using in-situ soil moisture readings, and 3) incorporating variation in stock use intensity by sampling across the entire available gradient of pack stock use. Increased cover of bare ground was detected only within “dry” meadow areas at the two most heavily used pack stock meadows (maximum animals per night per hectare). There was no difference in plant community composition for any level of soil moisture or pack stock use. Increased local-scale spatial variability in plant community composition (species dispersion) was detected in “wet” meadow areas at the two most heavily used meadows. These results suggest that at the meadow scale, plant communities are generally resistant to the contemporary levels of recreational pack stock use. However, finer-scale within-meadow responses such as increased bare ground or spatial variability in the plant community can be a function of local-scale hydrological conditions. Wilderness managers can improve monitoring of disturbance in Sierra Nevada meadows by adopting multiple plant community indices while simultaneously considering local moisture regimes.

Wind turbine wake interactions at field scale: An LES study of the SWiFT facility

NASA Astrophysics Data System (ADS)

Yang, Xiaolei; Boomsma, Aaron; Barone, Matthew; Sotiropoulos, Fotis

2014-06-01

The University of Minnesota Virtual Wind Simulator (VWiS) code is employed to simulate turbine/atmosphere interactions in the Scaled Wind Farm Technology (SWiFT) facility developed by Sandia National Laboratories in Lubbock, TX, USA. The facility presently consists of three turbines and the simulations consider the case of wind blowing from South such that two turbines are in the free stream and the third turbine in the direct wake of one upstream turbine with separation of 5 rotor diameters. Large-eddy simulation (LES) on two successively finer grids is carried out to examine the sensitivity of the computed solutions to grid refinement. It is found that the details of the break-up of the tip vortices into small-scale turbulence structures can only be resolved on the finer grid. It is also shown that the power coefficient CP of the downwind turbine predicted on the coarse grid is somewhat higher than that obtained on the fine mesh. On the other hand, the rms (root-mean-square) of the CP fluctuations are nearly the same on both grids, although more small-scale turbulence structures are resolved upwind of the downwind turbine on the finer grid.

Demersal ichthyofaunal shelf communities from the Dumont d’Urville Sea (East Antarctica)

NASA Astrophysics Data System (ADS)

Causse, Romain; Ozouf-Costaz, Catherine; Koubbi, Philippe; Lamy, Dominique; Eléaume, Marc; Dettaï, Agnès; Duhamel, Guy; Busson, Frédéric; Pruvost, Patrice; Post, Alexandra; Beaman, Robin J.; Riddle, Martin J.

2011-08-01

The RSV Aurora Australis survey allowed the first comprehensive study of the demersal ichthyofaunal environment and of the diversity of the Dumont d’Urville Sea. We observed a high dominance of the Notothenioidei in both the number of species and in integrated abundances. The Nototheniidae was the most abundant family with 44.7% of the total integrated abundance, followed by Bathydraconidae (18.8%). Trematomus eulepidotus was the dominant species with 19.9% of the total individuals catch. Nevertheless, 43 of the 53 species caught could be considered as very rare. The Bathydraconidae was the most diversified family with 11 species caught. The highest integrated abundances of fish were found from 400 to 800 m. Well-structured species communities were observed, with high species richness from 570 to 681 m. The richest zones were located along the basins and along their upper-sides. Statistical analyses indicated large-scale spatial patterns in species composition, with clear differences in fish communities from the continental slopes, the basins and on the shelf. At a finer spatial scale, the current in the George V Basin and iceberg scouring on the banks and their sides tended to create locally heterogeneous small-scale habitats. We suggest that the glacial history and the structured habitats allowed successive colonisations of the seabed by demersal fish.

Can spatial statistical river temperature models be transferred between catchments?

NASA Astrophysics Data System (ADS)

Jackson, Faye L.; Fryer, Robert J.; Hannah, David M.; Malcolm, Iain A.

2017-09-01

There has been increasing use of spatial statistical models to understand and predict river temperature (Tw) from landscape covariates. However, it is not financially or logistically feasible to monitor all rivers and the transferability of such models has not been explored. This paper uses Tw data from four river catchments collected in August 2015 to assess how well spatial regression models predict the maximum 7-day rolling mean of daily maximum Tw (Twmax) within and between catchments. Models were fitted for each catchment separately using (1) landscape covariates only (LS models) and (2) landscape covariates and an air temperature (Ta) metric (LS_Ta models). All the LS models included upstream catchment area and three included a river network smoother (RNS) that accounted for unexplained spatial structure. The LS models transferred reasonably to other catchments, at least when predicting relative levels of Twmax. However, the predictions were biased when mean Twmax differed between catchments. The RNS was needed to characterise and predict finer-scale spatially correlated variation. Because the RNS was unique to each catchment and thus non-transferable, predictions were better within catchments than between catchments. A single model fitted to all catchments found no interactions between the landscape covariates and catchment, suggesting that the landscape relationships were transferable. The LS_Ta models transferred less well, with particularly poor performance when the relationship with the Ta metric was physically implausible or required extrapolation outside the range of the data. A single model fitted to all catchments found catchment-specific relationships between Twmax and the Ta metric, indicating that the Ta metric was not transferable. These findings improve our understanding of the transferability of spatial statistical river temperature models and provide a foundation for developing new approaches for predicting Tw at unmonitored locations across multiple catchments and larger spatial scales.

The implementation and validation of improved landsurface hydrology in an atmospheric general circulation model

NASA Technical Reports Server (NTRS)

Johnson, Kevin D.; Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

Landsurface hydrological parameterizations are implemented in the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: (1) runoff and evapotranspiration functions that include the effects of subgrid scale spatial variability and use physically based equations of hydrologic flux at the soil surface, and (2) a realistic soil moisture diffusion scheme for the movement of water in the soil column. A one dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three dimensional GCM. Results of the final simulation with the GISS GCM and the new landsurface hydrology indicate that the runoff rate, especially in the tropics is significantly improved. As a result, the remaining components of the heat and moisture balance show comparable improvements when compared to observations. The validation of model results is carried from the large global (ocean and landsurface) scale, to the zonal, continental, and finally the finer river basin scales.

Programming curvature using origami tessellations

NASA Astrophysics Data System (ADS)

Dudte, Levi H.; Vouga, Etienne; Tachi, Tomohiro; Mahadevan, L.

2016-05-01

Origami describes rules for creating folded structures from patterns on a flat sheet, but does not prescribe how patterns can be designed to fit target shapes. Here, starting from the simplest periodic origami pattern that yields one-degree-of-freedom collapsible structures--we show that scale-independent elementary geometric constructions and constrained optimization algorithms can be used to determine spatially modulated patterns that yield approximations to given surfaces of constant or varying curvature. Paper models confirm the feasibility of our calculations. We also assess the difficulty of realizing these geometric structures by quantifying the energetic barrier that separates the metastable flat and folded states. Moreover, we characterize the trade-off between the accuracy to which the pattern conforms to the target surface, and the effort associated with creating finer folds. Our approach enables the tailoring of origami patterns to drape complex surfaces independent of absolute scale, as well as the quantification of the energetic and material cost of doing so.

Advances in Light Microscopy for Neuroscience

PubMed Central

Wilt, Brian A.; Burns, Laurie D.; Ho, Eric Tatt Wei; Ghosh, Kunal K.; Mukamel, Eran A.

2010-01-01

Since the work of Golgi and Cajal, light microscopy has remained a key tool for neuroscientists to observe cellular properties. Ongoing advances have enabled new experimental capabilities using light to inspect the nervous system across multiple spatial scales, including ultrastructural scales finer than the optical diffraction limit. Other progress permits functional imaging at faster speeds, at greater depths in brain tissue, and over larger tissue volumes than previously possible. Portable, miniaturized fluorescence microscopes now allow brain imaging in freely behaving mice. Complementary progress on animal preparations has enabled imaging in head-restrained behaving animals, as well as time-lapse microscopy studies in the brains of live subjects. Mouse genetic approaches permit mosaic and inducible fluorescence-labeling strategies, whereas intrinsic contrast mechanisms allow in vivo imaging of animals and humans without use of exogenous markers. This review surveys such advances and highlights emerging capabilities of particular interest to neuroscientists. PMID:19555292

Simulating the impacts of disturbances on forest carbon cycling in North America: Processes, data, models, and challenges

USGS Publications Warehouse

Liu, Shuguang; Bond-Lamberty, Ben; Hicke, Jeffrey A.; Vargas, Rodrigo; Zhao, Shuqing; Chen, Jing; Edburg, Steven L.; Hu, Yueming; Liu, Jinxun; McGuire, A. David; Xiao, Jingfeng; Keane, Robert; Yuan, Wenping; Tang, Jianwu; Luo, Yiqi; Potter, Christopher; Oeding, Jennifer

2011-01-01

Forest disturbances greatly alter the carbon cycle at various spatial and temporal scales. It is critical to understand disturbance regimes and their impacts to better quantify regional and global carbon dynamics. This review of the status and major challenges in representing the impacts of disturbances in modeling the carbon dynamics across North America revealed some major advances and challenges. First, significant advances have been made in representation, scaling, and characterization of disturbances that should be included in regional modeling efforts. Second, there is a need to develop effective and comprehensive process‐based procedures and algorithms to quantify the immediate and long‐term impacts of disturbances on ecosystem succession, soils, microclimate, and cycles of carbon, water, and nutrients. Third, our capability to simulate the occurrences and severity of disturbances is very limited. Fourth, scaling issues have rarely been addressed in continental scale model applications. It is not fully understood which finer scale processes and properties need to be scaled to coarser spatial and temporal scales. Fifth, there are inadequate databases on disturbances at the continental scale to support the quantification of their effects on the carbon balance in North America. Finally, procedures are needed to quantify the uncertainty of model inputs, model parameters, and model structures, and thus to estimate their impacts on overall model uncertainty. Working together, the scientific community interested in disturbance and its impacts can identify the most uncertain issues surrounding the role of disturbance in the North American carbon budget and develop working hypotheses to reduce the uncertainty

Spatial relationships of levees and wetland systems within floodplains of the Wabash Basin, USA

NASA Astrophysics Data System (ADS)

Bray, E. N.; Morrison, R. R.; Nardi, F.; Annis, A.; Dong, Q.

2017-12-01

Given the unique biogeochemical, physical, and hydrologic services provided by floodplain wetlands, proper management of river systems should include an understanding of how floodplain modifications influences wetland ecosystems. The construction of levees can reduce river-floodplain connectivity, yet it is unclear how levees affect wetlands within a river system, let alone the cumulative impacts within an entire watershed. This paper explores spatial relationships between levee and floodplain wetland systems in the Wabash basin, United States. We used a hydrogeomorphic floodplain delineation technique to map floodplain extents and identify wetlands that may be hydrologically connected to river networks. We then spatially examined the relationship between levee presence, wetland area, and other river network attributes within discrete HUC-12 sub-basins. Our results show that cumulative wetland area is relatively constant in sub-basins that contain levees, regardless of maximum stream order within the sub-basin. In sub-basins that do not contain levees, cumulative wetland area increases with maximum stream order. However, we found that wetland distributions around levees can be complex, and further studies on the influence of levees on wetland habitat may need to be evaluated at finer-resolution spatial scales.

Application of Geostatistical Simulation to Enhance Satellite Image Products

NASA Technical Reports Server (NTRS)

Hlavka, Christine A.; Dungan, Jennifer L.; Thirulanambi, Rajkumar; Roy, David

2004-01-01

With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.

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

PubMed

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

2018-01-01

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

Mapping social values for urban green spaces using Public Participation GIS: the influence of spatial scale and implications for landscape planning.

NASA Astrophysics Data System (ADS)

Ives, Christopher

2015-04-01

Measuring social values for landscapes is an emerging field of research and is critical to the successful management of urban ecosystems. Green open space planning has traditionally relied on rigid standards and metrics without considering the physical requirements of green spaces that are valued for different reasons and by different people. Relating social landscape values to key environmental variables provides a much stronger evidence base for planning landscapes that are both socially desirable and environmentally sustainable. This study spatially quantified residents' values for green space in the Lower Hunter Valley of New South Wales, Australia by enabling participants to mark their values for specific open spaces on interactive paper maps. The survey instrument was designed to evaluate the effect of spatial scale by providing maps of residents' local area at both suburb and municipality scales. The importance of open space values differed depending on whether they were indicated via marker dots or reported on in a general aspatial sense. This suggests that certain open space functions were inadequately provided for in the local area (specifically, cultural significance and health/therapeutic value). Additionally, all value types recorded a greater abundance of marker dots at the finer (suburb) scale compared to the coarser (municipality) scale, but this pattern was more pronounced for some values than others (e.g. physical exercise value). Finally, significant relationships were observed between the abundance of value marker dots in parks and their environmental characteristics (e.g. percentage of vegetation). These results have interesting implications when considering the compatibility between different functions of green spaces and how planners can incorporate information about social values with more traditional approaches to green space planning.

CMIP5 ensemble-based spatial rainfall projection over homogeneous zones of India

NASA Astrophysics Data System (ADS)

Akhter, Javed; Das, Lalu; Deb, Argha

2017-09-01

Performances of the state-of-the-art CMIP5 models in reproducing the spatial rainfall patterns over seven homogeneous rainfall zones of India viz. North Mountainous India (NMI), Northwest India (NWI), North Central India (NCI), Northeast India (NEI), West Peninsular India (WPI), East Peninsular India (EPI) and South Peninsular India (SPI) have been assessed using different conventional performance metrics namely spatial correlation (R), index of agreement (d-index), Nash-Sutcliffe efficiency (NSE), Ratio of RMSE to the standard deviation of the observations (RSR) and mean bias (MB). The results based on these indices revealed that majority of the models are unable to reproduce finer-scaled spatial patterns over most of the zones. Thereafter, four bias correction methods i.e. Scaling, Standardized Reconstruction, Empirical Quantile Mapping and Gamma Quantile Mapping have been applied on GCM simulations to enhance the skills of the GCM projections. It has been found that scaling method compared to other three methods shown its better skill in capturing mean spatial patterns. Multi-model ensemble (MME) comprising 25 numbers of better performing bias corrected (Scaled) GCMs, have been considered for developing future rainfall patterns over seven zones. Models' spread from ensemble mean (uncertainty) has been found to be larger in RCP 8.5 than RCP4.5 ensemble. In general, future rainfall projections from RCP 4.5 and RCP 8.5 revealed an increasing rainfall over seven zones during 2020s, 2050s, and 2080s. The maximum increase has been found over southwestern part of NWI (12-30%), northwestern part of WPI (3-30%), southeastern part of NEI (5-18%) and northern and eastern part of SPI (6-24%). However, the contiguous region comprising by the southeastern part of NCI and northeastern part of EPI, may experience slight decreasing rainfall (about 3%) during 2020s whereas the western part of NMI may also receive around 3% reduction in rainfall during both 2050s and 2080s.

A non-parametric, supervised classification of vegetation types on the Kaibab National Forest using decision trees

Treesearch

Suzanne M. Joy; R. M. Reich; Richard T. Reynolds

2003-01-01

Traditional land classification techniques for large areas that use Landsat Thematic Mapper (TM) imagery are typically limited to the fixed spatial resolution of the sensors (30m). However, the study of some ecological processes requires land cover classifications at finer spatial resolutions. We model forest vegetation types on the Kaibab National Forest (KNF) in...

Insights into the physico-chemical evolution of pyrogenic organic carbon emissions from biomass burning using coupled Lagrangian-Eulerian simulations

NASA Astrophysics Data System (ADS)

Suciu, L. G.; Griffin, R. J.; Masiello, C. A.

2017-12-01

Wildfires and prescribed burning are important sources of particulate and gaseous pyrogenic organic carbon (PyOC) emissions to the atmosphere. These emissions impact atmospheric chemistry, air quality and climate, but the spatial and temporal variabilities of these impacts are poorly understood, primarily because small and fresh fire plumes are not well predicted by three-dimensional Eulerian chemical transport models due to their coarser grid size. Generally, this results in underestimation of downwind deposition of PyOC, hydroxyl radical reactivity, secondary organic aerosol formation and ozone (O3) production. However, such models are very good for simulation of multiple atmospheric processes that could affect the lifetimes of PyOC emissions over large spatiotemporal scales. Finer resolution models, such as Lagrangian reactive plumes models (or plume-in-grid), could be used to trace fresh emissions at the sub-grid level of the Eulerian model. Moreover, Lagrangian plume models need background chemistry predicted by the Eulerian models to accurately simulate the interactions of the plume material with the background air during plume aging. Therefore, by coupling the two models, the physico-chemical evolution of the biomass burning plumes can be tracked from local to regional scales. In this study, we focus on the physico-chemical changes of PyOC emissions from sub-grid to grid levels using an existing chemical mechanism. We hypothesize that finer scale Lagrangian-Eulerian simulations of several prescribed burns in the U.S. will allow more accurate downwind predictions (validated by airborne observations from smoke plumes) of PyOC emissions (i.e., submicron particulate matter, organic aerosols, refractory black carbon) as well as O3 and other trace gases. Simulation results could be used to optimize the implementation of additional PyOC speciation in the existing chemical mechanism.

A MULTISCALE FRAMEWORK FOR THE STOCHASTIC ASSIMILATION AND MODELING OF UNCERTAINTY ASSOCIATED NCF COMPOSITE MATERIALS

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

Mehrez, Loujaine; Ghanem, Roger; McAuliffe, Colin

multiscale framework to construct stochastic macroscopic constitutive material models is proposed. A spectral projection approach, specifically polynomial chaos expansion, has been used to construct explicit functional relationships between the homogenized properties and input parameters from finer scales. A homogenization engine embedded in Multiscale Designer, software for composite materials, has been used for the upscaling process. The framework is demonstrated using non-crimp fabric composite materials by constructing probabilistic models of the homogenized properties of a non-crimp fabric laminate in terms of the input parameters together with the homogenized properties from finer scales.

Fruit availability drives the distribution of a folivorous-frugivorous primate within a large forest remnant.

PubMed

Camaratta, Danielle; Chaves, Óscar M; Bicca-Marques, Júlio César

2017-03-01

Understanding the ecological factors that influence the presence, abundance, and distribution of species within their habitats is critical for ensuring their long-term conservation. In the case of primary consumers, such as most primates, the availability and richness of plant foods are considered key drivers of population density at these variables influence the spatial distribution of social units within a finer, habitat patch level scale. We tested the hypothesis that the spatiotemporal availability and richness of plant foods, drive the spatial distribution of brown howler monkeys (Alouatta guariba clamitans) at a fine spatial scale. We established five line transects (2.6-4.3 km long) to census the population of brown howlers in Morro São Pedro, a 1,200 ha Atlantic forest remnant in southern Brazil, every 2 weeks from January to June 2015. We used data from tree inventories performed in sighting and control plots, and phenological surveys of 17 top food tree species to estimate bi-weekly food availability. We recorded a total of 95 sightings. The number of sightings per sampling period ranged from 2 to 12. The availability of fruit (ripe and unripe) was higher in sighting than in control plots, whereas leaf availability and the richness of food tree species was similar. We conclude that the spatial distribution of fruiting trees and the availability of fruit drive the pattern of habitat use, and spacing of brown howler groups in Morro São Pedro. © 2017 Wiley Periodicals, Inc.

The spatiotemporal association of non-prescription retail sales with cases during the 2009 influenza pandemic in Great Britain.

PubMed

Todd, Stacy; Diggle, Peter J; White, Peter J; Fearne, Andrew; Read, Jonathan M

2014-04-29

To assess whether retail sales of non-prescription products can be used for syndromic surveillance and whether it can detect influenza activity at different spatial scales. A secondary objective was to assess whether changes in purchasing behaviour were related to public health advice or levels of media or public interest. The UK. National and regional influenza case estimates and retail sales from a major British supermarket. Weekly, seasonally adjusted sales of over-the-counter symptom remedies and non-pharmaceutical products; recommended as part of the advice offered by public health agencies; were compared with weekly influenza case estimates. Comparisons were made at national and regional spatial resolutions. We also compared sales to national measures of contemporaneous media output and public interest (Internet search volume) related to the pandemic. At a national scale there was no significant correlation between retail sales of symptom remedies and cases for the whole pandemic period in 2009. At the regional scale, a minority of regions showed statistically significant positive correlations between cases and sales of adult 'cold and flu' remedies and cough remedies (3.2%, 5/156, 3.8%, 6/156), but a greater number of regions showed a significant positive correlation between cases and symptomatic remedies for children (35.6%, 55/156). Significant positive correlations between cases and sales of thermometers and antiviral hand gels/wash were seen at both spatial scales (Cor 0.477 (95% CI 0.171 to 0.699); 0.711 (95% CI 0.495 to 0.844)). We found no significant association between retail sales and media reporting or Internet search volume. This study provides evidence that the British public responded appropriately to health messaging about hygiene. Non-prescription retail sales at a national level are not useful for the detection of cases. However, at finer spatial scales, in particular age-groups, retail sales may help augment existing surveillance and merit further study.

On the effects of scale for ecosystem services mapping

USGS Publications Warehouse

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

On the Effects of Scale for Ecosystem Services Mapping

PubMed Central

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability. PMID:25549256

The spatiotemporal association of non-prescription retail sales with cases during the 2009 influenza pandemic in Great Britain

PubMed Central

Todd, Stacy; Diggle, Peter J; White, Peter J; Fearne, Andrew; Read, Jonathan M

2014-01-01

Objective To assess whether retail sales of non-prescription products can be used for syndromic surveillance and whether it can detect influenza activity at different spatial scales. A secondary objective was to assess whether changes in purchasing behaviour were related to public health advice or levels of media or public interest. Setting The UK. Participants National and regional influenza case estimates and retail sales from a major British supermarket. Outcome measures Weekly, seasonally adjusted sales of over-the-counter symptom remedies and non-pharmaceutical products; recommended as part of the advice offered by public health agencies; were compared with weekly influenza case estimates. Comparisons were made at national and regional spatial resolutions. We also compared sales to national measures of contemporaneous media output and public interest (Internet search volume) related to the pandemic. Results At a national scale there was no significant correlation between retail sales of symptom remedies and cases for the whole pandemic period in 2009. At the regional scale, a minority of regions showed statistically significant positive correlations between cases and sales of adult ‘cold and flu’ remedies and cough remedies (3.2%, 5/156, 3.8%, 6/156), but a greater number of regions showed a significant positive correlation between cases and symptomatic remedies for children (35.6%, 55/156). Significant positive correlations between cases and sales of thermometers and antiviral hand gels/wash were seen at both spatial scales (Cor 0.477 (95% CI 0.171 to 0.699); 0.711 (95% CI 0.495 to 0.844)). We found no significant association between retail sales and media reporting or Internet search volume. Conclusions This study provides evidence that the British public responded appropriately to health messaging about hygiene. Non-prescription retail sales at a national level are not useful for the detection of cases. However, at finer spatial scales, in particular age-groups, retail sales may help augment existing surveillance and merit further study. PMID:24780494

On the effects of scale for ecosystem services mapping.

PubMed

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

Genome-wide SNPs reveal the drivers of gene flow in an urban population of the Asian Tiger Mosquito, Aedes albopictus.

PubMed

Schmidt, Thomas L; Rašić, Gordana; Zhang, Dongjing; Zheng, Xiaoying; Xi, Zhiyong; Hoffmann, Ary A

2017-10-01

Aedes albopictus is a highly invasive disease vector with an expanding worldwide distribution. Genetic assays using low to medium resolution markers have found little evidence of spatial genetic structure even at broad geographic scales, suggesting frequent passive movement along human transportation networks. Here we analysed genetic structure of Aedes albopictus collected from 12 sample sites in Guangzhou, China, using thousands of genome-wide single nucleotide polymorphisms (SNPs). We found evidence for passive gene flow, with distance from shipping terminals being the strongest predictor of genetic distance among mosquitoes. As further evidence of passive dispersal, we found multiple pairs of full-siblings distributed between two sample sites 3.7 km apart. After accounting for geographical variability, we also found evidence for isolation by distance, previously undetectable in Ae. albopictus. These findings demonstrate how large SNP datasets and spatially-explicit hypothesis testing can be used to decipher processes at finer geographic scales than formerly possible. Our approach can be used to help predict new invasion pathways of Ae. albopictus and to refine strategies for vector control that involve the transformation or suppression of mosquito populations.

Spatial distribution of the dagger nematode Xiphinema index and its associated Grapevine fanleaf virus in French vineyard.

PubMed

Villate, L; Fievet, V; Hanse, B; Delemarre, F; Plantard, O; Esmenjaud, D; van Helden, M

2008-08-01

The nematode Xiphinema index is, economically, the major virus vector in viticulture, transmitting specifically the Grapevine fanleaf virus (GFLV), the most severe grapevine virus disease worldwide. Increased knowledge of the spatial distribution of this nematode, both horizontally and vertically, and of correlative GFLV plant infections, is essential to efficiently control the disease. In two infested blocks of the Bordeaux vineyard, vertical distribution data showed that the highest numbers of individuals occurred at 40 to 110 cm depth, corresponding to the two layers where the highest densities of fine roots were observed. Horizontal distribution based on a 10 x 15 m grid sampling procedure revealed a significant aggregative pattern but no significant neighborhood structure of nematode densities. At a finer scale ( approximately 2 x 2 m), nematode sampling performed in a third block confirmed a significant aggregative pattern, with patches of 6 to 8 m diameter, together with a significant neighborhood structure of nematode densities, thus identifying the relevant sampling scale to describe the nematode distribution. Nematode patches correlate significantly with those of GFLV-infected grapevine plants. Finally, nematode and virus spread were shown to extend preferentially parallel to vine rows, probably due to tillage during mechanical weeding.

Remote sensing of soil moisture using airborne hyperspectral data

USGS Publications Warehouse

Finn, M.; Lewis, M.; Bosch, D.; Giraldo, Mario; Yamamoto, K.; Sullivan, D.; Kincaid, R.; Luna, R.; Allam, G.; Kvien, Craig; Williams, M.

2011-01-01

Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.

Remote sensing of soil moisture using airborne hyperspectral data

USGS Publications Warehouse

Finn, Michael P.; Lewis, Mark (David); Bosch, David D.; Giraldo, Mario; Yamamoto, Kristina H.; Sullivan, Dana G.; Kincaid, Russell; Luna, Ronaldo; Allam, Gopala Krishna; Kvien, Craig; Williams, Michael S.

2011-01-01

Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R 2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.

Multimodel Simulation of Water Flow: Uncertainty Analysis

USDA-ARS?s Scientific Manuscript database

Simulations of soil water flow require measurements of soil hydraulic properties which are particularly difficult at the field scale. Laboratory measurements provide hydraulic properties at scales finer than the field scale, whereas pedotransfer functions (PTFs) integrate information on hydraulic pr...

Finer parcellation reveals detailed correlational structure of resting-state fMRI signals.

PubMed

Dornas, João V; Braun, Jochen

2018-01-15

Even in resting state, the human brain generates functional signals (fMRI) with complex correlational structure. To simplify this structure, it is common to parcellate a standard brain into coarse chunks. Finer parcellations are considered less reproducible and informative, due to anatomical and functional variability of individual brains. Grouping signals with similar local correlation profiles, restricted to each anatomical region (Tzourio-Mazoyer et al., 2002), we divide a standard brain into 758 'functional clusters' averaging 1.7cm 3 gray matter volume ('MD758' parcellation). We compare 758 'spatial clusters' of similar size ('S758'). 'Functional clusters' are spatially contiguous and cluster quality (integration and segregation of temporal variance) is far superior to 'spatial clusters', comparable to multi-modal parcellations of half the resolution (Craddock et al., 2012; Glasser et al., 2016). Moreover, 'functional clusters' capture many long-range functional correlations, with O(10 5 ) reproducibly correlated cluster pairs in different anatomical regions. The pattern of functional correlations closely mirrors long-range anatomical connectivity established by fibre tracking. MD758 is comparable to coarser parcellations (Craddock et al., 2012; Glasser et al., 2016) in terms of cluster quality, correlational structure (54% relative mutual entropy vs 60% and 61%), and sparseness (35% significant pairwise correlations vs 36% and 44%). We describe and evaluate a simple path to finer functional parcellations of the human brain. Detailed correlational structure is surprisingly consistent between individuals, opening new possibilities for comparing functional correlations between cognitive conditions, states of health, or pharmacological interventions. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Sedimentary architecture of the Shaler outcrop, Gale Crater, Mars: paleoenvironmental and sediment transport implications

NASA Astrophysics Data System (ADS)

Gupta, S.; Edgar, L. A.; Rubin, D. M.; Lewis, K. W.; Kocurek, G.; Anderson, R. B.; Bell, J. F.; Dromart, G.; Edgett, K. S.; Grotzinger, J. P.; Hardgrove, C. J.; Kah, L. C.; Leveille, R. J.; Malin, M.; Mangold, N.; Milliken, R.; Minitti, M. E.; Muller, J.; Rice, M. S.; Rowland, S. K.; Schieber, J.; Stack, K.; Sumner, D. Y.; Team, M.

2013-12-01

Sedimentary rocks are archives of ancient depositional processes and environments on planetary surfaces. Reconstructing such processes and environments requires observations of sedimentary structures and architecture (the large-scale geometry and organisation of sedimentary bedsets). We report the analysis of the distinct Shaler outcrop, a prominent stratified unit located between the Bathurst Inlet outcrop and the floor of Yellowknife bay. The Shaler outcrop is an ~1 m thick stratal unit that spans approximately 30 m outcrop in length, and was examined by Curiosity on sols 120-121 and more recently on sols 309-324. Detailed stereo observations of the outcrop across most of its entire lateral extent were made using Navigation and Mast Cameras. These data permit detailed analysis of stratal geometries, distribution of sedimentary structures, and broad grain size trends. Overall the Shaler outcrop comprises a heterogeneous assemblage of interstratified platy sandstones separated by recessive, likely finer-grained beds. Coarser-grained beds are characterised by decimeter-scale trough cross-bedding. The north-eastern section of the outcrop shows greater abundance of interstratified sandstones and finer-grained beds. The southwestern section is characterised by darker bedsets that are likely coarser grained interstratified with finer-grained sandstones. The darker bedsets appear to comprise stacked trough-cross stratified bedsets. Finer-grained recessive intervals are not apparent in this section. The presence and scale of trough cross-stratification indicates that sediment was transported by the migration of sinuous crested dunes. Bedding geometries indicate sub-critical angles of climb. We examine the large-scale bedset architecture to evaluate the original depositional geometry of the Shaler sedimentary system, and consider its plausible depositional processes and paleoenvironmental setting. Finally, we consider its relationship to the sedimentary succession exposed in the Yellowknife bay region.

Delineating Biophysical Environments of the Sunda Banda Seascape, Indonesia

PubMed Central

Wang, Mingshu; Ahmadia, Gabby N.; Chollett, Iliana; Huang, Charles; Fox, Helen; Wijonarno, Anton; Madden, Marguerite

2015-01-01

The Sunda Banda Seascape (SBS), located in the center of the Coral Triangle, is a global center of marine biodiversity and a conservation priority. We proposed the first biophysical environmental delineation of the SBS using globally available satellite remote sensing and model-assimilated data to categorize this area into unique and meaningful biophysical classes. Specifically, the SBS was partitioned into eight biophysical classes characterized by similar sea surface temperature, chlorophyll a concentration, currents, and salinity patterns. Areas within each class were expected to have similar habitat types and ecosystem functions. Our work supplemented prevailing global marine management schemes by focusing in on a regional scale with finer spatial resolution. It also provided a baseline for academic research, ecological assessments and will facilitate marine spatial planning and conservation activities in the area. In addition, the framework and methods of delineating biophysical environments we presented can be expanded throughout the whole Coral Triangle to support research and conservation activities in this important region. PMID:25648170

A multi-scale evaluation of pack stock effects on subalpine meadow plant communities in the Sierra Nevada

PubMed Central

Berlow, Eric L.; Ostoja, Steven M.; Brooks, Matthew L.; Génin, Alexandre; Matchett, John R.; Hart, Stephen C.

2017-01-01

We evaluated the influence of pack stock (i.e., horse and mule) use on meadow plant communities in Sequoia and Yosemite National Parks in the Sierra Nevada of California. Meadows were sampled to account for inherent variability across multiple scales by: 1) controlling for among-meadow variability by using remotely sensed hydro-climatic and geospatial data to pair stock use meadows with similar non-stock (reference) sites, 2) accounting for within-meadow variation in the local hydrology using in-situ soil moisture readings, and 3) incorporating variation in stock use intensity by sampling across the entire available gradient of pack stock use. Increased cover of bare ground was detected only within “dry” meadow areas at the two most heavily used pack stock meadows (maximum animals per night per hectare). There was no difference in plant community composition for any level of soil moisture or pack stock use. Increased local-scale spatial variability in plant community composition (species dispersion) was detected in “wet” meadow areas at the two most heavily used meadows. These results suggest that at the meadow scale, plant communities are generally resistant to the contemporary levels of recreational pack stock use. However, finer-scale within-meadow responses such as increased bare ground or spatial variability in the plant community can be a function of local-scale hydrological conditions. Wilderness managers can improve monitoring of disturbance in Sierra Nevada meadows by adopting multiple plant community indices while simultaneously considering local moisture regimes. PMID:28609464

Multi-Scale Soil Moisture Monitoring and Modeling at ARS Watersheds for NASA's Soil Moisture Active Passive (SMAP) Calibration/Validation Mission

NASA Astrophysics Data System (ADS)

Coopersmith, E. J.; Cosh, M. H.

2014-12-01

NASA's SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networks. This can be achieved via the integration of NLDAS precipitation data to perform calibration of models at each ­in-situ gauge. In turn, these models and the gauges' volumetric estimations are used to generate soil moisture estimates at a 500m scale throughout a given test watershed by leveraging, at each location, the gauge-calibrated models deemed most appropriate in terms of proximity, calibration efficacy, soil-textural similarity, and topography. Four ARS watersheds, located in Iowa, Oklahoma, Georgia, and Arizona are employed to demonstrate the utility of this approach. The South Fork watershed in Iowa represents the simplest case - the soil textures and topography are relative constants and the variability of soil moisture is simply tied to the spatial variability of precipitation. The Little Washita watershed in Oklahoma adds soil textural variability (but remains topographically simple), while the Little River watershed in Georgia incorporates topographic classification. Finally, the Walnut Gulch watershed in Arizona adds a dense precipitation network to be employed for even finer-scale modeling estimates. Results suggest RMSE values at or below the 4% volumetric standard adopted for the SMAP mission are attainable over the desired spatial scales via this integration of modeling efforts and existing in-situ networks.

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

USGS Publications Warehouse

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

2016-01-01

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

Environmental variables measured at multiple spatial scales exert uneven influence on fish assemblages of floodplain lakes

USGS Publications Warehouse

Dembkowski, Daniel J.; Miranda, Leandro E.

2014-01-01

We examined the interaction between environmental variables measured at three different scales (i.e., landscape, lake, and in-lake) and fish assemblage descriptors across a range of over 50 floodplain lakes in the Mississippi Alluvial Valley of Mississippi and Arkansas. Our goal was to identify important local- and landscape-level determinants of fish assemblage structure. Relationships between fish assemblage structure and variables measured at broader scales (i.e., landscape-level and lake-level) were hypothesized to be stronger than relationships with variables measured at finer scales (i.e., in-lake variables). Results suggest that fish assemblage structure in floodplain lakes was influenced by variables operating on three different scales. However, and contrary to expectations, canonical correlations between in-lake environmental characteristics and fish assemblage structure were generally stronger than correlations between landscape-level and lake-level variables and fish assemblage structure, suggesting a hierarchy of influence. From a resource management perspective, our study suggests that landscape-level and lake-level variables may be manipulated for conservation or restoration purposes, and in-lake variables and fish assemblage structure may be used to monitor the success of such efforts.

Multi-scale individual-based model of microbial and bioconversion dynamics in aerobic granular sludge.

PubMed

Xavier, Joao B; De Kreuk, Merle K; Picioreanu, Cristian; Van Loosdrecht, Mark C M

2007-09-15

Aerobic granular sludge is a novel compact biological wastewater treatment technology for integrated removal of COD (chemical oxygen demand), nitrogen, and phosphate charges. We present here a multiscale model of aerobic granular sludge sequencing batch reactors (GSBR) describing the complex dynamics of populations and nutrient removal. The macro scale describes bulk concentrations and effluent composition in six solutes (oxygen, acetate, ammonium, nitrite, nitrate, and phosphate). A finer scale, the scale of one granule (1.1 mm of diameter), describes the two-dimensional spatial arrangement of four bacterial groups--heterotrophs, ammonium oxidizers, nitrite oxidizers, and phosphate accumulating organisms (PAO)--using individual based modeling (IbM) with species-specific kinetic models. The model for PAO includes three internal storage compounds: polyhydroxyalkanoates (PHA), poly phosphate, and glycogen. Simulations of long-term reactor operation show how the microbial population and activity depends on the operating conditions. Short-term dynamics of solute bulk concentrations are also generated with results comparable to experimental data from lab scale reactors. Our results suggest that N-removal in GSBR occurs mostly via alternating nitrification/denitrification rather than simultaneous nitrification/denitrification, supporting an alternative strategy to improve N-removal in this promising wastewater treatment process.

Incorporating Cold-Air Pooling into Downscaled Climate Models Increases Potential Refugia for Snow-Dependent Species within the Sierra Nevada Ecoregion, CA

PubMed Central

Curtis, Jennifer A.; Flint, Lorraine E.; Flint, Alan L.; Lundquist, Jessica D.; Hudgens, Brian; Boydston, Erin E.; Young, Julie K.

2014-01-01

We present a unique water-balance approach for modeling snowpack under historic, current and future climates throughout the Sierra Nevada Ecoregion. Our methodology uses a finer scale (270 m) than previous regional studies and incorporates cold-air pooling, an atmospheric process that sustains cooler temperatures in topographic depressions thereby mitigating snowmelt. Our results are intended to support management and conservation of snow-dependent species, which requires characterization of suitable habitat under current and future climates. We use the wolverine (Gulo gulo) as an example species and investigate potential habitat based on the depth and extent of spring snowpack within four National Park units with proposed wolverine reintroduction programs. Our estimates of change in spring snowpack conditions under current and future climates are consistent with recent studies that generally predict declining snowpack. However, model development at a finer scale and incorporation of cold-air pooling increased the persistence of April 1st snowpack. More specifically, incorporation of cold-air pooling into future climate projections increased April 1st snowpack by 6.5% when spatially averaged over the study region and the trajectory of declining April 1st snowpack reverses at mid-elevations where snow pack losses are mitigated by topographic shading and cold-air pooling. Under future climates with sustained or increased precipitation, our results indicate a high likelihood for the persistence of late spring snowpack at elevations above approximately 2,800 m and identify potential climate refugia sites for snow-dependent species at mid-elevations, where significant topographic shading and cold-air pooling potential exist. PMID:25188379

Incorporating cold-air pooling into downscaled climate models increases potential refugia for snow-dependent species within the Sierra Nevada Ecoregion, CA

USGS Publications Warehouse

Curtis, Jennifer A.; Flint, Lorraine E.; Flint, Alan L.; Lundquist, Jessica D.; Hudgens, Brian; Boydston, Erin E.; Young, Julie K.

2014-01-01

We present a unique water-balance approach for modeling snowpack under historic, current and future climates throughout the Sierra Nevada Ecoregion. Our methodology uses a finer scale (270 m) than previous regional studies and incorporates cold-air pooling, an atmospheric process that sustains cooler temperatures in topographic depressions thereby mitigating snowmelt. Our results are intended to support management and conservation of snow-dependent species, which requires characterization of suitable habitat under current and future climates. We use the wolverine (Gulo gulo) as an example species and investigate potential habitat based on the depth and extent of spring snowpack within four National Park units with proposed wolverine reintroduction programs. Our estimates of change in spring snowpack conditions under current and future climates are consistent with recent studies that generally predict declining snowpack. However, model development at a finer scale and incorporation of cold-air pooling increased the persistence of April 1st snowpack. More specifically, incorporation of cold-air pooling into future climate projections increased April 1st snowpack by 6.5% when spatially averaged over the study region and the trajectory of declining April 1st snowpack reverses at mid-elevations where snow pack losses are mitigated by topographic shading and cold-air pooling. Under future climates with sustained or increased precipitation, our results indicate a high likelihood for the persistence of late spring snowpack at elevations above approximately 2,800 m and identify potential climate refugia sites for snow-dependent species at mid-elevations, where significant topographic shading and cold-air pooling potential exist.

A phylogenetic comparative study of flowering phenology along an elevational gradient in the Canadian subarctic.

PubMed

Lessard-Therrien, Malie; Davies, T Jonathan; Bolmgren, Kjell

2014-05-01

Climate change is affecting high-altitude and high-latitude communities in significant ways. In the short growing season of subarctic habitats, it is essential that the timing and duration of phenological phases match favorable environmental conditions. We explored the time of the first appearance of flowers (first flowering day, FFD) and flowering duration across subarctic species composing different communities, from boreal forest to tundra, along an elevational gradient (600-800 m). The study was conducted on Mount Irony (856 m), North-East Canada (54°90'N, 67°16'W) during summer 2012. First, we quantified phylogenetic signal in FFD at different spatial scales. Second, we used phylogenetic comparative methods to explore the relationship between FFD, flowering duration, and elevation. We found that the phylogenetic signal for FFD was stronger at finer spatial scales and at lower elevations, indicating that closely related species tend to flower at similar times when the local environment is less harsh. The comparatively weaker phylogenetic signal at higher elevation may be indicative of convergent evolution for FFD. Flowering duration was correlated significantly with mean FFD, with later-flowering species having a longer flowering duration, but only at the lowest elevation. Our results indicate significant evolutionary conservatism in responses to phenological cues, but high phenotypic plasticity in flowering times. We suggest that phylogenetic relationships should be considered in the search for predictions and drivers of flowering time in comparative analyses, because species cannot be considered as statistically independent. Further, phenological drivers should be measured at spatial scales such that variation in flowering matches variation in environment.

A Parameter Estimation Scheme for Multiscale Kalman Smoother (MKS) Algorithm Used in Precipitation Data Fusion

NASA Technical Reports Server (NTRS)

Wang, Shugong; Liang, Xu

2013-01-01

A new approach is presented in this paper to effectively obtain parameter estimations for the Multiscale Kalman Smoother (MKS) algorithm. This new approach has demonstrated promising potentials in deriving better data products based on data of different spatial scales and precisions. Our new approach employs a multi-objective (MO) parameter estimation scheme (called MO scheme hereafter), rather than using the conventional maximum likelihood scheme (called ML scheme) to estimate the MKS parameters. Unlike the ML scheme, the MO scheme is not simply built on strict statistical assumptions related to prediction errors and observation errors, rather, it directly associates the fused data of multiple scales with multiple objective functions in searching best parameter estimations for MKS through optimization. In the MO scheme, objective functions are defined to facilitate consistency among the fused data at multiscales and the input data at their original scales in terms of spatial patterns and magnitudes. The new approach is evaluated through a Monte Carlo experiment and a series of comparison analyses using synthetic precipitation data. Our results show that the MKS fused precipitation performs better using the MO scheme than that using the ML scheme. Particularly, improvements are significant compared to that using the ML scheme for the fused precipitation associated with fine spatial resolutions. This is mainly due to having more criteria and constraints involved in the MO scheme than those included in the ML scheme. The weakness of the original ML scheme that blindly puts more weights onto the data associated with finer resolutions is overcome in our new approach.

CryoSat Plus For Oceans: an ESA Project for CryoSat-2 Data Exploitation Over Ocean

NASA Astrophysics Data System (ADS)

Benveniste, J.; Cotton, D.; Clarizia, M.; Roca, M.; Gommenginger, C. P.; Naeije, M. C.; Labroue, S.; Picot, N.; Fernandes, J.; Andersen, O. B.; Cancet, M.; Dinardo, S.; Lucas, B. M.

2012-12-01

The ESA CryoSat-2 mission is the first space mission to carry a space-borne radar altimeter that is able to operate in the conventional pulsewidth-limited (LRM) mode and in the novel Synthetic Aperture Radar (SAR) mode. Although the prime objective of the Cryosat-2 mission is dedicated to monitoring land and marine ice, the SAR mode capability of the Cryosat-2 SIRAL altimeter also presents the possibility of demonstrating significant potential benefits of SAR altimetry for ocean applications, based on expected performance enhancements which include improved range precision and finer along track spatial resolution. With this scope in mind, the "CryoSat Plus for Oceans" (CP4O) Project, dedicated to the exploitation of CryoSat-2 Data over ocean, supported by the ESA STSE (Support To Science Element) programme, brings together an expert European consortium comprising: DTU Space, isardSAT, National Oceanography Centre , Noveltis, SatOC, Starlab, TU Delft, the University of Porto and CLS (supported by CNES),. The objectives of CP4O are: - to build a sound scientific basis for new scientific and operational applications of Cryosat-2 data over the open ocean, polar ocean, coastal seas and for sea-floor mapping. - to generate and evaluate new methods and products that will enable the full exploitation of the capabilities of the Cryosat-2 SIRAL altimeter , and extend their application beyond the initial mission objectives. - to ensure that the scientific return of the Cryosat-2 mission is maximised. In particular four themes will be addressed: -Open Ocean Altimetry: Combining GOCE Geoid Model with CryoSat Oceanographic LRM Products for the retrieval of CryoSat MSS/MDT model over open ocean surfaces and for analysis of mesoscale and large scale prominent open ocean features. Under this priority the project will also foster the exploitation of the finer resolution and higher SNR of novel CryoSat SAR Data to detect short spatial scale open ocean features. -High Resolution Polar Ocean Altimetry: Combination of GOCE Geoid Model with CryoSat Oceanographic SAR Products over polar oceans for the retrieval of CryoSat MSS/MDT and currents circulations system improving the polar tides models and studying the coupling between blowing wind and current pattern. -High Resolution Coastal Zone Altimetry: Exploitation of the finer resolution and higher SNR of novel CryoSat SAR Data to get the radar altimetry closer to the shore exploiting the SARIn mode for the discrimination of off-nadir land targets (e.g. steep cliffs) in the radar footprint from nadir sea return. -High Resolution Sea-Floor Altimetry: Exploitation of the finer resolution and higher SNR of novel CryoSat SAR Data to resolve the weak short-wavelength sea surface signals caused by sea-floor topography elements and to map uncharted sea-mounts/trenches. One of the first project activities is the consolidation of preliminary scientific requirements for the four themes under investigation. This paper will present the CP4O project content and objectives and will address the first initial results from the on-going work to define the scientific requirements.

Using delimiting surveys to characterize the spatiotemporal dynamics facilitates the management of an invasive non-native insect

Treesearch

Patrick C. Tobin; Laura M. Blackburn; Rebecca H. Gray; Christopher T. Lettau; Andrew M. Liebhold; Kenneth F. Raffa

2013-01-01

The ability to ascertain abundance and spatial extent of a nascent population of a non-native species can inform management decisions. Following initial detection, delimiting surveys, which involve the use of a finer network of samples around the focal point of a newly detected colony, are often used to quantify colony size, spatial extent, and the location of the...

Performance measures for freight & general traffic : investigating similarities and differences using alternate data sources.

DOT National Transportation Integrated Search

2015-06-01

Recent advances in probe vehicle data collection systems have enabled monitoring traffic : conditions at finer temporal and spatial resolution. The primary objective of the current study is : to leverage these probe data sources to understand if ther...

A time series of urban extent in China using DSMP/OLS nighttime light data

PubMed Central

Chen, Dongsheng; Chen, Le; Wang, Huan; Guan, Qingfeng

2018-01-01

Urban extent data play an important role in urban management and urban studies, such as monitoring the process of urbanization and changes in the spatial configuration of urban areas. Traditional methods of extracting urban-extent information are primarily based on manual investigations and classifications using remote sensing images, and these methods have such problems as large costs in labor and time and low precision. This study proposes an improved, simplified and flexible method for extracting urban extents over multiple scales and the construction of spatiotemporal models using DMSP/OLS nighttime light (NTL) for practical situations. This method eliminates the regional temporal and spatial inconsistency of thresholding NTL in large-scale and multi-temporal scenes. Using this method, we have extracted the urban extents and calculated the corresponding areas on the county, municipal and provincial scales in China from 2000 to 2012. In addition, validation with the data of reference data shows that the overall accuracy (OA), Kappa and F1 Scores were 0.996, 0.793, and 0.782, respectively. We increased the spatial resolution of the urban extent to 500 m (approximately four times finer than the results of previous studies). Based on the urban extent dataset proposed above, we analyzed changes in urban extents over time and observed that urban sprawl has grown in all of the counties of China. We also identified three patterns of urban sprawl: Early Urban Growth, Constant Urban Growth and Recent Urban Growth. In addition, these trends of urban sprawl are consistent with the western, eastern and central cities of China, respectively, in terms of their spatial distribution, socioeconomic characteristics and historical background. Additionally, the urban extents display the spatial configurations of urban areas intuitively. The proposed urban extent dataset is available for download and can provide reference data and support for future studies of urbanization and urban planning. PMID:29795685

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation.

PubMed

Qin, Changbo; Jia, Yangwen; Su, Z; Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-07-29

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems.

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

PubMed Central

Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

2008-01-01

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946

Diagnosing isopycnal diffusivity in an eddying, idealized midlatitude ocean basin via Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT)

DOE PAGES

Wolfram, Phillip J.; Ringler, Todd D.; Maltrud, Mathew E.; ...

2015-08-01

Isopycnal diffusivity due to stirring by mesoscale eddies in an idealized, wind-forced, eddying, midlatitude ocean basin is computed using Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT). Simulation is performed via LIGHT within the Model for Prediction across Scales Ocean (MPAS-O). Simulations are performed at 4-, 8-, 16-, and 32-km resolution, where the first Rossby radius of deformation (RRD) is approximately 30 km. Scalar and tensor diffusivities are estimated at each resolution based on 30 ensemble members using particle cluster statistics. Each ensemble member is composed of 303 665 particles distributed across five potential density surfaces. Diffusivity dependence upon modelmore » resolution, velocity spatial scale, and buoyancy surface is quantified and compared with mixing length theory. The spatial structure of diffusivity ranges over approximately two orders of magnitude with values of O(10 5) m 2 s –1 in the region of western boundary current separation to O(10 3) m 2 s –1 in the eastern region of the basin. Dominant mixing occurs at scales twice the size of the first RRD. Model resolution at scales finer than the RRD is necessary to obtain sufficient model fidelity at scales between one and four RRD to accurately represent mixing. Mixing length scaling with eddy kinetic energy and the Lagrangian time scale yield mixing efficiencies that typically range between 0.4 and 0.8. In conclusion, a reduced mixing length in the eastern region of the domain relative to the west suggests there are different mixing regimes outside the baroclinic jet region.« less

Non-Invasive Methods to Characterize Soil-Plant Interactions at Different Scales

NASA Astrophysics Data System (ADS)

Javaux, M.; Kemna, A.; Muench, M.; Oberdoerster, C.; Pohlmeier, A.; Vanderborght, J.; Vereecken, H.

2006-05-01

Root water uptake is a dynamic and non-linear process, which interacts with the soil natural variability and boundary conditions to generate heterogeneous spatial distributions of soil water. Soil-root fluxes are spatially variable due to heterogeneous gradients and hydraulic connections between soil and roots. While 1-D effective representation of the root water uptake has been successfully applied to predict transpiration and average water content profiles, finer spatial characterization of the water distribution may be needed when dealing with solute transport. Indeed, root water uptake affects the water velocity field, which has an effect on solute velocity and dispersion. Although this variability originates from small-scale processes, these may still play an important role at larger scales. Therefore, in addition to investigate the variability of the soil hydraulic properties, experimental and numerical tools for characterizing root water uptake (and its effects on soil water distribution) from the pore to the field scales are needed to predict in a proper way the solute transport. Obviously, non-invasive and modeling techniques which are helpful to achieve this objective will evolve with the scale of interest. At the pore scale, soil structure and root-soil interface phenomena have to be investigated to understand the interactions between soil and roots. Magnetic resonance imaging may help to monitor water gradients and water content changes around roots while spectral induced polarization techniques may be used to characterize the structure of the pore space. At the column scale, complete root architecture of small plants and water content depletion around roots can be imaged by magnetic resonance. At that scale, models should explicitly take into account the three-dimensional gradient dependency of the root water uptake, to be able to predict solute transport. At larger scales however, simplified models, which implicitly take into account the heterogeneous root water uptake along roots, should be preferred given the complexity of the system. At such scales, electrical resistance tomography or ground-penetrating radar can be used to map the water content changes and derive effective parameters for predicting solute transport.

Motivational Differences in Seeking Out Evaluative Categorization Information.

PubMed

Smallman, Rachel; Becker, Brittney

2017-07-01

Previous research shows that people draw finer evaluative distinctions when rating liked versus disliked objects (e.g., wanting a 5-point scale to evaluate liked cuisines and a 3-point scale to rate disliked cuisines). Known as the preference-categorization effect, this pattern may exist not only in how individuals form evaluative distinctions but also in how individuals seek out evaluative information. The current research presents three experiments that examine motivational differences in evaluative information seeking (rating scales and attributes). Experiment 1 found that freedom of choice (the ability to avoid undesirable stimuli) and sensitivity to punishment (as measured by the Behavior Inhibition System/Behavioral Approach System [BIS/BAS] scale) influenced preferences for desirable and undesirable evaluative information in a health-related decision. Experiment 2 examined choice optimization, finding that maximizers prefer finer evaluative information for both liked and disliked options in a consumer task. Experiment 3 found that this pattern generalizes to another type of evaluative categorization, attributes.

Extrusion rate of the Mount St. Helens lava dome estimated from terrestrial imagery, November 2004-December 2005: Chapter 12 in A volcano rekindled: the renewed eruption of Mount St. Helens, 2004-2006

USGS Publications Warehouse

Major, Jon J.; Kingsbury, Cole G.; Poland, Michael P.; LaHusen, Richard G.; Sherrod, David R.; Scott, William E.; Stauffer, Peter H.

2008-01-01

Oblique, terrestrial imagery from a single, fixed-position camera was used to estimate linear extrusion rates during sustained exogenous growth of the Mount St. Helens lava dome from November 2004 through December 2005. During that 14-month period, extrusion rates declined logarithmically from about 8-10 m/d to about 2 m/d. The overall ebbing of effusive output was punctuated, however, by episodes of fluctuating extrusion rates that varied on scales of days to weeks. The overall decline of effusive output and finer scale rate fluctuations correlated approximately with trends in seismicity and deformation. Those correlations portray an extrusion that underwent episodic, broad-scale stick-slip behavior superposed on the finer scale, smaller magnitude stick-slip behavior that has been hypothesized by other researchers to correlate with repetitive, nearly periodic shallow earthquakes.

Shape-driven 3D segmentation using spherical wavelets.

PubMed

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

2006-01-01

This paper presents a novel active surface segmentation algorithm using a multiscale shape representation and prior. We define a parametric model of a surface using spherical wavelet functions and learn a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial locations in a training set. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior in the segmentation framework. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to the segmentation of brain caudate nucleus, of interest in the study of schizophrenia. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm by capturing finer shape details.

End of the chain? Rugosity and fine-scale bathymetry from existing underwater digital imagery using structure-from-motion (SfM) technology

USGS Publications Warehouse

Storlazzi, Curt; Dartnell, Peter; Hatcher, Gerry; Gibbs, Ann E.

2016-01-01

The rugosity or complexity of the seafloor has been shown to be an important ecological parameter for fish, algae, and corals. Historically, rugosity has been measured either using simple and subjective manual methods such as ‘chain-and-tape’ or complicated and expensive geophysical methods. Here, we demonstrate the application of structure-from-motion (SfM) photogrammetry to generate high-resolution, three-dimensional bathymetric models of a fringing reef from existing underwater video collected to characterize the seafloor. SfM techniques are capable of achieving spatial resolution that can be orders of magnitude greater than large-scale lidar and sonar mapping of coral reef ecosystems. The resulting data provide finer-scale measurements of bathymetry and rugosity that are more applicable to ecological studies of coral reefs than provided by the more expensive and time-consuming geophysical methods. Utilizing SfM techniques for characterizing the benthic habitat proved to be more effective and quantitatively powerful than conventional methods and thus might portend the end of the ‘chain-and-tape’ method for measuring benthic complexity.

Spatial information outflow from the hippocampal circuit: distributed spatial coding and phase precession in the subiculum.

PubMed

Kim, Steve M; Ganguli, Surya; Frank, Loren M

2012-08-22

Hippocampal place cells convey spatial information through a combination of spatially selective firing and theta phase precession. The way in which this information influences regions like the subiculum that receive input from the hippocampus remains unclear. The subiculum receives direct inputs from area CA1 of the hippocampus and sends divergent output projections to many other parts of the brain, so we examined the firing patterns of rat subicular neurons. We found a substantial transformation in the subicular code for space from sparse to dense firing rate representations along a proximal-distal anatomical gradient: neurons in the proximal subiculum are more similar to canonical, sparsely firing hippocampal place cells, whereas neurons in the distal subiculum have higher firing rates and more distributed spatial firing patterns. Using information theory, we found that the more distributed spatial representation in the subiculum carries, on average, more information about spatial location and context than the sparse spatial representation in CA1. Remarkably, despite the disparate firing rate properties of subicular neurons, we found that neurons at all proximal-distal locations exhibit robust theta phase precession, with similar spiking oscillation frequencies as neurons in area CA1. Our findings suggest that the subiculum is specialized to compress sparse hippocampal spatial codes into highly informative distributed codes suitable for efficient communication to other brain regions. Moreover, despite this substantial compression, the subiculum maintains finer scale temporal properties that may allow it to participate in oscillatory phase coding and spike timing-dependent plasticity in coordination with other regions of the hippocampal circuit.

Characterizing the relationship between Asian tiger mosquito abundance and habitat in urban New Jersey

NASA Astrophysics Data System (ADS)

Ferwerda, Carolin

2009-12-01

Since its introduction to North America in 1987, the Asian tiger mosquito (Aedes albopictus) has spread rapidly. Due to its unique ecology and preference for container breeding sites, Ae. albopictus commonly inhabits urban/suburban areas and is often in close contact with humans. An aggressive pest, this mosquito species is a vector of multiple arboviruses. In order for mosquito control efforts to remain effective, control of this important vector must be guided by spatially explicit habitat models that aid in predicting mosquito outbreaks. Using linear regression, I determined the relationship between adult Ae. albopictus abundance and climate, census, and land use factors in nine urban/suburban study sites in central New Jersey. Systematically collected adult counts (females and males) from July to October 2008, served as estimates of abundance. Fine-scale land use/land cover data were obtained from object-oriented classifications of 2007 CIR orthophotos in Definiens eCognition. Mosquito abundance data were tested for spatial autocorrelation via Moran's I, semivariograms, and hotspot analysis in order to reveal consistent patterns in abundance. Spatial pattern analysis produced little evidence of consistent spatial autocorrelation, though several sites exhibited recurring hotspots, especially in areas near residential housing and vegetation. Stepwise multiple regression was able to explain 20-25 percent of variation in Ae. albopictus abundance at the 'backyard' or cell level and 72-78 percent of variation in abundance at the 'neighborhood' or study site level. Meteorological variables (temperature on the trap date and precipitation), census variables (vacant housing units and population density), and more detailed land use/land cover classes (deciduous woody vegetation, rights-of-way and vacant lots) were frequently selected in all eight models, though many other independent variables were included in the individual models. The results of the spatial statistics suggest that clustering may occur at a broader extent, while the superior predictive ability of the site level models over the finer grain cell level models supports this conclusion. Future work should focus on validating these models with 2009 field data and testing whether finer grain weather and census data enhance the models' predictive ability. Given the major differences between individual county models, future studies should further explore variations in Ae. albopictus habitat preferences in different geographic locations.

Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer.

PubMed

Ashtiani, Matin N; Kheradpisheh, Saeed R; Masquelier, Timothée; Ganjtabesh, Mohammad

2017-01-01

The human visual system contains a hierarchical sequence of modules that take part in visual perception at different levels of abstraction, i.e., superordinate, basic, and subordinate levels. One important question is to identify the "entry" level at which the visual representation is commenced in the process of object recognition. For a long time, it was believed that the basic level had a temporal advantage over two others. This claim has been challenged recently. Here we used a series of psychophysics experiments, based on a rapid presentation paradigm, as well as two computational models, with bandpass filtered images of five object classes to study the processing order of the categorization levels. In these experiments, we investigated the type of visual information required for categorizing objects in each level by varying the spatial frequency bands of the input image. The results of our psychophysics experiments and computational models are consistent. They indicate that the different spatial frequency information had different effects on object categorization in each level. In the absence of high frequency information, subordinate and basic level categorization are performed less accurately, while the superordinate level is performed well. This means that low frequency information is sufficient for superordinate level, but not for the basic and subordinate levels. These finer levels rely more on high frequency information, which appears to take longer to be processed, leading to longer reaction times. Finally, to avoid the ceiling effect, we evaluated the robustness of the results by adding different amounts of noise to the input images and repeating the experiments. As expected, the categorization accuracy decreased and the reaction time increased significantly, but the trends were the same. This shows that our results are not due to a ceiling effect. The compatibility between our psychophysical and computational results suggests that the temporal advantage of the superordinate (resp. basic) level to basic (resp. subordinate) level is mainly due to the computational constraints (the visual system processes higher spatial frequencies more slowly, and categorization in finer levels depends more on these higher spatial frequencies).

Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer

PubMed Central

Ashtiani, Matin N.; Kheradpisheh, Saeed R.; Masquelier, Timothée; Ganjtabesh, Mohammad

2017-01-01

The human visual system contains a hierarchical sequence of modules that take part in visual perception at different levels of abstraction, i.e., superordinate, basic, and subordinate levels. One important question is to identify the “entry” level at which the visual representation is commenced in the process of object recognition. For a long time, it was believed that the basic level had a temporal advantage over two others. This claim has been challenged recently. Here we used a series of psychophysics experiments, based on a rapid presentation paradigm, as well as two computational models, with bandpass filtered images of five object classes to study the processing order of the categorization levels. In these experiments, we investigated the type of visual information required for categorizing objects in each level by varying the spatial frequency bands of the input image. The results of our psychophysics experiments and computational models are consistent. They indicate that the different spatial frequency information had different effects on object categorization in each level. In the absence of high frequency information, subordinate and basic level categorization are performed less accurately, while the superordinate level is performed well. This means that low frequency information is sufficient for superordinate level, but not for the basic and subordinate levels. These finer levels rely more on high frequency information, which appears to take longer to be processed, leading to longer reaction times. Finally, to avoid the ceiling effect, we evaluated the robustness of the results by adding different amounts of noise to the input images and repeating the experiments. As expected, the categorization accuracy decreased and the reaction time increased significantly, but the trends were the same. This shows that our results are not due to a ceiling effect. The compatibility between our psychophysical and computational results suggests that the temporal advantage of the superordinate (resp. basic) level to basic (resp. subordinate) level is mainly due to the computational constraints (the visual system processes higher spatial frequencies more slowly, and categorization in finer levels depends more on these higher spatial frequencies). PMID:28790954

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

PubMed

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

2017-07-01

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

Muscle Functional Morphology in Paleobiology: The Past, Present, and Future of "Paleomyology".

PubMed

Perry, Jonathan M G; Prufrock, Kristen A

2018-03-01

Our knowledge of muscle anatomy and physiology in vertebrates has increased dramatically over the last two-hundred years. Today, much is understood about how muscles contract and about the functional meaning of muscular variation at multiple scales. Progress in muscle anatomy has profited from the availability of broad comparative samples, advances in microscopy have permitted comparisons at increasingly finer scales, and progress in muscle physiology has profited from many carefully designed and executed experiments. Several avenues of future work are promising. In particular, muscle ontogeny (growth and development) is poorly understood for many vertebrate groups. We consider which types of advances in muscle functional morphology are of use to paleobiologists. These are only a modest subset for muscle anatomy and a very small subset for muscle physiology. The relationship between muscle and bone - spatially and mechanically-is critical to any future advances in "paleomyology". Anat Rec, 301:538-555, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Using adaptive-mesh refinement in SCFT simulations of surfactant adsorption

NASA Astrophysics Data System (ADS)

Sides, Scott; Kumar, Rajeev; Jamroz, Ben; Crockett, Robert; Pletzer, Alex

2013-03-01

Adsorption of surfactants at interfaces is relevant to many applications such as detergents, adhesives, emulsions and ferrofluids. Atomistic simulations of interface adsorption are challenging due to the difficulty of modeling the wide range of length scales in these problems: the thin interface region in equilibrium with a large bulk region that serves as a reservoir for the adsorbed species. Self-consistent field theory (SCFT) has been extremely useful for studying the morphologies of dense block copolymer melts. Field-theoretic simulations such as these are able to access large length and time scales that are difficult or impossible for particle-based simulations such as molecular dynamics. However, even SCFT methods can be difficult to apply to systems in which small spatial regions might require finer resolution than most of the simulation grid (eg. interface adsorption and confinement). We will present results on interface adsorption simulations using PolySwift++, an object-oriented, polymer SCFT simulation code aided by the Tech-X Chompst library that enables via block-structured AMR calculations with PETSc.

Microtopographic and depth controls on active layer chemistry in Arctic polygonal ground

DOE PAGES

Newman, Brent D.; Throckmorton, Heather M.; Graham, David E.; ...

2015-03-24

Polygonal ground is a signature characteristic of Arctic lowlands, and carbon release from permafrost thaw can alter feedbacks to Arctic ecosystems and climate. This study describes the first comprehensive spatial examination of active layer biogeochemistry that extends across high- and low-centered, ice wedge polygons, their features, and with depth. Water chemistry measurements of 54 analytes were made on surface and active layer pore waters collected near Barrow, Alaska, USA. Significant differences were observed between high- and low-centered polygons suggesting that polygon types may be useful for landscape-scale geochemical classification. However, differences were found for polygon features (centers and troughs) formore » analytes that were not significant for polygon type, suggesting that finer-scale features affect biogeochemistry differently from polygon types. Depth variations were also significant, demonstrating important multidimensional aspects of polygonal ground biogeochemistry. These results have major implications for understanding how polygonal ground ecosystems function, and how they may respond to future change.« less

Footprint Characteristics of Cosmic-Ray Neutron Sensors for Soil Moisture Monitoring

NASA Astrophysics Data System (ADS)

Schrön, Martin; Köhli, Markus; Zreda, Marek; Dietrich, Peter; Zacharias, Steffen

2015-04-01

Cosmic-ray neutron sensing is a unique and an increasingly accepted method to monitor the effective soil water content at the field scale. The technology is famous for its low maintenance, non-invasiveness, continuous measurement, and most importantly, for its large footprint. Being more representative than point data and finer resolved than remote-sensing products, cosmic-ray neutron derived soil moisture products provide unrivaled advantage for mesoscale hydrologic and land surface models. The method takes advantage of neutrons induced by cosmic radiation which are extraordinarily sensitive to hydrogen and behave like a hot gas. Information about nearby water sources are quickly mixed in a domain of tens of hectares in air. Since experimental determination of the actual spatial extent is hardly possible, scientists have applied numerical models to address the footprint characteristics. We have revisited previous neutron transport simulations and present a modified conceptual design and refined physical assumptions. Our revised study reveals new insights into probing distance and water sensitivity of detected neutrons under various environmental conditions. These results sharpen the range of interpretation concerning the spatial extent of integral soil moisture products derived from cosmic-ray neutron counts. Our findings will have important impact on calibration strategies, on scales for data assimilation and on the interpolation of soil moisture data derived from mobile cosmic-ray neutron surveys.

Scaling Optimization of the SIESTA MHD Code

NASA Astrophysics Data System (ADS)

Seal, Sudip; Hirshman, Steven; Perumalla, Kalyan

2013-10-01

SIESTA is a parallel three-dimensional plasma equilibrium code capable of resolving magnetic islands at high spatial resolutions for toroidal plasmas. Originally designed to exploit small-scale parallelism, SIESTA has now been scaled to execute efficiently over several thousands of processors P. This scaling improvement was accomplished with minimal intrusion to the execution flow of the original version. First, the efficiency of the iterative solutions was improved by integrating the parallel tridiagonal block solver code BCYCLIC. Krylov-space generation in GMRES was then accelerated using a customized parallel matrix-vector multiplication algorithm. Novel parallel Hessian generation algorithms were integrated and memory access latencies were dramatically reduced through loop nest optimizations and data layout rearrangement. These optimizations sped up equilibria calculations by factors of 30-50. It is possible to compute solutions with granularity N/P near unity on extremely fine radial meshes (N > 1024 points). Grid separation in SIESTA, which manifests itself primarily in the resonant components of the pressure far from rational surfaces, is strongly suppressed by finer meshes. Large problem sizes of up to 300 K simultaneous non-linear coupled equations have been solved on the NERSC supercomputers. Work supported by U.S. DOE under Contract DE-AC05-00OR22725 with UT-Battelle, LLC.

Predicted deep-sea coral habitat suitability for the U.S. West coast.

PubMed

Guinotte, John M; Davies, Andrew J

2014-01-01

Regional scale habitat suitability models provide finer scale resolution and more focused predictions of where organisms may occur. Previous modelling approaches have focused primarily on local and/or global scales, while regional scale models have been relatively few. In this study, regional scale predictive habitat models are presented for deep-sea corals for the U.S. West Coast (California, Oregon and Washington). Model results are intended to aid in future research or mapping efforts and to assess potential coral habitat suitability both within and outside existing bottom trawl closures (i.e. Essential Fish Habitat (EFH)) and identify suitable habitat within U.S. National Marine Sanctuaries (NMS). Deep-sea coral habitat suitability was modelled at 500 m×500 m spatial resolution using a range of physical, chemical and environmental variables known or thought to influence the distribution of deep-sea corals. Using a spatial partitioning cross-validation approach, maximum entropy models identified slope, temperature, salinity and depth as important predictors for most deep-sea coral taxa. Large areas of highly suitable deep-sea coral habitat were predicted both within and outside of existing bottom trawl closures and NMS boundaries. Predicted habitat suitability over regional scales are not currently able to identify coral areas with pin point accuracy and probably overpredict actual coral distribution due to model limitations and unincorporated variables (i.e. data on distribution of hard substrate) that are known to limit their distribution. Predicted habitat results should be used in conjunction with multibeam bathymetry, geological mapping and other tools to guide future research efforts to areas with the highest probability of harboring deep-sea corals. Field validation of predicted habitat is needed to quantify model accuracy, particularly in areas that have not been sampled.

Predicted Deep-Sea Coral Habitat Suitability for the U.S. West Coast

PubMed Central

Guinotte, John M.; Davies, Andrew J.

2014-01-01

Regional scale habitat suitability models provide finer scale resolution and more focused predictions of where organisms may occur. Previous modelling approaches have focused primarily on local and/or global scales, while regional scale models have been relatively few. In this study, regional scale predictive habitat models are presented for deep-sea corals for the U.S. West Coast (California, Oregon and Washington). Model results are intended to aid in future research or mapping efforts and to assess potential coral habitat suitability both within and outside existing bottom trawl closures (i.e. Essential Fish Habitat (EFH)) and identify suitable habitat within U.S. National Marine Sanctuaries (NMS). Deep-sea coral habitat suitability was modelled at 500 m×500 m spatial resolution using a range of physical, chemical and environmental variables known or thought to influence the distribution of deep-sea corals. Using a spatial partitioning cross-validation approach, maximum entropy models identified slope, temperature, salinity and depth as important predictors for most deep-sea coral taxa. Large areas of highly suitable deep-sea coral habitat were predicted both within and outside of existing bottom trawl closures and NMS boundaries. Predicted habitat suitability over regional scales are not currently able to identify coral areas with pin point accuracy and probably overpredict actual coral distribution due to model limitations and unincorporated variables (i.e. data on distribution of hard substrate) that are known to limit their distribution. Predicted habitat results should be used in conjunction with multibeam bathymetry, geological mapping and other tools to guide future research efforts to areas with the highest probability of harboring deep-sea corals. Field validation of predicted habitat is needed to quantify model accuracy, particularly in areas that have not been sampled. PMID:24759613

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.

Spatial Variability of Wet Troposphere Delays Over Inland Water Bodies

NASA Astrophysics Data System (ADS)

Mehran, Ali; Clark, Elizabeth A.; Lettenmaier, Dennis P.

2017-11-01

Satellite radar altimetry has enabled the study of water levels in large lakes and reservoirs at a global scale. The upcoming Surface Water and Ocean Topography (SWOT) satellite mission (scheduled launch 2020) will simultaneously measure water surface extent and elevation at an unprecedented accuracy and resolution. However, SWOT retrieval accuracy will be affected by a number of factors, including wet tropospheric delay—the delay in the signal's passage through the atmosphere due to atmospheric water content. In past applications, the wet tropospheric delay over large inland water bodies has been corrected using atmospheric moisture profiles based on atmospheric reanalysis data at relatively coarse (tens to hundreds of kilometers) spatial resolution. These products cannot resolve subgrid variations in wet tropospheric delays at the spatial resolutions (of 1 km and finer) that SWOT is intended to resolve. We calculate zenith wet tropospheric delays (ZWDs) and their spatial variability from Weather Research and Forecasting (WRF) numerical weather prediction model simulations at 2.33 km spatial resolution over the southwestern U.S., with attention in particular to Sam Rayburn, Ray Hubbard, and Elephant Butte Reservoirs which have width and length dimensions that are of order or larger than the WRF spatial resolution. We find that spatiotemporal variability of ZWD over the inland reservoirs depends on climatic conditions at the reservoir location, as well as distance from ocean, elevation, and surface area of the reservoir, but that the magnitude of subgrid variability (relative to analysis and reanalysis products) is generally less than 10 mm.

Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system

USGS Publications Warehouse

Bastille-Rousseau, Guillaume; Gibbs, James P.; Yackulic, Charles B.; Frair, Jacqueline L.; Cabrera, Fredy; Rousseau, Louis-Philippe

2016-01-01

Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad-scale spatial-temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter-annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi-scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter-annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 106 tortoise re-locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio-temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non-migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large-scale predictions for movement strategies, based on environmental structuring, with finer-scale analysis of space-use. Integrating different organizational levels of analysis provides a deeper understanding of the eco-evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics.

Mesoscale data assimilation for a local severe rainfall event with the NHM-LETKF system

NASA Astrophysics Data System (ADS)

Kunii, M.

2013-12-01

This study aims to improve forecasts of local severe weather events through data assimilation and ensemble forecasting approaches. Here, the local ensemble transform Kalman filter (LETKF) is implemented with the Japan Meteorological Agency's nonhydrostatic model (NHM). The newly developed NHM-LETKF contains an adaptive inflation scheme and a spatial covariance localization scheme with physical distance. One-way nested analysis in which a finer-resolution LETKF is conducted by using the outputs of an outer model also becomes feasible. These new contents should enhance the potential of the LETKF for convective scale events. The NHM-LETKF is applied to a local severe rainfall event in Japan in 2012. Comparison of the root mean square errors between the model first guess and analysis reveals that the system assimilates observations appropriately. Analysis ensemble spreads indicate a significant increase around the time torrential rainfall occurred, which would imply an increase in the uncertainty of environmental fields. Forecasts initialized with LETKF analyses successfully capture intense rainfalls, suggesting that the system can work effectively for local severe weather. Investigation of probabilistic forecasts by ensemble forecasting indicates that this could become a reliable data source for decision making in the future. A one-way nested data assimilation scheme is also tested. The experiment results demonstrate that assimilation with a finer-resolution model provides an advantage in the quantitative precipitation forecasting of local severe weather conditions.

Accounting for groundwater in stream fish thermal habitat responses to climate change

USGS Publications Warehouse

Snyder, Craig D.; Hitt, Nathaniel P.; Young, John A.

2015-01-01

Forecasting climate change effects on aquatic fauna and their habitat requires an understanding of how water temperature responds to changing air temperature (i.e., thermal sensitivity). Previous efforts to forecast climate effects on brook trout habitat have generally assumed uniform air-water temperature relationships over large areas that cannot account for groundwater inputs and other processes that operate at finer spatial scales. We developed regression models that accounted for groundwater influences on thermal sensitivity from measured air-water temperature relationships within forested watersheds in eastern North America (Shenandoah National Park, USA, 78 sites in 9 watersheds). We used these reach-scale models to forecast climate change effects on stream temperature and brook trout thermal habitat, and compared our results to previous forecasts based upon large-scale models. Observed stream temperatures were generally less sensitive to air temperature than previously assumed, and we attribute this to the moderating effect of shallow groundwater inputs. Predicted groundwater temperatures from air-water regression models corresponded well to observed groundwater temperatures elsewhere in the study area. Predictions of brook trout future habitat loss derived from our fine-grained models were far less pessimistic than those from prior models developed at coarser spatial resolutions. However, our models also revealed spatial variation in thermal sensitivity within and among catchments resulting in a patchy distribution of thermally suitable habitat. Habitat fragmentation due to thermal barriers therefore may have an increasingly important role for trout population viability in headwater streams. Our results demonstrate that simple adjustments to air-water temperature regression models can provide a powerful and cost-effective approach for predicting future stream temperatures while accounting for effects of groundwater.

Assessment of habitat representation across a network of marine protected areas with implications for the spatial design of monitoring.

PubMed

Young, Mary; Carr, Mark

2015-01-01

Networks of marine protected areas (MPAs) are being adopted globally to protect ecosystems and supplement fisheries management. The state of California recently implemented a coast-wide network of MPAs, a statewide seafloor mapping program, and ecological characterizations of species and ecosystems targeted for protection by the network. The main goals of this study were to use these data to evaluate how well seafloor features, as proxies for habitats, are represented and replicated across an MPA network and how well ecological surveys representatively sampled fish habitats inside MPAs and adjacent reference sites. Seafloor data were classified into broad substrate categories (rock and sediment) and finer scale geomorphic classifications standard to marine classification schemes using surface analyses (slope, ruggedness, etc.) done on the digital elevation model derived from multibeam bathymetry data. These classifications were then used to evaluate the representation and replication of seafloor structure within the MPAs and across the ecological surveys. Both the broad substrate categories and the finer scale geomorphic features were proportionately represented for many of the classes with deviations of 1-6% and 0-7%, respectively. Within MPAs, however, representation of seafloor features differed markedly from original estimates, with differences ranging up to 28%. Seafloor structure in the biological monitoring design had mismatches between sampling in the MPAs and their corresponding reference sites and some seafloor structure classes were missed entirely. The geomorphic variables derived from multibeam bathymetry data for these analyses are known determinants of the distribution and abundance of marine species and for coastal marine biodiversity. Thus, analyses like those performed in this study can be a valuable initial method of evaluating and predicting the conservation value of MPAs across a regional network.

Assessment of Habitat Representation across a Network of Marine Protected Areas with Implications for the Spatial Design of Monitoring

PubMed Central

Young, Mary; Carr, Mark

2015-01-01

Networks of marine protected areas (MPAs) are being adopted globally to protect ecosystems and supplement fisheries management. The state of California recently implemented a coast-wide network of MPAs, a statewide seafloor mapping program, and ecological characterizations of species and ecosystems targeted for protection by the network. The main goals of this study were to use these data to evaluate how well seafloor features, as proxies for habitats, are represented and replicated across an MPA network and how well ecological surveys representatively sampled fish habitats inside MPAs and adjacent reference sites. Seafloor data were classified into broad substrate categories (rock and sediment) and finer scale geomorphic classifications standard to marine classification schemes using surface analyses (slope, ruggedness, etc.) done on the digital elevation model derived from multibeam bathymetry data. These classifications were then used to evaluate the representation and replication of seafloor structure within the MPAs and across the ecological surveys. Both the broad substrate categories and the finer scale geomorphic features were proportionately represented for many of the classes with deviations of 1-6% and 0-7%, respectively. Within MPAs, however, representation of seafloor features differed markedly from original estimates, with differences ranging up to 28%. Seafloor structure in the biological monitoring design had mismatches between sampling in the MPAs and their corresponding reference sites and some seafloor structure classes were missed entirely. The geomorphic variables derived from multibeam bathymetry data for these analyses are known determinants of the distribution and abundance of marine species and for coastal marine biodiversity. Thus, analyses like those performed in this study can be a valuable initial method of evaluating and predicting the conservation value of MPAs across a regional network. PMID:25760858

Assessing exotic plant species invasions and associated soil characteristics: A case study in eastern Rocky Mountain National Park, Colorado, USA, using the pixel nested plot design

USGS Publications Warehouse

Kalkhan, M.A.; Stafford, E.J.; Woodly, P.J.; Stohlgren, T.J.

2007-01-01

Rocky Mountain National Park (RMNP), Colorado, USA, contains a diversity of plant species. However, many exotic plant species have become established, potentially impacting the structure and function of native plant communities. Our goal was to quantify patterns of exotic plant species in relation to native plant species, soil characteristics, and other abiotic factors that may indicate or predict their establishment and success. Our research approach for field data collection was based on a field plot design called the pixel nested plot. The pixel nested plot provides a link to multi-phase and multi-scale spatial modeling-mapping techniques that can be used to estimate total species richness and patterns of plant diversity at finer landscape scales. Within the eastern region of RMNP, in an area of approximately 35,000 ha, we established a total of 60 pixel nested plots in 9 vegetation types. We used canonical correspondence analysis (CCA) and multiple linear regressions to quantify relationships between soil characteristics and native and exotic plant species richness and cover. We also used linear correlation, spatial autocorrelation and cross correlation statistics to test for the spatial patterns of variables of interest. CCA showed that exotic species were significantly (P < 0.05) associated with photosynthetically active radiation (r = 0.55), soil nitrogen (r = 0.58) and bare ground (r = -0.66). Pearson's correlation statistic showed significant linear relationships between exotic species, organic carbon, soil nitrogen, and bare ground. While spatial autocorrelations indicated that our 60 pixel nested plots were spatially independent, the cross correlation statistics indicated that exotic plant species were spatially associated with bare ground, in general, exotic plant species were most abundant in areas of high native species richness. This indicates that resource managers should focus on the protection of relatively rare native rich sites with little canopy cover, and fertile soils. Using the pixel nested plot approach for data collection can facilitate the ecological monitoring of these vulnerable areas at the landscape scale in a time- and cost-effective manner. ?? 2006 Elsevier B.V. All rights reserved.

Thoughts on Scale

ERIC Educational Resources Information Center

Schoenfeld, Alan H.

2015-01-01

This essay reflects on the challenges of thinking about scale--of making sense of phenomena such as continuous professional development (CPD) at the system level, while holding on to detail at the finer grain size(s) of implementation. The stimuli for my reflections are three diverse studies of attempts at scale--an attempt to use ideas related to…

Using an Ecological Land Hierarchy to Predict Seasonal-Wetland Abundance in Upland Forests

Treesearch

Brian J. Palik; Richard Buech; Leanne Egeland

2003-01-01

Hierarchy theory, when applied to landscapes, predicts that broader-scale ecosystems constrain the development of finer-scale, nested ecosystems. This prediction finds application in hierarchical land classifications. Such classifications typically apply to physiognomically similar ecosystems, or ecological land units, e.g., a set of multi-scale forest ecosystems. We...

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.

Evaluation of remotely sensed actual evapotranspiration data for modeling small scale irrigation in Ethiopia.

NASA Astrophysics Data System (ADS)

Taddele, Y. D.; Ayana, E.; Worqlul, A. W.; Srinivasan, R.; Gerik, T.; Clarke, N.

2017-12-01

The research presented in this paper is conducted in Ethiopia, which is located in the horn of Africa. Ethiopian economy largely depends on rainfed agriculture, which employs 80% of the labor force. The rainfed agriculture is frequently affected by droughts and dry spells. Small scale irrigation is considered as the lifeline for the livelihoods of smallholder farmers in Ethiopia. Biophysical models are highly used to determine the agricultural production, environmental sustainability, and socio-economic outcomes of small scale irrigation in Ethiopia. However, detailed spatially explicit data is not adequately available to calibrate and validate simulations from biophysical models. The Soil and Water Assessment Tool (SWAT) model was setup using finer resolution spatial and temporal data. The actual evapotranspiration (AET) estimation from the SWAT model was compared with two remotely sensed data, namely the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectrometer (MODIS). The performance of the monthly satellite data was evaluated with correlation coefficient (R2) over the different land use groups. The result indicated that over the long term and monthly the AVHRR AET captures the pattern of SWAT simulated AET reasonably well, especially on agricultural dominated landscapes. A comparison between SWAT simulated AET and AVHRR AET provided mixed results on grassland dominated landscapes and poor agreement on forest dominated landscapes. Results showed that the AVHRR AET products showed superior agreement with the SWAT simulated AET than MODIS AET. This suggests that remotely sensed products can be used as valuable tool in properly modeling small scale irrigation.

Using variance structure to quantify responses to perturbation in fish catches

USGS Publications Warehouse

Vidal, Tiffany E.; Irwin, Brian J.; Wagner, Tyler; Rudstam, Lars G.; Jackson, James R.; Bence, James R.

2017-01-01

We present a case study evaluation of gill-net catches of Walleye Sander vitreus to assess potential effects of large-scale changes in Oneida Lake, New York, including the disruption of trophic interactions by double-crested cormorants Phalacrocorax auritus and invasive dreissenid mussels. We used the empirical long-term gill-net time series and a negative binomial linear mixed model to partition the variability in catches into spatial and coherent temporal variance components, hypothesizing that variance partitioning can help quantify spatiotemporal variability and determine whether variance structure differs before and after large-scale perturbations. We found that the mean catch and the total variability of catches decreased following perturbation but that not all sampling locations responded in a consistent manner. There was also evidence of some spatial homogenization concurrent with a restructuring of the relative productivity of individual sites. Specifically, offshore sites generally became more productive following the estimated break point in the gill-net time series. These results provide support for the idea that variance structure is responsive to large-scale perturbations; therefore, variance components have potential utility as statistical indicators of response to a changing environment more broadly. The modeling approach described herein is flexible and would be transferable to other systems and metrics. For example, variance partitioning could be used to examine responses to alternative management regimes, to compare variability across physiographic regions, and to describe differences among climate zones. Understanding how individual variance components respond to perturbation may yield finer-scale insights into ecological shifts than focusing on patterns in the mean responses or total variability alone.

Evaluating historical climate and hydrologic trends in the Central Appalachian region of the United States

NASA Astrophysics Data System (ADS)

Gaertner, B. A.; Zegre, N.

2015-12-01

Climate change is surfacing as one of the most important environmental and social issues of the 21st century. Over the last 100 years, observations show increasing trends in global temperatures and intensity and frequency of precipitation events such as flooding, drought, and extreme storms. Global circulation models (GCM) show similar trends for historic and future climate indicators, albeit with geographic and topographic variability at regional and local scale. In order to assess the utility of GCM projections for hydrologic modeling, it is important to quantify how robust GCM outputs are compared to robust historical observations at finer spatial scales. Previous research in the United States has primarily focused on the Western and Northeastern regions due to dominance of snow melt for runoff and aquifer recharge but the impact of climate warming in the mountainous central Appalachian Region is poorly understood. In this research, we assess the performance of GCM-generated historical climate compared to historical observations primarily in the context of forcing data for macro-scale hydrologic modeling. Our results show significant spatial heterogeneity of modeled climate indices when compared to observational trends at the watershed scale. Observational data is showing considerable variability within maximum temperature and precipitation trends, with consistent increases in minimum temperature. The geographic, temperature, and complex topographic gradient throughout the central Appalachian region is likely the contributing factor in temperature and precipitation variability. Variable climate changes are leading to more severe and frequent climate events such as temperature extremes and storm events, which can have significant impacts on our drinking water supply, infrastructure, and health of all downstream communities.

Scanning Backscatter Lidar Observations for Characterizing 4-D Cloud and Aerosol Fields to Improve Radiative Transfer Parameterizations

NASA Technical Reports Server (NTRS)

Schwemmer, Geary K.; Miller, David O.

2005-01-01

Clouds have a powerful influence on atmospheric radiative transfer and hence are crucial to understanding and interpreting the exchange of radiation between the Earth's surface, the atmosphere, and space. Because clouds are highly variable in space, time and physical makeup, it is important to be able to observe them in three dimensions (3-D) with sufficient resolution that the data can be used to generate and validate parameterizations of cloud fields at the resolution scale of global climate models (GCMs). Simulation of photon transport in three dimensionally inhomogeneous cloud fields show that spatial inhomogeneities tend to decrease cloud reflection and absorption and increase direct and diffuse transmission, Therefore it is an important task to characterize cloud spatial structures in three dimensions on the scale of GCM grid elements. In order to validate cloud parameterizations that represent the ensemble, or mean and variance of cloud properties within a GCM grid element, measurements of the parameters must be obtained on a much finer scale so that the statistics on those measurements are truly representative. High spatial sampling resolution is required, on the order of 1 km or less. Since the radiation fields respond almost instantaneously to changes in the cloud field, and clouds changes occur on scales of seconds and less when viewed on scales of approximately 100m, the temporal resolution of cloud properties should be measured and characterized on second time scales. GCM time steps are typically on the order of an hour, but in order to obtain sufficient statistical representations of cloud properties in the parameterizations that are used as model inputs, averaged values of cloud properties should be calculated on time scales on the order of 10-100 s. The Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE) provides exceptional temporal (100 ms) and spatial (30 m) resolution measurements of aerosol and cloud backscatter in three dimensions. HARLIE was used in a ground-based configuration in several recent field campaigns. Principal data products include aerosol backscatter profiles, boundary layer heights, entrainment zone thickness, cloud fraction as a function of altitude and horizontal wind vector profiles based on correlating the motions of clouds and aerosol structures across portions of the scan. Comparisons will be made between various cloud detecting instruments to develop a baseline performance metric.

A Structure-Based Distance Metric for High-Dimensional Space Exploration with Multi-Dimensional Scaling

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

Lee, Hyun Jung; McDonnell, Kevin T.; Zelenyuk, Alla

2014-03-01

Although the Euclidean distance does well in measuring data distances within high-dimensional clusters, it does poorly when it comes to gauging inter-cluster distances. This significantly impacts the quality of global, low-dimensional space embedding procedures such as the popular multi-dimensional scaling (MDS) where one can often observe non-intuitive layouts. We were inspired by the perceptual processes evoked in the method of parallel coordinates which enables users to visually aggregate the data by the patterns the polylines exhibit across the dimension axes. We call the path of such a polyline its structure and suggest a metric that captures this structure directly inmore » high-dimensional space. This allows us to better gauge the distances of spatially distant data constellations and so achieve data aggregations in MDS plots that are more cognizant of existing high-dimensional structure similarities. Our MDS plots also exhibit similar visual relationships as the method of parallel coordinates which is often used alongside to visualize the high-dimensional data in raw form. We then cast our metric into a bi-scale framework which distinguishes far-distances from near-distances. The coarser scale uses the structural similarity metric to separate data aggregates obtained by prior classification or clustering, while the finer scale employs the appropriate Euclidean distance.« less

Shape-Driven 3D Segmentation Using Spherical Wavelets

PubMed Central

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

2013-01-01

This paper presents a novel active surface segmentation algorithm using a multiscale shape representation and prior. We define a parametric model of a surface using spherical wavelet functions and learn a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial locations in a training set. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior in the segmentation framework. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to the segmentation of brain caudate nucleus, of interest in the study of schizophrenia. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm by capturing finer shape details. PMID:17354875

Spatial analysis and land use regression of VOCs and NO(2) from school-based urban air monitoring in Detroit/Dearborn, USA.

PubMed

Mukerjee, Shaibal; Smith, Luther A; Johnson, Mary M; Neas, Lucas M; Stallings, Casson A

2009-08-01

Passive ambient air sampling for nitrogen dioxide (NO(2)) and volatile organic compounds (VOCs) was conducted at 25 school and two compliance sites in Detroit and Dearborn, Michigan, USA during the summer of 2005. Geographic Information System (GIS) data were calculated at each of 116 schools. The 25 selected schools were monitored to assess and model intra-urban gradients of air pollutants to evaluate impact of traffic and urban emissions on pollutant levels. Schools were chosen to be statistically representative of urban land use variables such as distance to major roadways, traffic intensity around the schools, distance to nearest point sources, population density, and distance to nearest border crossing. Two approaches were used to investigate spatial variability. First, Kruskal-Wallis analyses and pairwise comparisons on data from the schools examined coarse spatial differences based on city section and distance from heavily trafficked roads. Secondly, spatial variation on a finer scale and as a response to multiple factors was evaluated through land use regression (LUR) models via multiple linear regression. For weeklong exposures, VOCs did not exhibit spatial variability by city section or distance from major roads; NO(2) was significantly elevated in a section dominated by traffic and industrial influence versus a residential section. Somewhat in contrast to coarse spatial analyses, LUR results revealed spatial gradients in NO(2) and selected VOCs across the area. The process used to select spatially representative sites for air sampling and the results of coarse and fine spatial variability of air pollutants provide insights that may guide future air quality studies in assessing intra-urban gradients.

The need to consider temporal variability when modelling exchange at the sediment-water interface

USGS Publications Warehouse

Rosenberry, Donald O.

2011-01-01

Most conceptual or numerical models of flows and processes at the sediment-water interface assume steady-state conditions and do not consider temporal variability. The steady-state assumption is required because temporal variability, if quantified at all, is usually determined on a seasonal or inter-annual scale. In order to design models that can incorporate finer-scale temporal resolution we first need to measure variability at a finer scale. Automated seepage meters that can measure flow across the sediment-water interface with temporal resolution of seconds to minutes were used in a variety of settings to characterize seepage response to rainfall, wind, and evapotranspiration. Results indicate that instantaneous seepage fluxes can be much larger than values commonly reported in the literature, although seepage does not always respond to hydrological processes. Additional study is needed to understand the reasons for the wide range and types of responses to these hydrologic and atmospheric events.

Spatial and temporal dynamics of commercial reef-fish fisheries on the West Florida Shelf: Understanding drivers of fleet behavior and the implications for future management

NASA Astrophysics Data System (ADS)

Cockrell, M.; Murawski, S. A.; Sanchirico, J. N.; O'Farrell, S.; Strelcheck, A.

2016-02-01

Spatial and temporal patterns of fishing activity have historically been described over relatively coarse scales or with limited datasets. However, new and innovative approaches for fisheries management will require an understanding of both species population dynamics and fleet behavior at finer spatial and temporal resolution. In this study we describe the spatial and temporal patterns of commercial reef-fish fisheries on the West Florida Shelf (WFS) from 2006-14, using a combination of on-board observer, catch logbook, and vessel satellite tracking data. The satellite tracking data is both high resolution (ie, records from each vessel at least once every hour for the duration of a trip), and required of all federally-permitted reef fish vessels in the Gulf of Mexico, making this a uniquely rich and powerful dataset. Along with spatial and temporal fishery dynamics, we quantified concomitant patterns in fishery economics and catch metrics, such as total landings and catch composition. Fishery patterns were correlated to a number of variables across the vessel, trip, and whole fleet scales, including vessel size, distance from home port, number of days at sea, and days available to fish. Notably, changes in management structure during the years examined (eg, establishment of a seasonal closed area in 2009 and implementation of an individual fishing quota system for Grouper-Tilefish in 2010), as well as emergency spatial closures during the Deepwater Horizon oil spill in 2010, enabled us to examine the impacts of specific management frameworks on the WFS reef-fish fishery. This research highlights the need to better understand the biological, economic, and social impacts within fisheries when managing for conservation and fisheries sustainability. We discuss our results in the context of a changing policy and management landscape for marine and coastal resources in the Gulf of Mexico.

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

NASA Astrophysics Data System (ADS)

Larson, T.

2010-12-01

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

Rapid Effects of Marine Reserves via Larval Dispersal

PubMed Central

Cudney-Bueno, Richard; Lavín, Miguel F.; Marinone, Silvio G.; Raimondi, Peter T.; Shaw, William W.

2009-01-01

Marine reserves have been advocated worldwide as conservation and fishery management tools. It is argued that they can protect ecosystems and also benefit fisheries via density-dependent spillover of adults and enhanced larval dispersal into fishing areas. However, while evidence has shown that marine reserves can meet conservation targets, their effects on fisheries are less understood. In particular, the basic question of if and over what temporal and spatial scales reserves can benefit fished populations via larval dispersal remains unanswered. We tested predictions of a larval transport model for a marine reserve network in the Gulf of California, Mexico, via field oceanography and repeated density counts of recently settled juvenile commercial mollusks before and after reserve establishment. We show that local retention of larvae within a reserve network can take place with enhanced, but spatially-explicit, recruitment to local fisheries. Enhancement occurred rapidly (2 yrs), with up to a three-fold increase in density of juveniles found in fished areas at the downstream edge of the reserve network, but other fishing areas within the network were unaffected. These findings were consistent with our model predictions. Our findings underscore the potential benefits of protecting larval sources and show that enhancement in recruitment can be manifested rapidly. However, benefits can be markedly variable within a local seascape. Hence, effects of marine reserve networks, positive or negative, may be overlooked when only focusing on overall responses and not considering finer spatially-explicit responses within a reserve network and its adjacent fishing grounds. Our results therefore call for future research on marine reserves that addresses this variability in order to help frame appropriate scenarios for the spatial management scales of interest. PMID:19129910

mizuRoute version 1: A river network routing tool for a continental domain water resources applications

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Sampson, Kevin; Nijssen, Bart; Mao, Yixin; McMillan, Hilary; Viger, Roland; Markstrom, Steven; Hay, Lauren E.; Woods, Ross; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

This paper describes the first version of a stand-alone runoff routing tool, mizuRoute. The mizuRoute tool post-processes runoff outputs from any distributed hydrologic model or land surface model to produce spatially distributed streamflow at various spatial scales from headwater basins to continental-wide river systems. The tool can utilize both traditional grid-based river network and vector-based river network data. Both types of river network include river segment lines and the associated drainage basin polygons, but the vector-based river network can represent finer-scale river lines than the grid-based network. Streamflow estimates at any desired location in the river network can be easily extracted from the output of mizuRoute. The routing process is simulated as two separate steps. First, hillslope routing is performed with a gamma-distribution-based unit-hydrograph to transport runoff from a hillslope to a catchment outlet. The second step is river channel routing, which is performed with one of two routing scheme options: (1) a kinematic wave tracking (KWT) routing procedure; and (2) an impulse response function – unit-hydrograph (IRF-UH) routing procedure. The mizuRoute tool also includes scripts (python, NetCDF operators) to pre-process spatial river network data. This paper demonstrates mizuRoute's capabilities to produce spatially distributed streamflow simulations based on river networks from the United States Geological Survey (USGS) Geospatial Fabric (GF) data set in which over 54 000 river segments and their contributing areas are mapped across the contiguous United States (CONUS). A brief analysis of model parameter sensitivity is also provided. The mizuRoute tool can assist model-based water resources assessments including studies of the impacts of climate change on streamflow.

Impact of high-resolution a priori profiles on satellite-based formaldehyde retrievals

NASA Astrophysics Data System (ADS)

Kim, Si-Wan; Natraj, Vijay; Lee, Seoyoung; Kwon, Hyeong-Ahn; Park, Rokjin; de Gouw, Joost; Frost, Gregory; Kim, Jhoon; Stutz, Jochen; Trainer, Michael; Tsai, Catalina; Warneke, Carsten

2018-06-01

Formaldehyde (HCHO) is either directly emitted from sources or produced during the oxidation of volatile organic compounds (VOCs) in the troposphere. It is possible to infer atmospheric HCHO concentrations using space-based observations, which may be useful for studying emissions and tropospheric chemistry at urban to global scales depending on the quality of the retrievals. In the near future, an unprecedented volume of satellite-based HCHO measurement data will be available from both geostationary and polar-orbiting platforms. Therefore, it is essential to develop retrieval methods appropriate for the next-generation satellites that measure at higher spatial and temporal resolution than the current ones. In this study, we examine the importance of fine spatial and temporal resolution a priori profile information on the retrieval by conducting approximately 45 000 radiative transfer (RT) model calculations in the Los Angeles Basin (LA Basin) megacity. Our analyses suggest that an air mass factor (AMF, a factor converting observed slant columns to vertical columns) based on fine spatial and temporal resolution a priori profiles can better capture the spatial distributions of the enhanced HCHO plumes in an urban area than the nearly constant AMFs used for current operational products by increasing the columns by ˜ 50 % in the domain average and up to 100 % at a finer scale. For this urban area, the AMF values are inversely proportional to the magnitude of the HCHO mixing ratios in the boundary layer. Using our optimized model HCHO results in the Los Angeles Basin that mimic the HCHO retrievals from future geostationary satellites, we illustrate the effectiveness of HCHO data from geostationary measurements for understanding and predicting tropospheric ozone and its precursors.

Multi-scale analysis of neural activity in humans: Implications for micro-scale electrocorticography.

PubMed

Kellis, Spencer; Sorensen, Larry; Darvas, Felix; Sayres, Conor; O'Neill, Kevin; Brown, Richard B; House, Paul; Ojemann, Jeff; Greger, Bradley

2016-01-01

Electrocorticography grids have been used to study and diagnose neural pathophysiology for over 50 years, and recently have been used for various neural prosthetic applications. Here we provide evidence that micro-scale electrodes are better suited for studying cortical pathology and function, and for implementing neural prostheses. This work compares dynamics in space, time, and frequency of cortical field potentials recorded by three types of electrodes: electrocorticographic (ECoG) electrodes, non-penetrating micro-ECoG (μECoG) electrodes that use microelectrodes and have tighter interelectrode spacing; and penetrating microelectrodes (MEA) that penetrate the cortex to record single- or multiunit activity (SUA or MUA) and local field potentials (LFP). While the finest spatial scales are found in LFPs recorded intracortically, we found that LFP recorded from μECoG electrodes demonstrate scales of linear similarity (i.e., correlation, coherence, and phase) closer to the intracortical electrodes than the clinical ECoG electrodes. We conclude that LFPs can be recorded intracortically and epicortically at finer scales than clinical ECoG electrodes are capable of capturing. Recorded with appropriately scaled electrodes and grids, field potentials expose a more detailed representation of cortical network activity, enabling advanced analyses of cortical pathology and demanding applications such as brain-computer interfaces. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

An operational methodology for riparian land cover fine scale regional mapping for the study of landscape influence on river ecological status

NASA Astrophysics Data System (ADS)

Tormos, T.; Kosuth, P.; Souchon, Y.; Villeneuve, B.; Durrieu, S.; Chandesris, A.

2010-12-01

Preservation and restoration of river ecosystems require an improved understanding of the mechanisms through which they are influenced by landscape at multiple spatial scales and particularly at river corridor scale considering the role of riparian vegetation for regulating and protecting river ecological status and the relevance of this specific area for implementing efficient and realistic strategies. Assessing correctly this influence over large river networks involves accurate broad scale (i.e. at least regional) information on Land Cover within Riparian Areas (LCRA). As the structure of land cover along rivers is generally not accessible using moderate-scale satellite imagery, finer spatial resolution imagery and specific mapping techniques are needed. For this purpose we developed a generic multi-scale Object Based Image Analysis (OBIA) scheme able to produce LCRA maps in different geographic context by exploiting information available from very high spatial resolution imagery (satellite or airborne) and/or metric to decametric spatial thematic data on a given study zone thanks to fuzzy expert knowledge classification rules. A first experimentation was carried out on the Herault river watershed (southern of France), a 2650 square kilometers basin that presents a contrasted landscape (different ecoregions) and a total stream length of 1150 Km, using high and very high multispectral remotely-sensed images (10m Spot5 multispectral images and 0.5m aerial photography) and existing spatial thematic data. Application of the OBIA scheme produced a detailed (22 classes) LCRA map with an overall accuracy of 89% and a Kappa index of 83% according to a land cover pressures typology (six categories). A second experimentation (using the same data sources) was carried out on a larger test zone, a part of the Normandy river network (25 000 square kilometers basin; 6000 km long river network; 155 ecological stations). This second work aimed at elaborating a robust statistical eco-regional model to study links between land cover spatial indicators calculated at local and watershed scales, and river ecological status assessed with macroinvertebrate indicators. Application of the OBIA scheme produced a detailed (62 classes) LCRA map which allowed the model to highlight influence of specific land use patterns: (i) the significant beneficial effect of 20-m riparian tree vegetation strip near a station and 20-m riparian grassland strip along the upstream network of a station and (ii) the negative impact on river ecological status of urban areas and roads on the upstream flood plain of a station. Results of these two experimentations highlight that (i) the application of an OBIA scheme using multi-source spatial data provides an efficient approach for mapping and monitoring LCRA that can be implemented operationally at regional or national scale and (ii) and the interest of using LCRA-maps derived from very high spatial resolution imagery (satellite or airborne) and/or metric spatial thematic data to study landscape influence on river ecological status and support managers in the definition of optimized riparian preservation and restoration strategies.

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

NASA Astrophysics Data System (ADS)

Houben, Peter

2008-10-01

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

A data fusion approach for mapping daily evapotranspiration at field scale

USDA-ARS?s Scientific Manuscript database

The capability for mapping water consumption over cropped landscapes on a daily and seasonal basis is increasingly relevant given forecasted scenarios of reduced water availability. Prognostic modeling of water losses to the atmosphere, or evapotranspiration (ET), at field or finer scales in agricul...

Globalization: Ecological consequences of global-scale connectivity in people, resources and information

USDA-ARS?s Scientific Manuscript database

Globalization is a phenomenon affecting all facets of the Earth System. Within the context of ecological systems, it is becoming increasingly apparent that global connectivity among terrestrial systems, the atmosphere, and oceans is driving many ecological dynamics at finer scales and pushing thresh...

Cloud-Free Satellite Image Mosaics with Regression Trees and Histogram Matching.

Treesearch

E.H. Helmer; B. Ruefenacht

2005-01-01

Cloud-free optical satellite imagery simplifies remote sensing, but land-cover phenology limits existing solutions to persistent cloudiness to compositing temporally resolute, spatially coarser imagery. Here, a new strategy for developing cloud-free imagery at finer resolution permits simple automatic change detection. The strategy uses regression trees to predict...

Microfabricated particle focusing device

DOEpatents

Ravula, Surendra K.; Arrington, Christian L.; Sigman, Jennifer K.; Branch, Darren W.; Brener, Igal; Clem, Paul G.; James, Conrad D.; Hill, Martyn; Boltryk, Rosemary June

2013-04-23

A microfabricated particle focusing device comprises an acoustic portion to preconcentrate particles over large spatial dimensions into particle streams and a dielectrophoretic portion for finer particle focusing into single-file columns. The device can be used for high throughput assays for which it is necessary to isolate and investigate small bundles of particles and single particles.

Environmental analysis of groundwater in Mecosta County, Michigan.

PubMed

Steinman, Alan D; Biddanda, Bopi; Chu, Xuefeng; Thompson, Kurt; Rediske, Rick

2007-11-01

Groundwater withdrawal has major economic, social, and environmental implications. In Michigan, recent legislative activity has begun to address the issue of groundwater sustainability. However, more hydrologic data are needed to help inform policy and legislation. A study was conducted in Mecosta County, Michigan to: (1) determine if a relationship could be established between land use/land cover and groundwater quality; and (2) develop a conceptual model for the shallow groundwater system of the study region. In general, groundwater quality was good, with below detection levels of E. coli, low total bacterial counts, and relatively low nutrient concentrations. No statistically significant associations were found between the bacterial numbers and either land use or the physical/chemical attributes measured, which may be because the scale of our spatial analysis was too coarse to detect patterns. Finer-scale, localized processes may have a greater influence on microorganism growth and abundance than coarser-scale, regional processes in this area. Our groundwater analysis suggested that shallow groundwater flow paths are generally consistent with regional surface water flow networks, and that shallow groundwater levels in most of the region have fluctuated within 1-2 m over the past 30 years, with no obvious increasing or decreasing trend.

Estimating occupancy in large landscapes: evaluation of amphibian monitoring in the greater Yellowstone ecosystem

USGS Publications Warehouse

Gould, William R.; Patla, Debra A.; Daley, Rob; Corn, Paul Stephen; Hossack, Blake R.; Bennetts, Robert E.; Peterson, Charles R.

2012-01-01

Monitoring of natural resources is crucial to ecosystem conservation, and yet it can pose many challenges. Annual surveys for amphibian breeding occupancy were conducted in Yellowstone and Grand Teton National Parks over a 4-year period (2006–2009) at two scales: catchments (portions of watersheds) and individual wetland sites. Catchments were selected in a stratified random sample with habitat quality and ease of access serving as strata. All known wetland sites with suitable habitat were surveyed within selected catchments. Changes in breeding occurrence of tiger salamanders, boreal chorus frogs, and Columbia-spotted frogs were assessed using multi-season occupancy estimation. Numerous a priori models were considered within an information theoretic framework including those with catchment and site-level covariates. Habitat quality was the most important predictor of occupancy. Boreal chorus frogs demonstrated the greatest increase in breeding occupancy at the catchment level. Larger changes for all 3 species were detected at the finer site-level scale. Connectivity of sites explained occupancy rates more than other covariates, and may improve understanding of the dynamic processes occurring among wetlands within this ecosystem. Our results suggest monitoring occupancy at two spatial scales within large study areas is feasible and informative.

Subsurface Monitoring of CO2 Sequestration - A Review and Look Forward

NASA Astrophysics Data System (ADS)

Daley, T. M.

2012-12-01

The injection of CO2 into subsurface formations is at least 50 years old with large-scale utilization of CO2 for enhanced oil recovery (CO2-EOR) beginning in the 1970s. Early monitoring efforts had limited measurements in available boreholes. With growing interest in CO2 sequestration beginning in the 1990's, along with growth in geophysical reservoir monitoring, small to mid-size sequestration monitoring projects began to appear. The overall goals of a subsurface monitoring plan are to provide measurement of CO2 induced changes in subsurface properties at a range of spatial and temporal scales. The range of spatial scales allows tracking of the location and saturation of the plume with varying detail, while finer temporal sampling (up to continuous) allows better understanding of dynamic processes (e.g. multi-phase flow) and constraining of reservoir models. Early monitoring of small scale pilots associated with CO2-EOR (e.g., the McElroy field and the Lost Hills field), developed many of the methodologies including tomographic imaging and multi-physics measurements. Large (reservoir) scale sequestration monitoring began with the Sleipner and Weyburn projects. Typically, large scale monitoring, such as 4D surface seismic, has limited temporal sampling due to costs. Smaller scale pilots can allow more frequent measurements as either individual time-lapse 'snapshots' or as continuous monitoring. Pilot monitoring examples include the Frio, Nagaoka and Otway pilots using repeated well logging, crosswell imaging, vertical seismic profiles and CASSM (continuous active-source seismic monitoring). For saline reservoir sequestration projects, there is typically integration of characterization and monitoring, since the sites are not pre-characterized resource developments (oil or gas), which reinforces the need for multi-scale measurements. As we move beyond pilot sites, we need to quantify CO2 plume and reservoir properties (e.g. pressure) over large scales, while still obtaining high resolution. Typically the high-resolution (spatial and temporal) tools are deployed in permanent or semi-permanent borehole installations, where special well design may be necessary, such as non-conductive casing for electrical surveys. Effective utilization of monitoring wells requires an approach of modular borehole monitoring (MBM) were multiple measurements can be made. An example is recent work at the Citronelle pilot injection site where an MBM package with seismic, fluid sampling and distributed fiber sensing was deployed. For future large scale sequestration monitoring, an adaptive borehole-monitoring program is proposed.

An initial assessment of a SMAP soil moisture disaggregation scheme using TIR surface evaporation data over the continental United States

NASA Astrophysics Data System (ADS)

Mishra, Vikalp; Ellenburg, W. Lee; Griffin, Robert E.; Mecikalski, John R.; Cruise, James F.; Hain, Christopher R.; Anderson, Martha C.

2018-06-01

The Soil Moisture Active Passive (SMAP) mission is dedicated toward global soil moisture mapping. Typically, an L-band microwave radiometer has spatial resolution on the order of 36-40 km, which is too coarse for many specific hydro-meteorological and agricultural applications. With the failure of the SMAP active radar within three months of becoming operational, an intermediate (9-km) and finer (3-km) scale soil moisture product solely from the SMAP mission is no longer possible. Therefore, the focus of this study is a disaggregation of the 36-km resolution SMAP passive-only surface soil moisture (SSM) using the Soil Evaporative Efficiency (SEE) approach to spatial scales of 3-km and 9-km. The SEE was computed using thermal-infrared (TIR) estimation of surface evaporation over Continental U.S. (CONUS). The disaggregation results were compared with the 3 months of SMAP-Active (SMAP-A) and Active/Passive (AP) products, while comparisons with SMAP-Enhanced (SMAP-E), SMAP-Passive (SMAP-P), as well as with more than 180 Soil Climate Analysis Network (SCAN) stations across CONUS were performed for a 19 month period. At the 9-km spatial scale, the TIR-Downscaled data correlated strongly with the SMAP-E SSM both spatially (r = 0.90) and temporally (r = 0.87). In comparison with SCAN observations, overall correlations of 0.49 and 0.47; bias of -0.022 and -0.019 and unbiased RMSD of 0.105 and 0.100 were found for SMAP-E and TIR-Downscaled SSM across the Continental U.S., respectively. At 3-km scale, TIR-Downscaled and SMAP-A had a mean temporal correlation of only 0.27. In terms of gain statistics, the highest percentage of SCAN sites with positive gains (>55%) was observed with the TIR-Downscaled SSM at 9-km. Overall, the TIR-based downscaled SSM showed strong correspondence with SMAP-E; compared to SCAN, and overall both SMAP-E and TIR-Downscaled performed similarly, however, gain statistics show that TIR-Downscaled SSM slightly outperformed SMAP-E.

Decomposition of Sources of Errors in Seasonal Streamflow Forecasts in a Rainfall-Runoff Dominated Basin

NASA Astrophysics Data System (ADS)

Sinha, T.; Arumugam, S.

2012-12-01

Seasonal streamflow forecasts contingent on climate forecasts can be effectively utilized in updating water management plans and optimize generation of hydroelectric power. Streamflow in the rainfall-runoff dominated basins critically depend on forecasted precipitation in contrast to snow dominated basins, where initial hydrological conditions (IHCs) are more important. Since precipitation forecasts from Atmosphere-Ocean-General Circulation Models are available at coarse scale (~2.8° by 2.8°), spatial and temporal downscaling of such forecasts are required to implement land surface models, which typically runs on finer spatial and temporal scales. Consequently, multiple sources are introduced at various stages in predicting seasonal streamflow. Therefore, in this study, we addresses the following science questions: 1) How do we attribute the errors in monthly streamflow forecasts to various sources - (i) model errors, (ii) spatio-temporal downscaling, (iii) imprecise initial conditions, iv) no forecasts, and (iv) imprecise forecasts? and 2) How does monthly streamflow forecast errors propagate with different lead time over various seasons? In this study, the Variable Infiltration Capacity (VIC) model is calibrated over Apalachicola River at Chattahoochee, FL in the southeastern US and implemented with observed 1/8° daily forcings to estimate reference streamflow during 1981 to 2010. The VIC model is then forced with different schemes under updated IHCs prior to forecasting period to estimate relative mean square errors due to: a) temporally disaggregation, b) spatial downscaling, c) Reverse Ensemble Streamflow Prediction (imprecise IHCs), d) ESP (no forecasts), and e) ECHAM4.5 precipitation forecasts. Finally, error propagation under different schemes are analyzed with different lead time over different seasons.

Field Scale Optimization for Long-Term Sustainability of Best Management Practices in Watersheds

NASA Astrophysics Data System (ADS)

Samuels, A.; Babbar-Sebens, M.

2012-12-01

Agricultural and urban land use changes have led to disruption of natural hydrologic processes and impairment of streams and rivers. Multiple previous studies have evaluated Best Management Practices (BMPs) as means for restoring existing hydrologic conditions and reducing impairment of water resources. However, planning of these practices have relied on watershed scale hydrologic models for identifying locations and types of practices at scales much coarser than the actual field scale, where landowners have to plan, design and implement the practices. Field scale hydrologic modeling provides means for identifying relationships between BMP type, spatial location, and the interaction between BMPs at a finer farm/field scale that is usually more relevant to the decision maker (i.e. the landowner). This study focuses on development of a simulation-optimization approach for field-scale planning of BMPs in the School Branch stream system of Eagle Creek Watershed, Indiana, USA. The Agricultural Policy Environmental Extender (APEX) tool is used as the field scale hydrologic model, and a multi-objective optimization algorithm is used to search for optimal alternatives. Multiple climate scenarios downscaled to the watershed-scale are used to test the long term performance of these alternatives and under extreme weather conditions. The effectiveness of these BMPs under multiple weather conditions are included within the simulation-optimization approach as a criteria/goal to assist landowners in identifying sustainable design of practices. The results from these scenarios will further enable efficient BMP planning for current and future usage.

Downscaling hydrodynamics features to depict causes of major productivity of Sicilian-Maltese area and implications for resource management.

PubMed

Capodici, Fulvio; Ciraolo, Giuseppe; Cosoli, Simone; Maltese, Antonino; Mangano, M Cristina; Sarà, Gianluca

2018-07-01

Chlorophyll-a (CHL-a) and sea surface temperature (SST) are generally accepted as proxies for water quality. They can be easily retrieved in a quasi-near real time mode through satellite remote sensing and, as such, they provide an overview of the water quality on a synoptic scale in open waters. Their distributions evolve in space and time in response to local and remote forcing, such as winds and currents, which however have much finer temporal and spatial scales than those resolvable by satellites in spite of recent advances in satellite remote-sensing techniques. Satellite data are often characterized by a moderate temporal resolution to adequately catch the actual sub-grid physical processes. Conventional pointwise measurements can resolve high-frequency motions such as tides or high-frequency wind-driven currents, however they are inadequate to resolve their spatial variability over wide areas. We show in this paper that a combined use of near-surface currents, available through High-Frequency (HF) radars, and satellite data (e.g., TERRA and AQUA/MODIS), can properly resolve the main oceanographic features in both coastal and open-sea regions, particularly at the coastal boundaries where satellite imageries fail, and are complementary tools to interpret ocean productivity and resource management in the Sicily Channel. Copyright © 2018. Published by Elsevier B.V.

Local differentiation amidst extensive allele sharing in Oryza nivara and O. rufipogon

PubMed Central

Banaticla-Hilario, Maria Celeste N; van den Berg, Ronald G; Hamilton, Nigel Ruaraidh Sackville; McNally, Kenneth L

2013-01-01

Genetic variation patterns within and between species may change along geographic gradients and at different spatial scales. This was revealed by microsatellite data at 29 loci obtained from 119 accessions of three Oryza series Sativae species in Asia Pacific: Oryza nivara Sharma and Shastry, O. rufipogon Griff., and O. meridionalis Ng. Genetic similarities between O. nivara and O. rufipogon across their distribution are evident in the clustering and ordination results and in the large proportion of shared alleles between these taxa. However, local-level species separation is recognized by Bayesian clustering and neighbor-joining analyses. At the regional scale, the two species seem more differentiated in South Asia than in Southeast Asia as revealed by FST analysis. The presence of strong gene flow barriers in smaller spatial units is also suggested in the analysis of molecular variance (AMOVA) results where 64% of the genetic variation is contained among populations (as compared to 26% within populations and 10% among species). Oryza nivara (HE = 0.67) exhibits slightly lower diversity and greater population differentiation than O. rufipogon (HE = 0.70). Bayesian inference identified four, and at a finer structural level eight, genetically distinct population groups that correspond to geographic populations within the three taxa. Oryza meridionalis and the Nepalese O. nivara seemed diverged from all the population groups of the series, whereas the Australasian O. rufipogon appeared distinct from the rest of the species. PMID:24101993

Skin Friction Reduction Through Large-Scale Forcing

NASA Astrophysics Data System (ADS)

Bhatt, Shibani; Artham, Sravan; Gnanamanickam, Ebenezer

2017-11-01

Flow structures in a turbulent boundary layer larger than an integral length scale (δ), referred to as large-scales, interact with the finer scales in a non-linear manner. By targeting these large-scales and exploiting this non-linear interaction wall shear stress (WSS) reduction of over 10% has been achieved. The plane wall jet (PWJ), a boundary layer which has highly energetic large-scales that become turbulent independent of the near-wall finer scales, is the chosen model flow field. It's unique configuration allows for the independent control of the large-scales through acoustic forcing. Perturbation wavelengths from about 1 δ to 14 δ were considered with a reduction in WSS for all wavelengths considered. This reduction, over a large subset of the wavelengths, scales with both inner and outer variables indicating a mixed scaling to the underlying physics, while also showing dependence on the PWJ global properties. A triple decomposition of the velocity fields shows an increase in coherence due to forcing with a clear organization of the small scale turbulence with respect to the introduced large-scale. The maximum reduction in WSS occurs when the introduced large-scale acts in a manner so as to reduce the turbulent activity in the very near wall region. This material is based upon work supported by the Air Force Office of Scientific Research under Award Number FA9550-16-1-0194 monitored by Dr. Douglas Smith.

Multi-scale coupled modelling of waves and currents on the Catalan shelf.

NASA Astrophysics Data System (ADS)

Grifoll, M.; Warner, J. C.; Espino, M.; Sánchez-Arcilla, A.

2012-04-01

Catalan shelf circulation is characterized by a background along-shelf flow to the southwest (including some meso-scale features) plus episodic storm driven patterns. To investigate these dynamics, a coupled multi-scale modeling system is applied to the Catalan shelf (North-western Mediterranean Sea). The implementation consists of a set of increasing-resolution nested models, based on the circulation model ROMS and the wave model SWAN as part of the COAWST modeling system, covering from the slope and shelf region (~1 km horizontal resolution) down to a local area around Barcelona city (~40 m). The system is initialized with MyOcean products in the coarsest outer domain, and uses atmospheric forcing from other sources for the increasing resolution inner domains. Results of the finer resolution domains exhibit improved agreement with observations relative to the coarser model results. Several hydrodynamic configurations were simulated to determine dominant forcing mechanisms and hydrodynamic processes that control coastal scale processes. The numerical results reveal that the short term (hours to days) inner-shelf variability is strongly influenced by local wind variability, while sea-level slope, baroclinic effects, radiation stresses and regional circulation constitute second-order processes. Additional analysis identifies the significance of shelf/slope exchange fluxes, river discharge and the effect of the spatial resolution of the atmospheric fluxes.

An economic prediction of the finer resolution level wavelet coefficients in electronic structure calculations.

PubMed

Nagy, Szilvia; Pipek, János

2015-12-21

In wavelet based electronic structure calculations, introducing a new, finer resolution level is usually an expensive task, this is why often a two-level approximation is used with very fine starting resolution level. This process results in large matrices to calculate with and a large number of coefficients to be stored. In our previous work we have developed an adaptively refined solution scheme that determines the indices, where the refined basis functions are to be included, and later a method for predicting the next, finer resolution coefficients in a very economic way. In the present contribution, we would like to determine whether the method can be applied for predicting not only the first, but also the other, higher resolution level coefficients. Also the energy expectation values of the predicted wave functions are studied, as well as the scaling behaviour of the coefficients in the fine resolution limit.

Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: Models and mechanisms.

PubMed

Cabral, Joana; Kringelbach, Morten L; Deco, Gustavo

2017-10-15

Over the last decade, we have observed a revolution in brain structural and functional Connectomics. On one hand, we have an ever-more detailed characterization of the brain's white matter structural connectome. On the other, we have a repertoire of consistent functional networks that form and dissipate over time during rest. Despite the evident spatial similarities between structural and functional connectivity, understanding how different time-evolving functional networks spontaneously emerge from a single structural network requires analyzing the problem from the perspective of complex network dynamics and dynamical system's theory. In that direction, bottom-up computational models are useful tools to test theoretical scenarios and depict the mechanisms at the genesis of resting-state activity. Here, we provide an overview of the different mechanistic scenarios proposed over the last decade via computational models. Importantly, we highlight the need of incorporating additional model constraints considering the properties observed at finer temporal scales with MEG and the dynamical properties of FC in order to refresh the list of candidate scenarios. Copyright © 2017 Elsevier Inc. All rights reserved.

NPP-VIIRS DNB-based reallocating subpopulations to mercury in Urumqi city cluster, central Asia

NASA Astrophysics Data System (ADS)

Zhou, X.; Feng, X. B.; Dai, W.; Li, P.; Ju, C. Y.; Bao, Z. D.; Han, Y. L.

2017-02-01

Accurate and update assignment of population-related environmental matters onto fine grid cells in oasis cities of arid areas remains challenging. We present the approach based on Suomi National Polar-orbiting Partnership (S-NPP) -Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) to reallocate population onto a regular finer surface. The number of potential population to the mercury were reallocated onto 0.1x0.1 km reference grid in Urumqi city cluster of China’s Xinjiang, central Asia. The result of Monte Carlo modelling indicated that the range of 0.5 to 2.4 million people was reliable. The study highlights that the NPP-VIIRS DNB-based multi-layered, dasymetric, spatial method enhances our abilities to remotely estimate the distribution and size of target population at the street-level scale and has the potential to transform control strategies for epidemiology, public policy and other socioeconomic fields.

Observation-Corrected Precipitation Estimates in GEOS-5

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Qing

2014-01-01

Several GEOS-5 applications, including the GEOS-5 seasonal forecasting system and the MERRA-Land data product, rely on global precipitation data that have been corrected with satellite and or gauge-based precipitation observations. This document describes the methodology used to generate the corrected precipitation estimates and their use in GEOS-5 applications. The corrected precipitation estimates are derived by disaggregating publicly available, observationally based, global precipitation products from daily or pentad totals to hourly accumulations using background precipitation estimates from the GEOS-5 atmospheric data assimilation system. Depending on the specific combination of the observational precipitation product and the GEOS-5 background estimates, the observational product may also be downscaled in space. The resulting corrected precipitation data product is at the finer temporal and spatial resolution of the GEOS-5 background and matches the observed precipitation at the coarser scale of the observational product, separately for each day (or pentad) and each grid cell.

Near term climate projections for invasive species distributions

USGS Publications Warehouse

Jarnevich, C.S.; Stohlgren, T.J.

2009-01-01

Climate change and invasive species pose important conservation issues separately, and should be examined together. We used existing long term climate datasets for the US to project potential climate change into the future at a finer spatial and temporal resolution than the climate change scenarios generally available. These fine scale projections, along with new species distribution modeling techniques to forecast the potential extent of invasive species, can provide useful information to aide conservation and invasive species management efforts. We created habitat suitability maps for Pueraria montana (kudzu) under current climatic conditions and potential average conditions up to 30 years in the future. We examined how the potential distribution of this species will be affected by changing climate, and the management implications associated with these changes. Our models indicated that P. montana may increase its distribution particularly in the Northeast with climate change and may decrease in other areas. ?? 2008 Springer Science+Business Media B.V.

Experimental realization of a subwavelength optical potential based on atomic dark state

NASA Astrophysics Data System (ADS)

Wang, Yang; Subhankar, Sarthak; Rolston, Steven; Porto, James

2017-04-01

As a well-established tool optical lattice (OL) provides the unique opportunity to exploit the rich manybody physics. However, ``traditional'' OL, either via laser beam interference or direct projection with spatial light modulator, has a length scale around the wavelength (0.1 10 λ) that is set by diffraction, a fundamental limit from the wave nature of the light. Recent theoretical proposals suggest an alternative route, where the geometric potential, stemming from light-atom interaction, can be engineered to generate a much finer potential landscape which is essentially limited by the wave nature of the slow moving cold atoms. We report on the progress towards an experimental realization of these ideas using degenerate fermionic ytterbium atoms. Such subwavelength optical potential could open the gate to study physics beyond currently available parameter regimes, such as enhanced super-exchange coupling, magnetic dipolar coupling, and tunnel junction in atomtronics.

Charge Sharing and Charge Loss in a Cadmium-Zinc-Telluride Fine-Pixel Detector Array

NASA Technical Reports Server (NTRS)

Gaskin, J. A.; Sharma, D. P.; Ramsey, B. D.; Six, N. Frank (Technical Monitor)

2002-01-01

Because of its high atomic number, room temperature operation, low noise, and high spatial resolution a Cadmium-Zinc-Telluride (CZT) multi-pixel detector is ideal for hard x-ray astrophysical observation. As part of on-going research at MSFC (Marshall Space Flight Center) to develop multi-pixel CdZnTe detectors for this purpose, we have measured charge sharing and charge loss for a 4x4 (750micron pitch), lmm thick pixel array and modeled these results using a Monte-Carlo simulation. This model was then used to predict the amount of charge sharing for a much finer pixel array (with a 300micron pitch). Future work will enable us to compare the simulated results for the finer array to measured values.

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

Chen, Gang

Mid-latitude extreme weather events are responsible for a large part of climate-related damage. Yet large uncertainties remain in climate model projections of heat waves, droughts, and heavy rain/snow events on regional scales, limiting our ability to effectively use these projections for climate adaptation and mitigation. These uncertainties can be attributed to both the lack of spatial resolution in the models, and to the lack of a dynamical understanding of these extremes. The approach of this project is to relate the fine-scale features to the large scales in current climate simulations, seasonal re-forecasts, and climate change projections in a very widemore » range of models, including the atmospheric and coupled models of ECMWF over a range of horizontal resolutions (125 to 10 km), aqua-planet configuration of the Model for Prediction Across Scales and High Order Method Modeling Environments (resolutions ranging from 240 km – 7.5 km) with various physics suites, and selected CMIP5 model simulations. The large scale circulation will be quantified both on the basis of the well tested preferred circulation regime approach, and very recently developed measures, the finite amplitude Wave Activity (FAWA) and its spectrum. The fine scale structures related to extremes will be diagnosed following the latest approaches in the literature. The goal is to use the large scale measures as indicators of the probability of occurrence of the finer scale structures, and hence extreme events. These indicators will then be applied to the CMIP5 models and time-slice projections of a future climate.« less

The National Map - Orthoimagery

USGS Publications Warehouse

Mauck, James; Brown, Kim; Carswell, William J.

2009-01-01

Orthorectified digital aerial photographs and satellite images of 1-meter (m) pixel resolution or finer make up the orthoimagery component of The National Map. The process of orthorectification removes feature displacements and scale variations caused by terrain relief and sensor geometry. The result is a combination of the image characteristics of an aerial photograph or satellite image and the geometric qualities of a map. These attributes allow users to: *Measure distance *Calculate areas *Determine shapes of features *Calculate directions *Determine accurate coordinates *Determine land cover and use *Perform change detection *Update maps The standard digital orthoimage is a 1-m or finer resolution, natural color or color infra-red product. Most are now produced as GeoTIFFs and accompanied by a Federal Geographic Data Committee (FGDC)-compliant metadata file. The primary source for 1-m data is the National Agriculture Imagery Program (NAIP) leaf-on imagery. The U.S. Geological Survey (USGS) utilizes NAIP imagery as the image layer on its 'Digital- Map' - a new generation of USGS topographic maps (http://nationalmap.gov/digital_map). However, many Federal, State, and local governments and organizations require finer resolutions to meet a myriad of needs. Most of these images are leaf-off, natural-color products at resolutions of 1-foot (ft) or finer.

Spatial distribution and risk factors of Schistosoma haematobium and hookworm infections among schoolchildren in Kwale, Kenya

PubMed Central

Chadeka, Evans Asena; Nagi, Sachiyo; Sunahara, Toshihiko; Cheruiyot, Ngetich Benard; Bahati, Felix; Ozeki, Yuriko; Inoue, Manabu; Osada-Oka, Mayuko; Okabe, Mayuko; Hirayama, Yukio; Changoma, Mwatasa; Adachi, Keishi; Mwende, Faith; Kikuchi, Mihoko; Nakamura, Risa; Kalenda, Yombo Dan Justin; Kaneko, Satoshi; Hirayama, Kenji; Shimada, Masaaki; Ichinose, Yoshio; Njenga, Sammy M.; Matsumoto, Sohkichi

2017-01-01

Background Large-scale schistosomiasis control programs are implemented in regions with diverse social and economic environments. A key epidemiological feature of schistosomiasis is its small-scale heterogeneity. Locally profiling disease dynamics including risk factors associated with its transmission is essential for designing appropriate control programs. To determine spatial distribution of schistosomiasis and its drivers, we examined schoolchildren in Kwale, Kenya. Methodology/Principal findings We conducted a cross-sectional study of 368 schoolchildren from six primary schools. Soil-transmitted helminths and Schistosoma mansoni eggs in stool were evaluated by the Kato-Katz method. We measured the intensity of Schistosoma haematobium infection by urine filtration. The geometrical mean intensity of S. haematobium was 3.1 eggs/10 ml urine (school range, 1.4–9.2). The hookworm geometric mean intensity was 3.2 eggs/g feces (school range, 0–17.4). Heterogeneity in the intensity of S. haematobium and hookworm infections was evident in the study area. To identify factors associated with the intensity of helminth infections, we utilized negative binomial generalized linear mixed models. The intensity of S. haematobium infection was associated with religion and socioeconomic status (SES), while that of hookworm infection was related to SES, sex, distance to river and history of anthelmintic treatment. Conclusions/Significance Both S. haematobium and hookworm infections showed micro-geographical heterogeneities in this Kwale community. To confirm and explain our observation of high S. haematobium risk among Muslims, further extensive investigations are necessary. The observed small scale clustering of the S. haematobium and hookworm infections might imply less uniform strategies even at finer scale for efficient utilization of limited resources. PMID:28863133

Water Balance in the Amazon Basin from a Land Surface Model Ensemble

NASA Technical Reports Server (NTRS)

Getirana, Augusto C. V.; Dutra, Emanuel; Guimberteau, Matthieu; Kam, Jonghun; Li, Hong-Yi; Decharme, Bertrand; Zhang, Zhengqiu; Ducharne, Agnes; Boone, Aaron; Balsamo, Gianpaolo;

Simulating Non-Fickian Transport across Péclet Regimes by doing Lévy Flights in the Rank Space of Velocity

NASA Astrophysics Data System (ADS)

Most, S.; Dentz, M.; Bolster, D.; Bijeljic, B.; Nowak, W.

2017-12-01

Transport in real porous media shows non-Fickian characteristics. In the Lagrangian perspective this leads to skewed distributions of particle arrival times. The skewness is triggered by particles' memory of velocity that persists over a characteristic length. Capturing process memory is essential to represent non-Fickianity thoroughly. Classical non-Fickian models (e.g., CTRW models) simulate the effects of memory but not the mechanisms leading to process memory. CTRWs have been applied successfully in many studies but nonetheless they have drawbacks. In classical CTRWs each particle makes a spatial transition for which each particle adapts a random transit time. Consecutive transit times are drawn independently from each other, and this is only valid for sufficiently large spatial transitions. If we want to apply a finer numerical resolution than that, we have to implement memory into the simulation. Recent CTRW methods use transitions matrices to simulate correlated transit times. However, deriving such transition matrices require transport data of a fine-scale transport simulation, and the obtained transition matrix is solely valid for this single Péclet regime. The CTRW method we propose overcomes all three drawbacks: 1) We simulate transport without restrictions in transition length. 2) We parameterize our CTRW without requiring a transport simulation. 3) Our parameterization scales across Péclet regimes. We do so by sampling the pore-scale velocity distribution to generate correlated transit times as a Lévy flight on the CDF-axis of velocities with reflection at 0 and 1. The Lévy flight is parametrized only by the correlation length. We explicitly model memory including the evolution and decay of non-Fickianity, so it extends from local via pre-asymptotic to asymptotic scales.

Improved microgrid arrangement for integrated imaging polarimeters.

PubMed

LeMaster, Daniel A; Hirakawa, Keigo

2014-04-01

For almost 20 years, microgrid polarimetric imaging systems have been built using a 2×2 repeating pattern of polarization analyzers. In this Letter, we show that superior spatial resolution is achieved over this 2×2 case when the analyzers are arranged in a 2×4 repeating pattern. This unconventional result, in which a more distributed sampling pattern results in finer spatial resolution, is also achieved without affecting the conditioning of the polarimetric data-reduction matrix. Proof is provided theoretically and through Stokes image reconstruction of synthesized data.

Using regional bird density distribution models to evaluate protected area networks and inform conservation planning

Treesearch

John D. Alexander; Jaime L. Stephens; Sam Veloz; Leo Salas; Josée S. Rousseau; C. John Ralph; Daniel A. Sarr

2017-01-01

As data about populations of indicator species become available, proactive strategies that improve representation of biological diversity within protected area networks should consider finer-scaled evaluations, especially in regions identified as important through course-scale analyses. We use density distribution models derived from a robust regional bird...

Indicators of climate change in Idaho: An assessment framework for coupling biophysical change and social perception

USDA-ARS?s Scientific Manuscript database

Climate change is well documented at the global scale, but local and regional changes are not as well understood. Finer, local-to-regional scale information is needed for creating specific, place-based planning and adaption efforts. Here we detail the development of an indicator-focused climate chan...

Socioeconomic evaluation of broad-scale land management strategies.

Treesearch

Lisa K. Crone; Richard W. Haynes

2001-01-01

This paper examines the socioeconomic effects of alternative management strategies for Forest Service and Bureau of Land Management lands in the interior Columbia basin. From a broad-scale perspective, there is little impact or variation between alternatives in terms of changes in total economic activity or social conditions in the region. However, adopting a finer...

Preindustrial nitrous oxide emissions from the land biosphere estimated by using a global biogeochemistry model

NASA Astrophysics Data System (ADS)

Xu, Rongting; Tian, Hanqin; Lu, Chaoqun; Pan, Shufen; Chen, Jian; Yang, Jia; Zhang, Bowen

2017-07-01

To accurately assess how increased global nitrous oxide (N2O) emission has affected the climate system requires a robust estimation of the preindustrial N2O emissions since only the difference between current and preindustrial emissions represents net drivers of anthropogenic climate change. However, large uncertainty exists in previous estimates of preindustrial N2O emissions from the land biosphere, while preindustrial N2O emissions on the finer scales, such as regional, biome, or sector scales, have not been well quantified yet. In this study, we applied a process-based Dynamic Land Ecosystem Model (DLEM) to estimate the magnitude and spatial patterns of preindustrial N2O fluxes at the biome, continental, and global level as driven by multiple environmental factors. Uncertainties associated with key parameters were also evaluated. Our study indicates that the mean of the preindustrial N2O emission was approximately 6.20 Tg N yr-1, with an uncertainty range of 4.76 to 8.13 Tg N yr-1. The estimated N2O emission varied significantly at spatial and biome levels. South America, Africa, and Southern Asia accounted for 34.12, 23.85, and 18.93 %, respectively, together contributing 76.90 % of global total emission. The tropics were identified as the major source of N2O released into the atmosphere, accounting for 64.66 % of the total emission. Our multi-scale estimates provide a robust reference for assessing the climate forcing of anthropogenic N2O emission from the land biosphere

Interactions of multi-scale heterogeneity in the lithosphere: Australia

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

A low-rank control variate for multilevel Monte Carlo simulation of high-dimensional uncertain systems

NASA Astrophysics Data System (ADS)

Fairbanks, Hillary R.; Doostan, Alireza; Ketelsen, Christian; Iaccarino, Gianluca

2017-07-01

Multilevel Monte Carlo (MLMC) is a recently proposed variation of Monte Carlo (MC) simulation that achieves variance reduction by simulating the governing equations on a series of spatial (or temporal) grids with increasing resolution. Instead of directly employing the fine grid solutions, MLMC estimates the expectation of the quantity of interest from the coarsest grid solutions as well as differences between each two consecutive grid solutions. When the differences corresponding to finer grids become smaller, hence less variable, fewer MC realizations of finer grid solutions are needed to compute the difference expectations, thus leading to a reduction in the overall work. This paper presents an extension of MLMC, referred to as multilevel control variates (MLCV), where a low-rank approximation to the solution on each grid, obtained primarily based on coarser grid solutions, is used as a control variate for estimating the expectations involved in MLMC. Cost estimates as well as numerical examples are presented to demonstrate the advantage of this new MLCV approach over the standard MLMC when the solution of interest admits a low-rank approximation and the cost of simulating finer grids grows fast.

Soil Moisture Estimation Across Scales with Mobile Sensors for Cosmic-Ray Neutrons from the Ground and Air

NASA Astrophysics Data System (ADS)

Schrön, Martin; Köhler, Mandy; Bannehr, Lutz; Köhli, Markus; Fersch, Benjamin; Rebmann, Corinna; Mai, Juliane; Cuntz, Matthias; Kögler, Simon; Schröter, Ingmar; Wollschläger, Ute; Oswald, Sascha; Dietrich, Peter; Zacharias, Steffen

2016-04-01

Soil moisture is a key variable for environmental sciences, but its determination at various scales and depths is still an open challenge. Cosmic-ray neutron sensing has become a well accepted and unique method to monitor an effective soil water content, covering tens of hectares in area and tens of centimeters in depth. The technology is famous for its low maintanance, non-invasiveness, continous measurement, and most importantly its large footprint and penetration depth. Beeing more representative than point data, and finer resolved plus deeper penetrating than remote-sensing products, cosmic-ray neutron derived soil moisture products provide unrivaled advantage for agriculture, regional hydrologic and land surface models. The method takes advantage of omnipresent neutrons which are extraordinarily sensitive to hydrogen in soil, plants, snow and air. Unwanted hydrogen sources in the footprint can be excluded by local calibration to extract the pure soil water information. However, this procedure is not feasible for mobile measurements, where neutron detectors are mounted on a car to do catchment-scale surveys. As a solution to that problem, we suggest strategies to correct spatial neutron data with the help of available spatial data of soil type, landuse and vegetation. We further present results of mobile rover campaigns at various scales and conditions, covering small sites from 0.2 km2 to catchments of 100 km2 area, and complex terrain from agricultural fields, urban areas, forests, to snowy alpine sites. As the rover is limited to accessible roads, we further investigated the applicability of airborne measurements. First tests with a gyrocopter at 150 to 200m heights proofed the concept of airborne neutron detection for environmental sciences. Moreover, neutron transport simulations confirm an improved areal coverage during these campaigns. Mobile neutron measurements at the ground or air are a promising tool for the detection of water sources across many scales. The method has a great potential to improve spatial performance of hydrological models, and help to assess regional soil moisture states for agriculture and flood risk management.

Spatial variability in land-atmosphere coupling strength at the ARM Southern Great Plains site under different cloud regimes

NASA Astrophysics Data System (ADS)

Tang, Q.; Xie, S.; Zhang, Y.

2016-12-01

The paucity of land/soil observations is a long-standing limitation for land-atmosphere (LA) coupling studies, in particular for estimating the spatial variability in the coupling strengths. Spatially dense atmospheric radiation measurement (ARM) sites deployed at the U.S. Southern Great Plains (SGP) covers a wide range of vegetation, surface, and soil types, and thus allow us to observe the spatial patterns of LA coupling. The upcoming "super site" at SGP will facilitate these studies at even finer scales. While many previous studies have focused only on the observations from the central facility (CF) site or the domain mean from multiple sites, in the present work we examine the robustness of many key surface and land observations (e.g., radiation, turbulence fluxes, soil moisture, etc.) at extended sites besides the CF site for a decade. The coupling strengths are estimated with temporal covariations between important variables. We subsample the data to different categories based on different cloud regimes (e.g., clear sky, shallow cumulus, and deep cumulus. These cloud regimes are strongly impacted by local factors. The spatial variability of coupling strengths at different ARM sites is assessed with respect to dominant drivers (i.e., vegetation, land type, etc.). The results of this study will provide insights for improving the representation of LA coupling in climate models by providing observational constraints to parameterizations, e.g., shallow convective schemes. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-698523

Scaling Soil Microbe-Water Interactions from Pores to Ecosystems

NASA Astrophysics Data System (ADS)

Manzoni, S.; Katul, G. G.

2014-12-01

The spatial scales relevant to soil microbial activity are much finer than scales relevant to whole-ecosystem function and biogeochemical cycling. On the one hand, how to link such different scales and develop scale-aware biogeochemical and ecohydrological models remains a major challenge. On the other hand, resolving these linkages is becoming necessary for testing ecological hypotheses and resolving data-theory inconsistencies. Here, the relation between microbial respiration and soil moisture expressed in water potential is explored. Such relation mediates the water availability effects on ecosystem-level heterotrophic respiration and is of paramount importance for understanding CO2 emissions under increasingly variable rainfall regimes. Respiration has been shown to decline as the soil dries in a remarkably consistent way across climates and soil types (open triangles in Figure). Empirical models based on these respiration-moisture relations are routinely used in Earth System Models to predict moisture effects on ecosystem respiration. It has been hypothesized that this consistency in microbial respiration decline is due to breakage of water film continuity causing in turn solute diffusion limitations in dry conditions. However, this hypothesis appears to be at odds with what is known about soil hydraulic properties. Water film continuity estimated from soil water retention (SWR) measurements at the 'Darcy' scale breaks at far less negative water potential (<-0.1 MPa) levels than where microbial respiration ceases (approximately -15 MPa) as shown in the Figure (violet frequency distribution). Also, this threshold point inferred from SWR shows strong texture dependence, in contrast to the respiration curves. Employing theoretical tools from percolation theory, it is demonstrated that hydrological measurements can be spatially downscaled at a micro-level relevant to microbial activity. Such downscaling resolves the inconsistency between respiration thresholds and hydrological thresholds. This result, together with observations of residual microbial activity well below -15 MPa (dashed back curve in Figure), lends support to the hypothesis that soil microbes are substrate-limited in dry conditions.

Integrating Phenological, Trait and Environmental Data For Continental Scale Analysis: A Community Approach

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; Walls, R.; Guralnick, R. P.; Rosemartin, A.; Deck, J.; Powers, L. A.

2014-12-01

There is a wealth of biodiversity and environmental data that can provide the basis for addressing global scale questions of societal concern. However, our ability to discover, access and integrate these data for use in broader analyses is hampered by the lack of standardized languages and systems. New tools (e.g. ontologies, data standards, integration tools, unique identifiers) are being developed that enable establishment of a framework for linked and open data. Relative to other domains, these tools are nascent in biodiversity and environmental sciences and will require effort to develop, though work can capitalize on lessons learned from previous efforts. Here we discuss needed next steps to provide consistently described and formatted ecological data for immediate application in ecological analysis, focusing on integrating phenology, trait and environmental data to understand local to continental-scale biophysical processes and inform natural resource management practices. As more sources of data become available at finer spatial and temporal resolution, e.g., from national standardized earth observing systems (e.g., NEON, LTER and LTAR Networks, USA NPN), these challenges will become more acute. Here we provide an overview of the standards and ontology development landscape specifically related to phenological and trait data, and identify requirements to overcome current challenges. Second, we outline a workflow for formatting and integrating existing datasets to address key scientific and resource management questions such as: "What traits determine differential phenological responses to changing environmental conditions?" or "What is the role of granularity of observation, and of spatiotemporal scale, in controlling phenological responses to different driving variables?" Third, we discuss methods to semantically annotate datasets to greatly decrease time needed to assemble heterogeneous data for use in ecological analyses on varying spatial scales. We close by making a call to interested community members for a working group to model phenology, trait and environmental data products from continental-scale efforts (e.g. NEON, USA-NPN and others) focusing on ways to assure discoverability and interoperability.

Social and spatial effects on genetic variation between foraging flocks in a wild bird population.

PubMed

Radersma, Reinder; Garroway, Colin J; Santure, Anna W; de Cauwer, Isabelle; Farine, Damien R; Slate, Jon; Sheldon, Ben C

2017-10-01

Social interactions are rarely random. In some instances, animals exhibit homophily or heterophily, the tendency to interact with similar or dissimilar conspecifics, respectively. Genetic homophily and heterophily influence the evolutionary dynamics of populations, because they potentially affect sexual and social selection. Here, we investigate the link between social interactions and allele frequencies in foraging flocks of great tits (Parus major) over three consecutive years. We constructed co-occurrence networks which explicitly described the splitting and merging of 85,602 flocks through time (fission-fusion dynamics), at 60 feeding sites. Of the 1,711 birds in those flocks, we genotyped 962 individuals at 4,701 autosomal single nucleotide polymorphisms (SNPs). By combining genomewide genotyping with repeated field observations of the same individuals, we were able to investigate links between social structure and allele frequencies at a much finer scale than was previously possible. We explicitly accounted for potential spatial effects underlying genetic structure at the population level. We modelled social structure and spatial configuration of great tit fission-fusion dynamics with eigenvector maps. Variance partitioning revealed that allele frequencies were strongly affected by group fidelity (explaining 27%-45% of variance) as individuals tended to maintain associations with the same conspecifics. These conspecifics were genetically more dissimilar than expected, shown by genomewide heterophily for pure social (i.e., space-independent) grouping preferences. Genomewide homophily was linked to spatial configuration, indicating spatial segregation of genotypes. We did not find evidence for homophily or heterophily for putative socially relevant candidate genes or any other SNP markers. Together, these results demonstrate the importance of distinguishing social and spatial processes in determining population structure. © 2017 John Wiley & Sons Ltd.

Darwin's naturalization hypothesis up-close: Intermountain grassland invaders differ morphologically and phenologically from native community dominants

Treesearch

Dean E. Pearson; Yvette K. Ortega; Samantha J. Sears

2012-01-01

Darwin's naturalization hypothesis predicts that successful invaders will tend to differ taxonomically from native species in recipient communities because less related species exhibit lower niche overlap and experience reduced biotic resistance. This hypothesis has garnered substantial support at coarse scales. However, at finer scales, the influence of traits...

Can local adaptation explain varying patterns of herbivory tolerance in a recently introduced woody plant in North America?

USDA-ARS?s Scientific Manuscript database

Trends in tree mortality have been linked to global scale environmental changes, such as extreme drought and heat stress, more frequent and intense fires, and increased episodic outbreaks of insects and pathogens. Finer scale studies have also focused on survival and mortality in response to physiol...

Reconciling paleodistribution models and comparative phylogeography in the Wet Tropics rainforest land snail Gnarosophia bellendenkerensis (Brazier 1875).

PubMed

Hugall, Andrew; Moritz, Craig; Moussalli, Adnan; Stanisic, John

2002-04-30

Comparative phylogeography has proved useful for investigating biological responses to past climate change and is strongest when combined with extrinsic hypotheses derived from the fossil record or geology. However, the rarity of species with sufficient, spatially explicit fossil evidence restricts the application of this method. Here, we develop an alternative approach in which spatial models of predicted species distributions under serial paleoclimates are compared with a molecular phylogeography, in this case for a snail endemic to the rainforests of North Queensland, Australia. We also compare the phylogeography of the snail to those from several endemic vertebrates and use consilience across all of these approaches to enhance biogeographical inference for this rainforest fauna. The snail mtDNA phylogeography is consistent with predictions from paleoclimate modeling in relation to the location and size of climatic refugia through the late Pleistocene-Holocene and broad patterns of extinction and recolonization. There is general agreement between quantitative estimates of population expansion from sequence data (using likelihood and coalescent methods) vs. distributional modeling. The snail phylogeography represents a composite of both common and idiosyncratic patterns seen among vertebrates, reflecting the geographically finer scale of persistence and subdivision in the snail. In general, this multifaceted approach, combining spatially explicit paleoclimatological models and comparative phylogeography, provides a powerful approach to locating historical refugia and understanding species' responses to them.

Reconciling paleodistribution models and comparative phylogeography in the Wet Tropics rainforest land snail Gnarosophia bellendenkerensis (Brazier 1875)

PubMed Central

Hugall, Andrew; Moritz, Craig; Moussalli, Adnan; Stanisic, John

2002-01-01

Comparative phylogeography has proved useful for investigating biological responses to past climate change and is strongest when combined with extrinsic hypotheses derived from the fossil record or geology. However, the rarity of species with sufficient, spatially explicit fossil evidence restricts the application of this method. Here, we develop an alternative approach in which spatial models of predicted species distributions under serial paleoclimates are compared with a molecular phylogeography, in this case for a snail endemic to the rainforests of North Queensland, Australia. We also compare the phylogeography of the snail to those from several endemic vertebrates and use consilience across all of these approaches to enhance biogeographical inference for this rainforest fauna. The snail mtDNA phylogeography is consistent with predictions from paleoclimate modeling in relation to the location and size of climatic refugia through the late Pleistocene-Holocene and broad patterns of extinction and recolonization. There is general agreement between quantitative estimates of population expansion from sequence data (using likelihood and coalescent methods) vs. distributional modeling. The snail phylogeography represents a composite of both common and idiosyncratic patterns seen among vertebrates, reflecting the geographically finer scale of persistence and subdivision in the snail. In general, this multifaceted approach, combining spatially explicit paleoclimatological models and comparative phylogeography, provides a powerful approach to locating historical refugia and understanding species' responses to them. PMID:11972064

Assessing climate change impacts on fresh water resources of the Athabasca River Basin, Canada.

PubMed

Shrestha, Narayan Kumar; Du, Xinzhong; Wang, Junye

2017-12-01

Proper management of blue and green water resources is important for the sustainability of ecosystems and for the socio-economic development of river basins such as the Athabasca River Basin (ARB) in Canada. For this reason, quantifying climate change impacts on these water resources at a finer temporal and spatial scale is often necessary. In this study, we used a Soil and Water Assessment Tool (SWAT) to assess climate change impacts on fresh water resources, focusing explicitly on the impacts to both blue and green water. We used future climate data generated by the Canadian Center for Climate Modelling and Analysis Regional Climate Model (CanRCM4) with a spatial resolution of 0.22°×0.22° (~25km) for two emission scenarios (RCP 4.5 and 8.5). Results projected the climate of the ARB to be wetter by 21-34% and warmer by 2-5.4°C on an annual time scale. Consequently, the annual average blue and green water flow was projected to increase by 16-54% and 11-34%, respectively, depending on the region, future period, and emission scenario. Furthermore, the annual average green water storage at the boreal region was expected to increase by 30%, while the storage was projected to remain fairly stable or decrease in other regions, especially during the summer season. On average, the fresh water resources in the ARB are likely to increase in the future. However, evidence of temporal and spatial heterogeneity could pose many future challenges to water resource planners and managers. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

An assessment of the feasibility of the use of satellite-only rainfall estimates for the hydrological monitoring in central Italy

NASA Astrophysics Data System (ADS)

Campo, Lorenzo; Caparrini, Francesca

2013-04-01

The need for accurate distributed hydrological modelling has constantly increased in last years for several purposes: agricultural applications, water resources management, hydrological balance at watershed scale, floods forecast. The main input for the hydrological numerical models is rainfall data that present, at the same time, a large availability of measures (in gauged regions, with respect to other micro-meteorological variables) and the most complex spatial patterns. While also in presence of densely gauged watersheds the spatial interpolation of the rainfall is a non-trivial problem, due to the spatial intermittence of the variable (especially at finer temporal scales), ungauged regions need an alternative source of rainfall data in order to perform the hydrological modelling. Such source can be constituted by the satellite-estimated rainfall fields, with reference to both geostationary and polar-orbit platforms. In this work the rainfall product obtained by the Aqua-AIRS sensor were used in order to assess the feasibility of the use of satellite-based rainfall as input for distributed hydrological modelling. The MOBIDIC (MOdello di BIlancio Distribuito e Continuo) model, developed at the Department of civil and Environmental Engineering of the University of Florence and operationally used by Tuscany Region and Umbria Region for flood prediction and management, was used for the experiments. In particular three experiments were carried on: a) hydrological simulation with the use of rain-gauges data, b) simulation with the use of satellite-only rainfall estimates, c) simulation with the combined use of the two sources of data in order to obtain an optimal estimate of the actual rainfall fields. The domain of the study was the central Italy. Several critical events occurred in the area were analyzed. A discussion of the results is provided.

Quantifying geological uncertainty for flow and transport modeling in multi-modal heterogeneous formations

NASA Astrophysics Data System (ADS)

Feyen, Luc; Caers, Jef

2006-06-01

In this work, we address the problem of characterizing the heterogeneity and uncertainty of hydraulic properties for complex geological settings. Hereby, we distinguish between two scales of heterogeneity, namely the hydrofacies structure and the intrafacies variability of the hydraulic properties. We employ multiple-point geostatistics to characterize the hydrofacies architecture. The multiple-point statistics are borrowed from a training image that is designed to reflect the prior geological conceptualization. The intrafacies variability of the hydraulic properties is represented using conventional two-point correlation methods, more precisely, spatial covariance models under a multi-Gaussian spatial law. We address the different levels and sources of uncertainty in characterizing the subsurface heterogeneity, and explore their effect on groundwater flow and transport predictions. Typically, uncertainty is assessed by way of many images, termed realizations, of a fixed statistical model. However, in many cases, sampling from a fixed stochastic model does not adequately represent the space of uncertainty. It neglects the uncertainty related to the selection of the stochastic model and the estimation of its input parameters. We acknowledge the uncertainty inherent in the definition of the prior conceptual model of aquifer architecture and in the estimation of global statistics, anisotropy, and correlation scales. Spatial bootstrap is used to assess the uncertainty of the unknown statistical parameters. As an illustrative example, we employ a synthetic field that represents a fluvial setting consisting of an interconnected network of channel sands embedded within finer-grained floodplain material. For this highly non-stationary setting we quantify the groundwater flow and transport model prediction uncertainty for various levels of hydrogeological uncertainty. Results indicate the importance of accurately describing the facies geometry, especially for transport predictions.

Climate change and human health: Spatial modeling of water availability, malnutrition, and livelihoods in Mali, Africa

USGS Publications Warehouse

Jankowska, Marta M.; Lopez-Carr, David; Funk, Chris; Husak, Gregory J.; Chafe, Z.A.

2012-01-01

This study develops a novel approach for projecting climate trends in the Sahel in relation to shifting livelihood zones and health outcomes. Focusing on Mali, we explore baseline relationships between temperature, precipitation, livelihood, and malnutrition in 407 Demographic and Health Survey (DHS) clusters with a total of 14,238 children, resulting in a thorough spatial analysis of coupled climate-health dynamics. Results suggest links between livelihoods and each measure of malnutrition, as well as a link between climate and stunting. A ‘front-line’ of vulnerability, related to the transition between agricultural and pastoral livelihoods, is identified as an area where mitigation efforts might be usefully targeted. Additionally, climate is projected to 2025 for the Sahel, and demographic trends are introduced to explore how the intersection of climate and demographics may shift the vulnerability ‘front-line’, potentially exposing an additional 6 million people in Mali, up to a million of them children, to heightened risk of malnutrition from climate and livelihood changes. Results indicate that, holding constant morbidity levels, approximately one quarter of a million children will suffer stunting, nearly two hundred thousand will be malnourished, and over one hundred thousand will become anemic in this expanding arid zone by 2025. Climate and health research conducted at finer spatial scales and within shorter projected time lines can identify vulnerability hot spots that are of the highest priority for adaptation interventions; such an analysis can also identify areas with similar characteristics that may be at heightened risk. Such meso-scale coupled human-environment research may facilitate appropriate policy interventions strategically located beyond today’s vulnerability front-line.

Enhancing PTFs with remotely sensed data for multi-scale soil water retention estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.

2011-03-01

SummaryUse of remotely sensed data products in the earth science and water resources fields is growing due to increasingly easy availability of the data. Traditionally, pedotransfer functions (PTFs) employed for soil hydraulic parameter estimation from other easily available data have used basic soil texture and structure information as inputs. Inclusion of surrogate/supplementary data such as topography and vegetation information has shown some improvement in the PTF's ability to estimate more accurate soil hydraulic parameters. Artificial neural networks (ANNs) are a popular tool for PTF development, and are usually applied across matching spatial scales of inputs and outputs. However, different hydrologic, hydro-climatic, and contaminant transport models require input data at different scales, all of which may not be easily available from existing databases. In such a scenario, it becomes necessary to scale the soil hydraulic parameter values estimated by PTFs to suit the model requirements. Also, uncertainties in the predictions need to be quantified to enable users to gauge the suitability of a particular dataset in their applications. Bayesian Neural Networks (BNNs) inherently provide uncertainty estimates for their outputs due to their utilization of Markov Chain Monte Carlo (MCMC) techniques. In this paper, we present a PTF methodology to estimate soil water retention characteristics built on a Bayesian framework for training of neural networks and utilizing several in situ and remotely sensed datasets jointly. The BNN is also applied across spatial scales to provide fine scale outputs when trained with coarse scale data. Our training data inputs include ground/remotely sensed soil texture, bulk density, elevation, and Leaf Area Index (LAI) at 1 km resolutions, while similar properties measured at a point scale are used as fine scale inputs. The methodology was tested at two different hydro-climatic regions. We also tested the effect of varying the support scale of the training data for the BNNs by sequentially aggregating finer resolution training data to coarser resolutions, and the applicability of the technique to upscaling problems. The BNN outputs are corrected for bias using a non-linear CDF-matching technique. Final results show good promise of the suitability of this Bayesian Neural Network approach for soil hydraulic parameter estimation across spatial scales using ground-, air-, or space-based remotely sensed geophysical parameters. Inclusion of remotely sensed data such as elevation and LAI in addition to in situ soil physical properties improved the estimation capabilities of the BNN-based PTF in certain conditions.

Multiple energetic injections in a strong spike-like solar burst

NASA Technical Reports Server (NTRS)

Kaufmann, P.; Correia, E.; Costa, J. E. R.; Dennis, B. R.; Hurford, G. H.; Brown, J. C.

1983-01-01

An intense and fast spike-like solar burst was built up of short time scale structures superimposed on an underlying gradual emission, the time evolution of which shows remarkable proportionality between hard X-ray and microwave fluxes. The finer time structure were best defined at mm-microwaves. At the peak of the event, the finer structures repeat every 30x60ms. The more slowly varying component with a time scale of about 1 second was identified in microwave hard X-rays throughout the burst duration. It is suggested that X-ray fluxes might also be proportional to the repetition rate of basic units of energy injection (quasi-quantized). The relevant parameters of one primary energy release site are estimated both in the case where hard X-rays are produced primarily by thick-target bremsstrahlung, and when they are purely thermal. The relation of this figure to global energy considerations is discussed.

Modeling Spatial and Temporal Variability in Ammonia Emissions from Agricultural Fertilization

NASA Astrophysics Data System (ADS)

Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

2013-12-01

Ammonia (NH3), is an important component of the reactive nitrogen cycle and a precursor to formation of atmospheric particulate matter (PM). Predicting regional PM concentrations and deposition of nitrogen species to ecosystems requires representative emission inventories. Emission inventories have traditionally been developed using top down approaches and more recently from data assimilation based on satellite and ground based ambient concentrations and wet deposition data. The National Emission Inventory (NEI) indicates agricultural fertilization as the predominant contributor (56%) to NH3 emissions in Midwest USA, in 2002. However, due to limited understanding of the complex interactions between fertilizer usage, farm practices, soil and meteorological conditions and absence of detailed statistical data, such emission estimates are currently based on generic emission factors, time-averaged temporal factors and coarse spatial resolution. Given the significance of this source, our study focuses on developing an improved NH3 emission inventory for agricultural fertilization at finer spatial and temporal scales for air quality modeling studies. Firstly, a high-spatial resolution 4 km x 4 km NH3 emission inventory for agricultural fertilization has been developed for Illinois by modifying spatial allocation of emissions based on combining crop-specific fertilization rates with cropland distribution in the Sparse Matrix Operator Kernel Emissions model. Net emission estimates of our method are within 2% of NEI, since both methods are constrained by fertilizer sales data. However, we identified localized crop-specific NH3 emission hotspots at sub-county resolutions absent in NEI. Secondly, we have adopted the use of the DeNitrification-DeComposition (DNDC) Biogeochemistry model to simulate the physical and chemical processes that control volatilization of nitrogen as NH3 to the atmosphere after fertilizer application and resolve the variability at the hourly scale. Representative temporal factors are being developed to capture crop-specific NH3 emission variability by combining knowledge of local crop management practices with high resolution cropland and soil maps. This improved spatially and temporally dependent NH3 emission inventory for agricultural fertilization is being prepared as a direct input to a state of the art air quality model to evaluate the effects of agricultural fertilization on regional air quality and atmospheric deposition of reactive nitrogen species.

Channel representation in physically based models coupling groundwater and surface water: pitfalls and how to avoid them.

PubMed

Käser, Daniel; Graf, Tobias; Cochand, Fabien; McLaren, Rob; Therrien, René; Brunner, Philip

2014-01-01

Recent models that couple three-dimensional subsurface flow with two-dimensional overland flow are valuable tools for quantifying complex groundwater/stream interactions and for evaluating their influence on watershed processes. For the modeler who is used to defining streams as a boundary condition, the representation of channels in integrated models raises a number of conceptual and technical issues. These models are far more sensitive to channel topography than conventional groundwater models. On all spatial scales, both the topography of a channel and its connection with the floodplain are important. For example, the geometry of river banks influences bank storage and overbank flooding; the slope of the river is a primary control on the behavior of a catchment; and at the finer scale bedform characteristics affect hyporheic exchange. Accurate data on streambed topography, however, are seldom available, and the spatial resolution of digital elevation models is typically too coarse in river environments, resulting in unrealistic or undulating streambeds. Modelers therefore perform some kind of manual yet often cumbersome correction to the available topography. In this context, the paper identifies some common pitfalls, and provides guidance to overcome these. Both aspects of topographic representation and mesh discretization are addressed. Additionally, two tutorials are provided to illustrate: (1) the interpolation of channel cross-sectional data and (2) the refinement of a mesh along a stream in areas of high topographic variability. © 2014, National Ground Water Association.

Spatio-temporal Granger causality: a new framework

PubMed Central

Luo, Qiang; Lu, Wenlian; Cheng, Wei; Valdes-Sosa, Pedro A.; Wen, Xiaotong; Ding, Mingzhou; Feng, Jianfeng

2015-01-01

That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data. PMID:23643924

The impact of climate change measured at relevant spatial scales: new hope for tropical lizards.

PubMed

Logan, Michael L; Huynh, Ryan K; Precious, Rachel A; Calsbeek, Ryan G

2013-10-01

Much attention has been given to recent predictions that widespread extinctions of tropical ectotherms, and tropical forest lizards in particular, will result from anthropogenic climate change. Most of these predictions, however, are based on environmental temperature data measured at a maximum resolution of 1 km(2), whereas individuals of most species experience thermal variation on a much finer scale. To address this disconnect, we combined thermal performance curves for five populations of Anolis lizard from the Bay Islands of Honduras with high-resolution temperature distributions generated from physical models. Previous research has suggested that open-habitat species are likely to invade forest habitat and drive forest species to extinction. We test this hypothesis, and compare the vulnerabilities of closely related, but allopatric, forest species. Our data suggest that the open-habitat populations we studied will not invade forest habitat and may actually benefit from predicted warming for many decades. Conversely, one of the forest species we studied should experience reduced activity time as a result of warming, while two others are unlikely to experience a significant decline in performance. Our results suggest that global-scale predictions generated using low-resolution temperature data may overestimate the vulnerability of many tropical ectotherms to climate change. © 2013 John Wiley & Sons Ltd.

Seafloor Mapping and Benthic Habitats off Assateague Island National Seashore: can we Resolve any Effects of Superstorm Sandy?

NASA Astrophysics Data System (ADS)

Miller, D.; Trembanis, A. C.; Kennedy, E.; Rusch, H.; Rothermel, E.

2016-02-01

The National Park Service has partnered with faculty and students at the University of Delaware to map the length of Assateague Island and sample benthic communities there for two purposes: (1) to provide a complete inventory of benthic habitats and their biota, and (2) to determine if any changes from a pre-storm survey can be ascribed to Superstorm Sandy in 2012. During the 2014 and 2015 field seasons over 75 km2 of high-resolution ( 50 cm/pixel) side-scan sonar and collocated bathymetry were collected with a surface vessel mounted bathy side-scan sonar (EdgeTech 6205), spanning the shore from depths of less than 2 m out to a distance of approximately 1 nautical mile and depths of 10-12 m. Furthermore, we have resampled using standard methodology (modified Young grab and 0.5-mm sieve) a subset of the previously sampled benthic stations that represent all sediment classes identified in prior studies. Additionally, we have obtained novel data with our ROV and AUV assets, including finer scale bottom video and multibeam bathymetry, at specifically chosen locations in order to enhance understanding of the benthic habitat and bottom type changes. In addition to providing a habitat and faunal inventory for resource management purposes, we will compare our side scan and benthic survey data to the pre-storm 2011 data products with comparable coverage. To date we have found that ArcGIS and ENVI sediment classifications agree well with those from the 2011 study, but spatially we note more areas of finer sediments and less of gravel. As was expected, 2014 benthic assemblages differ significantly among sediment classes (PRIMER ANOSIM), and sediment class is the best predictor of the benthic community (PERMANOVA+ distance-based RDA). Our goal here is to use consistent analytical approaches to characterize changes that occur over season and inter-annual time scales. This is a critical step toward attributing sediment, habitat and biological changes to Superstorm Sandy.

Improving the integration of recreation management with management of other natural resources by applying concepts of scale from ecology.

PubMed

Morse, Wayde C; Hall, Troy E; Kruger, Linda E

2009-03-01

In this article, we examine how issues of scale affect the integration of recreation management with the management of other natural resources on public lands. We present two theories used to address scale issues in ecology and explore how they can improve the two most widely applied recreation-planning frameworks. The theory of patch dynamics and hierarchy theory are applied to the recreation opportunity spectrum (ROS) and the limits of acceptable change (LAC) recreation-planning frameworks. These frameworks have been widely adopted internationally, and improving their ability to integrate with other aspects of natural resource management has significant social and conservation implications. We propose that incorporating ecologic criteria and scale concepts into these recreation-planning frameworks will improve the foundation for integrated land management by resolving issues of incongruent boundaries, mismatched scales, and multiple-scale analysis. Specifically, we argue that whereas the spatially explicit process of the ROS facilitates integrated decision making, its lack of ecologic criteria, broad extent, and large patch size decrease its usefulness for integration at finer scales. The LAC provides explicit considerations for weighing competing values, but measurement of recreation disturbances within an LAC analysis is often done at too fine a grain and at too narrow an extent for integration with other recreation and resource concerns. We suggest that planners should perform analysis at multiple scales when making management decisions that involve trade-offs among competing values. The United States Forest Service is used as an example to discuss how resource-management agencies can improve this integration.

Large-area Soil Moisture Surveys Using a Cosmic-ray Rover: Approaches and Results from Australia

NASA Astrophysics Data System (ADS)

Hawdon, A. A.; McJannet, D. L.; Renzullo, L. J.; Baker, B.; Searle, R.

2017-12-01

Recent improvements in satellite instrumentation has increased the resolution and frequency of soil moisture observations, and this in turn has supported the development of higher resolution land surface process models. Calibration and validation of these products is restricted by the mismatch of scales between remotely sensed and contemporary ground based observations. Although the cosmic ray neutron soil moisture probe can provide estimates soil moisture at a scale useful for the calibration and validation purposes, it is spatially limited to a single, fixed location. This scaling issue has been addressed with the development of mobile soil moisture monitoring systems that utilizes the cosmic ray neutron method, typically referred to as a `rover'. This manuscript describes a project designed to develop approaches for undertaking rover surveys to produce soil moisture estimates at scales comparable to satellite observations and land surface process models. A custom designed, trailer-mounted rover was used to conduct repeat surveys at two scales in the Mallee region of Victoria, Australia. A broad scale survey was conducted at 36 x 36 km covering an area of a standard SMAP pixel and an intensive scale survey was conducted over a 10 x 10 km portion of the broad scale survey, which is at a scale equivalent to that used for national water balance modelling. We will describe the design of the rover, the methods used for converting neutron counts into soil moisture and discuss factors controlling soil moisture variability. We found that the intensive scale rover surveys produced reliable soil moisture estimates at 1 km resolution and the broad scale at 9 km resolution. We conclude that these products are well suited for future analysis of satellite soil moisture retrievals and finer scale soil moisture models.

Towards a High-Resolution Global Inundation Delineation Dataset

NASA Astrophysics Data System (ADS)

Fluet-Chouinard, E.; Lehner, B.

2011-12-01

Although their importance for biodiversity, flow regulation and ecosystem service provision is widely recognized, wetlands and temporarily inundated landscapes remain poorly mapped globally because of their inherent elusive nature. Inventorying of wetland resources has been identified in international agreements as an essential component of appropriate conservation efforts and management initiatives of these threatened ecosystems. However, despite recent advances in remote sensing surface water monitoring, current inventories of surface water variations remain incomplete at the regional-to-global scale due to methodological limitations restricting truly global application. Remote sensing wetland applications such as SAR L-band are particularly constrained by image availability and heterogeneity of acquisition dates, while coarse resolution passive microwave and multi-sensor methods cannot discriminate distinct surface water bodies. As a result, the most popular global wetland dataset remains to this day the Global Lake & Wetland Database (Lehner and Doll, 2004) a spatially inconsistent database assembled from various existing data sources. The approach taken in this project circumvents the limitations of current global wetland monitoring methods by combining globally available topographic and hydrographic data to downscale coarse resolution global inundation data (Prigent et al., 2007) and thus create a superior inundation delineation map product. The developed procedure downscales inundation data from the coarse resolution (~27km) of current passive microwave sensors to the finer spatial resolution (~500m) of the topographic and hydrographic layers of HydroSHEDS' data suite (Lehner et al., 2006), while retaining the high temporal resolution of the multi-sensor inundation dataset. From the downscaling process emerges new information on the specific location of inundation, but also on its frequency and duration. The downscaling algorithm employs a decision tree classifier trained on regional remote sensing wetland maps, to derive inundation probability followed by a seeded region growing segmentation process to redistribute the inundated area at the finer resolution. Assessment of the algorithm's performance is accomplished by evaluating the level of agreement between its outputted downscaled inundation maps and existing regional remote sensing inundation delineation. Upon completion, this project's will offer a dynamic globally seamless inundation map at an unprecedented spatial and temporal scale, which will provide the baseline inventory long requested by the research community, and will open the door to a wide array of possible conservation and hydrological modeling applications which were until now data-restricted. Literature Lehner, B., K. Verdin, and A. Jarvis. 2008. New global hydrography derived from spaceborne elevation data. Eos 89, no. 10. Lehner, B, and P Doll. 2004. Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology 296, no. 1-4: 1-22. Prigent, C., F. Papa, F. Aires, W. B. Rossow, and E. Matthews. 2007. Global inundation dynamics inferred from multiple satellite observations, 1993-2000. Journal of Geophysical Research 112, no. D12: 1-13.

Structure-level fuel load assessment in the wildland-urban interface: a fusion of airborne laser scanning and spectral remote-sensing methodologies

Treesearch

Nicholas S. Skowronski; Scott Haag; Jim Trimble; Kenneth L. Clark; Michael R. Gallagher; Richard G. Lathrop

2015-01-01

Large-scale fuel assessments are useful for developing policy aimed at mitigating wildfires in the wildland-urban interface (WUI), while finer-scale characterisation is necessary for maximising the effectiveness of fuel reduction treatments and directing suppression activities. We developed and tested an objective, consistent approach for characterising hazardous fuels...

NEIGHBORHOOD SCALE AIR QUALITY MODELING IN HOUSTON USING URBAN CANOPY PARAMETERS IN MM5 AND CMAQ WITH IMPROVED CHARACTERIZATION OF MESOSCALE LAKE-LAND BREEZE CIRCULATION

EPA Science Inventory

Advanced capability of air quality simulation models towards accurate performance at finer scales will be needed for such models to serve as tools for performing exposure and risk assessments in urban areas. It is recognized that the impact of urban features such as street and t...

Temporal carbon dynamics of forests in Washington, US: implications for ecological theory and carbon management

Treesearch

Crystal L. Raymond; Donald McKenzie

2014-01-01

We quantified carbon (C) dynamics of forests in Washington, US using theoretical models of C dynamics as a function of forest age. We fit empirical models to chronosequences of forest inventory data at two scales: a coarse-scale ecosystem classification (ecosections) and forest types (potential vegetation) within ecosections. We hypothesized that analysis at the finer...

Impact of bimodal textural heterogeneity and connectivity on flow and transport through unsaturated mine waste rock

NASA Astrophysics Data System (ADS)

Appels, Willemijn M.; Ireson, Andrew M.; Barbour, S. Lee

2018-02-01

Mine waste rock dumps have highly variable flowpaths caused by contrasting textures and geometry of materials laid down during the 'plug dumping' process. Numerical experiments were conducted to investigate how these characteristics control unsaturated zone flow and transport. Hypothetical profiles of inner-lift structure were generated with multiple point statistics and populated with hydraulic parameters of a finer and coarser material. Early arrival of water and solutes at the bottom of the lifts was observed after spring snowmelt. The leaching efficiency, a measure of the proportion of a resident solute that is flushed out of the rock via infiltrating snowmelt or rainfall, was consistently high, but modified by the structure and texture of the lift. Under high rates of net percolation during snowmelt, preferential flow was generated in coarse textured part of the rock, and solutes in the fine textured parts of the rock remained stagnant. Under lower rates of net percolation during the summer and fall, finer materialswere flushed too, and the spatial variability of solute concentration in the lift was reduced. Layering of lifts leads to lower flow rates at depth, minimizing preferential flow and increased leaching of resident solutes. These findings highlight the limited role of large scale connected geometries on focusing flow and transport under dynamic surface net percolation conditions. As such, our findings agree with recent numerical results from soil studies with Gaussian connected geometries as well as recent experimental findings, emphasizing the dominant role of matrix flow and high leaching efficiency in large waste rock dumps.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

There's No Place Like Home: Crown-of-Thorns Outbreaks in the Central Pacific Are Regionally Derived and Independent Events

PubMed Central

Timmers, Molly A.; Bird, Christopher E.; Skillings, Derek J.; Smouse, Peter E.; Toonen, Robert J.

2012-01-01

One of the most significant biological disturbances on a tropical coral reef is a population outbreak of the fecund, corallivorous crown-of-thorns sea star, Acanthaster planci. Although the factors that trigger an initial outbreak may vary, successive outbreaks within and across regions are assumed to spread via the planktonic larvae released from a primary outbreak. This secondary outbreak hypothesis is predominantly based on the high dispersal potential of A. planci and the assertion that outbreak populations (a rogue subset of the larger population) are genetically more similar to each other than they are to low-density non-outbreak populations. Here we use molecular techniques to evaluate the spatial scale at which A. planci outbreaks can propagate via larval dispersal in the central Pacific Ocean by inferring the location and severity of gene flow restrictions from the analysis of mtDNA control region sequence (656 specimens, 17 non-outbreak and six outbreak locations, six archipelagos, and three regions). Substantial regional, archipelagic, and subarchipelagic-scale genetic structuring of A. planci populations indicate that larvae rarely realize their dispersal potential and outbreaks in the central Pacific do not spread across the expanses of open ocean. On a finer scale, genetic partitioning was detected within two of three islands with multiple sampling sites. The finest spatial structure was detected at Pearl & Hermes Atoll, between the lagoon and forereef habitats (<10 km). Despite using a genetic marker capable of revealing subtle partitioning, we found no evidence that outbreaks were a rogue genetic subset of a greater population. Overall, outbreaks that occur at similar times across population partitions are genetically independent and likely due to nutrient inputs and similar climatic and ecological conditions that conspire to fuel plankton blooms. PMID:22363570

Phylodynamics of the HIV-1 CRF02_AG clade in Cameroon

PubMed Central

Faria, Nuno Rodrigues; Suchard, Marc A; Abecasis, Ana; Sousa, J. D.; Ndembi, Nicaise; Camacho, R.J.; Vandamme, Anne-Mieke; Peeters, Martine; Lemey, Philippe

2015-01-01

Evolutionary analyses have revealed an origin of pandemic HIV-1 group M in the Congo River basin in the first part of the XXth century, but the patterns of historical viral spread in or around its epicentre remain largely unexplored. Here, we combine epidemiologic and molecular sequence data to investigate the spatiotemporal patterns of the CRF02_AG clade. By explicitly integrating prevalence counts and genetic population size estimates we date the epidemic emergence of CRF02_AG at 1973.1 (1972.1, 1975.3 95% CI). To infer their phylogeographic signature at a regional scale, we analyze pol and env time-stamped sequence data from 8 countries using a Bayesian phylogeographic approach based on a discrete asymmetric model. Our data confirms a spatial origin of this clade in the Democratic Republic of Congo (DRC) and suggests that viral dissemination to Cameroon occurred at an early stage of the evolutionary history of CRF02_AG. We find considerable support for epidemiological linkage between neighbour countries. Compilation of ethnographic data suggests that well-supported viral migration was related with chance exportation events rather than by sustained human migratory flows. Finally, using sequence data from 15 locations in Cameroon, we use relaxed random walk models to explore the spatiotemporal dynamics of CRF02_AG at a finer geographical detail. Phylogeographic dispersal in continuous space reveals that at least two distinct CRF02_AG lineages are circulating in overlapping regions that are evolving at different evolutionary and diffusion rates. Altogether, by combining molecular and epidemiological data, our results provide a time scale for CRF02_AG, place its spatial root within the putative root of group-M diversity and propose a scenario for the spatiotemporal patterns of a successful HIV-1 lineage both at a regional and country-scale. PMID:21565285

Examining Extreme Events Using Dynamically Downscaled 12-km WRF Simulations

EPA Science Inventory

Continued improvements in the speed and availability of computational resources have allowed dynamical downscaling of global climate model (GCM) projections to be conducted at increasingly finer grid scales and over extended time periods. The implementation of dynamical downscal...

The contribution of area-level walkability to geographic variation in physical activity: a spatial analysis of 95,837 participants from the 45 and Up Study living in Sydney, Australia.

PubMed

Mayne, Darren J; Morgan, Geoffrey G; Jalaludin, Bin B; Bauman, Adrian E

2017-10-03

Individual-level studies support a positive relation between walkable built environments and participation in moderate-intensity walking. However, the utility of this evidence for population-level planning is less clear as it is derived at much finer spatial scales than those used for regional programming. The aims of this study were to: evaluate if individual-level relations between walkability and walking to improve health manifest at population-level spatial scales; assess the specificity of area-level walkability for walking relative to other moderate and vigorous physical activity (MVPA); describe geographic variation in walking and other MVPA; and quantify the contribution of walkability to this variation. Data on sufficient walking, sufficient MVPA, and high MVPA to improve health were analyzed for 95,837 Sydney respondents to the baseline survey of the 45 and Up Study between January 2006 and April 2010. We used conditional autoregressive models to create smoothed MVPA "disease maps" and assess relations between sufficient MVPA to improve health and area-level walkability adjusted for individual-level demographic, socioeconomic, and health factors, and area-level relative socioeconomic disadvantage. Within-cohort prevalence of meeting recommendations for sufficient walking, sufficient MVPA, and high MVPA were 31.7 (95% CI 31.4-32.0), 69.4 (95% CI 69.1-69.7), and 56.1 (95% CI 55.8-56.4) percent. Prevalence of sufficient walking was increased by 1.20 (95% CrI 1.12-1.29) and 1.07 (95% CrI 1.01-1.13) for high and medium-high versus low walkability postal areas, and for sufficient MVPA by 1.05 (95% CrI 1.01-1.08) for high versus low walkability postal areas. Walkability was not related to high MVPA. Postal area walkability explained 65.8 and 47.4 percent of residual geographic variation in sufficient walking and sufficient MVPA not attributable to individual-level factors. Walkability is associated with area-level prevalence and geographic variation in sufficient walking and sufficient MVPA to improve health in Sydney, Australia. Our study supports the use of walkability indexes at multiple spatial scales for informing population-level action to increase physical activity and the utility of spatial analysis for walkability research and planning.

Maintaining a Local Data Integration System in Support of Weather Forecast Operations

NASA Technical Reports Server (NTRS)

Watson, Leela R.; Blottman, Peter F.; Sharp, David W.; Hoeth, Brian

2010-01-01

Since 2000, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) at Johnson Space Center in Houston, TX have used a local data integration system (LDIS) as part of their forecast and warning operations. The original LDIS was developed by NASA's Applied Meteorology Unit (AMU; Bauman et ai, 2004) in 1998 (Manobianco and Case 1998) and has undergone subsequent improvements. Each has benefited from three-dimensional (3-D) analyses that are delivered to forecasters every 15 minutes across the peninsula of Florida. The intent is to generate products that enhance short-range weather forecasts issued in support of NWS MLB and SMG operational requirements within East Central Florida. The current LDIS uses the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) package as its core, which integrates a wide variety of national, regional, and local observational data sets. It assimilates all available real-time data within its domain and is run at a finer spatial and temporal resolution than current national- or regional-scale analysis packages. As such, it provides local forecasters with a more comprehensive understanding of evolving fine-scale weather features

Vulnerability of deep groundwater in the Bengal Aquifer System to contamination by arsenic

USGS Publications Warehouse

Burgess, W.G.; Hoque, M.A.; Michael, H.A.; Voss, C.I.; Breit, G.N.; Ahmed, K.M.

2010-01-01

Shallow groundwater, the primary water source in the Bengal Basin, contains up to 100 times the World Health Organization (WHO) drinking-water guideline of 10g l 1 arsenic (As), threatening the health of 70 million people. Groundwater from a depth greater than 150m, which almost uniformly meets the WHO guideline, has become the preferred alternative source. The vulnerability of deep wells to contamination by As is governed by the geometry of induced groundwater flow paths and the geochemical conditions encountered between the shallow and deep regions of the aquifer. Stratification of flow separates deep groundwater from shallow sources of As in some areas. Oxidized sediments also protect deep groundwater through the ability of ferric oxyhydroxides to adsorb As. Basin-scale groundwater flow modelling suggests that, over large regions, deep hand-pumped wells for domestic supply may be secure against As invasion for hundreds of years. By contrast, widespread deep irrigation pumping might effectively eliminate deep groundwater as an As-free resource within decades. Finer-scale models, incorporating spatial heterogeneity, are needed to investigate the security of deep municipal abstraction at specific urban locations. ?? 2010 Macmillan Publishers Limited. All rights reserved.

The Use of Census Migration Data to Approximate Human Movement Patterns across Temporal Scales

PubMed Central

Wesolowski, Amy; Buckee, Caroline O.; Pindolia, Deepa K.; Eagle, Nathan; Smith, David L.; Garcia, Andres J.; Tatem, Andrew J.

2013-01-01

Human movement plays a key role in economies and development, the delivery of services, and the spread of infectious diseases. However, it remains poorly quantified partly because reliable data are often lacking, particularly for low-income countries. The most widely available are migration data from human population censuses, which provide valuable information on relatively long timescale relocations across countries, but do not capture the shorter-scale patterns, trips less than a year, that make up the bulk of human movement. Census-derived migration data may provide valuable proxies for shorter-term movements however, as substantial migration between regions can be indicative of well connected places exhibiting high levels of movement at finer time scales, but this has never been examined in detail. Here, an extensive mobile phone usage data set for Kenya was processed to extract movements between counties in 2009 on weekly, monthly, and annual time scales and compared to data on change in residence from the national census conducted during the same time period. We find that the relative ordering across Kenyan counties for incoming, outgoing and between-county movements shows strong correlations. Moreover, the distributions of trip durations from both sources of data are similar, and a spatial interaction model fit to the data reveals the relationships of different parameters over a range of movement time scales. Significant relationships between census migration data and fine temporal scale movement patterns exist, and results suggest that census data can be used to approximate certain features of movement patterns across multiple temporal scales, extending the utility of census-derived migration data. PMID:23326367

Examination of turbulent entrainment-mixing mechanisms using a combined approach

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

Lu, C.; Liu, Y.; Niu, S.

2011-10-01

Turbulent entrainment-mixing mechanisms are investigated by applying a combined approach to the aircraft measurements of three drizzling and two nondrizzling stratocumulus clouds collected over the U.S. Department of Energy's Atmospheric Radiation Measurement Southern Great Plains site during the March 2000 cloud Intensive Observation Period. Microphysical analysis shows that the inhomogeneous entrainment-mixing process occurs much more frequently than the homogeneous counterpart, and most cases of the inhomogeneous entrainment-mixing process are close to the extreme scenario, having drastically varying cloud droplet concentration but roughly constant volume-mean radius. It is also found that the inhomogeneous entrainment-mixing process can occur both near the cloudmore » top and in the middle level of a cloud, and in both the nondrizzling clouds and nondrizzling legs in the drizzling clouds. A new dimensionless number, the scale number, is introduced as a dynamical measure for different entrainment-mixing processes, with a larger scale number corresponding to a higher degree of homogeneous entrainment mixing. Further empirical analysis shows that the scale number that separates the homogeneous from the inhomogeneous entrainment-mixing process is around 50, and most legs have smaller scale numbers. Thermodynamic analysis shows that sampling average of filament structures finer than the instrumental spatial resolution also contributes to the dominance of inhomogeneous entrainment-mixing mechanism. The combined microphysical-dynamical-thermodynamic analysis sheds new light on developing parameterization of entrainment-mixing processes and their microphysical and radiative effects in large-scale models.« less

Simulation of all-scale atmospheric dynamics on unstructured meshes

NASA Astrophysics Data System (ADS)

Smolarkiewicz, Piotr K.; Szmelter, Joanna; Xiao, Feng

2016-10-01

The advance of massively parallel computing in the nineteen nineties and beyond encouraged finer grid intervals in numerical weather-prediction models. This has improved resolution of weather systems and enhanced the accuracy of forecasts, while setting the trend for development of unified all-scale atmospheric models. This paper first outlines the historical background to a wide range of numerical methods advanced in the process. Next, the trend is illustrated with a technical review of a versatile nonoscillatory forward-in-time finite-volume (NFTFV) approach, proven effective in simulations of atmospheric flows from small-scale dynamics to global circulations and climate. The outlined approach exploits the synergy of two specific ingredients: the MPDATA methods for the simulation of fluid flows based on the sign-preserving properties of upstream differencing; and the flexible finite-volume median-dual unstructured-mesh discretisation of the spatial differential operators comprising PDEs of atmospheric dynamics. The paper consolidates the concepts leading to a family of generalised nonhydrostatic NFTFV flow solvers that include soundproof PDEs of incompressible Boussinesq, anelastic and pseudo-incompressible systems, common in large-eddy simulation of small- and meso-scale dynamics, as well as all-scale compressible Euler equations. Such a framework naturally extends predictive skills of large-eddy simulation to the global atmosphere, providing a bottom-up alternative to the reverse approach pursued in the weather-prediction models. Theoretical considerations are substantiated by calculations attesting to the versatility and efficacy of the NFTFV approach. Some prospective developments are also discussed.

Individual differences in mental rotation: what does gesture tell us?

PubMed

Göksun, Tilbe; Goldin-Meadow, Susan; Newcombe, Nora; Shipley, Thomas

2013-05-01

Gestures are common when people convey spatial information, for example, when they give directions or describe motion in space. Here, we examine the gestures speakers produce when they explain how they solved mental rotation problems (Shepard and Meltzer in Science 171:701-703, 1971). We asked whether speakers gesture differently while describing their problems as a function of their spatial abilities. We found that low-spatial individuals (as assessed by a standard paper-and-pencil measure) gestured more to explain their solutions than high-spatial individuals. While this finding may seem surprising, finer-grained analyses showed that low-spatial participants used gestures more often than high-spatial participants to convey "static only" information but less often than high-spatial participants to convey dynamic information. Furthermore, the groups differed in the types of gestures used to convey static information: high-spatial individuals were more likely than low-spatial individuals to use gestures that captured the internal structure of the block forms. Our gesture findings thus suggest that encoding block structure may be as important as rotating the blocks in mental spatial transformation.

Uncertainty of future projections of species distributions in mountainous regions.

PubMed

Tang, Ying; Winkler, Julie A; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution.

Uncertainty of future projections of species distributions in mountainous regions

PubMed Central

Tang, Ying; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution. PMID:29320501

From functional architecture to functional connectomics.

PubMed

Reid, R Clay

2012-07-26

"Receptive Fields, Binocular Interaction and Functional Architecture in the Cat's Visual Cortex" by Hubel and Wiesel (1962) reported several important discoveries: orientation columns, the distinct structures of simple and complex receptive fields, and binocular integration. But perhaps the paper's greatest influence came from the concept of functional architecture (the complex relationship between in vivo physiology and the spatial arrangement of neurons) and several models of functionally specific connectivity. They thus identified two distinct concepts, topographic specificity and functional specificity, which together with cell-type specificity constitute the major determinants of nonrandom cortical connectivity. Orientation columns are iconic examples of topographic specificity, whereby axons within a column connect with cells of a single orientation preference. Hubel and Wiesel also saw the need for functional specificity at a finer scale in their model of thalamic inputs to simple cells, verified in the 1990s. The difficult but potentially more important question of functional specificity between cortical neurons is only now becoming tractable with new experimental techniques. Copyright © 2012 Elsevier Inc. All rights reserved.

Transport and radiative impacts of atmospheric pollen using online, observation-based emissions

NASA Astrophysics Data System (ADS)

Wozniak, M. C.; Steiner, A. L.; Solmon, F.; Li, Y.

2015-12-01

Atmospheric pollen emitted from trees and grasses exhibits both a high temporal variability and a highly localized spatial distribution that has been difficult to quantify in the atmosphere. Pollen's radiative impact is also not quantified because it is neglected in climate modeling studies. Here we couple an online, meteorological active pollen emissions model guided by observations of airborne pollen to understand the role of pollen in the atmosphere. We use existing pollen counts from 2003-2008 across the continental U.S. in conjunction with a tree database and historical meteorological data to create an observation-based phenological model that produces accurately scaled and timed emissions. These emissions are emitted and transported within the regional climate model (RegCM4) and the direct radiative effect is calculated. Additionally, we simulate the rupture of coarse pollen grains into finer particles by adding a second size mode for pollen emissions, which contributes to the shortwave radiative forcing and also has an indirect effect on climate.

Discovering loose group movement patterns from animal trajectories

USGS Publications Warehouse

Wang, Yuwei; Luo, Ze; Xiong, Yan; Prosser, Diann J.; Newman, Scott H.; Takekawa, John Y.; Yan, Baoping

2015-01-01

The technical advances of positioning technologies enable us to track animal movements at finer spatial and temporal scales, and further help to discover a variety of complex interactive relationships. In this paper, considering the loose gathering characteristics of the real-life groups' members during the movements, we propose two kinds of loose group movement patterns and corresponding discovery algorithms. Firstly, we propose the weakly consistent group movement pattern which allows the gathering of a part of the members and individual temporary leave from the whole during the movements. To tolerate the high dispersion of the group at some moments (i.e. to adapt the discontinuity of the group's gatherings), we further scheme the weakly consistent and continuous group movement pattern. The extensive experimental analysis and comparison with the real and synthetic data shows that the group pattern discovery algorithms proposed in this paper are similar to the the real-life frequent divergences of the members during the movements, can discover more complete memberships, and have considerable performance.

Scaling of surface energy fluxes using remotely sensed data

NASA Astrophysics Data System (ADS)

French, Andrew Nichols

Accurate estimates of evapotranspiration (ET) across multiple terrains would greatly ease challenges faced by hydrologists, climate modelers, and agronomists as they attempt to apply theoretical models to real-world situations. One ET estimation approach uses an energy balance model to interpret a combination of meteorological observations taken at the surface and data captured by remote sensors. However, results of this approach have not been accurate because of poor understanding of the relationship between surface energy flux and land cover heterogeneity, combined with limits in available resolution of remote sensors. The purpose of this study was to determine how land cover and image resolution affect ET estimates. Using remotely sensed data collected over El Reno, Oklahoma, during four days in June and July 1997, scale effects on the estimation of spatially distributed ET were investigated. Instantaneous estimates of latent and sensible heat flux were calculated using a two-source surface energy balance model driven by thermal infrared, visible-near infrared, and meteorological data. The heat flux estimates were verified by comparison to independent eddy-covariance observations. Outcomes of observations taken at coarser resolutions were simulated by aggregating remote sensor data and estimated surface energy balance components from the finest sensor resolution (12 meter) to hypothetical resolutions as coarse as one kilometer. Estimated surface energy flux components were found to be significantly dependent on observation scale. For example, average evaporative fraction varied from 0.79, using 12-m resolution data, to 0.93, using 1-km resolution data. Resolution effects upon flux estimates were related to a measure of landscape heterogeneity known as operational scale, reflecting the size of dominant landscape features. Energy flux estimates based on data at resolutions less than 100 m and much greater than 400 m showed a scale-dependent bias. But estimates derived from data taken at about 400-m resolution (the operational scale at El Reno) were susceptible to large error due to mixing of surface types. The El Reno experiments show that accurate instantaneous estimates of ET require precise image alignment and image resolutions finer than landscape operational scale. These findings are valuable for the design of sensors and experiments to quantify spatially-varying hydrologic processes.

Spatial forecasting of disease risk and uncertainty

USGS Publications Warehouse

De Cola, L.

2002-01-01

Because maps typically represent the value of a single variable over 2-dimensional space, cartographers must simplify the display of multiscale complexity, temporal dynamics, and underlying uncertainty. A choropleth disease risk map based on data for polygonal regions might depict incidence (cases per 100,000 people) within each polygon for a year but ignore the uncertainty that results from finer-scale variation, generalization, misreporting, small numbers, and future unknowns. In response to such limitations, this paper reports on the bivariate mapping of data "quantity" and "quality" of Lyme disease forecasts for states of the United States. Historical state data for 1990-2000 are used in an autoregressive model to forecast 2001-2010 disease incidence and a probability index of confidence, each of which is then kriged to provide two spatial grids representing continuous values over the nation. A single bivariate map is produced from the combination of the incidence grid (using a blue-to-red hue spectrum), and a probabilistic confidence grid (used to control the saturation of the hue at each grid cell). The resultant maps are easily interpretable, and the approach may be applied to such problems as detecting unusual disease occurences, visualizing past and future incidence, and assembling a consistent regional disease atlas showing patterns of forecasted risks in light of probabilistic confidence.

Hurricane frequency and landfall distribution for coastal wetlands of the Gulf coast, USA

USGS Publications Warehouse

Doyle, T.W.

2009-01-01

The regularity and severity of tropical storms are major determinants controlling ecosystem structure and succession for coastal ecosystems. Hurricane landfall rates vary greatly with high and low frequency for given coastal stretches of the southeastern United States. Site-specific meteorological data of hurricane wind speeds and direction, however, are only available for select populated cities of relatively sparse distribution and inland from the coast. A spatial simulation model of hurricane circulation, HURASIM, was applied to reconstruct chronologies of hurricane wind speeds and vectors for northern Gulf coast locations derived from historical tracking data of North Atlantic tropical storms dating back to 1851. Contrasts of storm frequencies showed that tropical storm incidence is nearly double for Florida coastal ecosystems than the westernmost stretches of Texas coastline. Finer-scale spatial simulations for the north-central Gulf coast exhibited sub-regional differences in storm strength and frequency with coastal position and latitude. The overall pattern of storm incidence in the Gulf basin indicates that the disturbance regime of coastal areas varies greatly along the coast, inland from the coast, and temporally over the period of record. Field and modeling studies of coastal ecosystems will benefit from this retrospective analysis of hurricane incidence and intensity both on a local or regional basis. ?? 2009 The Society of Wetland Scientists.

Great influence of geographic isolation on the genetic differentiation of Myriophyllum spicatum under a steep environmental gradient

PubMed Central

Wu, Zhigang; Yu, Dan; Wang, Zhong; Li, Xing; Xu, Xinwei

2015-01-01

Understanding how natural processes affect population genetic structures is an important issue in evolutionary biology. One effective method is to assess the relative importance of environmental and geographical factors in the genetic structure of populations. In this study, we examined the spatial genetic variation of thirteen Myriophyllum spicatum populations from the Qinghai-Tibetan Plateau (QTP) and adjacent highlands (Yunnan-Guizhou Plateau, YGP) by using microsatellite loci and environmental and geographical factors. Bioclim layers, hydrological properties and elevation were considered as environmental variables and reduced by principal component analysis. The genetic isolation by geographic distance (IBD) was tested by Mantel tests and the relative importance of environmental variables on population genetic differentiation was determined by a partial Mantel test and multiple matrix regression with randomization (MMRR). Two genetic clusters corresponding to the QTP and YGP were identified. Both tests and MMRR revealed a significant and strong correlation between genetic divergence and geographic isolation under the influence of environmental heterogeneity at the overall and finer spatial scales. Our findings suggested the dominant role of geography on the evolution of M. spicatum under a steep environmental gradient in the alpine landscape as a result of dispersal limitation and genetic drift. PMID:26494202

Multiple energetic injections in a strong spike-like solar burst

NASA Technical Reports Server (NTRS)

Kaufmann, P.; Correia, E.; Costa, J. E. R.; Dennis, B. R.; Hurford, G. J.; Brown, J. C.

1984-01-01

An intense and fast spike-like solar burst was built up of short time scale structures superimposed on an underlying gradual emission, the time evolution of which shows remarkable proportionality between hard X-ray and microwave fluxes. The finer time structures were best defined at mm-microwaves. At the peak of the event, the finer structures repeat every 30 x 60 ms. The more slowly varying component with a time scale of about 1 second was identified in microwave hard X-rays throughout the burst duration. It is suggested that X-ray fluxes might also be proportional to the repetition rate of basic units of energy injection (quasi-quantized). The relevant parameters of one primary energy release site are estimated both in the case where hard X-rays are produced primarily by thick-target bremsstrahlung, and when they are purely thermal. The relation of this figure to global energy considerations is discussed. Previously announced in STAR as N83-35983

Sounds different: inbreeding depression in sexually selected traits in the cricket Teleogryllus commodus.

PubMed

Drayton, J M; Hunt, J; Brooks, R; Jennions, M D

2007-05-01

If male sexual signalling is honest because it captures genetic variation in condition then traits that are important mate choice cues should be disproportionately affected by inbreeding relative to other traits. To test this, we investigated the effect of brother-sister mating on advertisement calling by male field crickets Teleogryllus commodus. We quantified the effect of one generation of inbreeding on nightly calling effort and five finer-scale aspects of call structure that have been shown to influence attractiveness. We also quantified inbreeding depression on six life history traits and one morphological trait. Inbreeding significantly reduced hatching success, nymph survival and adult lifespan but had no detectable effect on hatching rate, developmental rate or adult body mass. The effect of inbreeding on sexually selected traits was equivocal. There was no decline in calling effort (seconds of sound production/night) by inbred males, but there were highly significant changes in three of five finer-scale call parameters. Sexually selected traits clearly vary in their susceptibility to inbreeding depression.

Global motion perception in children with amblyopia as a function of spatial and temporal stimulus parameters.

PubMed

Meier, Kimberly; Sum, Brian; Giaschi, Deborah

2016-10-01

Global motion sensitivity in typically developing children depends on the spatial (Δx) and temporal (Δt) displacement parameters of the motion stimulus. Specifically, sensitivity for small Δx values matures at a later age, suggesting it may be the most vulnerable to damage by amblyopia. To explore this possibility, we compared motion coherence thresholds of children with amblyopia (7-14years old) to age-matched controls. Three Δx values were used with two Δt values, yielding six conditions covering a range of speeds (0.3-30deg/s). We predicted children with amblyopia would show normal coherence thresholds for the same parameters on which 5-year-olds previously demonstrated mature performance, and elevated coherence thresholds for parameters on which 5-year-olds demonstrated immaturities. Consistent with this, we found that children with amblyopia showed deficits with amblyopic eye viewing compared to controls for small and medium Δx values, regardless of Δt value. The fellow eye showed similar results at the smaller Δt. These results confirm that global motion perception in children with amblyopia is particularly deficient at the finer spatial scales that typically mature later in development. An additional implication is that carefully designed stimuli that are adequately sensitive must be used to assess global motion function in developmental disorders. Stimulus parameters for which performance matures early in life may not reveal global motion perception deficits. Copyright © 2016 Elsevier Ltd. All rights reserved.

Testing spatial heterogeneity with stock assessment models

PubMed Central

Eero, Margit; Silva, Alexandra; Ulrich, Clara; Pawlowski, Lionel; Holmes, Steven J.; Ibaibarriaga, Leire; De Oliveira, José A. A.; Riveiro, Isabel; Alzorriz, Nekane; Citores, Leire; Scott, Finlay; Uriarte, Andres; Carrera, Pablo; Duhamel, Erwan; Mosqueira, Iago

2018-01-01

This paper describes a methodology that combines meta-population theory and stock assessment models to gain insights about spatial heterogeneity of the meta-population in an operational time frame. The methodology was tested with stochastic simulations for different degrees of connectivity between sub-populations and applied to two case studies, North Sea cod (Gadus morua) and Northeast Atlantic sardine (Sardina pilchardus). Considering that the biological components of a population can be partitioned into discrete spatial units, we extended this idea into a property of additivity of sub-population abundances. If the additivity results hold true for putative sub-populations, then assessment results based on sub-populations will provide information to develop and monitor the implementation of finer scale/local management. The simulation study confirmed that when sub-populations are independent and not too heterogeneous with regards to productivity, the sum of stock assessment model estimates of sub-populations’ SSB is similar to the SSB estimates of the meta-population. It also showed that a strong diffusion process can be detected and that the stronger the connection between SSB and recruitment, the better the diffusion process will be detected. On the other hand it showed that weak to moderate diffusion processes are not easy to identify and large differences between sub-populations productivities may be confounded with weak diffusion processes. The application to North Sea cod and Atlantic sardine exemplified how much insight can be gained. In both cases the results obtained were sufficiently robust to support the regional analysis. PMID:29364901

Classification of JERS-1 Image Mosaic of Central Africa Using A Supervised Multiscale Classifier of Texture Features

NASA Technical Reports Server (NTRS)

Saatchi, Sassan; DeGrandi, Franco; Simard, Marc; Podest, Erika

1999-01-01

In this paper, a multiscale approach is introduced to classify the Japanese Research Satellite-1 (JERS-1) mosaic image over the Central African rainforest. A series of texture maps are generated from the 100 m mosaic image at various scales. Using a quadtree model and relating classes at each scale by a Markovian relationship, the multiscale images are classified from course to finer scale. The results are verified at various scales and the evolution of classification is monitored by calculating the error at each stage.

Fine-scale assessment of home ranges and activity patterns for resident black vultures (Coragyps atratus) and turkey vultures (Cathartes aura)

DOE PAGES

Holland, Amanda E.; Byrne, Michael E.; Bryan, A. Lawrence; ...

2017-07-05

Knowledge of black vulture (Coragyps atratus) and turkey vulture (Cathartes aura) spatial ecology is surprisingly limited despite their vital ecological roles. Fine-scale assessments of space use patterns and resource selection are particularly lacking, although development of tracking technologies has allowed data collection at finer temporal and spatial resolution. The objectives of this study were to conduct the first assessment of monthly home range and core area sizes of resident black and turkey vultures with consideration to sex, as well as elucidate differences in monthly, seasonal, and annual activity patterns based on fine-scale movement data analyses. We collected 2.8-million locations formore » 9 black and 9 turkey vultures from June 2013 –August 2015 using solar-powered GSM/GPS transmitters. We quantified home ranges and core areas using the dynamic Brownian bridge movement model and evaluated differences as a function of species, sex, and month. Mean monthly home ranges for turkey vultures were ~50% larger than those of black vultures, although mean core area sizes did not differ between species. Turkey vulture home ranges varied little across months, with exception to a notable reduction in space-use in May, which corresponds with timing of chick-rearing activities. Black vulture home ranges and core areas as well as turkey vulture core areas were larger in breeding season months (January–April). Comparison of space use between male and female vultures was only possible for black vultures, and space use was only slightly larger for females during breeding months (February–May). Analysis of activity patterns revealed turkey vultures spend more time in flight and switch motion states (between flight and stationary) more frequently than black vultures across temporal scales. Our study reveals substantive variability in space use and activity rates between sympatric black and turkey vultures, providing insights into potential behavioral mechanisms contributing to niche differentiation between these species.« less

Development and Application of a Process-based River System Model at a Continental Scale

NASA Astrophysics Data System (ADS)

Kim, S. S. H.; Dutta, D.; Vaze, J.; Hughes, J. D.; Yang, A.; Teng, J.

2014-12-01

Existing global and continental scale river models, mainly designed for integrating with global climate model, are of very course spatial resolutions and they lack many important hydrological processes, such as overbank flow, irrigation diversion, groundwater seepage/recharge, which operate at a much finer resolution. Thus, these models are not suitable for producing streamflow forecast at fine spatial resolution and water accounts at sub-catchment levels, which are important for water resources planning and management at regional and national scale. A large-scale river system model has been developed and implemented for water accounting in Australia as part of the Water Information Research and Development Alliance between Australia's Bureau of Meteorology (BoM) and CSIRO. The model, developed using node-link architecture, includes all major hydrological processes, anthropogenic water utilisation and storage routing that influence the streamflow in both regulated and unregulated river systems. It includes an irrigation model to compute water diversion for irrigation use and associated fluxes and stores and a storage-based floodplain inundation model to compute overbank flow from river to floodplain and associated floodplain fluxes and stores. An auto-calibration tool has been built within the modelling system to automatically calibrate the model in large river systems using Shuffled Complex Evolution optimiser and user-defined objective functions. The auto-calibration tool makes the model computationally efficient and practical for large basin applications. The model has been implemented in several large basins in Australia including the Murray-Darling Basin, covering more than 2 million km2. The results of calibration and validation of the model shows highly satisfactory performance. The model has been operalisationalised in BoM for producing various fluxes and stores for national water accounting. This paper introduces this newly developed river system model describing the conceptual hydrological framework, methods used for representing different hydrological processes in the model and the results and evaluation of the model performance. The operational implementation of the model for water accounting is discussed.

Imputing forest carbon stock estimates from inventory plots to a nationally continuous coverage

PubMed Central

2013-01-01

The U.S. has been providing national-scale estimates of forest carbon (C) stocks and stock change to meet United Nations Framework Convention on Climate Change (UNFCCC) reporting requirements for years. Although these currently are provided as national estimates by pool and year to meet greenhouse gas monitoring requirements, there is growing need to disaggregate these estimates to finer scales to enable strategic forest management and monitoring activities focused on various ecosystem services such as C storage enhancement. Through application of a nearest-neighbor imputation approach, spatially extant estimates of forest C density were developed for the conterminous U.S. using the U.S.’s annual forest inventory. Results suggest that an existing forest inventory plot imputation approach can be readily modified to provide raster maps of C density across a range of pools (e.g., live tree to soil organic carbon) and spatial scales (e.g., sub-county to biome). Comparisons among imputed maps indicate strong regional differences across C pools. The C density of pools closely related to detrital input (e.g., dead wood) is often highest in forests suffering from recent mortality events such as those in the northern Rocky Mountains (e.g., beetle infestations). In contrast, live tree carbon density is often highest on the highest quality forest sites such as those found in the Pacific Northwest. Validation results suggest strong agreement between the estimates produced from the forest inventory plots and those from the imputed maps, particularly when the C pool is closely associated with the imputation model (e.g., aboveground live biomass and live tree basal area), with weaker agreement for detrital pools (e.g., standing dead trees). Forest inventory imputed plot maps provide an efficient and flexible approach to monitoring diverse C pools at national (e.g., UNFCCC) and regional scales (e.g., Reducing Emissions from Deforestation and Forest Degradation projects) while allowing timely incorporation of empirical data (e.g., annual forest inventory). PMID:23305341

Fine-scale assessment of home ranges and activity patterns for resident black vultures (Coragyps atratus) and turkey vultures (Cathartes aura)

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

Holland, Amanda E.; Byrne, Michael E.; Bryan, A. Lawrence

Knowledge of black vulture (Coragyps atratus) and turkey vulture (Cathartes aura) spatial ecology is surprisingly limited despite their vital ecological roles. Fine-scale assessments of space use patterns and resource selection are particularly lacking, although development of tracking technologies has allowed data collection at finer temporal and spatial resolution. The objectives of this study were to conduct the first assessment of monthly home range and core area sizes of resident black and turkey vultures with consideration to sex, as well as elucidate differences in monthly, seasonal, and annual activity patterns based on fine-scale movement data analyses. We collected 2.8-million locations formore » 9 black and 9 turkey vultures from June 2013 –August 2015 using solar-powered GSM/GPS transmitters. We quantified home ranges and core areas using the dynamic Brownian bridge movement model and evaluated differences as a function of species, sex, and month. Mean monthly home ranges for turkey vultures were ~50% larger than those of black vultures, although mean core area sizes did not differ between species. Turkey vulture home ranges varied little across months, with exception to a notable reduction in space-use in May, which corresponds with timing of chick-rearing activities. Black vulture home ranges and core areas as well as turkey vulture core areas were larger in breeding season months (January–April). Comparison of space use between male and female vultures was only possible for black vultures, and space use was only slightly larger for females during breeding months (February–May). Analysis of activity patterns revealed turkey vultures spend more time in flight and switch motion states (between flight and stationary) more frequently than black vultures across temporal scales. Our study reveals substantive variability in space use and activity rates between sympatric black and turkey vultures, providing insights into potential behavioral mechanisms contributing to niche differentiation between these species.« less

Properties and spatial distribution of galaxy superclusters

NASA Astrophysics Data System (ADS)

Liivamägi, Lauri Juhan

2017-01-01

Astronomy is a science that can offer plenty of unforgettable imagery, and the large-scale distribution of galaxies is no exception. Among the first features the viewer's eye is likely to be drawn to, are large concentrations of galaxies - galaxy superclusters, contrasting to the seemingly empty regions beside them. Superclusters can extend from tens to over hundred megaparsecs, they contain from hundreds to thousands of galaxies, and many galaxy groups and clusters. Unlike galaxy clusters, superclusters are clearly unrelaxed systems, not gravitationally bound as crossing times exceed the age of the universe, and show little to no radial symmetry. Superclusters, as part of the large-scale structure, are sensitive to the initial power spectrum and the following evolution. They are massive enough to leave an imprint on the cosmic microwave background radiation. Superclusters can also provide an unique environment for their constituent galaxies and galaxy clusters. In this study we used two different observational and one simulated galaxy samples to create several catalogues of structures that, we think, correspond to what are generally considered galaxy superclusters. Superclusters were delineated as continuous over-dense regions in galaxy luminosity density fields. When calculating density fields several corrections were applied to remove small-scale redshift distortions and distance-dependent selection effects. Resulting catalogues of objects display robust statistical properties, showing that flux-limited galaxy samples can be used to create nearly volume-limited catalogues of superstructures. Generally, large superclusters can be regarded as massive, often branching filamentary structures, that are mainly characterised by their length. Smaller superclusters, on the other hand, can display a variety of shapes. Spatial distribution of superclusters shows large-scale variations, with high-density concentrations often found in semi-regularly spaced groups. Future studies are needed to quantify the relations between superclusters and finer details of the galaxy distribution. Supercluster catalogues from this thesis have already been used in numerous other studies.

Identification and simulation of space-time variability of past hydrological drought events in the Limpopo river basin, Southern Africa

NASA Astrophysics Data System (ADS)

Trambauer, P.; Maskey, S.; Werner, M.; Pappenberger, F.; van Beek, L. P. H.; Uhlenbrook, S.

2014-03-01

Droughts are widespread natural hazards and in many regions their frequency seems to be increasing. A finer resolution version (0.05° x 0.05°) of the continental scale hydrological model PCR-GLOBWB was set up for the Limpopo river basin, one of the most water stressed basins on the African continent. An irrigation module was included to account for large irrigated areas of the basin. The finer resolution model was used to analyse droughts in the Limpopo river basin in the period 1979-2010 with a view to identifying severe droughts that have occurred in the basin. Evaporation, soil moisture, groundwater storage and runoff estimates from the model were derived at a spatial resolution of 0.05° (approximately 5 km) on a daily time scale for the entire basin. PCR-GLOBWB was forced with daily precipitation, temperature and other meteorological variables obtained from the ERA-Interim global atmospheric reanalysis product from the European Centre for Medium-Range Weather Forecasts. Two agricultural drought indicators were computed: the Evapotranspiration Deficit Index (ETDI) and the Root Stress Anomaly Index (RSAI). Hydrological drought was characterised using the Standardized Runoff Index (SRI) and the Groundwater Resource Index (GRI), which make use of the streamflow and groundwater storage resulting from the model. Other more widely used drought indicators, such as the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evaporation Index (SPEI) were also computed for different aggregation periods. Results show that a carefully set up process-based model that makes use of the best available input data can successfully identify hydrological droughts even if the model is largely uncalibrated. The indicators considered are able to represent the most severe droughts in the basin and to some extent identify the spatial variability of droughts. Moreover, results show the importance of computing indicators that can be related to hydrological droughts, and how these add value to the identification of droughts/floods and the temporal evolution of events that would otherwise not have been apparent when considering only meteorological indicators. In some cases, meteorological indicators alone fail to capture the severity of the drought. Therefore, a combination of some of these indicators (e.g. SPEI-3, SRI-6, SPI-12) is found to be a useful measure for identifying hydrological droughts in the Limpopo river basin. Additionally, it is possible to make a characterisation of the drought severity, indicated by its duration and intensity.

What is the effect of local controls on the temporal stability of soil water contents?

NASA Astrophysics Data System (ADS)

Martinez, G.; Pachepsky, Y. A.; Vereecken, H.; Vanderlinden, K.; Hardelauf, H.; Herbst, M.

2012-04-01

Temporal stability of soil water content (TS SWC) reflects the spatio-temporal organization of SWC. Factors and their interactions that control this organization, are not completely understood and have not been quantified yet. It is understood that these factors should be classified into groups of local and non-local controls. This work is a first attempt to evaluate the effects of soil properties at a certain location as local controls Time series of SWC were generated by running water flow simulations with the HYDRUS6 code. Bare and grassed sandy loam, loam and clay soils were represented by sets of 100 independent soil columns. Within each set, values of saturated hydraulic conductivity (Ks) were generated randomly assuming for the standard deviation of the scaling factor of ln Ks a value ranging from 0.1 to 1.0. Weather conditions were the same for all of the soil columns. SWC at depths of 0.05 and 0.60 m, and the average water content of the top 1 m were analyzed. The temporal stability was characterized by calculating the mean relative differences (MRD) of soil water content. MRD distributions from simulations, developed from the log-normal distribution of Ks, agreed well with the experimental studies found in the literature. Generally, Ks was the leading variable to define the MRD rank for a specific location. Higher MRD corresponded to the lowest values of Ks when a single textural class was considered. Higher MRD were found in the finer texture when mixtures of textural classes were considered and similar values of Ks were compared. The relationships between the spread of the MRD distributions and the scaling factor of ln Ks were nonlinear. Variation in MRD was higher in coarser textures than in finer ones and more variability was seen in the topsoil than in the subsoil. Established vegetation decreased variability of MRD in the root zone and increased variability below. The dependence of MRD on Ks opens the possibility of using SWC sensor networks to relate variations of MRD of measured SWC time series to spatial variations of Ks. TS of SWC can provide information on Ks variability at ungauged watersheds if the effect of non-local controls of SWC on TS is not significant. Using the spatiotemporal statistics to convert the information about the temporal variability of soil moisture into information about the spatial variability of soil hydraulic properties presents an interesting avenue for further exploration.

Estimation of Satellite-Based SO42- and NH4+ Composition of Ambient Fine Particulate Matter Over China Using Chemical Transport Model

NASA Astrophysics Data System (ADS)

Si, Y.; Li, S.; Chen, L.; Yu, C.; Zhu, W.

2018-04-01

Epidemiologic and health impact studies have examined the chemical composition of ambient PM2.5 in China but have been constrained by the paucity of long-term ground measurements. Using the GEOS-Chem chemical transport model and satellite-derived PM2.5 data, sulfate and ammonium levels were estimated over China from 2004 to 2014. A comparison of the satellite-estimated dataset with model simulations based on ground measurements obtained from the literature indicated our results are more accurate. Using satellite-derived PM2.5 data with a spatial resolution of 0.1° × 0.1°, we further presented finer satellite-estimated sulfate and ammonium concentrations in anthropogenic polluted regions, including the NCP (the North China Plain), the SCB (the Sichuan Basin) and the PRD (the Pearl River Delta). Linear regression results obtained on a national scale yielded an r value of 0.62, NMB of -35.9 %, NME of 48.2 %, ARB_50 % of 53.68 % for sulfate and an r value of 0.63, slope of 0.67, and intercept of 5.14 for ammonium. In typical regions, the satellite-derived dataset was significantly robust. Based on the satellite-derived dataset, the spatial-temporal variation of 11-year annual average satellite-derived SO42- and NH4+ concentrations and time series of monthly average concentrations were also investigated. On a national scale, both exhibited a downward trend each year between 2004 and 2014 (SO42-: -0.61 %; NH4+: -0.21 %), large values were mainly concentrated in the NCP and SCB. For regions captured at a finer resolution, the inter-annual variation trends presented a positive trend over the periods 2004-2007 and 2008-2011, followed by a negative trend over the period 2012-2014, and sulfate concentrations varied appreciably. Moreover, the seasonal distributions of the 11-year satellite-derived dataset over China were presented. The distribution of both sulfate and ammonium concentrations exhibited seasonal characteristics, with the seasonal concentrations ranking as follows: winter > summer > autumn > spring. High concentrations of these species were concentrated in the NCP and SCB, originating from coal-fired power plants and agricultural activities, respectively. Efforts to reduce sulfur dioxide (SO2) emissions have yielded remarkable results since the government has adopted stricter control measures in recent years. Moreover, ammonia emissions should be controlled while reducing the concentration of sulfur, nitrogen and particulate matter. This study provides an assessment of the population's exposure to certain chemical components.

A Simple Downscaling Algorithm for Remotely Sensed Land Surface Temperature

NASA Astrophysics Data System (ADS)

Sandholt, I.; Nielsen, C.; Stisen, S.

2009-05-01

The method is illustrated using a combination of MODIS NDVI data with a spatial resolution of 250m and 3 Km Meteosat Second Generation SEVIRI LST data. Geostationary Earth Observation data carry a large potential for assessment of surface state variables. Not the least the European Meteosat Second Generation platform with its SEVIRI sensor is well suited for studies of the dynamics of land surfaces due to its high temporal frequency (15 minutes) and its red, Near Infrared (NIR) channels that provides vegetation indices, and its two split window channels in the thermal infrared for assessment of Land Surface Temperature (LST). For some applications the spatial resolution in geostationary data is too coarse. Due to the low statial resolution of 4.8 km at nadir for the SEVIRI sensor, a means of providing sub pixel information is sought for. By combining and properly scaling two types of satellite images, namely data from the MODIS sensor onboard the polar orbiting platforms TERRA and AQUA and the coarse resolution MSG-SEVIRI, we exploit the best from two worlds. The vegetation index/surface temperature space has been used in a vast number of studies for assessment of air temperature, soil moisture, dryness indices, evapotranspiration and for studies of land use change. In this paper, we present an improved method to derive a finer resolution Land Surface Temperature (LST). A new, deterministic scaling method has been applied, and is compared to existing deterministic downscaling methods based on LST and NDVI. We also compare our results from in situ measurements of LST from the Dahra test site in West Africa.

Validation of non-stationary precipitation series for site-specific impact assessment: comparison of two statistical downscaling techniques

NASA Astrophysics Data System (ADS)

Mullan, Donal; Chen, Jie; Zhang, Xunchang John

2016-02-01

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

Spatial structure and nest demography reveal the influence of competition, parasitism and habitat quality on slavemaking ants and their hosts

PubMed Central

2011-01-01

Background Natural communities are structured by intra-guild competition, predation or parasitism and the abiotic environment. We studied the relative importance of these factors in two host-social parasite ecosystems in three ant communities in Europe (Bavaria) and North America (New York, West Virginia). We tested how these factors affect colony demography, life-history and the spatial pattern of colonies, using a large sample size of more than 1000 colonies. The strength of competition was measured by the distance to the nearest competitor. Distance to the closest social parasite colony was used as a measure of parasitism risk. Nest sites (i.e., sticks or acorns) are limited in these forest ecosystems and we therefore included nest site quality as an abiotic factor in the analysis. In contrast to previous studies based on local densities, we focus here on the positioning and spatial patterns and we use models to compare our predictions to random expectations. Results Colony demography was universally affected by the size of the nest site with larger and more productive colonies residing in larger nest sites of higher quality. Distance to the nearest competitor negatively influenced host demography and brood production in the Bavarian community, pointing to an important role of competition, while social parasitism was less influential in this community. The New York community was characterized by the highest habitat variability, and productive colonies were clustered in sites of higher quality. Colonies were clumped on finer spatial scales, when we considered only the nearest neighbors, but more regularly distributed on coarser scales. The analysis of spatial positioning within plots often produced different results compared to those based on colony densities. For example, while host and slavemaker densities are often positively correlated, slavemakers do not nest closer to potential host colonies than expected by random. Conclusions The three communities are differently affected by biotic and abiotic factors. Some of the differences can be attributed to habitat differences and some to differences between the two slavemaking-host ecosystems. The strong effect of competition in the Bavarian community points to the scarcity of resources in this uniform habitat compared to the other more diverse sites. The decrease in colony aggregation with scale indicates fine-scale resource hotspots: colonies are locally aggregated in small groups. Our study demonstrates that species relationships vary across scales and spatial patterns can provide important insights into species interactions. These results could not have been obtained with analyses based on local densities alone. Previous studies focused on social parasitism and its effect on host colonies. The broader approach taken here, considering several possible factors affecting colony demography and not testing each one in isolation, shows that competition and environmental variability can have a similar strong impact on demography and life-history of hosts. We conclude that the effects of parasites or predators should be studied in parallel to other ecological influences. PMID:21443778

Spatial structure and nest demography reveal the influence of competition, parasitism and habitat quality on slavemaking ants and their hosts.

PubMed

Scharf, Inon; Fischer-Blass, Birgit; Foitzik, Susanne

2011-03-28

Natural communities are structured by intra-guild competition, predation or parasitism and the abiotic environment. We studied the relative importance of these factors in two host-social parasite ecosystems in three ant communities in Europe (Bavaria) and North America (New York, West Virginia). We tested how these factors affect colony demography, life-history and the spatial pattern of colonies, using a large sample size of more than 1000 colonies. The strength of competition was measured by the distance to the nearest competitor. Distance to the closest social parasite colony was used as a measure of parasitism risk. Nest sites (i.e., sticks or acorns) are limited in these forest ecosystems and we therefore included nest site quality as an abiotic factor in the analysis. In contrast to previous studies based on local densities, we focus here on the positioning and spatial patterns and we use models to compare our predictions to random expectations. Colony demography was universally affected by the size of the nest site with larger and more productive colonies residing in larger nest sites of higher quality. Distance to the nearest competitor negatively influenced host demography and brood production in the Bavarian community, pointing to an important role of competition, while social parasitism was less influential in this community. The New York community was characterized by the highest habitat variability, and productive colonies were clustered in sites of higher quality. Colonies were clumped on finer spatial scales, when we considered only the nearest neighbors, but more regularly distributed on coarser scales. The analysis of spatial positioning within plots often produced different results compared to those based on colony densities. For example, while host and slavemaker densities are often positively correlated, slavemakers do not nest closer to potential host colonies than expected by random. The three communities are differently affected by biotic and abiotic factors. Some of the differences can be attributed to habitat differences and some to differences between the two slavemaking-host ecosystems. The strong effect of competition in the Bavarian community points to the scarcity of resources in this uniform habitat compared to the other more diverse sites. The decrease in colony aggregation with scale indicates fine-scale resource hotspots: colonies are locally aggregated in small groups. Our study demonstrates that species relationships vary across scales and spatial patterns can provide important insights into species interactions. These results could not have been obtained with analyses based on local densities alone. Previous studies focused on social parasitism and its effect on host colonies. The broader approach taken here, considering several possible factors affecting colony demography and not testing each one in isolation, shows that competition and environmental variability can have a similar strong impact on demography and life-history of hosts. We conclude that the effects of parasites or predators should be studied in parallel to other ecological influences.

Nested high-resolution large-eddy simulations in WRF to support wind power

NASA Astrophysics Data System (ADS)

Mirocha, J.; Kirkil, G.; Kosovic, B.; Lundquist, J. K.

2009-12-01

The WRF model’s grid nesting capability provides a potentially powerful framework for simulating flow over a wide range of scales. One such application is computation of realistic inflow boundary conditions for large eddy simulations (LES) by nesting LES domains within mesoscale domains. While nesting has been widely and successfully applied at GCM to mesoscale resolutions, the WRF model’s nesting behavior at the high-resolution (Δx < 1000m) end of the spectrum is less well understood. Nesting LES within msoscale domains can significantly improve turbulent flow prediction at the scale of a wind park, providing a basis for superior site characterization, or for improved simulation of turbulent inflows encountered by turbines. We investigate WRF’s grid nesting capability at high mesh resolutions using nested mesoscale and large-eddy simulations. We examine the spatial scales required for flow structures to equilibrate to the finer mesh as flow enters a nest, and how the process depends on several parameters, including grid resolution, turbulence subfilter stress models, relaxation zones at nest interfaces, flow velocities, surface roughnesses, terrain complexity and atmospheric stability. Guidance on appropriate domain sizes and turbulence models for LES in light of these results is provided This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 LLNL-ABS-416482

Wastewater Treatment Energy Recovery Potential For Adaptation To Global Change: An Integrated Assessment

NASA Astrophysics Data System (ADS)

Breach, Patrick A.; Simonovic, Slobodan P.

2018-04-01

Approximately 20% of wastewaters globally do not receive treatment, whereas wastewater discharges are projected to increase, thereby leading to excessive water quality degradation of surface waters on a global scale. Increased treatment could help alleviate water quality issues by constructing more treatment plants; however, in many areas there exist economic constraints. Energy recovery methods including the utilization of biogas and incineration of biosolids generated during the treatment process may help to alleviate treatment costs. This study explores the potential for investments in energy recovery from wastewater to increase treatment levels and thus improve surface water quality. This was done by examining the relationships between nutrient over-enrichment, wastewater treatment, and energy recovery at a global scale using system dynamics simulation as part of the ANEMI integrated assessment model. The results show that a significant amount of energy can be recovered from wastewater, which helps to alleviate some of the costs of treatment. It was found that wastewater treatment levels could be increased by 34%, helping to offset the higher nutrient loading from a growing population with access to improved sanitation. The production of renewable natural gas from biogas was found to have the potential to prolong the depletion of natural gas resources used to produce electricity and heat. It is recommended that agricultural nutrient discharges be better managed to help reduce nutrient over-enrichment on global scale. To increase the utility of the simulation, a finer spatial scale should be used to consider regional treatment, economic, and water quality characteristics.

Wastewater Treatment Energy Recovery Potential For Adaptation To Global Change: An Integrated Assessment.

PubMed

Breach, Patrick A; Simonovic, Slobodan P

2018-04-01

Approximately 20% of wastewaters globally do not receive treatment, whereas wastewater discharges are projected to increase, thereby leading to excessive water quality degradation of surface waters on a global scale. Increased treatment could help alleviate water quality issues by constructing more treatment plants; however, in many areas there exist economic constraints. Energy recovery methods including the utilization of biogas and incineration of biosolids generated during the treatment process may help to alleviate treatment costs. This study explores the potential for investments in energy recovery from wastewater to increase treatment levels and thus improve surface water quality. This was done by examining the relationships between nutrient over-enrichment, wastewater treatment, and energy recovery at a global scale using system dynamics simulation as part of the ANEMI integrated assessment model. The results show that a significant amount of energy can be recovered from wastewater, which helps to alleviate some of the costs of treatment. It was found that wastewater treatment levels could be increased by 34%, helping to offset the higher nutrient loading from a growing population with access to improved sanitation. The production of renewable natural gas from biogas was found to have the potential to prolong the depletion of natural gas resources used to produce electricity and heat. It is recommended that agricultural nutrient discharges be better managed to help reduce nutrient over-enrichment on global scale. To increase the utility of the simulation, a finer spatial scale should be used to consider regional treatment, economic, and water quality characteristics.

Interannual rainfall variability over China in the MetUM GA6 and GC2 configurations

NASA Astrophysics Data System (ADS)

Stephan, Claudia Christine; Klingaman, Nicholas P.; Vidale, Pier Luigi; Turner, Andrew G.; Demory, Marie-Estelle; Guo, Liang

2018-05-01

Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyse the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ˜ 200, 90 and 40 km in the zonal direction at the equator, respectively) are analysed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China but improve with finer resolution and coupling. Empirical orthogonal teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal mean time series. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Crosson, W. L.; Al-Hamdan, M. Z.; Estes, M. G., Jr.

2013-12-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981-2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a ';heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Linking Excessive Heat with Daily Heat-Related Mortality over the Coterminous United States

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Crosson, William L.; Al-Hamdan, Mohammad Z.; Estes, Maurice G., Jr.

2014-01-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

In need of combined topography and bathymetry DEM

NASA Astrophysics Data System (ADS)

Kisimoto, K.; Hilde, T.

2003-04-01

In many geoscience applications, digital elevation models (DEMs) are now more commonly used at different scales and greater resolution due to the great advancement in computer technology. Increasing the accuracy/resolution of the model and the coverage of the terrain (global model) has been the goal of users as mapping technology has improved and computers get faster and cheaper. The ETOPO5 (5 arc minutes spatial resolution land and seafloor model), initially developed in 1988 by Margo Edwards, then at Washington University, St. Louis, MO, has been the only global terrain model for a long time, and it is now being replaced by three new topographic and bathymetric DEMs, i.e.; the ETOPO2 (2 arc minutes spatial resolution land and seafloor model), the GTOPO30 land model with a spatial resolution of 30 arc seconds (c.a. 1km at equator) and the 'GEBCO 1-MINUTE GLOBAL BATHYMETRIC GRID' ocean floor model with a spatial resolution of 1 arc minute (c.a. 2 km at equator). These DEMs are products of projects through which compilation and reprocessing of existing and/or new datasets were made to meet user's new requirements. These ongoing efforts are valuable and support should be continued to refine and update these DEMs. On the other hand, a different approach to create a global bathymetric (seafloor) database exists. A method to estimate the seafloor topography from satellite altimetry combined with existing ships' conventional sounding data was devised and a beautiful global seafloor database created and made public by W.H. Smith and D.T. Sandwell in 1997. The big advantage of this database is the uniformity of coverage, i.e. there is no large area where depths are missing. It has a spatial resolution of 2 arc minute. Another important effort is found in making regional, not global, seafloor databases with much finer resolutions in many countries. The Japan Hydrographic Department has compiled and released a 500m-grid topography database around Japan, J-EGG500, in 1999. Although the coverage of this database is only a small portion of the Earth, the database has been highly appreciated in the academic community, and accepted in surprise by the general public when the database was displayed in 3D imagery to show its quality. This database could be rather smoothly combined with the finer land DEM of 250m spatial resolution (Japan250m.grd, K. Kisimoto, 2000). One of the most important applications of this combined DEM of topography and bathymetry is tsunami modeling. Understanding of the coastal environment, management and development of the coastal region are other fields in need of these data. There is, however, an important issue to consider when we create a combined DEM of topography and bathymetry in finer resolutions. The problem arises from the discrepancy of the standard datum planes or reference levels used for topographic leveling and bathymetric sounding. Land topography (altitude) is defined by leveling from the single reference point determined by average mean sea level, in other words, land height is measured from the geoid. On the other hand, depth charts are made based on depth measured from locally determined reference sea surface level, and this value of sea surface level is taken from the long term average of the lowest tidal height. So, to create a combined DEM of topography and bathymetry in very fine scale, we need to avoid this inconsistency between height and depth across the coastal region. Height and depth should be physically continuous relative to a single reference datum across the coast within such new high resolution DEMs. (N.B. Coast line is not equal to 'altitude-zero line' nor 'depth-zero line'. It is defined locally as the long term average of the highest tide level.) All of this said, we still need a lot of work on the ocean side. Global coverage with detailed bathymetric mapping is still poor. Seafloor imaging and other geophysical measurements/experiments should be organized and conducted internationally and interdisciplinary ways more than ever. We always need greater technological advancement and application of this technology in marine sciences, and more enthusiastic minds of seagoing researchers as well. Recent seafloor mapping technology/quality both in bathymetry and imagery is very promising and even favorably compared with the terrain mapping. We discuss and present on recent achievement and needs on the seafloor mapping using several most up-to-date global- and regional- DEMs available for science community at the poster session.

Reactivity of Aluminum-Based Mixtures with Early Transition Metals

DTIC Science & Technology

2014-08-01

particles are no longer equiaxed but lenticular and lammelar. Dimensions of the heavily deformed Ti particles are considerably finer (30 µm in length by...same. The Hf particles look coarse under light milling and attain a more lenticular appearance with heavy milling. There is large-scale mixing in this

Compact microwave imaging system to measure spatial distribution of plasma density

NASA Astrophysics Data System (ADS)

Ito, H.; Oba, R.; Yugami, N.; Nishida, Y.

2004-10-01

We have developed an advanced microwave interferometric system operating in the K band (18-27 GHz) with the use of a fan-shaped microwave based on a heterodyne detection system for measuring the spatial distribution of the plasma density. In order to make a simple, low-cost, and compact microwave interferometer with better spatial resolution, a microwave scattering technique by a microstrip antenna array is employed. Experimental results show that the imaging system with the microstrip antenna array can have finer spatial resolution than one with the diode antenna array and reconstruct a good spatially resolved image of the finite size dielectric phantoms placed between the horn antenna and the micro strip antenna array. The precise two-dimensional electron density distribution of the cylindrical plasma produced by an electron cyclotron resonance has been observed. As a result, the present imaging system is more suitable for a two- or three-dimensional display of the objects or stationary plasmas and it is possible to realize a compact microwave imaging system.

An Object-Based Approach to Evaluation of Climate Variability Projections and Predictions

NASA Astrophysics Data System (ADS)

Ammann, C. M.; Brown, B.; Kalb, C. P.; Bullock, R.

2017-12-01

Evaluations of the performance of earth system model predictions and projections are of critical importance to enhance usefulness of these products. Such evaluations need to address specific concerns depending on the system and decisions of interest; hence, evaluation tools must be tailored to inform about specific issues. Traditional approaches that summarize grid-based comparisons of analyses and models, or between current and future climate, often do not reveal important information about the models' performance (e.g., spatial or temporal displacements; the reason behind a poor score) and are unable to accommodate these specific information needs. For example, summary statistics such as the correlation coefficient or the mean-squared error provide minimal information to developers, users, and decision makers regarding what is "right" and "wrong" with a model. New spatial and temporal-spatial object-based tools from the field of weather forecast verification (where comparisons typically focus on much finer temporal and spatial scales) have been adapted to more completely answer some of the important earth system model evaluation questions. In particular, the Method for Object-based Diagnostic Evaluation (MODE) tool and its temporal (three-dimensional) extension (MODE-TD) have been adapted for these evaluations. More specifically, these tools can be used to address spatial and temporal displacements in projections of El Nino-related precipitation and/or temperature anomalies, ITCZ-associated precipitation areas, atmospheric rivers, seasonal sea-ice extent, and other features of interest. Examples of several applications of these tools in a climate context will be presented, using output of the CESM large ensemble. In general, these tools provide diagnostic information about model performance - accounting for spatial, temporal, and intensity differences - that cannot be achieved using traditional (scalar) model comparison approaches. Thus, they can provide more meaningful information that can be used in decision-making and planning. Future extensions and applications of these tools in a climate context will be considered.

Evaluation of sliding baseline methods for spatial estimation for cluster detection in the biosurveillance system

PubMed Central

Xing, Jian; Burkom, Howard; Moniz, Linda; Edgerton, James; Leuze, Michael; Tokars, Jerome

2009-01-01

Background The Centers for Disease Control and Prevention's (CDC's) BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of the daily disease monitoring task. Our study focused on finding useful anomalies at manageable alert rates according to available BioSense data history. Methods The study dataset included more than 3 years of daily counts of military outpatient clinic visits for respiratory and rash syndrome groupings. We applied four spatial estimation methods in implementations of space-time scan statistics cross-checked in Matlab and C. We compared the utility of these methods according to the resultant background cluster rate (a false alarm surrogate) and sensitivity to injected cluster signals. The comparison runs used a spatial resolution based on the facility zip code in the patient record and a finer resolution based on the residence zip code. Results Simple estimation methods that account for day-of-week (DOW) data patterns yielded a clear advantage both in background cluster rate and in signal sensitivity. A 28-day baseline gave the most robust results for this estimation; the preferred baseline is long enough to remove daily fluctuations but short enough to reflect recent disease trends and data representation. Background cluster rates were lower for the rash syndrome counts than for the respiratory counts, likely because of seasonality and the large scale of the respiratory counts. Conclusion The spatial estimation method should be chosen according to characteristics of the selected data streams. In this dataset with strong day-of-week effects, the overall best detection performance was achieved using subregion averages over a 28-day baseline stratified by weekday or weekend/holiday behavior. Changing the estimation method for particular scenarios involving different spatial resolution or other syndromes can yield further improvement. PMID:19615075

Large-scale expensive black-box function optimization

NASA Astrophysics Data System (ADS)

Rashid, Kashif; Bailey, William; Couët, Benoît

2012-09-01

This paper presents the application of an adaptive radial basis function method to a computationally expensive black-box reservoir simulation model of many variables. An iterative proxy-based scheme is used to tune the control variables, distributed for finer control over a varying number of intervals covering the total simulation period, to maximize asset NPV. The method shows that large-scale simulation-based function optimization of several hundred variables is practical and effective.

Assessing the competing roles of model resolution and meteorological forcing fidelity in hyperresolution simulations of snowpack and streamflow in the southern Rocky Mountains

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Dugger, A. L.; Karsten, L. R.; Barlage, M. J.; Sampson, K. M.; Yu, W.; Pan, L.; McCreight, J. L.; Howard, K.; Busto, J.; Deems, J. S.

2017-12-01

Hydrometeorological processes vary over comparatively short length scales in regions of complex terrain such as the southern Rocky Mountains. Changes in temperature, precipitation, wind and solar radiation can vary significantly across elevation gradients, terrain landform and land cover conditions throughout the region. Capturing such variability in hydrologic models can necessitate the utilization of so-called `hyper-resolution' spatial meshes with effective element spacings of less than 100m. However, it is often difficult to obtain meteorological forcings of high quality in such regions at those resolutions which can result in significant uncertainty in fundamental in hydrologic model inputs. In this study we examine the comparative influences of meteorological forcing data fidelity and spatial resolution on seasonal simulations of snowpack evolution, runoff and streamflow in a set of high mountain watersheds in southern Colorado. We utilize the operational, NOAA National Water Model configuration of the community WRF-Hydro system as a baseline and compare against it, additional model scenarios with differing specifications of meteorological forcing data, with and without topographic downscaling adjustments applied, with and without experimental high resolution radar derived precipitation estimates and with WRF-Hydro configurations of progressively finer spatial resolution. The results suggest significant influence from and importance of meteorological downscaling techniques in controlling spatial distributions of meltout and runoff timing. The use of radar derived precipitation exhibits clear sensitivity on hydrologic simulation skill compared with the use of coarser resolution, background precipitation analyses. Advantages and disadvantages of the utilization of progressively higher resolution model configurations both in terms of computational requirements and model fidelity are also discussed.

The influence of model spatial resolution on simulated ozone and fine particulate matter for Europe: implications for health impact assessments

NASA Astrophysics Data System (ADS)

Fenech, Sara; Doherty, Ruth M.; Heaviside, Clare; Vardoulakis, Sotiris; Macintyre, Helen L.; O'Connor, Fiona M.

2018-04-01

We examine the impact of model horizontal resolution on simulated concentrations of surface ozone (O3) and particulate matter less than 2.5 µm in diameter (PM2.5), and the associated health impacts over Europe, using the HadGEM3-UKCA chemistry-climate model to simulate pollutant concentrations at a coarse (˜ 140 km) and a finer (˜ 50 km) resolution. The attributable fraction (AF) of total mortality due to long-term exposure to warm season daily maximum 8 h running mean (MDA8) O3 and annual-average PM2.5 concentrations is then calculated for each European country using pollutant concentrations simulated at each resolution. Our results highlight a seasonal variation in simulated O3 and PM2.5 differences between the two model resolutions in Europe. Compared to the finer resolution results, simulated European O3 concentrations at the coarse resolution are higher on average in winter and spring (˜ 10 and ˜ 6 %, respectively). In contrast, simulated O3 concentrations at the coarse resolution are lower in summer and autumn (˜ -1 and ˜ -4 %, respectively). These differences may be partly explained by differences in nitrogen dioxide (NO2) concentrations simulated at the two resolutions. Compared to O3, we find the opposite seasonality in simulated PM2.5 differences between the two resolutions. In winter and spring, simulated PM2.5 concentrations are lower at the coarse compared to the finer resolution (˜ -8 and ˜ -6 %, respectively) but higher in summer and autumn (˜ 29 and ˜ 8 %, respectively). Simulated PM2.5 values are also mostly related to differences in convective rainfall between the two resolutions for all seasons. These differences between the two resolutions exhibit clear spatial patterns for both pollutants that vary by season, and exert a strong influence on country to country variations in estimated AF for the two resolutions. Warm season MDA8 O3 levels are higher in most of southern Europe, but lower in areas of northern and eastern Europe when simulated at the coarse resolution compared to the finer resolution. Annual-average PM2.5 concentrations are higher across most of northern and eastern Europe but lower over parts of southwest Europe at the coarse compared to the finer resolution. Across Europe, differences in the AF associated with long-term exposure to population-weighted MDA8 O3 range between -0.9 and +2.6 % (largest positive differences in southern Europe), while differences in the AF associated with long-term exposure to population-weighted annual mean PM2.5 range from -4.7 to +2.8 % (largest positive differences in eastern Europe) of the total mortality. Therefore this study, with its unique focus on Europe, demonstrates that health impact assessments calculated using modelled pollutant concentrations, are sensitive to a change in model resolution by up to ˜ ±5 % of the total mortality across Europe.

LLNL Scientists Use NERSC to Advance Global Aerosol Simulations

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

Bergmann, D J; Chuang, C; Rotman, D

2004-10-13

While ''greenhouse gases'' have been the focus of climate change research for a number of years, DOE's ''Aerosol Initiative'' is now examining how aerosols (small particles of approximately micron size) affect the climate on both a global and regional scale. Scientists in the Atmospheric Science Division at Lawrence Livermore National Laboratory (LLNL) are using NERSC's IBM supercomputer and LLNL's IMPACT (atmospheric chemistry) model to perform simulations showing the historic effects of sulfur aerosols at a finer spatial resolution than ever done before. Simulations were carried out for five decades, from the 1950s through the 1990s. The results clearly show themore » effects of the changing global pattern of sulfur emissions. Whereas in 1950 the United States emitted 41 percent of the world's sulfur aerosols, this figure had dropped to 15 percent by 1990, due to conservation and anti-pollution policies. By contrast, the fraction of total sulfur emissions of European origin has only dropped by a factor of 2 and the Asian emission fraction jumped six fold during the same time, from 7 percent in 1950 to 44 percent in 1990. Under a special allocation of computing time provided by the Office of Science INCITE (Innovative and Novel Computational Impact on Theory and Experiment) program, Dan Bergmann, working with a team of LLNL scientists including Cathy Chuang, Philip Cameron-Smith, and Bala Govindasamy, was able to carry out a large number of calculations during the past month, making the aerosol project one of the largest users of NERSC resources. The applications ran on 128 and 256 processors. The objective was to assess the effects of anthropogenic (man-made) sulfate aerosols. The IMPACT model calculates the rate at which SO{sub 2} (a gas emitted by industrial activity) is oxidized and forms particles known as sulfate aerosols. These particles have a short lifespan in the atmosphere, often washing out in about a week. This means that their effects on climate tend to be more regional, occurring near the area where the SO{sub 2} is emitted. To accurately study these regional effects, Bergmann needed to run the simulations at a finer horizontal resolution, as the coarser resolution (typically 300km by 300km) of other climate models are insufficient for studying changes on a regional scale. Livermore's use of CAM3, the Community Atmospheric Model which is a high-resolution climate model developed at NCAR (with collaboration from DOE), allows a 100km by 100km grid to be applied. NERSC's terascale computing capability provided the needed computational horsepower to run the application at the finer level.« less

Contemporary Remotely Sensed Data Products Refine Invasive Plants Risk Mapping in Data Poor Regions.

PubMed

Truong, Tuyet T A; Hardy, Giles E St J; Andrew, Margaret E

2017-01-01

Invasive weeds are a serious problem worldwide, threatening biodiversity and damaging economies. Modeling potential distributions of invasive weeds can prioritize locations for monitoring and control efforts, increasing management efficiency. Forecasts of invasion risk at regional to continental scales are enabled by readily available downscaled climate surfaces together with an increasing number of digitized and georeferenced species occurrence records and species distribution modeling techniques. However, predictions at a finer scale and in landscapes with less topographic variation may require predictors that capture biotic processes and local abiotic conditions. Contemporary remote sensing (RS) data can enhance predictions by providing a range of spatial environmental data products at fine scale beyond climatic variables only. In this study, we used the Global Biodiversity Information Facility (GBIF) and empirical maximum entropy (MaxEnt) models to model the potential distributions of 14 invasive plant species across Southeast Asia (SEA), selected from regional and Vietnam's lists of priority weeds. Spatial environmental variables used to map invasion risk included bioclimatic layers and recent representations of global land cover, vegetation productivity (GPP), and soil properties developed from Earth observation data. Results showed that combining climate and RS data reduced predicted areas of suitable habitat compared with models using climate or RS data only, with no loss in model accuracy. However, contributions of RS variables were relatively limited, in part due to uncertainties in the land cover data. We strongly encourage greater adoption of quantitative remotely sensed estimates of ecosystem structure and function for habitat suitability modeling. Through comprehensive maps of overall predicted area and diversity of invasive species, we found that among lifeforms (herb, shrub, and vine), shrub species have higher potential invasion risk in SEA. Native invasive species, which are often overlooked in weed risk assessment, may be as serious a problem as non-native invasive species. Awareness of invasive weeds and their environmental impacts is still nascent in SEA and information is scarce. Freely available global spatial datasets, not least those provided by Earth observation programs, and the results of studies such as this one provide critical information that enables strategic management of environmental threats such as invasive species.

Contemporary Remotely Sensed Data Products Refine Invasive Plants Risk Mapping in Data Poor Regions

PubMed Central

Truong, Tuyet T. A.; Hardy, Giles E. St. J.; Andrew, Margaret E.

2017-01-01

Invasive weeds are a serious problem worldwide, threatening biodiversity and damaging economies. Modeling potential distributions of invasive weeds can prioritize locations for monitoring and control efforts, increasing management efficiency. Forecasts of invasion risk at regional to continental scales are enabled by readily available downscaled climate surfaces together with an increasing number of digitized and georeferenced species occurrence records and species distribution modeling techniques. However, predictions at a finer scale and in landscapes with less topographic variation may require predictors that capture biotic processes and local abiotic conditions. Contemporary remote sensing (RS) data can enhance predictions by providing a range of spatial environmental data products at fine scale beyond climatic variables only. In this study, we used the Global Biodiversity Information Facility (GBIF) and empirical maximum entropy (MaxEnt) models to model the potential distributions of 14 invasive plant species across Southeast Asia (SEA), selected from regional and Vietnam’s lists of priority weeds. Spatial environmental variables used to map invasion risk included bioclimatic layers and recent representations of global land cover, vegetation productivity (GPP), and soil properties developed from Earth observation data. Results showed that combining climate and RS data reduced predicted areas of suitable habitat compared with models using climate or RS data only, with no loss in model accuracy. However, contributions of RS variables were relatively limited, in part due to uncertainties in the land cover data. We strongly encourage greater adoption of quantitative remotely sensed estimates of ecosystem structure and function for habitat suitability modeling. Through comprehensive maps of overall predicted area and diversity of invasive species, we found that among lifeforms (herb, shrub, and vine), shrub species have higher potential invasion risk in SEA. Native invasive species, which are often overlooked in weed risk assessment, may be as serious a problem as non-native invasive species. Awareness of invasive weeds and their environmental impacts is still nascent in SEA and information is scarce. Freely available global spatial datasets, not least those provided by Earth observation programs, and the results of studies such as this one provide critical information that enables strategic management of environmental threats such as invasive species. PMID:28555147

Monitoring Crop Phenology and Growth Stages from Space: Opportunities and Challenges

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.; Mladenova, I. E.; Kustas, W. P.; Alfieri, J. G.

2014-12-01

Crop growth stages in concert with weather and soil moisture conditions can have a significant impact on crop yields. In the U.S., crop growth stages and conditions are reported by farmers at the county level. These reports are somewhat subjective and fluctuate between different reporters, locations and times. Remote sensing data provide an alternative approach to monitoring crop growth over large areas in a more consistent and quantitative way. In the recent years, remote sensing data have been used to detect vegetation phenology at 1-km spatial resolution globally. However, agricultural applications at field scale require finer spatial resolution remote sensing data. Landsat (30-m) data have been successfully used for agricultural applications. There are many medium resolution sensors available today or in near future. These include Landsat, SPOT, RapidEye, ASTER and future Sentinel-2 etc. Approaches have been developed in the past several years to integrate remote sensing data from different sensors which may have different sensor characteristics, and spatial and temporal resolutions. This allows us opportunities today to map crop growth stages and conditions using dense time-series remote sensing at field scales. However, remotely sensed phenology (or phenological metrics) is normally derived based on the mathematical functions of the time-series data. The phenological metrics are determined by either identifying inflection (curvature) points or some pre-defined thresholds in the remote sensing phenology algorithms. Furthermore, physiological crop growth stages may not be directly correlated to the remotely sensed phenology. The relationship between remotely sensed phenology and crop growth stages is likely to vary for specific crop types and varieties, growing stages, conditions and even locations. In this presentation, we will examine the relationship between remotely sensed phenology and crop growth stages using in-situ measurements from Fluxnet sites and crop progress reports from USDA NASS. We will present remote sensing approaches and focus on: 1) integrating multiple sources of remote sensing data; and 2) extracting crop phenology at field scales. An example in the U.S. Corn Belt area will be presented and analyzed. Future directions for mapping crop growth stages will be discussed.

A theoretically consistent stochastic cascade for temporal disaggregation of intermittent rainfall

NASA Astrophysics Data System (ADS)

Lombardo, F.; Volpi, E.; Koutsoyiannis, D.; Serinaldi, F.

2017-06-01

Generating fine-scale time series of intermittent rainfall that are fully consistent with any given coarse-scale totals is a key and open issue in many hydrological problems. We propose a stationary disaggregation method that simulates rainfall time series with given dependence structure, wet/dry probability, and marginal distribution at a target finer (lower-level) time scale, preserving full consistency with variables at a parent coarser (higher-level) time scale. We account for the intermittent character of rainfall at fine time scales by merging a discrete stochastic representation of intermittency and a continuous one of rainfall depths. This approach yields a unique and parsimonious mathematical framework providing general analytical formulations of mean, variance, and autocorrelation function (ACF) for a mixed-type stochastic process in terms of mean, variance, and ACFs of both continuous and discrete components, respectively. To achieve the full consistency between variables at finer and coarser time scales in terms of marginal distribution and coarse-scale totals, the generated lower-level series are adjusted according to a procedure that does not affect the stochastic structure implied by the original model. To assess model performance, we study rainfall process as intermittent with both independent and dependent occurrences, where dependence is quantified by the probability that two consecutive time intervals are dry. In either case, we provide analytical formulations of main statistics of our mixed-type disaggregation model and show their clear accordance with Monte Carlo simulations. An application to rainfall time series from real world is shown as a proof of concept.

A new map of standardized terrestrial ecosystems of Africa

USGS Publications Warehouse

Sayre, Roger G.; Comer, Patrick; Hak, Jon; Josse, Carmen; Bow, Jacquie; Warner, Harumi; Larwanou, Mahamane; Kelbessa, Ensermu; Bekele, Tamrat; Kehl, Harald; Amena, Ruba; Andriamasimanana, Rado; Ba, Taibou; Benson, Laurence; Boucher, Timothy; Brown, Matthew; Cress, Jill J.; Dassering, Oueddo; Friesen, Beverly A.; Gachathi, Francis; Houcine, Sebei; Keita, Mahamadou; Khamala, Erick; Marangu, Dan; Mokua, Fredrick; Morou, Boube; Mucina, Ladislav; Mugisha, Samuel; Mwavu, Edward; Rutherford, Michael; Sanou, Patrice; Syampungani, Stephen; Tomor, Bojoi; Vall, Abdallahi Ould Mohamed; Vande Weghe, Jean Pierre; Wangui, Eunice; Waruingi, Lucy

2013-01-01

Terrestrial ecosystems and vegetation of Africa were classified and mapped as part of a larger effort and global protocol (GEOSS – the Global Earth Observation System of Systems), which includes an activity to map terrestrial ecosystems of the earth in a standardized, robust, and practical manner, and at the finest possible spatial resolution. To model the potential distribution of ecosystems, new continental datasets for several key physical environment datalayers (including coastline, landforms, surficial lithology, and bioclimates) were developed at spatial and classification resolutions finer than existing similar datalayers. A hierarchical vegetation classification was developed by African ecosystem scientists and vegetation geographers, who also provided sample locations of the newly classified vegetation units. The vegetation types and ecosystems were then mapped across the continent using a classification and regression tree (CART) inductive model, which predicted the potential distribution of vegetation types from a suite of biophysical environmental attributes including bioclimate region, biogeographic region, surficial lithology, landform, elevation and land cover. Multi-scale ecosystems were classified and mapped in an increasingly detailed hierarchical framework using vegetation-based concepts of class, subclass, formation, division, and macrogroup levels. The finest vegetation units (macrogroups) classified and mapped in this effort are defined using diagnostic plant species and diagnostic growth forms that reflect biogeographic differences in composition and sub-continental to regional differences in mesoclimate, geology, substrates, hydrology, and disturbance regimes (FGDC, 2008). The macrogroups are regarded as meso-scale (100s to 10,000s of hectares) ecosystems. A total of 126 macrogroup types were mapped, each with multiple, repeating occurrences on the landscape. The modeling effort was implemented at a base spatial resolution of 90 m. In addition to creating several rich, new continent-wide biophysical datalayers describing African vegetation and ecosystems, our intention was to explore feasible approaches to rapidly moving this type of standardized, continent-wide, ecosystem classification and mapping effort forward.

Estimation of wetland evapotranspiration in northern New York using infrared thermometry

NASA Astrophysics Data System (ADS)

Hwang, K.; Chandler, D. G.

2016-12-01

Evapotranspiration (ET) is an important component of the water budget and often regarded as a major water loss. In freshwater wetlands, cumulative annual ET can equal precipitation under well-watered conditions. Wetland ET is therefore an important control on contaminant and nutrient transport. Yet, quantification of wetland ET is challenged by complex surface characteristics, diverse plant species and density, and variations in wetland shape and size. As handheld infrared (IR) cameras have become available, studies exploiting the new technology have increased, especially in agriculture and hydrology. The benefits of IR cameras include (1) high spatial resolution, (2) high sample rates, (3) real-time imaging, (4) a constant viewing geometry, and (5) no need for atmosphere and cloud corrections. Compared with traditional methods, infrared thermometer is capable of monitoring at the scale of a small pond or localized plant community. This enables finer scale survey of heterogeneous land surfaces rather than strict dependence on atmospheric variables. Despite this potential, there has been a limited number of studies of ET and drought stress with IR cameras. In this study, the infrared thermometry-based method was applied to estimate ET over wetland plant species in St. Lawrence River Valley, NY. The results are evaluated with traditional methods to test applicability over multiple vegetation species in a same area.

Reconstruction of color images via Haar wavelet based on digital micromirror device

NASA Astrophysics Data System (ADS)

Liu, Xingjiong; He, Weiji; Gu, Guohua

2015-10-01

A digital micro mirror device( DMD) is introduced to form Haar wavelet basis , projecting on the color target image by making use of structured illumination, including red, green and blue light. The light intensity signals reflected from the target image are received synchronously by the bucket detector which has no spatial resolution, converted into voltage signals and then transferred into PC[1] .To reach the aim of synchronization, several synchronization processes are added during data acquisition. In the data collection process, according to the wavelet tree structure, the locations of significant coefficients at the finer scale are predicted by comparing the coefficients sampled at the coarsest scale with the threshold. The monochrome grayscale images are obtained under red , green and blue structured illumination by using Haar wavelet inverse transform algorithm, respectively. The color fusion algorithm is carried on the three monochrome grayscale images to obtain the final color image. According to the imaging principle, the experimental demonstration device is assembled. The letter "K" and the X-rite Color Checker Passport are projected and reconstructed as target images, and the final reconstructed color images have good qualities. This article makes use of the method of Haar wavelet reconstruction, reducing the sampling rate considerably. It provides color information without compromising the resolution of the final image.

Climate impacts on global hot spots of marine biodiversity.

PubMed

Ramírez, Francisco; Afán, Isabel; Davis, Lloyd S; Chiaradia, André

2017-02-01

Human activities drive environmental changes at scales that could potentially cause ecosystem collapses in the marine environment. We combined information on marine biodiversity with spatial assessments of the impacts of climate change to identify the key areas to prioritize for the conservation of global marine biodiversity. This process identified six marine regions of exceptional biodiversity based on global distributions of 1729 species of fish, 124 marine mammals, and 330 seabirds. Overall, these hot spots of marine biodiversity coincide with areas most severely affected by global warming. In particular, these marine biodiversity hot spots have undergone local to regional increasing water temperatures, slowing current circulation, and decreasing primary productivity. Furthermore, when we overlapped these hot spots with available industrial fishery data, albeit coarser than our estimates of climate impacts, they suggest a worrying coincidence whereby the world's richest areas for marine biodiversity are also those areas mostly affected by both climate change and industrial fishing. In light of these findings, we offer an adaptable framework for determining local to regional areas of special concern for the conservation of marine biodiversity. This has exposed the need for finer-scaled fishery data to assist in the management of global fisheries if the accumulative, but potentially preventable, effect of fishing on climate change impacts is to be minimized within areas prioritized for marine biodiversity conservation.

Complex mountain terrain and disturbance history drive variation in forest aboveground live carbon density in the western Oregon Cascades, USA

PubMed Central

Zald, Harold S.J.; Spies, Thomas A.; Seidl, Rupert; Pabst, Robert J.; Olsen, Keith A.; Steel, E. Ashley

2016-01-01

Forest carbon (C) density varies tremendously across space due to the inherent heterogeneity of forest ecosystems. Variation of forest C density is especially pronounced in mountainous terrain, where environmental gradients are compressed and vary at multiple spatial scales. Additionally, the influence of environmental gradients may vary with forest age and developmental stage, an important consideration as forest landscapes often have a diversity of stand ages from past management and other disturbance agents. Quantifying forest C density and its underlying environmental determinants in mountain terrain has remained challenging because many available data sources lack the spatial grain and ecological resolution needed at both stand and landscape scales. The objective of this study was to determine if environmental factors influencing aboveground live carbon (ALC) density differed between young versus old forests. We integrated aerial light detection and ranging (lidar) data with 702 field plots to map forest ALC density at a grain of 25 m across the H.J. Andrews Experimental Forest, a 6369 ha watershed in the Cascade Mountains of Oregon, USA. We used linear regressions, random forest ensemble learning (RF) and sequential autoregressive modeling (SAR) to reveal how mapped forest ALC density was related to climate, topography, soils, and past disturbance history (timber harvesting and wildfires). ALC increased with stand age in young managed forests, with much greater variation of ALC in relation to years since wildfire in old unmanaged forests. Timber harvesting was the most important driver of ALC across the entire watershed, despite occurring on only 23% of the landscape. More variation in forest ALC density was explained in models of young managed forests than in models of old unmanaged forests. Besides stand age, ALC density in young managed forests was driven by factors influencing site productivity, whereas variation in ALC density in old unmanaged forests was also affected by finer scale topographic conditions associated with sheltered sites. Past wildfires only had a small influence on current ALC density, which may be a result of long times since fire and/or prevalence of non-stand replacing fire. Our results indicate that forest ALC density depends on a suite of multi-scale environmental drivers mediated by complex mountain topography, and that these relationships are dependent on stand age. The high and context-dependent spatial variability of forest ALC density has implications for quantifying forest carbon stores, establishing upper bounds of potential carbon sequestration, and scaling field data to landscape and regional scales. PMID:27041818

An individual-based model of skipjack tuna (Katsuwonus pelamis) movement in the tropical Pacific ocean

NASA Astrophysics Data System (ADS)

Scutt Phillips, Joe; Sen Gupta, Alex; Senina, Inna; van Sebille, Erik; Lange, Michael; Lehodey, Patrick; Hampton, John; Nicol, Simon

2018-05-01

The distribution of marine species is often modeled using Eulerian approaches, in which changes to population density or abundance are calculated at fixed locations in space. Conversely, Lagrangian, or individual-based, models simulate the movement of individual particles moving in continuous space, with broader-scale patterns such as distribution being an emergent property of many, potentially adaptive, individuals. These models offer advantages in examining dynamics across spatiotemporal scales and making comparisons with observations from individual-scale data. Here, we introduce and describe such a model, the Individual-based Kinesis, Advection and Movement of Ocean ANimAls model (Ikamoana), which we use to replicate the movement processes of an existing Eulerian model for marine predators (the Spatial Ecosystem and Population Dynamics Model, SEAPODYM). Ikamoana simulates the movement of either individual or groups of animals by physical ocean currents, habitat-dependent stochastic movements (kinesis), and taxis movements representing active searching behaviours. Applying our model to Pacific skipjack tuna (Katsuwonus pelamis), we show that it accurately replicates the evolution of density distribution simulated by SEAPODYM with low time-mean error and a spatial correlation of density that exceeds 0.96 at all times. We demonstrate how the Lagrangian approach permits easy tracking of individuals' trajectories for examining connectivity between different regions, and show how the model can provide independent estimates of transfer rates between commonly used assessment regions. In particular, we find that retention rates in most assessment regions are considerably smaller (up to a factor of 2) than those estimated by this population of skipjack's primary assessment model. Moreover, these rates are sensitive to ocean state (e.g. El Nino vs La Nina) and so assuming fixed transfer rates between regions may lead to spurious stock estimates. A novel feature of the Lagrangian approach is that individual schools can be tracked through time, and we demonstrate that movement between two assessment regions at broad temporal scales includes extended transits through other regions at finer-scales. Finally, we discuss the utility of this modeling framework for the management of marine reserves, designing effective monitoring programmes, and exploring hypotheses regarding the behaviour of hard-to-observe oceanic animals.

It's the Heat AND the Humidity -- Assessment of Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health

NASA Technical Reports Server (NTRS)

Crosson, William L; Al-Hamdan, Mohammad Z.; Economou, Sigrid, A.; Estes, Maurice G.; Estes, Sue M.; Puckett, Mark; Quattrochi, Dale A

2013-01-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. In a NASA-funded project supporting the National Climate Assessment, we are providing historical and future measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The project s emphasis is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM output, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons, 2040 and 2090, are the focus of future assessments; these are compared to the recent past period of 1981-2000. We are characterizing regional-scale temperature and humidity conditions using GCM output for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM output have been analyzed to develop a heat stress climatology based on statistics of extreme heat indicators. Differences between the two future and past periods have been used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes, combined with hourly historical meteorological data at a spatial scale (12 km) much finer than that of GCMs, enable us to create future climate realizations, from which we compute the daily heat stress measures and related spatially-specific climatological fields. These include the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. All output is being provided at the 12 km spatial scale and will also be aggregated to the county level, which is a popular scale of analysis for public health researchers. County-level statistics will be made available by our collaborators at the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public. This addition of heat stress measures to CDC WONDER will allow decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. It will also allow public health researchers and policy makers to better include such heat stress measures in the context of national health data available in the CDC WONDER system. The users will be able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Genetic Variation of 17 Wild Yellow Perch Populations from the Midwest and East Coast Analyzed Via Microsatellites

USDA-ARS?s Scientific Manuscript database

We used microsatellite loci, including seven newly developed by us, to analyze the population genetic structure of wild yellow perch Perca flavescens from 17 sampling areas in the Upper Midwest and East Coast of the United States. Our results revealed greater genetic differentiation and finer-scale ...

Textual and Discoursal Resources Used in the Essay Genre in Sociology and English

ERIC Educational Resources Information Center

Bruce, Ian

2010-01-01

Research that has examined university assignment writing has varied from large-scale, inventorial surveys across disciplines to more specific, finer-grained analyses of the assignment requirements of specific disciplines. However, while such research has involved surveys of the views and expectations of faculty or the analysis of assignment tasks,…

Evaluating Effectiveness of Green Infrastructure Application of Stormwater Best Management Practices in Protecting Stream Habitat and Biotic Condition in New England

EPA Science Inventory

The US EPA is developing assessment tools to evaluate the effectiveness of green infrastructure (GI) applied in stormwater best management practices (BMPs) at the small watershed (HUC12 or finer) scale. Based on analysis of historical monitoring data using boosted regression tre...

Analysis of Long Wave Infrared (LWIR) Soil Data to Predict Reflectance Response

DTIC Science & Technology

2009-08-01

Aridisol red-orange sandy soil 6% x 16% 61 12% smectite Aridisol grey calcareous silty soil x 19% 49 22% smectite ...trace 16% 59 20% smectite ; grain size analysis of fraction finer than 2 mm indicates 35% finer than 20 micrometer (12% finer than 5 micrometer...Entisol red-orange sandy loam/alluvium see comment 8% x 10% 72 7% smectite ; 47% finer than 20 μm (22% finer than 5 μm) Entisol sandy

Rapid brain MRI acquisition techniques at ultra-high fields

PubMed Central

Setsompop, Kawin; Feinberg, David A.; Polimeni, Jonathan R.

2017-01-01

Ultra-high-field MRI provides large increases in signal-to-noise ratio as well as enhancement of several contrast mechanisms in both structural and functional imaging. Combined, these gains result in a substantial boost in contrast-to-noise ratio that can be exploited for higher spatial resolution imaging to extract finer-scale information about the brain. With increased spatial resolution, however, is a concurrent increased image encoding burden that can cause unacceptably long scan times for structural imaging and slow temporal sampling of the hemodynamic response in functional MRI—particularly when whole-brain imaging is desired. To address this issue, new directions of imaging technology development—such as the move from conventional 2D slice-by-slice imaging to more efficient Simultaneous MultiSlice (SMS) or MultiBand imaging (which can be viewed as “pseudo-3D” encoding) as well as full 3D imaging—have provided dramatic improvements in acquisition speed. Such imaging paradigms provide higher SNR efficiency as well as improved encoding efficiency. Moreover, SMS and 3D imaging can make better use of coil sensitivity information in multi-channel receiver arrays used for parallel imaging acquisitions through controlled aliasing in multiple spatial directions. This has enabled unprecedented acceleration factors of an order of magnitude or higher in these imaging acquisition schemes, with low image artifact levels and high SNR. Here we review the latest developments of SMS and 3D imaging methods and related technologies at ultra-high field for rapid high-resolution functional and structural imaging of the brain. PMID:26835884

Downscaling Global Emissions and Its Implications Derived from Climate Model Experiments

PubMed Central

Abe, Manabu; Kinoshita, Tsuguki; Hasegawa, Tomoko; Kawase, Hiroaki; Kushida, Kazuhide; Masui, Toshihiko; Oka, Kazutaka; Shiogama, Hideo; Takahashi, Kiyoshi; Tatebe, Hiroaki; Yoshikawa, Minoru

2017-01-01

In climate change research, future scenarios of greenhouse gas and air pollutant emissions generated by integrated assessment models (IAMs) are used in climate models (CMs) and earth system models to analyze future interactions and feedback between human activities and climate. However, the spatial resolutions of IAMs and CMs differ. IAMs usually disaggregate the world into 10–30 aggregated regions, whereas CMs require a grid-based spatial resolution. Therefore, downscaling emissions data from IAMs into a finer scale is necessary to input the emissions into CMs. In this study, we examined whether differences in downscaling methods significantly affect climate variables such as temperature and precipitation. We tested two downscaling methods using the same regionally aggregated sulfur emissions scenario obtained from the Asian-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. The downscaled emissions were fed into the Model for Interdisciplinary Research on Climate (MIROC). One of the methods assumed a strong convergence of national emissions intensity (e.g., emissions per gross domestic product), while the other was based on inertia (i.e., the base-year remained unchanged). The emissions intensities in the downscaled spatial emissions generated from the two methods markedly differed, whereas the emissions densities (emissions per area) were similar. We investigated whether the climate change projections of temperature and precipitation would significantly differ between the two methods by applying a field significance test, and found little evidence of a significant difference between the two methods. Moreover, there was no clear evidence of a difference between the climate simulations based on these two downscaling methods. PMID:28076446

Changing Pattern of Indian Monsoon Extremes: Global and Local Factors

NASA Astrophysics Data System (ADS)

Ghosh, Subimal; Shastri, Hiteshri; Pathak, Amey; Paul, Supantha

2017-04-01

Indian Summer Monsoon Rainfall (ISMR) extremes have remained a major topic of discussion in the field of global change and hydro-climatology over the last decade. This attributes to multiple conclusions on changing pattern of extremes along with poor understanding of multiple processes at global and local scales associated with monsoon extremes. At a spatially aggregate scale, when number of extremes in the grids are summed over, a statistically significant increasing trend is observed for both Central India (Goswami et al., 2006) and all India (Rajeevan et al., 2008). However, such a result over Central India does not satisfy flied significance test of increase and no decrease (Krishnamurthy et al., 2009). Statistically rigorous extreme value analysis that deals with the tail of the distribution reveals a spatially non-uniform trend of extremes over India (Ghosh et al., 2012). This results into statistically significant increasing trend of spatial variability. Such an increase of spatial variability points to the importance of local factors such as deforestation and urbanization. We hypothesize that increase of spatial average of extremes is associated with the increase of events occurring over large region, while increase in spatial variability attributes to local factors. A Lagrangian approach based dynamic recycling model reveals that the major contributor of moisture to wide spread extremes is Western Indian Ocean, while land surface also contributes around 25-30% of moisture during the extremes in Central India. We further test the impacts of local urbanization on extremes and find the impacts are more visible over West central, Southern and North East India. Regional atmospheric simulations coupled with Urban Canopy Model (UCM) shows that urbanization intensifies extremes in city areas, but not uniformly all over the city. The intensification occurs over specific pockets of the urban region, resulting an increase in spatial variability even within the city. This also points to the need of setting up multiple weather stations over the city at a finer resolution for better understanding of urban extremes. We conclude that the conventional method of considering large scale factors is not sufficient for analysing the monsoon extremes and characterization of the same needs a blending of both global and local factors. Ghosh, S., Das, D., Kao, S-C. & Ganguly, A. R. Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes. Nature Clim. Change 2, 86-91 (2012) Goswami, B. N., Venugopal, V., Sengupta, D., Madhusoodanan, M. S. & Xavier, P. K. Increasing trend of extreme rain events over India in a warming environment. Science 314, 1442-1445 (2006). Krishnamurthy, C. K. B., Lall, U. & Kwon, H-H. Changing frequency and intensity of rainfall extremes over India from 1951 to 2003. J. Clim. 22, 4737-4746 (2009). Rajeevan, M., Bhate, J. & Jaswal, A. K. Analysis of variability and trends of extreme rainfall events over India using 104 years of gridded daily rainfall data. Geophys. Res. Lett. 35, L18707 (2008).

Downscaling SMAP Radiometer Soil Moisture over the CONUS using Soil-Climate Information and Ensemble Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, P.; Moradkhani, H.

2017-12-01

Soil moisture contributes significantly towards the improvement of weather and climate forecast and understanding terrestrial ecosystem processes. It is known as a key hydrologic variable in the agricultural drought monitoring, flood modeling and irrigation management. While satellite retrievals can provide an unprecedented information on soil moisture at global-scale, the products are generally at coarse spatial resolutions (25-50 km2). This often hampers their use in regional or local studies, which normally require a finer resolution of the data set. This work presents a new framework based on an ensemble learning method while using soil-climate information derived from remote-sensing and ground-based observations to downscale the level 3 daily composite version (L3_SM_P) of SMAP radiometer soil moisture over the Continental U.S. (CONUS) at 1 km spatial resolution. In the proposed method, a suite of remotely sensed and in situ data sets in addition to soil texture information and topography data among others were used. The downscaled product was validated against in situ soil moisture measurements collected from a limited number of core validation sites and several hundred sparse soil moisture networks throughout the CONUS. The obtained results indicated a great potential of the proposed methodology to derive the fine resolution soil moisture information applicable for fine resolution hydrologic modeling, data assimilation and other regional studies.

Using a new high resolution regional model for malaria that accounts for population density and surface hydrology to determine sensitivity of malaria risk to climate drivers

NASA Astrophysics Data System (ADS)

Tompkins, Adrian; Ermert, Volker; Di Giuseppe, Francesca

2013-04-01

In order to better address the role of population dynamics and surface hydrology in the assessment of malaria risk, a new dynamical disease model been developed at ICTP, known as VECTRI: VECtor borne disease community model of ICTP, TRIeste (VECTRI). The model accounts for the temperature impact on the larvae, parasite and adult vector populations. Local host population density affects the transmission intensity, and the model thus reproduces the differences between peri-urban and rural transmission noted in Africa. A new simple pond model framework represents surface hydrology. The model can be used on with spatial resolutions finer than 10km to resolve individual health districts and thus can be used as a planning tool. Results of the models representation of interannual variability and longer term projections of malaria transmission will be shown for Africa. These will show that the model represents the seasonality and spatial variations of malaria transmission well matching a wide range of survey data of parasite rate and entomological inoculation rate (EIR) from across West and East Africa taken in the period prior to large-scale interventions. The model is used to determine the sensitivity of malaria risk to climate variations, both in rainfall and temperature, and then its use in a prototype forecasting system coupled with ECMWF forecasts will be demonstrated.

Preliminary Cost Benefit Assessment of Systems for Detection of Hazardous Weather. Volume I,

DTIC Science & Technology

1981-07-01

not be sufficient for adequate stream flow forecasting , it has important potential for real - time flash flood warning. This was illustrated by the 1977...provide a finer spatial resolution of the gridded data. See Table 9. 42 The results of a demonstration of the real - time capabilities of a radar-man system ...detailed real time measurement capabilities and scope for quantitative forecasting is most likely to provide the degree of lead time required if maximum

Application of Recent Advances in Forward Modeling of Emissions from Boreal and Temperate Wildfires to Real-time Forecasting of Aerosol and Trace Gas Concentrations

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Reid, J. S.; Kasischke, E. S.; Allen, D. J.

2005-12-01

The magnitude of trace gas and aerosol emissions from wildfires is a scientific problem with important implications for atmospheric composition, and is also integral to understanding carbon cycling in terrestrial ecosystems. Recent ecological research on modeling wildfire emissions has integrated theoretical advances derived from ecological fieldwork with improved spatial and temporal databases to produce "post facto" estimates of emissions with high spatial and temporal resolution. These advances have been shown to improve agreement with atmospheric observations at coarse scales, but can in principle be applied to applications, such as forecasting, at finer scales. However, several of the approaches employed in these forward models are incompatible with the requirements of real-time forecasting, requiring modification of data inputs and calculation methods. Because of the differences in data inputs used for real-time and "post-facto" emissions modeling, the key uncertainties in the forward problem are not necessarily the same for these two applications. However, adaptation of these advances in forward modeling to forecasting applications has the potential to improve air quality forecasts, and also to provide a large body of experimental data which can be used to constrain crucial uncertainties in current conceptual models of wildfire emissions. This talk describes a forward modeling method developed at the University of Maryland and its application to the Fire Locating and Modeling of Burning Emissions (FLAMBE) system at the Naval Research Laboratory. Methods for applying the outputs of the NRL aerosol forecasting system to the inverse problem of constraining emissions will also be discussed. The system described can use the feedback supplied by atmospheric observations to improve the emissions source description in the forecasting model, and can also be used for hypothesis testing regarding fire behavior and data inputs.

Evaluating interception of larval pallid sturgeon on the Lower Missouri River- data acquisition, interpolation, and visualization

NASA Astrophysics Data System (ADS)

Bulliner, E. A., IV; Erwin, S. O.; Anderson, B. J.; Wilson, H.; Jacobson, R. B.

2016-12-01

The transition from endogenous to exogenous feeding is an important life-stage transition for many riverine fish larvae. On the Missouri River, U.S., riverine alteration has decreased connectivity between the navigation channel and complex, food-producing and foraging areas on the channel margins, namely shallow side channels and sandbar complexes. A favored hypothesis, the interception hypothesis, for recruitment failure of pallid sturgeon is that drifting larvae are not able to exit the highly engineered navigation channel, and therefore starve. We present work exploring measures of hydraulic connectivity between the navigation channel and channel margins using multiple data-collection protocols with acoustic Doppler current profilers (ADCPs). As ADCP datasets alone often do not have high enough spatial resolution to characterize interception and connectivity sufficiently at the scale of drifting sturgeon larvae, they are often supplemented with physical and empirical models. Using boat-mounted ADCPs, we collected 3-dimensional current velocities with a variety of driving techniques (specifically, regularly spaced transects, reciprocal transects, and irregular patterns) around areas of potential larval interception. We then used toolkits based in Python to interpolate 3-dimensional velocity fields at spatial scales finer than the original measurements, and visualized resultant velocity vectors and flowlines in the software package Paraview. Using these visualizations, we investigated the necessary resolution of field measurements required to model connectivity with channel margin areas on large, highly engineered river ecosystems such as the Missouri River. We anticipate that results from this work will be used to help inform models of larval interception under current conditions. Furthermore, results from this work will be useful in developing monitoring strategies to evaluate the restoration of channel complexity to support ecological functions.

Strong and nonlinear effects of fragmentation on ecosystem service provision at multiple scales

NASA Astrophysics Data System (ADS)

Mitchell, Matthew G. E.; Bennett, Elena M.; Gonzalez, Andrew

2015-09-01

Human actions, such as converting natural land cover to agricultural or urban land, result in the loss and fragmentation of natural habitat, with important consequences for the provision of ecosystem services. Such habitat loss is especially important for services that are supplied by fragments of natural land cover and that depend on flows of organisms, matter, or people across the landscape to produce benefits, such as pollination, pest regulation, recreation and cultural services. However, our quantitative knowledge about precisely how different patterns of landscape fragmentation might affect the provision of these types of services is limited. We used a simple, spatially explicit model to evaluate the potential impact of natural land cover loss and fragmentation on the provision of hypothetical ecosystem services. Based on current literature, we assumed that fragments of natural land cover provide ecosystem services to the area surrounding them in a distance-dependent manner such that ecosystem service flow depended on proximity to fragments. We modeled seven different patterns of natural land cover loss across landscapes that varied in the overall level of landscape fragmentation. Our model predicts that natural land cover loss will have strong and unimodal effects on ecosystem service provision, with clear thresholds indicating rapid loss of service provision beyond critical levels of natural land cover loss. It also predicts the presence of a tradeoff between maximizing ecosystem service provision and conserving natural land cover, and a mismatch between ecosystem service provision at landscape versus finer spatial scales. Importantly, the pattern of landscape fragmentation mitigated or intensified these tradeoffs and mismatches. Our model suggests that managing patterns of natural land cover loss and fragmentation could help influence the provision of multiple ecosystem services and manage tradeoffs and synergies between services across different human-dominated landscapes.

Using Satellite Aerosol Retrievals to Monitor Surface Particulate Air Quality

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Lorraine A.; Kahn, Ralph A.; Chu, D. Allen; Mattoo, Shana; Holben, Brent N.; Schafer, Joel S.

2011-01-01

The MODIS and MISR aerosol products were designed nearly two decades ago for the purpose of climate applications. Since launch of Terra in 1999, these two sensors have provided global, quantitative information about column-integrated aerosol properties, including aerosol optical depth (AOD) and relative aerosol type parameters (such as Angstrom exponent). Although primarily designed for climate, the air quality (AQ) community quickly recognized that passive satellite products could be used for particulate air quality monitoring and forecasting. However, AOD and particulate matter (PM) concentrations have different units, and represent aerosol conditions in different layers of the atmosphere. Also, due to low visible contrast over brighter surface conditions, satellite-derived aerosol retrievals tend to have larger uncertainty in urban or populated regions. Nonetheless, the AQ community has made significant progress in relating column-integrated AOD at ambient relative humidity (RH) to surface PM concentrations at dried RH. Knowledge of aerosol optical and microphysical properties, ambient meteorological conditions, and especially vertical profile, are critical for physically relating AOD and PM. To make urban-scale maps of PM, we also must account for spatial variability. Since surface PM may vary on a finer spatial scale than the resolution of standard MODIS (10 km) and MISR (17km) products, we test higher-resolution versions of MODIS (3km) and MISR (1km research mode) retrievals. The recent (July 2011) DISCOVER-AQ campaign in the mid-Atlantic offers a comprehensive network of sun photometers (DRAGON) and other data that we use for validating the higher resolution satellite data. In the future, we expect that the wealth of aircraft and ground-based measurements, collected during DISCOVER-AQ, will help us quantitatively link remote sensed and ground-based measurements in the urban region.

Objects Grouping for Segmentation of Roads Network in High Resolution Images of Urban Areas

NASA Astrophysics Data System (ADS)

Maboudi, M.; Amini, J.; Hahn, M.

2016-06-01

Updated road databases are required for many purposes such as urban planning, disaster management, car navigation, route planning, traffic management and emergency handling. In the last decade, the improvement in spatial resolution of VHR civilian satellite sensors - as the main source of large scale mapping applications - was so considerable that GSD has become finer than size of common urban objects of interest such as building, trees and road parts. This technological advancement pushed the development of "Object-based Image Analysis (OBIA)" as an alternative to pixel-based image analysis methods. Segmentation as one of the main stages of OBIA provides the image objects on which most of the following processes will be applied. Therefore, the success of an OBIA approach is strongly affected by the segmentation quality. In this paper, we propose a purpose-dependent refinement strategy in order to group road segments in urban areas using maximal similarity based region merging. For investigations with the proposed method, we use high resolution images of some urban sites. The promising results suggest that the proposed approach is applicable in grouping of road segments in urban areas.

Hierarchical Micro/Nano Structures by Combined Self-Organized Dewetting and Photopatterning of Photoresist Thin Films.

PubMed

Sachan, Priyanka; Kulkarni, Manish; Sharma, Ashutosh

2015-11-17

Photoresists are the materials of choice for micro/nanopatterning and device fabrication but are rarely used as a self-assembly material. We report for the first time a novel interplay of self-assembly and photolithography for fabrication of hierarchical and ordered micro/nano structures. We create self-organized structures by the intensified dewetting of unstable thin (∼10 nm to 1 μm) photoresist films by annealing them in an optimal solvent and nonsolvent liquid mixture that allows spontaneous dewetting to form micro/nano smooth dome-like structures. The density, size (∼100 nm to millimeters), and curvature/contact angle of the dome/droplet structures are controlled by the film thickness, composition of the dewetting liquid, and time of annealing. Ordered dewetted structures are obtained simply by creating spatial variation of viscosity by ultraviolet exposure or by photopatterning before dewetting. Further, the structures thus fabricated are readily photopatterned again on the finer length scales after dewetting. We illustrate the approach by fabricating several three-dimensional structures of varying complexity with secondary and tertiary features.

A methodological critique on using temperature-conditioned resampling for climate projections as in the paper of Gerstengarbe et al. (2013) winter storm- and summer thunderstorm-related loss events in Theoretical and Applied Climatology (TAC)

NASA Astrophysics Data System (ADS)

Wechsung, Frank; Wechsung, Maximilian

2016-11-01

The STatistical Analogue Resampling Scheme (STARS) statistical approach was recently used to project changes of climate variables in Germany corresponding to a supposed degree of warming. We show by theoretical and empirical analysis that STARS simply transforms interannual gradients between warmer and cooler seasons into climate trends. According to STARS projections, summers in Germany will inevitably become dryer and winters wetter under global warming. Due to the dominance of negative interannual correlations between precipitation and temperature during the year, STARS has a tendency to generate a net annual decrease in precipitation under mean German conditions. Furthermore, according to STARS, the annual level of global radiation would increase in Germany. STARS can be still used, e.g., for generating scenarios in vulnerability and uncertainty studies. However, it is not suitable as a climate downscaling tool to access risks following from changing climate for a finer than general circulation model (GCM) spatial scale.

Route visualization using detail lenses.

PubMed

Karnick, Pushpak; Cline, David; Jeschke, Stefan; Razdan, Anshuman; Wonka, Peter

2010-01-01

We present a method designed to address some limitations of typical route map displays of driving directions. The main goal of our system is to generate a printable version of a route map that shows the overview and detail views of the route within a single, consistent visual frame. Our proposed visualization provides a more intuitive spatial context than a simple list of turns. We present a novel multifocus technique to achieve this goal, where the foci are defined by points of interest (POI) along the route. A detail lens that encapsulates the POI at a finer geospatial scale is created for each focus. The lenses are laid out on the map to avoid occlusion with the route and each other, and to optimally utilize the free space around the route. We define a set of layout metrics to evaluate the quality of a lens layout for a given route map visualization. We compare standard lens layout methods to our proposed method and demonstrate the effectiveness of our method in generating aesthetically pleasing layouts. Finally, we perform a user study to evaluate the effectiveness of our layout choices.

Challenges of model transferability to data-scarce regions (Invited)

NASA Astrophysics Data System (ADS)

Samaniego, L. E.

2013-12-01

Developing the ability to globally predict the movement of water on the land surface at spatial scales from 1 to 5 km constitute one of grand challenges in land surface modelling. Copying with this grand challenge implies that land surface models (LSM) should be able to make reliable predictions across locations and/or scales other than those used for parameter estimation. In addition to that, data scarcity and quality impose further difficulties in attaining reliable predictions of water and energy fluxes at the scales of interest. Current computational limitations impose also seriously limitations to exhaustively investigate the parameter space of LSM over large domains (e.g. greater than half a million square kilometers). Addressing these challenges require holistic approaches that integrate the best techniques available for parameter estimation, field measurements and remotely sensed data at their native resolutions. An attempt to systematically address these issues is the multiscale parameterisation technique (MPR) that links high resolution land surface characteristics with effective model parameters. This technique requires a number of pedo-transfer functions and a much fewer global parameters (i.e. coefficients) to be inferred by calibration in gauged basins. The key advantage of this technique is the quasi-scale independence of the global parameters which enables to estimate global parameters at coarser spatial resolutions and then to transfer them to (ungauged) areas and scales of interest. In this study we show the ability of this technique to reproduce the observed water fluxes and states over a wide range of climate and land surface conditions ranging from humid to semiarid and from sparse to dense forested regions. Results of transferability of global model parameters in space (from humid to semi-arid basins) and across scales (from coarser to finer) clearly indicate the robustness of this technique. Simulations with coarse data sets (e.g. EOBS forcing 25x25 km2, FAO soil map 1:5000000) using parameters obtained with high resolution information (REGNIE forcing 1x1 km2, BUEK soil map 1:1000000) in different climatic regions indicate the potential of MPR for prediction in data-scarce regions. In this presentation, we will also discuss how the transferability of global model parameters across scales and locations helps to identify deficiencies in model structure and regionalization functions.

Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data

NASA Astrophysics Data System (ADS)

Higginbottom, Thomas P.; Symeonakis, Elias; Meyer, Hanna; van der Linden, Sebastian

2018-05-01

Increasing attention is being directed at mapping the fractional woody cover of savannahs using Earth-observation data. In this study, we test the utility of Landsat TM/ ETM-based spectral-temporal variability metrics for mapping regional-scale woody cover in the Limpopo Province of South Africa, for 2010. We employ a machine learning framework to compare the accuracies of Random Forest models derived using metrics calculated from different seasons. We compare these results to those from fused Landsat-PALSAR data to establish if seasonal metrics can compensate for structural information from the PALSAR signal. Furthermore, we test the applicability of a statistical variable selection method, the recursive feature elimination (RFE), in the automation of the model building process in order to reduce model complexity and processing time. All of our tests were repeated at four scales (30, 60, 90, and 120 m-pixels) to investigate the role of spatial resolution on modelled accuracies. Our results show that multi-seasonal composites combining imagery from both the dry and wet seasons produced the highest accuracies (R2 = 0.77, RMSE = 9.4, at the 120 m scale). When using a single season of observations, dry season imagery performed best (R2 = 0.74, RMSE = 9.9, at the 120 m resolution). Combining Landsat and radar imagery was only marginally beneficial, offering a mean relative improvement of 1% in accuracy at the 120 m scale. However, this improvement was concentrated in areas with lower densities of woody coverage (<30%), which are areas of concern for environmental monitoring. At finer spatial resolutions, the inclusion of SAR data actually reduced accuracies. Overall, the RFE was able to produce the most accurate model (R2 = 0.8, RMSE = 8.9, at the 120 m pixel scale). For mapping savannah woody cover at the 30 m pixel scale, we suggest that monitoring methodologies continue to exploit the Landsat archive, but should aim to use multi-seasonal derived information. When the coarser 120 m pixel scale is adequate, integration of Landsat and SAR data should be considered, especially in areas with lower woody cover densities. The use of multiple seasonal compositing periods offers promise for large-area mapping of savannahs, even in regions with a limited historical Landsat coverage.

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

PubMed Central

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

2018-01-01

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

Spatial Searching for Solar Physics Data

NASA Astrophysics Data System (ADS)

Hourcle, Joseph; Spencer, J. L.; The VSO Team

2013-07-01

The Virtual Solar Observatory allows searching across many collections of solar physics data, but does not yet allow a researcher to search based on the location and extent of the observation, other than by selecting general categories such as full disk or off limb. High resolution instruments that observe only a portion of the the solar disk require greater specificity than is currently available. We believe that finer-grained spatial searching will allow for improved access to data from existing instruments such as TRACE, XRT and SOT, and well as from upcoming missions such as ATST and IRIS. Our proposed solution should also help scientists to search on the field of view of full-disk images that are out of the Sun-Earth line, such as STEREO/EUVI and obserations from the upcoming Solar Orbiter and Solar Probe Plus missions. We present our current work on cataloging sub field images for spatial searching so that researchers can more easily search for observations of a given feature of interest, with the intent of soliciting information about researcher's requirements and recommendations for further improvements.Abstract (2,250 Maximum Characters): The Virtual Solar Observatory allows searching across many collections of solar physics data, but does not yet allow a researcher to search based on the location and extent of the observation, other than by selecting general categories such as full disk or off limb. High resolution instruments that observe only a portion of the the solar disk require greater specificity than is currently available. We believe that finer-grained spatial searching will allow for improved access to data from existing instruments such as TRACE, XRT and SOT, and well as from upcoming missions such as ATST and IRIS. Our proposed solution should also help scientists to search on the field of view of full-disk images that are out of the Sun-Earth line, such as STEREO/EUVI and obserations from the upcoming Solar Orbiter and Solar Probe Plus missions. We present our current work on cataloging sub field images for spatial searching so that researchers can more easily search for observations of a given feature of interest, with the intent of soliciting information about researcher's requirements and recommendations for further improvements.

Understanding the dust cycle at high latitudes: integrating models and observations

NASA Astrophysics Data System (ADS)

Albani, S.; Mahowald, N. M.; Maggi, V.; Delmonte, B.; Winckler, G.; Potenza, M. A. C.; Baccolo, G.; Balkanski, Y.

2017-12-01

Changing climate conditions affect dust emissions and the global dust cycle, which in turn affects climate and biogeochemistry. Paleodust archives from land, ocean, and ice sheets preserve the history of dust deposition for a range of spatial scales from close to the major hemispheric sources to remote sinks such as the polar ice sheets. In each hemisphere common features on the glacial-interglacial time scale mark the baseline evolution of the dust cycle, and inspired the hypothesis that increased dust deposition to ocean stimulated the glacial biological pump contributing to the reduction of atmospheric carbon dioxide levels. On the other hand finer geographical and temporal scales features are superposed to these glacial-interglacial trends, providing the chance of a more sophisticated understanding of the dust cycle, for instance allowing distinctions in terms of source availability or transport patterns as recorded by different records. As such paleodust archives can prove invaluable sources of information, especially when characterized by a quantitative estimation of the mass accumulation rates, and interpreted in connection with climate models. We review our past work and present ongoing research showing how climate models can help in the interpretation of paleodust records, as well as the potential of the same observations for constraining the representation of the global dust cycle embedded in Earth System Models, both in terms of magnitude and physical parameters related to particle sizes and optical properties. Finally we show the impacts on climate, based on this kind of observationally constrained model simulations.

Surface geophysical methods for characterising frozen ground in transitional permafrost landscapes

USGS Publications Warehouse

Briggs, Martin A.; Campbell, Seth; Nolan, Jay; Walvoord, Michelle Ann; Ntarlagiannis, Dimitrios; Day-Lewis, Frederick D.; Lane, John W.

2017-01-01

The distribution of shallow frozen ground is paramount to research in cold regions, and is subject to temporal and spatial changes influenced by climate, landscape disturbance and ecosystem succession. Remote sensing from airborne and satellite platforms is increasing our understanding of landscape-scale permafrost distribution, but typically lacks the resolution to characterise finer-scale processes and phenomena, which are better captured by integrated surface geophysical methods. Here, we demonstrate the use of electrical resistivity imaging (ERI), electromagnetic induction (EMI), ground penetrating radar (GPR) and infrared imaging over multiple summer field seasons around the highly dynamic Twelvemile Lake, Yukon Flats, central Alaska, USA. Twelvemile Lake has generally receded in the past 30 yr, allowing permafrost aggradation in the receded margins, resulting in a mosaic of transient frozen ground adjacent to thick, older permafrost outside the original lakebed. ERI and EMI best evaluated the thickness of shallow, thin permafrost aggradation, which was not clear from frost probing or GPR surveys. GPR most precisely estimated the depth of the active layer, which forward electrical resistivity modelling indicated to be a difficult target for electrical methods, but could be more tractable in time-lapse mode. Infrared imaging of freshly dug soil pit walls captured active-layer thermal gradients at unprecedented resolution, which may be useful in calibrating emerging numerical models. GPR and EMI were able to cover landscape scales (several kilometres) efficiently, and new analysis software showcased here yields calibrated EMI data that reveal the complicated distribution of shallow permafrost in a transitional landscape.

Overview of the National Inventory and Monitoring Applications Center (NIMAC)

Treesearch

Charles T. Scott

2009-01-01

The National Inventory and Monitoring Applications Center (NIMAC) was created by the Forest Inventory and Analysis (FIA) program in 2006. NIMAC addresses a growing need, expressed by FIA partners, for technical assistance in designing and implementing monitoring plans for forests at scales finer than that provided by the FIA standard inventory. NIMAC's goal is to...

Polymerase Chain Reaction (PCR) applications in white pine blister rust resistance screening

Treesearch

Sam Hendricks; Wendy Sutton; Jeffrey Stone; Richard Sniezko; Angelia Kegley; Anna Schoettle

2011-01-01

A goal of breeding programs for resistance to white pine blister rust is the development of multigenic resistance, even if the genetics and mechanisms of resistance may be imperfectly understood. The goal of multigenic resistance has prompted efforts to categorize host resistance reactions at increasingly finer scales, to identify heritable traits that may confer...

Greater sage-grouse population trends across Wyoming

USGS Publications Warehouse

Edmunds, David; Aldridge, Cameron L.; O'Donnell, Michael; Monroe, Adrian

2018-01-01

The scale at which analyses are performed can have an effect on model results and often one scale does not accurately describe the ecological phenomena of interest (e.g., population trends) for wide-ranging species: yet, most ecological studies are performed at a single, arbitrary scale. To best determine local and regional trends for greater sage-grouse (Centrocercus urophasianus) in Wyoming, USA, we modeled density-independent and -dependent population growth across multiple spatial scales relevant to management and conservation (Core Areas [habitat encompassing approximately 83% of the sage-grouse population on ∼24% of surface area in Wyoming], local Working Groups [7 regional areas for which groups of local experts are tasked with implementing Wyoming's statewide sage-grouse conservation plan at the local level], Core Area status (Core Area vs. Non-Core Area) by Working Groups, and Core Areas by Working Groups). Our goal was to determine the influence of fine-scale population trends (Core Areas) on larger-scale populations (Working Group Areas). We modeled the natural log of change in population size ( peak M lek counts) by time to calculate the finite rate of population growth (λ) for each population of interest from 1993 to 2015. We found that in general when Core Area status (Core Area vs. Non-Core Area) was investigated by Working Group Area, the 2 populations trended similarly and agreed with the overall trend of the Working Group Area. However, at the finer scale where Core Areas were analyzed separately, Core Areas within the same Working Group Area often trended differently and a few large Core Areas could influence the overall Working Group Area trend and mask trends occurring in smaller Core Areas. Relatively close fine-scale populations of sage-grouse can trend differently, indicating that large-scale trends may not accurately depict what is occurring across the landscape (e.g., local effects of gas and oil fields may be masked by increasing larger populations). 

Direct and indirect effects of multiple stressors on stream invertebrates across watershed, reach and site scales: A structural equation modelling better informing on hydromorphological impacts.

PubMed

Villeneuve, B; Piffady, J; Valette, L; Souchon, Y; Usseglio-Polatera, P

2018-01-15

The purpose of our approach was to take into account the nested spatial scales driving stream functioning in the description of pressures/ecological status links by analysing the results of a hierarchical model. The development of this model has allowed us to answer the following questions: Does the consideration of the indirect links between anthropogenic pressures and stream ecological status modify the hierarchy of pressure types impacting benthic invertebrates? Do the different nested scales play different roles in the anthropogenic pressures/ecological status relationship? Does this model lead to better understanding of the specific role of hydromorphology in the evaluation of stream ecological status? To achieve that goal, we used the Partial Least Square (PLS) path modelling method to develop a structural model linking variables describing (i) land use and hydromorphological alterations at the watershed scale, (ii) hydromorphological alterations at the reach scale, (iii) nutrients-organic matter contamination levels at the site scale, and (iv) substrate characteristics at the sampling site scale, to explain variation in values of a macroinvertebrate-based multimetric index: the French I 2 M 2 . We have highlighted the importance of land use effects exerted on both hydromorphological and chemical characteristics of streams observed at finer scales and their subsequent indirect impact on stream ecological status. Hydromorphological alterations have an effect on the substrate mosaic structure and on the concentrations of nutrients and organic matter at site scale. This result implies that stream hydromorphology can have a major indirect effect on macroinvertebrate assemblages and that the hierarchy of impacts of anthropogenic pressures on stream ecological status generally described in the literature - often determining strategic restoration priorities - has to be re-examined. Finally, the effects of nutrients and organic matter on macroinvertebrate assemblages are lower than expected when all the indirect effects of land use and hydromorphological alterations are taken into account. Copyright © 2017 Elsevier B.V. All rights reserved.

Development and application of a large scale river system model for National Water Accounting in Australia

NASA Astrophysics Data System (ADS)

Dutta, Dushmanta; Vaze, Jai; Kim, Shaun; Hughes, Justin; Yang, Ang; Teng, Jin; Lerat, Julien

2017-04-01

Existing global and continental scale river models, mainly designed for integrating with global climate models, are of very coarse spatial resolutions and lack many important hydrological processes, such as overbank flow, irrigation diversion, groundwater seepage/recharge, which operate at a much finer resolution. Thus, these models are not suitable for producing water accounts, which have become increasingly important for water resources planning and management at regional and national scales. A continental scale river system model called Australian Water Resource Assessment River System model (AWRA-R) has been developed and implemented for national water accounting in Australia using a node-link architecture. The model includes major hydrological processes, anthropogenic water utilisation and storage routing that influence the streamflow in both regulated and unregulated river systems. Two key components of the model are an irrigation model to compute water diversion for irrigation use and associated fluxes and stores and a storage-based floodplain inundation model to compute overbank flow from river to floodplain and associated floodplain fluxes and stores. The results in the Murray-Darling Basin shows highly satisfactory performance of the model with median daily Nash-Sutcliffe Efficiency (NSE) of 0.64 and median annual bias of less than 1% for the period of calibration (1970-1991) and median daily NSE of 0.69 and median annual bias of 12% for validation period (1992-2014). The results have demonstrated that the performance of the model is less satisfactory when the key processes such as overbank flow, groundwater seepage and irrigation diversion are switched off. The AWRA-R model, which has been operationalised by the Australian Bureau of Meteorology for continental scale water accounting, has contributed to improvements in the national water account by substantially reducing accounted different volume (gain/loss).

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010.

PubMed

Zulu, Leo C; Kalipeni, Ezekiel; Johannes, Eliza

2014-05-23

Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi's estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across 'sub-epidemics' while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV "hotspots" clustered among eleven southern districts/cities while a "coldspot" captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale.

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010

PubMed Central

2014-01-01

Background Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi’s estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Methods Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Results Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across ‘sub-epidemics’ while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV “hotspots” clustered among eleven southern districts/cities while a “coldspot” captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Conclusions Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale. PMID:24886573

Exploring the Utility of the Planned CYGNSS Mission for Investigating the Initiation and Development of the Madden-Julian Oscillation

NASA Technical Reports Server (NTRS)

Lang, Timothy; Mecikalski, John; Li, Xuanli; Chronis, Themis; Brewer, Alan; Churnside, James; Rutledge, Steve

2014-01-01

CYGNSS is a planned constellation consisting of multiple micro-satellites that leverage the Global Positioning System (GPS) to provide rapidly updated, high resolution (approx. 15-50 km, approx. 4 h) surface wind speeds (via bi-static scatterometry) over the tropical oceans in any weather condition, including heavy rainfall. The approach of the work to be presented at this conference is to utilize a limited-domain, cloud-system resolving model (Weather Research and Forecasting or WRF) and its attendant data assimilation scheme (Three-Dimensional Variational Assimilation or 3DVAR) to investigate the utility of the CYGNSS mission for helping characterize key convectiveto- mesoscale processes - such as surface evaporation, moisture advection and convergence, and upscale development of precipitation systems - that help drive the initiation and development of the Madden-Julian Oscillation (MJO) in the equatorial Indian Ocean. The proposed work will focus on three scientific objectives. Objective 1 is to produce a high-resolution surface wind dataset resolution (approx. 0.5 h, approx. 1-4 km) for multiple MJO onsets using WRF-assimilated winds and other data from the DYNAmics of the MJO (DYNAMO) field campaign, which took place during October 2011 - March 2012. Objective 2 is to study the variability of surface winds during MJO onsets at temporal and spatial scales of finer resolution than future CYGNSS data. The goal is to understand how sub-CYGNSS-resolution processes will shape the observations made by the satellite constellation. Objective 3 is to ingest simulated CYGNSS data into the WRF model in order to perform observing system simulation experiments (OSSEs). These will be used to test and quantify the potential beneficial effects provided by CYGNSS, particularly for characterizing the physical processes driving convective organization and upscale development during the initiation and development of the MJO. The proposed research is ideal for answering important questions about the CYGNSS mission, such as the representativeness of surface wind retrievals in the context of the complex airflow processes that occur during heavy precipitation, as well as the tradeoffs in retrieval accuracy that result from finer spatial resolution of the CYGNSS winds versus increased errors/noisiness in those data. Research plans and initial progress toward these objectives will be presented.

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

PubMed

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

2007-04-01

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

Multiscale 3-D Shape Representation and Segmentation Using Spherical Wavelets

PubMed Central

Nain, Delphine; Haker, Steven; Bobick, Aaron

2013-01-01

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

Random field theory to interpret the spatial variability of lacustrine soils

NASA Astrophysics Data System (ADS)

Russo, Savino; Vessia, Giovanna

2015-04-01

The lacustrine soils are quaternary soils, dated from Pleistocene to Holocene periods, generated in low-energy depositional environments and characterized by soil mixture of clays, sands and silts with alternations of finer and coarser grain size layers. They are often met at shallow depth filling several tens of meters of tectonic or erosive basins typically placed in internal Appenine areas. The lacustrine deposits are often locally interbedded by detritic soils resulting from the failure of surrounding reliefs. Their heterogeneous lithology is associated with high spatial variability of physical and mechanical properties both along horizontal and vertical directions. The deterministic approach is still commonly adopted to accomplish the mechanical characterization of these heterogeneous soils where undisturbed sampling is practically not feasible (if the incoherent fraction is prevalent) or not spatially representative (if the cohesive fraction prevails). The deterministic approach consists on performing in situ tests, like Standard Penetration Tests (SPT) or Cone Penetration Tests (CPT) and deriving design parameters through "expert judgment" interpretation of the measure profiles. These readings of tip and lateral resistances (Rp and RL respectively) are almost continuous but highly variable in soil classification according to Schmertmann (1978). Thus, neglecting the spatial variability cannot be the best strategy to estimated spatial representative values of physical and mechanical parameters of lacustrine soils to be used for engineering applications. Hereafter, a method to draw the spatial variability structure of the aforementioned measure profiles is presented. It is based on the theory of the Random Fields (Vanmarcke 1984) applied to vertical readings of Rp measures from mechanical CPTs. The proposed method relies on the application of the regression analysis, by which the spatial mean trend and fluctuations about this trend are derived. Moreover, the scale of fluctuation is calculated to measure the maximum length beyond which profiles of measures are independent. The spatial mean trend can be used to identify "quasi-homogeneous" soil layers where the standard deviation and the scale of fluctuation can be calculated. In this study, five Rp profiles performed in the lacustrine deposits of the high River Pescara Valley have been analyzed. There, silty clay deposits with thickness ranging from a few meters to about 60m, and locally rich in sands and peats, are investigated. In this study, vertical trends of Rp profiles have been derived to be converted into design parameter mean trends. Furthermore, the variability structure derived from Rp readings can be propagated to design parameters to calculate the "characteristic values" requested by the European building codes. References Schmertmann J.H. 1978. Guidelines for Cone Penetration Test, Performance and Design. Report No. FHWA-TS-78-209, U.S. Department of Transportation, Washington, D.C., pp. 145. Vanmarcke E.H. 1984. Random Fields, analysis and synthesis. Cambridge (USA): MIT Press.

Towards realistic Holocene land cover scenarios: integration of archaeological, palynological and geomorphological records and comparison to global land cover scenarios.

NASA Astrophysics Data System (ADS)

De Brue, Hanne; Verstraeten, Gert; Broothaerts, Nils; Notebaert, Bastiaan

2016-04-01

Accurate and spatially explicit landscape reconstructions for distinct time periods in human history are essential for the quantification of the effect of anthropogenic land cover changes on, e.g., global biogeochemical cycles, ecology, and geomorphic processes, and to improve our understanding of interaction between humans and the environment in general. A long-term perspective covering Mid and Late Holocene land use changes is recommended in this context, as it provides a baseline to evaluate human impact in more recent periods. Previous efforts to assess the evolution and intensity of agricultural land cover in past centuries or millennia have predominantly focused on palynological records. An increasing number of quantitative techniques has been developed during the last two decades to transfer palynological data to land cover estimates. However, these techniques have to deal with equifinality issues and, furthermore, do not sufficiently allow to reconstruct spatial patterns of past land cover. On the other hand, several continental and global databases of historical anthropogenic land cover changes based on estimates of global population and the required agricultural land per capita have been developed in the past decennium. However, at such long temporal and spatial scales, reconstruction of past anthropogenic land cover intensities and spatial patterns necessarily involves many uncertainties and assumptions as well. Here, we present a novel approach that combines archaeological, palynological and geomorphological data for the Dijle catchment in the central Belgium Loess Belt in order to arrive at more realistic Holocene land cover histories. Multiple land cover scenarios (> 60.000) are constructed using probabilistic rules and used as input into a sediment delivery model (WaTEM/SEDEM). Model outcomes are confronted with a detailed geomorphic dataset on Holocene sediment fluxes and with REVEALS based estimates of vegetation cover using palynological data from six alluvial sites. This comparison drastically reduces the number of realistic land cover scenarios for various cultural periods. REVEALS based land cover histories provide more accurate estimates of Holocene sediment fluxes compared to global land cover scenarios (KK10 and HYDE 3.1). Both global land cover scenarios produce erroneous results when applied at their original coarse scale resolution. However, spatially allocating KK10 land cover data to a finer spatial resolution increases its performance, whereas this is not the case for HYDE 3.1. Results suggest that KK10 also offers a more realistic history of human impact than HYDE 3.1 although it overestimates human impact in the Belgian Loess Belt prior to the Roman Age, whereas it underestimates human impact from the Medieval Period onwards.

Convergence behavior of idealized convection-resolving simulations of summertime deep moist convection over land

NASA Astrophysics Data System (ADS)

Panosetti, Davide; Schlemmer, Linda; Schär, Christoph

2018-05-01

Convection-resolving models (CRMs) can explicitly simulate deep convection and resolve interactions between convective updrafts. They are thus increasingly used in numerous weather and climate applications. However, the truncation of the continuous energy cascade at scales of O (1 km) poses a serious challenge, as in kilometer-scale simulations the size and properties of the simulated convective cells are often determined by the horizontal grid spacing (Δ x ).In this study, idealized simulations of deep moist convection over land are performed to assess the convergence behavior of a CRM at Δ x = 8, 4, 2, 1 km and 500 m. Two types of convergence estimates are investigated: bulk convergence addressing domain-averaged and integrated variables related to the water and energy budgets, and structural convergence addressing the statistics and scales of individual clouds and updrafts. Results show that bulk convergence generally begins at Δ x =4 km, while structural convergence is not yet fully achieved at the kilometer scale, despite some evidence that the resolution sensitivity of updraft velocities and convective mass fluxes decreases at finer resolution. In particular, at finer grid spacings the maximum updraft velocity generally increases, and the size of the smallest clouds is mostly determined by Δ x . A number of different experiments are conducted, and it is found that the presence of orography and environmental vertical wind shear yields more energetic structures at scales much larger than Δ x , sometimes reducing the resolution sensitivity. Overall the results lend support to the use of kilometer-scale resolutions in CRMs, despite the inability of these models to fully resolve the associated cloud field.

Developing perturbations for Climate Change Impact Assessments

NASA Astrophysics Data System (ADS)

Hewitson, Bruce

Following the 2001 Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report [TAR; IPCC, 2001], and the paucity of climate change impact assessments from developing nations, there has been a significant growth in activities to redress this shortcoming. However, undertaking impact assessments (in relation to malaria, crop stress, regional water supply, etc.) is contingent on available climate-scale scenarios at time and space scales of relevance to the regional issues of importance. These scales are commonly far finer than even the native resolution of the Global Climate Models (GCMs) (the principal tools for climate change research), let alone the skillful resolution (scales of aggregation at which GCM observational error is acceptable for a given application) of GCMs.Consequently, there is a growing demand for regional-scale scenarios, which in turn are reliant on techniques to downscale from GCMs, such as empirical downscaling or nested Regional Climate Models (RCMs). These methods require significant skill, experiential knowledge, and computational infrastructure in order to derive credible regional-scale scenarios. In contrast, it is often the case that impact assessment researchers in developing nations have inadequate resources with limited access to scientists in the broader international scientific community who have the time and expertise to assist. However, where developing effective downscaled scenarios is problematic, it is possible that much useful information can still be obtained for impact assessments by examining the system sensitivity to largerscale climate perturbations. Consequently, one may argue that the early phase of assessing sensitivity and vulnerability should first be characterized by evaluation of the first-order impacts, rather than immediately addressing the finer, secondary factors that are dependant on scenarios derived through downscaling.

What is feasible with imaging human brain function and connectivity using functional magnetic resonance imaging

PubMed Central

2016-01-01

When we consider all of the methods we employ to detect brain function, from electrophysiology to optical techniques to functional magnetic resonance imaging (fMRI), we do not really have a ‘golden technique’ that meets all of the needs for studying the brain. We have methods, each of which has significant limitations but provide often complimentary information. Clearly, there are many questions that need to be answered about fMRI, which unlike other methods, allows us to study the human brain. However, there are also extraordinary accomplishments or demonstration of the feasibility of reaching new and previously unexpected scales of function in the human brain. This article reviews some of the work we have pursued, often with extensive collaborations with other co-workers, towards understanding the underlying mechanisms of the methodology, defining its limitations, and developing solutions to advance it. No doubt, our knowledge of human brain function has vastly expanded since the introduction of fMRI. However, methods and instrumentation in this dynamic field have evolved to a state that discoveries about the human brain based on fMRI principles, together with information garnered at a much finer spatial and temporal scale through other methods, are poised to significantly accelerate in the next decade. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574313

What is feasible with imaging human brain function and connectivity using functional magnetic resonance imaging.

PubMed

Ugurbil, Kamil

2016-10-05

When we consider all of the methods we employ to detect brain function, from electrophysiology to optical techniques to functional magnetic resonance imaging (fMRI), we do not really have a 'golden technique' that meets all of the needs for studying the brain. We have methods, each of which has significant limitations but provide often complimentary information. Clearly, there are many questions that need to be answered about fMRI, which unlike other methods, allows us to study the human brain. However, there are also extraordinary accomplishments or demonstration of the feasibility of reaching new and previously unexpected scales of function in the human brain. This article reviews some of the work we have pursued, often with extensive collaborations with other co-workers, towards understanding the underlying mechanisms of the methodology, defining its limitations, and developing solutions to advance it. No doubt, our knowledge of human brain function has vastly expanded since the introduction of fMRI. However, methods and instrumentation in this dynamic field have evolved to a state that discoveries about the human brain based on fMRI principles, together with information garnered at a much finer spatial and temporal scale through other methods, are poised to significantly accelerate in the next decade.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Author(s).

Climate impacts on global hot spots of marine biodiversity

PubMed Central

Ramírez, Francisco; Afán, Isabel; Davis, Lloyd S.; Chiaradia, André

2017-01-01

Human activities drive environmental changes at scales that could potentially cause ecosystem collapses in the marine environment. We combined information on marine biodiversity with spatial assessments of the impacts of climate change to identify the key areas to prioritize for the conservation of global marine biodiversity. This process identified six marine regions of exceptional biodiversity based on global distributions of 1729 species of fish, 124 marine mammals, and 330 seabirds. Overall, these hot spots of marine biodiversity coincide with areas most severely affected by global warming. In particular, these marine biodiversity hot spots have undergone local to regional increasing water temperatures, slowing current circulation, and decreasing primary productivity. Furthermore, when we overlapped these hot spots with available industrial fishery data, albeit coarser than our estimates of climate impacts, they suggest a worrying coincidence whereby the world’s richest areas for marine biodiversity are also those areas mostly affected by both climate change and industrial fishing. In light of these findings, we offer an adaptable framework for determining local to regional areas of special concern for the conservation of marine biodiversity. This has exposed the need for finer-scaled fishery data to assist in the management of global fisheries if the accumulative, but potentially preventable, effect of fishing on climate change impacts is to be minimized within areas prioritized for marine biodiversity conservation. PMID:28261659

EnviroAtlas: Providing Nationwide Geospatial Ecosystem Goods and Services Indicators and Indices to Inform Decision-Making, Research, and Education

NASA Astrophysics Data System (ADS)

Neale, A. C.

2016-12-01

EnviroAtlas is a multi-organization effort led by the US Environmental Protection Agency to develop, host and display a large suite of nation-wide geospatial indicators and indices of ecosystem services. This open access tool allows users to view, analyze, and download a wealth of geospatial data and other resources related to ecosystem goods and services. More than 160 national indicators of ecosystem service supply, demand, and drivers of change provide a framework to inform decisions and policies at multiple spatial scales, educate a range of audiences, and supply data for research. A higher resolution component is also available, providing over 100 data layers for finer-scale analyses for selected communities across the US. The ecosystem goods and services data are organized into seven general ecosystem benefit categories: clean and plentiful water; natural hazard mitigation; food, fuel, and materials; climate stabilization; clean air; biodiversity conservation; and recreation, culture, and aesthetics. Each indicator is described in terms of how it is important to human health or well-being. EnviroAtlas includes data describing existing ecosystem markets for water quality and quantity, biodiversity, wetland mitigation, and carbon credits. This presentation will briefly describe the EnviroAtlas data and tools and how they are being developed and used in ongoing research studies and in decision-making contexts.

Space Weather Tools of the Trade - A Changing Mix

NASA Astrophysics Data System (ADS)

Kunches, J.; Crowley, G.; Pilinski, M.; Winkler, C.; Fish, C. S.; Hunton, D.; Reynolds, A.; Azeem, I.

2014-12-01

Historically, operational space weather tools have focused on the large-scale. The Sun, solar wind, magnetosphere, and ionosphere were the domains that, rightly so, needed the attention of experimentalists and scientists to fashion the best sensors and physics-based models available. These initiatives resulted in significant improvements for operational forecasters. For example, geomagnetic storm predictions now do not have to rely on proxies for CMEs, such as type II sweep, but rather make use of available actual observations of CMEs from which the true velocity vector may be determined. The users of space weather services profited from the better large-scale observations, but now have expressed their desire for even better spatially and time-resolved granularity of products and services. This natural evolution towards refining products has ushered in the era of the smaller mission, the more efficient sensor. CubeSats and compact ionospheric monitors are examples of the instrumental suite now emerging to bring in this new era. This presentation will show examples of the new mix of smaller systems that enable finer, more well-resolved products and services for the operational world. A number of technologies are now in the marketplace demonstrating the value of more observations at a decreasing cost. In addition, new models are looming to take advantage of these better observations. Examples of models poised to take advantage of new observations will be given.

Microscale optical cryptography using a subdiffraction-limit optical key

NASA Astrophysics Data System (ADS)

Ogura, Yusuke; Aino, Masahiko; Tanida, Jun

2018-04-01

We present microscale optical cryptography using a subdiffraction-limit optical pattern, which is finer than the diffraction-limit size of the decrypting optical system, as a key and a substrate with a reflectance distribution as an encrypted image. Because of the subdiffraction-limit spatial coding, this method enables us to construct a secret image with the diffraction-limit resolution. Simulation and experimental results demonstrate, both qualitatively and quantitatively, that the secret image becomes recognizable when and only when the substrate is illuminated with the designed key pattern.

Piloted studies of Enhanced or Synthetic Vision display parameters

NASA Technical Reports Server (NTRS)

Harris, Randall L., Sr.; Parrish, Russell V.

1992-01-01

This paper summarizes the results of several studies conducted at Langley Research Center over the past few years. The purposes of these studies were to investigate parameters of pictorial displays and imaging sensors that affect pilot approach and landing performance. Pictorial displays have demonstrated exceptional tracking performance and improved the pilots' spatial awareness. Stereopsis cueing improved pilot flight performance and reduced pilot stress. Sensor image parameters such as increased field-of-view. faster image update rate, and aiding symbology improved flare initiation. Finer image resolution and magnification improved attitude control performance parameters.

Enhancing GIS Capabilities for High Resolution Earth Science Grids

NASA Astrophysics Data System (ADS)

Koziol, B. W.; Oehmke, R.; Li, P.; O'Kuinghttons, R.; Theurich, G.; DeLuca, C.

2017-12-01

Applications for high performance GIS will continue to increase as Earth system models pursue more realistic representations of Earth system processes. Finer spatial resolution model input and output, unstructured or irregular modeling grids, data assimilation, and regional coordinate systems present novel challenges for GIS frameworks operating in the Earth system modeling domain. This presentation provides an overview of two GIS-driven applications that combine high performance software with big geospatial datasets to produce value-added tools for the modeling and geoscientific community. First, a large-scale interpolation experiment using National Hydrography Dataset (NHD) catchments, a high resolution rectilinear CONUS grid, and the Earth System Modeling Framework's (ESMF) conservative interpolation capability will be described. ESMF is a parallel, high-performance software toolkit that provides capabilities (e.g. interpolation) for building and coupling Earth science applications. ESMF is developed primarily by the NOAA Environmental Software Infrastructure and Interoperability (NESII) group. The purpose of this experiment was to test and demonstrate the utility of high performance scientific software in traditional GIS domains. Special attention will be paid to the nuanced requirements for dealing with high resolution, unstructured grids in scientific data formats. Second, a chunked interpolation application using ESMF and OpenClimateGIS (OCGIS) will demonstrate how spatial subsetting can virtually remove computing resource ceilings for very high spatial resolution interpolation operations. OCGIS is a NESII-developed Python software package designed for the geospatial manipulation of high-dimensional scientific datasets. An overview of the data processing workflow, why a chunked approach is required, and how the application could be adapted to meet operational requirements will be discussed here. In addition, we'll provide a general overview of OCGIS's parallel subsetting capabilities including challenges in the design and implementation of a scientific data subsetter.

Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex.

PubMed

Tong, Frank; Harrison, Stephenie A; Dewey, John A; Kamitani, Yukiyasu

2012-11-15

Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. Copyright © 2012 Elsevier Inc. All rights reserved.

Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex

PubMed Central

Tong, Frank; Harrison, Stephenie A.; Dewey, John A.; Kamitani, Yukiyasu

2012-01-01

Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. PMID:22917989

Geographically weighted regression based methods for merging satellite and gauge precipitation

NASA Astrophysics Data System (ADS)

Chao, Lijun; Zhang, Ke; Li, Zhijia; Zhu, Yuelong; Wang, Jingfeng; Yu, Zhongbo

2018-03-01

Real-time precipitation data with high spatiotemporal resolutions are crucial for accurate hydrological forecasting. To improve the spatial resolution and quality of satellite precipitation, a three-step satellite and gauge precipitation merging method was formulated in this study: (1) bilinear interpolation is first applied to downscale coarser satellite precipitation to a finer resolution (PS); (2) the (mixed) geographically weighted regression methods coupled with a weighting function are then used to estimate biases of PS as functions of gauge observations (PO) and PS; and (3) biases of PS are finally corrected to produce a merged precipitation product. Based on the above framework, eight algorithms, a combination of two geographically weighted regression methods and four weighting functions, are developed to merge CMORPH (CPC MORPHing technique) precipitation with station observations on a daily scale in the Ziwuhe Basin of China. The geographical variables (elevation, slope, aspect, surface roughness, and distance to the coastline) and a meteorological variable (wind speed) were used for merging precipitation to avoid the artificial spatial autocorrelation resulting from traditional interpolation methods. The results show that the combination of the MGWR and BI-square function (MGWR-BI) has the best performance (R = 0.863 and RMSE = 7.273 mm/day) among the eight algorithms. The MGWR-BI algorithm was then applied to produce hourly merged precipitation product. Compared to the original CMORPH product (R = 0.208 and RMSE = 1.208 mm/hr), the quality of the merged data is significantly higher (R = 0.724 and RMSE = 0.706 mm/hr). The developed merging method not only improves the spatial resolution and quality of the satellite product but also is easy to implement, which is valuable for hydrological modeling and other applications.

Assessing changes to South African maize production areas in 2055 using empirical and process-based crop models

NASA Astrophysics Data System (ADS)

Estes, L.; Bradley, B.; Oppenheimer, M.; Beukes, H.; Schulze, R. E.; Tadross, M.

2010-12-01

Rising temperatures and altered precipitation patterns associated with climate change pose a significant threat to crop production, particularly in developing countries. In South Africa, a semi-arid country with a diverse agricultural sector, anthropogenic climate change is likely to affect staple crops and decrease food security. Here, we focus on maize production, South Africa’s most widely grown crop and one with high socio-economic value. We build on previous coarser-scaled studies by working at a finer spatial resolution and by employing two different modeling approaches: the process-based DSSAT Cropping System Model (CSM, version 4.5), and an empirical distribution model (Maxent). For climate projections, we use an ensemble of 10 general circulation models (GCMs) run under both high and low CO2 emissions scenarios (SRES A2 and B1). The models were down-scaled to historical climate records for 5838 quinary-scale catchments covering South Africa (mean area = 164.8 km2), using a technique based on self-organizing maps (SOMs) that generates precipitation patterns more consistent with observed gradients than those produced by the parent GCMs. Soil hydrological and mechanical properties were derived from textural and compositional data linked to a map of 26422 land forms (mean area = 46 km2), while organic carbon from 3377 soil profiles was mapped using regression kriging with 8 spatial predictors. CSM was run using typical management parameters for the several major dryland maize production regions, and with projected CO2 values. The Maxent distribution model was trained using maize locations identified using annual phenology derived from satellite images coupled with airborne crop sampling observations. Temperature and precipitation projections were based on GCM output, with an additional 10% increase in precipitation to simulate higher water-use efficiency under future CO2 concentrations. The two modeling approaches provide spatially explicit projections of gains and losses in maize productivity. We identify several areas-particularly along the southern and eastern boundaries of current production-with potential for increased productivity. However, larger areas, primarily in the more arid western and northern production regions, are likely to experience diminished productivity. The combination of process-based and distribution models for agricultural impacts assessments provides a useful comparison of two different crop modeling frameworks, as well as the finest scale investigation using a spatially-explicit implementation of a process-based model for South Africa. The large GCM ensemble and multiple emissions scenarios provide a broad climate risk assessment for current maize production. SOM downscaling can help improve climate impacts assessments by increasing their resolution, and by circumventing GCM precipitation schemes whose outcomes are highly divergent.

Precision of the anchor influences the amount of adjustment.

PubMed

Janiszewski, Chris; Uy, Dan

2008-02-01

The anchoring-and-adjustment heuristic has been used to account for a wide variety of numerical judgments. Five studies show that adjustment away from a numerical anchor is smaller if the anchor is precise than if it is rounded. Evidence suggests that precise anchors, compared with rounded anchors, are represented on a subjective scale with a finer resolution. If adjustment consists of a series of iterative mental movements along a subjective scale, then an adjustment from a precise anchor should result in a smaller overall correction than an adjustment from a rounded anchor.

Spatially explicit multi-threat assessment of food tree species in Burkina Faso: A fine-scale approach

PubMed Central

Kindt, Roeland; Loo, Judy; Schmidt, Marco; Bognounou, Fidèle; Da, Sié Sylvestre; Diallo, Ousmane Boukary; Ganaba, Souleymane; Gnoumou, Assan; Lompo, Djingdia; Lykke, Anne Mette; Mbayngone, Elisée; Nacoulma, Blandine Marie Ivette; Ouedraogo, Moussa; Ouédraogo, Oumarou; Parkouda, Charles; Porembski, Stefan; Savadogo, Patrice; Thiombiano, Adjima; Zerbo, Guibien; Vinceti, Barbara

2017-01-01

Over the last decades agroforestry parklands in Burkina Faso have come under increasing demographic as well as climatic pressures, which are threatening indigenous tree species that contribute substantially to income generation and nutrition in rural households. Analyzing the threats as well as the species vulnerability to them is fundamental for priority setting in conservation planning. Guided by literature and local experts we selected 16 important food tree species (Acacia macrostachya, Acacia senegal, Adansonia digitata, Annona senegalensis, Balanites aegyptiaca, Bombax costatum, Boscia senegalensis, Detarium microcarpum, Lannea microcarpa, Parkia biglobosa, Sclerocarya birrea, Strychnos spinosa, Tamarindus indica, Vitellaria paradoxa, Ximenia americana, Ziziphus mauritiana) and six key threats to them (overexploitation, overgrazing, fire, cotton production, mining and climate change). We developed a species-specific and spatially explicit approach combining freely accessible datasets, species distribution models (SDMs), climate models and expert survey results to predict, at fine scale, where these threats are likely to have the greatest impact. We find that all species face serious threats throughout much of their distribution in Burkina Faso and that climate change is predicted to be the most prevalent threat in the long term, whereas overexploitation and cotton production are the most important short-term threats. Tree populations growing in areas designated as ‘highly threatened’ due to climate change should be used as seed sources for ex situ conservation and planting in areas where future climate is predicting suitable habitats. Assisted regeneration is suggested for populations in areas where suitable habitat under future climate conditions coincides with high threat levels due to short-term threats. In the case of Vitellaria paradoxa, we suggest collecting seed along the northern margins of its distribution and considering assisted regeneration in the central part where the current threat level is high due to overexploitation. In the same way, population-specific recommendations can be derived from the individual and combined threat maps of the other 15 food tree species. The approach can be easily transferred to other countries and can be used to analyze general and species specific threats at finer and more local as well as at broader (continental) scales in order to plan more selective and efficient conservation actions in time. The concept can be applied anywhere as long as appropriate spatial data are available as well as knowledgeable experts. PMID:28880962

Spatially explicit multi-threat assessment of food tree species in Burkina Faso: A fine-scale approach.

PubMed

Gaisberger, Hannes; Kindt, Roeland; Loo, Judy; Schmidt, Marco; Bognounou, Fidèle; Da, Sié Sylvestre; Diallo, Ousmane Boukary; Ganaba, Souleymane; Gnoumou, Assan; Lompo, Djingdia; Lykke, Anne Mette; Mbayngone, Elisée; Nacoulma, Blandine Marie Ivette; Ouedraogo, Moussa; Ouédraogo, Oumarou; Parkouda, Charles; Porembski, Stefan; Savadogo, Patrice; Thiombiano, Adjima; Zerbo, Guibien; Vinceti, Barbara

2017-01-01

Over the last decades agroforestry parklands in Burkina Faso have come under increasing demographic as well as climatic pressures, which are threatening indigenous tree species that contribute substantially to income generation and nutrition in rural households. Analyzing the threats as well as the species vulnerability to them is fundamental for priority setting in conservation planning. Guided by literature and local experts we selected 16 important food tree species (Acacia macrostachya, Acacia senegal, Adansonia digitata, Annona senegalensis, Balanites aegyptiaca, Bombax costatum, Boscia senegalensis, Detarium microcarpum, Lannea microcarpa, Parkia biglobosa, Sclerocarya birrea, Strychnos spinosa, Tamarindus indica, Vitellaria paradoxa, Ximenia americana, Ziziphus mauritiana) and six key threats to them (overexploitation, overgrazing, fire, cotton production, mining and climate change). We developed a species-specific and spatially explicit approach combining freely accessible datasets, species distribution models (SDMs), climate models and expert survey results to predict, at fine scale, where these threats are likely to have the greatest impact. We find that all species face serious threats throughout much of their distribution in Burkina Faso and that climate change is predicted to be the most prevalent threat in the long term, whereas overexploitation and cotton production are the most important short-term threats. Tree populations growing in areas designated as 'highly threatened' due to climate change should be used as seed sources for ex situ conservation and planting in areas where future climate is predicting suitable habitats. Assisted regeneration is suggested for populations in areas where suitable habitat under future climate conditions coincides with high threat levels due to short-term threats. In the case of Vitellaria paradoxa, we suggest collecting seed along the northern margins of its distribution and considering assisted regeneration in the central part where the current threat level is high due to overexploitation. In the same way, population-specific recommendations can be derived from the individual and combined threat maps of the other 15 food tree species. The approach can be easily transferred to other countries and can be used to analyze general and species specific threats at finer and more local as well as at broader (continental) scales in order to plan more selective and efficient conservation actions in time. The concept can be applied anywhere as long as appropriate spatial data are available as well as knowledgeable experts.

Satellite based assessment of recent permafrost extent and active layer trends over Alaska and Northwest Canada

NASA Astrophysics Data System (ADS)

Kim, Y.; Kimball, J. S.; PARK, H.; Yi, Y.

2017-12-01

Climate change in the Boreal-Arctic region has experienced greater surface air temperature (SAT) warming than the global average in recent decades, which is promoting permafrost thawing and active layer deepening. Permafrost extent (PE) and active layer thickness (ALT) are key environmental indicators of recent climate change, and strongly impact other eco-hydrological processes including land-atmosphere carbon exchange. We developed a new approach for regional estimation and monitoring of PE using daily landscape freeze-thaw (FT) records derived from satellite microwave (37 GHz) brightness temperature (Tb) observations. ALT was estimated within the PE domain using empirical modeling of land cover dependent edaphic factors and an annual thawing index derived from MODIS land surface temperature (LST) observations and reanalysis based surface air temperatures (SAT). The PE and ALT estimates were derived over the 1980-2016 satellite record and NASA ABoVE (Arctic Boreal Vulnerability Experiment) domain encompassing Alaska and Northwest Canada. The baseline model estimates were derived at 25-km resolution consistent with the satellite FT global record. Our results show recent widespread PE decline and deepening ALT trends, with larger spatial variability and model uncertainty along the southern PE boundary. Larger PE and ALT variability occurs over heterogeneous permafrost subzones characterized by dense vegetation, and variable snow cover and organic layer conditions. We also tested alternative PE and ALT estimates derived using finer (6-km) scale satellite Tb (36.5 GHz) and FT retrievals from a calibrated AMSR-E and AMSR2 sensor record. The PE and ALT results were compared against other independent observations, including process model simulations, in situ measurements, and permafrost inventory records. A model sensitivity analysis was conducted to evaluate snow cover, soil organic layer, and vegetation composition impacts to ALT. The finer delineation of permafrost and active layer conditions provides enhanced regional monitoring of PE and ALT changes over the ABoVE domain, including heterogeneous permafrost subzones.

Bringing the Coastal Zone into Finer Focus

NASA Astrophysics Data System (ADS)

Guild, L. S.; Hooker, S. B.; Kudela, R. M.; Morrow, J. H.; Torres-Perez, J. L.; Palacios, S. L.; Negrey, K.; Dungan, J. L.

2015-12-01

Measurements over extents from submeter to 10s of meters are critical science requirements for the design and integration of remote sensing instruments for coastal zone research. Various coastal ocean phenomena operate at different scales (e.g. meters to kilometers). For example, river plumes and algal blooms have typical extents of 10s of meters and therefore can be resolved with satellite data, however, shallow benthic ecosystem (e.g., coral, seagrass, and kelp) biodiversity and change are best studied at resolutions of submeter to meter, below the pixel size of typical satellite products. The delineation of natural phenomena do not fit nicely into gridded pixels and the coastal zone is complicated by mixed pixels at the land-sea interface with a range of bio-optical signals from terrestrial and water components. In many standard satellite products, these coastal mixed pixels are masked out because they confound algorithms for the ocean color parameter suite. In order to obtain data at the land/sea interface, finer spatial resolution satellite data can be achieved yet spectral resolution is sacrificed. This remote sensing resolution challenge thwarts the advancement of research in the coastal zone. Further, remote sensing of benthic ecosystems and shallow sub-surface phenomena are challenged by the requirements to sense through the sea surface and through a water column with varying light conditions from the open ocean to the water's edge. For coastal waters, >80% of the remote sensing signal is scattered/absorbed due to the atmospheric constituents, sun glint from the sea surface, and water column components. In addition to in-water measurements from various platforms (e.g., ship, glider, mooring, and divers), low altitude aircraft outfitted with high quality bio-optical radiometer sensors and targeted channels matched with in-water sensors and higher altitude platform sensors for ocean color products, bridge the sea-truth measurements to the pixels acquired from satellite and high altitude platforms. We highlight a novel NASA airborne calibration, validation, and research capability for addressing the coastal remote sensing resolution challenge.

Two decades [1992-2012] of surface wind analyses based on satellite scatterometer observations

NASA Astrophysics Data System (ADS)

Desbiolles, Fabien; Bentamy, Abderrahim; Blanke, Bruno; Roy, Claude; Mestas-Nuñez, Alberto M.; Grodsky, Semyon A.; Herbette, Steven; Cambon, Gildas; Maes, Christophe

2017-04-01

Surface winds (equivalent neutral wind velocities at 10 m) from scatterometer missions since 1992 have been used to build up a 20-year climate series. Optimal interpolation and kriging methods have been applied to continuously provide surface wind speed and direction estimates over the global ocean on a regular grid in space and time. The use of other data sources such as radiometer data (SSM/I) and atmospheric wind reanalyses (ERA-Interim) has allowed building a blended product available at 1/4° spatial resolution and every 6 h from 1992 to 2012. Sampling issues throughout the different missions (ERS-1, ERS-2, QuikSCAT, and ASCAT) and their possible impact on the homogeneity of the gridded product are discussed. In addition, we assess carefully the quality of the blended product in the absence of scatterometer data (1992 to 1999). Data selection experiments show that the description of the surface wind is significantly improved by including the scatterometer winds. The blended winds compare well with buoy winds (1992-2012) and they resolve finer spatial scales than atmospheric reanalyses, which make them suitable for studying air-sea interactions at mesoscale. The seasonal cycle and interannual variability of the product compare well with other long-term wind analyses. The product is used to calculate 20-year trends in wind speed, as well as in zonal and meridional wind components. These trends show an important asymmetry between the southern and northern hemispheres, which may be an important issue for climate studies.

The role of density-dependent and -independent processes in spawning habitat selection by salmon in an Arctic riverscape.

PubMed

Huntsman, Brock M; Falke, Jeffrey A; Savereide, James W; Bennett, Katrina E

2017-01-01

Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species' evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. We developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperature as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. Additionally, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Furthermore, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. Our results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.

The 1 km resolution global data set: needs of the International Geosphere Biosphere Programme

USGS Publications Warehouse

Townshend, J.R.G.; Justice, C.O.; Skole, D.; Malingreau, J.-P.; Cihlar, J.; Teillet, P.; Sadowski, F.; Ruttenberg, S.

1994-01-01

Examination of the scientific priorities for the International Geosphere Biosphere Programme (IGBP) reveals a requirement for global land data sets in several of its Core Projects. These data sets need to be at several space and time scales. Requirements are demonstrated for the regular acquisition of data at spatial resolutions of 1 km and finer and at high temporal frequencies. Global daily data at a resolution of approximately 1 km are sensed by the Advanced Very High Resolution Radiometer (AVHRR), but they have not been available in a single archive. It is proposed, that a global data set of the land surface is created from remotely sensed data from the AVHRR to support a number of IGBP's projects. This data set should have a spatial resolution of 1 km and should be generated at least once every 10 days for the entire globe. The minimum length of record should be a year, and ideally a system should be put in place which leads to the continuous acquisition of 1 km data to provide a base line data set prior to the Earth Observing System (EOS) towards the end of the decade. Because of the high cloud cover in many parts of the world, it is necessary to plan for the collection of data from every orbit. Substantial effort will be required in the preprocessing of the data set involving radiometric calibration, atmospheric correction, geometric correction and temporal compositing, to make it suitable for the extraction of information.

The role of density-dependent and –independent processes in spawning habitat selection by salmon in an Arctic riverscape

DOE PAGES

Huntsman, Brock M.; Falke, Jeffrey A.; Savereide, James W.; ...

2017-05-22

Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species’ evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. Here, we developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperaturemore » as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. In addition, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Moreover, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. These results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.« less

SMAP Soil Moisture Disaggregation using Land Surface Temperature and Vegetation Data

NASA Astrophysics Data System (ADS)

Fang, B.; Lakshmi, V.

2016-12-01

Soil moisture (SM) is a key parameter in agriculture, hydrology and ecology studies. The global SM retrievals have been providing by microwave remote sensing technology since late 1970s and many SM retrieval algorithms have been developed, calibrated and applied on satellite sensors such as AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System), AMSR-2 (Advanced Microwave Scanning Radiometer 2) and SMOS (Soil Moisture and Ocean Salinity). Particularly, SMAP (Soil Moisture Active/Passive) satellite, which was developed by NASA, was launched in January 2015. SMAP provides soil moisture products of 9 km and 36 km spatial resolutions which are not capable for research and applications of finer scale. Toward this issue, this study applied a SM disaggregation algorithm to disaggregate SMAP passive microwave soil moisture 36 km product. This algorithm was developed based on the thermal inertial relationship between daily surface temperature variation and daily average soil moisture which is modulated by vegetation condition, by using remote sensing retrievals from AVHRR (Advanced Very High Resolution Radiometer, MODIS (Moderate Resolution Imaging Spectroradiometer), SPOT (Satellite Pour l'Observation de la Terre), as well as Land Surface Model (LSM) output from NLDAS (North American Land Data Assimilation System). The disaggregation model was built at 1/8o spatial resolution on monthly basis and was implemented to calculate and disaggregate SMAP 36 km SM retrievals to 1 km resolution in Oklahoma. The SM disaggregation results were also validated using MESONET (Mesoscale Network) and MICRONET (Microscale Network) ground SM measurements.

Description and evaluation of the Earth System Regional Climate Model (RegCM-ES)

NASA Astrophysics Data System (ADS)

Farneti, Riccardo; Sitz, Lina; Di Sante, Fabio; Fuentes-Franco, Ramon; Coppola, Erika; Mariotti, Laura; Reale, Marco; Sannino, Gianmaria; Barreiro, Marcelo; Nogherotto, Rita; Giuliani, Graziano; Graffino, Giorgio; Solidoro, Cosimo; Giorgi, Filippo

2017-04-01

The increasing availability of satellite remote sensing data, of high temporal frequency and spatial resolution, has provided a new and enhanced view of the global ocean and atmosphere, revealing strong air-sea coupling processes throughout the ocean basins. In order to obtain an accurate representation and better understanding of the climate system, its variability and change, the inclusion of all mechanisms of interaction among the different sub-components, at high temporal and spatial resolution, becomes ever more desirable. Recently, global coupled models have been able to progressively refine their horizontal resolution to attempt to resolve smaller-scale processes. However, regional coupled ocean-atmosphere models can achieve even finer resolutions and provide additional information on the mechanisms of air-sea interactions and feedbacks. Here we describe a new, state-of-the-art, Earth System Regional Climate Model (RegCM-ES). RegCM-ES presently includes the coupling between atmosphere, ocean, land surface and sea-ice components, as well as an hydrological and ocean biogeochemistry model. The regional coupled model has been implemented and tested over some of the COordinated Regional climate Downscaling Experiment (CORDEX) domains. RegCM-ES has shown improvements in the representation of precipitation and SST fields over the tested domains, as well as realistic representations of coupled air-sea processes and interactions. The RegCM-ES model, which can be easily implemented over any regional domain of interest, is open source making it suitable for usage by the large scientific community.

Local Data Integration in East Central Florida

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Manobianco, John T.

1999-01-01

The Applied Meteorology Unit has configured a Local Data Integration System (LDIS) for east central Florida which assimilates in-situ and remotely-sensed observational data into a series of high-resolution gridded analyses. The ultimate goal for running LDIS is to generate products that may enhance weather nowcasts and short-range (less than 6 h) forecasts issued in support of the 45th Weather Squadron (45 WS), Spaceflight Meteorology Group (SMG), and the Melbourne National Weather Service (NWS MLB) operational requirements. LDIS has the potential to provide added value for nowcasts and short-ten-n forecasts for two reasons. First, it incorporates all data operationally available in east central Florida. Second, it is run at finer spatial and temporal resolutions than current national-scale operational models such as the Rapid Update Cycle and Eta models. LDIS combines all available data to produce grid analyses of primary variables (wind, temperature, etc.) at specified temporal and spatial resolutions. These analyses of primary variables can be used to compute diagnostic quantities such as vorticity and divergence. This paper demonstrates the utility of LDIS over east central Florida for a warm season case study. The evolution of a significant thunderstorm outflow boundary is depicted through horizontal and vertical cross section plots of wind speed, divergence, and circulation. In combination with a suitable visualization too], LDIS may provide users with a more complete and comprehensive understanding of evolving mesoscale weather than could be developed by individually examining the disparate data sets over the same area and time.

The role of density-dependent and –independent processes in spawning habitat selection by salmon in an Arctic riverscape

USGS Publications Warehouse

Huntsman, Brock M.; Falke, Jeffrey A.; Savereide, James W.; Bennett, Katrina E.

2017-01-01

Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species’ evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. We developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperature as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. Additionally, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Furthermore, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. Our results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.

A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model

NASA Astrophysics Data System (ADS)

Abbaspour, K. C.; Rouholahnejad, E.; Vaghefi, S.; Srinivasan, R.; Yang, H.; Kløve, B.

2015-05-01

A combination of driving forces are increasing pressure on local, national, and regional water supplies needed for irrigation, energy production, industrial uses, domestic purposes, and the environment. In many parts of Europe groundwater quantity, and in particular quality, have come under sever degradation and water levels have decreased resulting in negative environmental impacts. Rapid improvements in the economy of the eastern European block of countries and uncertainties with regard to freshwater availability create challenges for water managers. At the same time, climate change adds a new level of uncertainty with regard to freshwater supplies. In this research we build and calibrate an integrated hydrological model of Europe using the Soil and Water Assessment Tool (SWAT) program. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals. Leaching of nitrate into groundwater is also simulated at a finer spatial level (HRU). The use of large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation. In this article we discuss issues with data availability, calibration of large-scale distributed models, and outline procedures for model calibration and uncertainty analysis. The calibrated model and results provide information support to the European Water Framework Directive and lay the basis for further assessment of the impact of climate change on water availability and quality. The approach and methods developed are general and can be applied to any large region around the world.

The neural bases of spatial frequency processing during scene perception

PubMed Central

Kauffmann, Louise; Ramanoël, Stephen; Peyrin, Carole

2014-01-01

Theories on visual perception agree that scenes are processed in terms of spatial frequencies. Low spatial frequencies (LSF) carry coarse information whereas high spatial frequencies (HSF) carry fine details of the scene. However, how and where spatial frequencies are processed within the brain remain unresolved questions. The present review addresses these issues and aims to identify the cerebral regions differentially involved in low and high spatial frequency processing, and to clarify their attributes during scene perception. Results from a number of behavioral and neuroimaging studies suggest that spatial frequency processing is lateralized in both hemispheres, with the right and left hemispheres predominantly involved in the categorization of LSF and HSF scenes, respectively. There is also evidence that spatial frequency processing is retinotopically mapped in the visual cortex. HSF scenes (as opposed to LSF) activate occipital areas in relation to foveal representations, while categorization of LSF scenes (as opposed to HSF) activates occipital areas in relation to more peripheral representations. Concomitantly, a number of studies have demonstrated that LSF information may reach high-order areas rapidly, allowing an initial coarse parsing of the visual scene, which could then be sent back through feedback into the occipito-temporal cortex to guide finer HSF-based analysis. Finally, the review addresses spatial frequency processing within scene-selective regions areas of the occipito-temporal cortex. PMID:24847226

The added value of stochastic spatial disaggregation for short-term rainfall forecasts currently available in Canada

NASA Astrophysics Data System (ADS)

Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René

2017-11-01

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

Experimental Investigation of Spatially-Periodic Scalar Patterns in an Inline Mixer

NASA Astrophysics Data System (ADS)

Baskan, Ozge; Speetjens, Michel F. M.; Clercx, Herman J. H.

2015-11-01

Spatially persisting patterns with exponentially decaying intensities form during the downstream evolution of passive scalars in three-dimensional (3D) spatially periodic flows due to the coupled effect of the chaotic nature of the flow and the diffusivity of the material. This has been investigated in many computational and theoretical studies on 3D spatially-periodic flow fields. However, in the limit of zero-diffusivity, the evolution of the scalar fields results in more detailed structures that can only be captured by experiments due to limitations in the computational tools. Our study employs the-state-of-the-art experimental methods to analyze the evolution of 3D advective scalar field in a representative inline mixer, called Quatro static mixer. The experimental setup consists of an optically accessible test section with transparent internal elements, accommodating a pressure-driven pipe flow and equipped with 3D Laser-Induced Fluorescence. The results reveal that the continuous process of stretching and folding of material creates finer structures as the flow progresses, which is an indicator of chaotic advection and the experiments outperform the simulations by revealing far greater level of detail.

Collaborative classification of hyperspectral and visible images with convolutional neural network

NASA Astrophysics Data System (ADS)

Zhang, Mengmeng; Li, Wei; Du, Qian

2017-10-01

Recent advances in remote sensing technology have made multisensor data available for the same area, and it is well-known that remote sensing data processing and analysis often benefit from multisource data fusion. Specifically, low spatial resolution of hyperspectral imagery (HSI) degrades the quality of the subsequent classification task while using visible (VIS) images with high spatial resolution enables high-fidelity spatial analysis. A collaborative classification framework is proposed to fuse HSI and VIS images for finer classification. First, the convolutional neural network model is employed to extract deep spectral features for HSI classification. Second, effective binarized statistical image features are learned as contextual basis vectors for the high-resolution VIS image, followed by a classifier. The proposed approach employs diversified data in a decision fusion, leading to an integration of the rich spectral information, spatial information, and statistical representation information. In particular, the proposed approach eliminates the potential problems of the curse of dimensionality and excessive computation time. The experiments evaluated on two standard data sets demonstrate better classification performance offered by this framework.

Experimental and Numerical Investigation of Controlled, Small-Scale Motions in a Turbulent Shear Layer

DTIC Science & Technology

2007-06-01

cross flow are taken at finer resolution, down to 6.5 μm/pixel. For the flow mapping, both the CCD camera and part of the laser -sheet optics are...Control of Supersonic Impinging Jet Flows using Microjets . AIAA Journal. 41(7):1347-1355, 2001. [9] M.J. Stanek, G. Raman, V. Kibens, J.A. Ross, J. Odedra

Co-evolution of Vegetation, Sediment Transport and Infiltration on semi-arid hillslopes

NASA Astrophysics Data System (ADS)

Harman, C. J.; Troch, P. A.; Lohse, K. A.; Sivapalan, M.

2011-12-01

Soils in semi-arid landscapes can vary over very small distances, with a great deal of variation associated with 'resource islands' created and maintained by woody vegetation. The distinct physical and hydraulic properties that arise in these islands can lead to spatial patterns of infiltration that have been implicated in the maintenance of the vegetation populating the island. Less well understood are the roles that the small-scale variability in soils plays in determining the transport of sediments, water and sediment-bound carbon and nitrogen across hillslopes. Here we explore these relationships using a coupled field and modeling approach. Detailed field data from hillslopes underlain by both granite and schist parent materials in the Santa Catalina mountains (part of the JSC Critical Zone Observatory) suggest that soils under individual velvet mesquite (latin name) contain higher concentration of soil organic matter and have higher hydraulic conductivity and water holding capacity. Greater infiltration and increased roughness under the canopy appears to lead to the formation of mounds that alter overland flow lines around the area under the canopy, particularly in the finer schist soils. This diversion leads to a complex distribution of shear stresses across the hillslope, creating systematic patterns in the transport of carbon and nitrogen rich soils under the canopies. The relationship between the small scale mechanism and the emergent pattern dynamics in the temporal variability of materials delivered to the stream from the hillslope are also examined, and the implications of these results for the modeling of water, sediment and nutrient fluxes at hillslope scales will be discussed.

Evaluation of precipitation trends from high-resolution satellite precipitation products over Mainland China

NASA Astrophysics Data System (ADS)

Chen, Fengrui; Gao, Yongqi

2018-01-01

Many studies have reported the excellent ability of high-resolution satellite precipitation products (0.25° or finer) to capture the spatial distribution of precipitation. However, it is not known whether the precipitation trends derived from them are reliable. For the first time, we have evaluated the annual and seasonal precipitation trends from two typical sources of high-resolution satellite-gauge products, TRMM 3B43 and PERSIANN-CDR, using rain gauge observations over China, and they were also compared with those from gauge-only products (0.25° and 0.5° precipitation products, hereafter called CN25 and CN50). The evaluation focused mainly on the magnitude, significance, sign, and relative order of the precipitation trends, and was conducted at gridded and regional scales. The following results were obtained: (1) at the gridded scale, neither satellite-gauge products precisely measure the magnitude of precipitation trends but they do reproduce their sign and relative order; regarding capturing the significance of trends, they exhibit relatively acceptable performance only over regions with a sufficient amount of significant precipitation trends; (2) at the regional scale, both satellite-gauge products generally provide reliable precipitation trends, although they do not reproduce the magnitude of trends in winter precipitation; and (3) overall, CN50 and TRMM 3B43 outperform others in reproducing all four aspects of the precipitation trends. Compared with CN25, PERSIANN-CDR performs better in determining the magnitude of precipitation trends but marginally worse in reproducing their sign and relative order; moreover, both of them are at a level in capturing the significance of precipitation trends.

How a European network may help with estimating methane emissions on the French national scale

NASA Astrophysics Data System (ADS)

Pison, Isabelle; Berchet, Antoine; Saunois, Marielle; Bousquet, Philippe; Broquet, Grégoire; Conil, Sébastien; Delmotte, Marc; Ganesan, Anita; Laurent, Olivier; Martin, Damien; O'Doherty, Simon; Ramonet, Michel; Spain, T. Gerard; Vermeulen, Alex; Yver Kwok, Camille

2018-03-01

Methane emissions on the national scale in France in 2012 are inferred by assimilating continuous atmospheric mixing ratio measurements from nine stations of the European network ICOS located in France and surrounding countries. To assess the robustness of the fluxes deduced by our inversion system based on an objectified quantification of uncertainties, two complementary inversion set-ups are computed and analysed: (i) a regional run correcting for the spatial distribution of fluxes in France and (ii) a sectorial run correcting fluxes for activity sectors on the national scale. In addition, our results for the two set-ups are compared with fluxes produced in the framework of the inversion inter-comparison exercise of the InGOS project. The seasonal variability in fluxes is consistent between different set-ups, with maximum emissions in summer, likely due to agricultural activity. However, very high monthly posterior uncertainties (up to ≈ 65 to 74 % in the sectorial run in May and June) make it difficult to attribute maximum emissions to a specific sector. On the yearly and national scales, the two inversions range from 3835 to 4050 Gg CH4 and from 3570 to 4190 Gg CH4 for the regional and sectorial runs, respectively, consistently with the InGOS products. These estimates are 25 to 55 % higher than the total national emissions from bottom-up approaches (biogeochemical models from natural emissions, plus inventories for anthropogenic ones), consistently pointing at missing or underestimated sources in the inventories and/or in natural sources. More specifically, in the sectorial set-up, agricultural emissions are inferred as 66% larger than estimates reported to the UNFCCC. Uncertainties in the total annual national budget are 108 and 312 Gg CH4, i.e, 3 to 8 %, for the regional and sectorial runs respectively, smaller than uncertainties in available bottom-up products, proving the added value of top-down atmospheric inversions. Therefore, even though the surface network used in 2012 does not allow us to fully constrain all regions in France accurately, a regional inversion set-up makes it possible to provide estimates of French methane fluxes with an uncertainty in the total budget of less than 10 % on the yearly timescale. Additional sites deployed since 2012 would help to constrain French emissions on finer spatial and temporal scales and attributing missing emissions to specific sectors.

Quantifying Diurnal and Spatial Variations in CO2 Concentrations and Partial Columns using High-Resolution Global Model Simulations

NASA Astrophysics Data System (ADS)

Pawson, S.; Nielsen, J.; Ott, L. E.; Darmenov, A.; Putman, W.

2015-12-01

Model-data fusion approaches, such as global inverse modeling for surface flux estimation, have traditionally been performed at spatial resolutions of several tens to a few hundreds of kilometers. Use of such coarse scales presents a fundamental limitation in reconciling the modeled field with both the atmospheric observations and the distribution of surface emissions and uptake. Emissions typically occur on small scales, including point sources (e.g. power plants, forest fires) or with inhomegeneous structure. Biological uptake can have spatial variations related to complex, diverse vegetation, etc. Atmospheric observations of CO2 are either surface based, providing information at a single point, or space based with a finite-sized footprint. For instance, GOSAT and OCO-2 have footprint sizes of around 10km and proposed active sensors (such as ASCENDS) will likely have even finer footprints. One important aspect of reconciling models to measurements is the representativeness of the observation for the model field, and this depends on the generally unknown spatio-temporal variations of the CO2 field around the measurement location and time. This work presents an assessment of the global spatio-temporal variations of the CO2 field using the "7km GEOS-5 Nature Run" (7km-G5NR), which includes CO2 emissions and uptake mapped to the finest possible resolution. Results are shown for surface CO2 concentrations, total-column CO2, and separate upper and lower tropospheric columns. Spatial variability is shown to be largest in regions with strong point sources and at night in regions with complex terrain, especially where biological processes dominate the local CO2 fluxes, where the day-night differences are also most marked. The spatio-temporal variations are strongest for surface concentrations and for lower tropospheric CO2. While these results are largely anticipated, these high resolution simulations provide quantitative estimates of the global nature of spatio-temporal CO2 variability. Implications for characterizing representativeness of passive CO2 observations will be discussed. Differences between daytime and nighttime structures will be considered in light of active CO2 sensors. Finally, some possible limitations of the model will be highlighted, using some global 3-km simulations.

Comparative theoretical and experimental study of a Shack-Hartmann and a phase diversity sensor, for high-precision wavefront sensing dedicated to space active optics

NASA Astrophysics Data System (ADS)

Montmerle Bonnefois, A.; Fusco, T.; Meimon, S.; Michau, V.; Mugnier, L.; Sauvage, J.-F.; Engel, C.; Escolle, C.; Ferrari, M.; Hugot, E.; Liotard, A.; Bernot, M.; Carlavan, M.; Falzon, F.; Bret-Dibat, T.; Laubier, D.

2017-11-01

Earth-imaging or Universe Science satellites are always in need of higher spatial resolutions, in order to discern finer and finer details in images. This means that every new generation of satellites must have a larger main mirror than the previous one, because of the diffraction. Since it allows the use of larger mirrors, active optics is presently studied for the next generation of satellites. To measure the aberrations of such an active telescope, the Shack-Hartmann (SH), and the phase-diversity (PD) are the two wavefront sensors (WFS) considered preferentially because they are able to work with an extended source like the Earth's surface, as well as point sources like stars. The RASCASSE project was commissioned by the French spatial agency (CNES) to study the SH and PD sensors for high-performance wavefront sensing. It involved ONERA and Thales Alenia Space (TAS), and LAM. Papers by TAS and LAM on the same project are available in this conference, too [1,2]. The purpose of our work at ONERA was to explore what the best performance both wavefront sensors can achieve in a space optics context. So we first performed a theoretical study in order to identify the main sources of errors and quantify them - then we validated those results experimentally. The outline of this paper follows this approach: we first discuss phase diversity theoretical results, then Shack-Hartmann's, then experimental results - to finally conclude on each sensor's performance, and compare their weak and strong points.

Evaluation of uncertainty in capturing the spatial variability and magnitudes of extreme hydrological events for the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Kusangaya, Samuel; Warburton Toucher, Michele L.; van Garderen, Emma Archer

2018-02-01

Downscaled General Circulation Models (GCMs) output are used to forecast climate change and provide information used as input for hydrological modelling. Given that our understanding of climate change points towards an increasing frequency, timing and intensity of extreme hydrological events, there is therefore the need to assess the ability of downscaled GCMs to capture these extreme hydrological events. Extreme hydrological events play a significant role in regulating the structure and function of rivers and associated ecosystems. In this study, the Indicators of Hydrologic Alteration (IHA) method was adapted to assess the ability of simulated streamflow (using downscaled GCMs (dGCMs)) in capturing extreme river dynamics (high and low flows), as compared to streamflow simulated using historical climate data from 1960 to 2000. The ACRU hydrological model was used for simulating streamflow for the 13 water management units of the uMngeni Catchment, South Africa. Statistically downscaled climate models obtained from the Climate System Analysis Group at the University of Cape Town were used as input for the ACRU Model. Results indicated that, high flows and extreme high flows (one in ten year high flows/large flood events) were poorly represented both in terms of timing, frequency and magnitude. Simulated streamflow using dGCMs data also captures more low flows and extreme low flows (one in ten year lowest flows) than that captured in streamflow simulated using historical climate data. The overall conclusion was that although dGCMs output can reasonably be used to simulate overall streamflow, it performs poorly when simulating extreme high and low flows. Streamflow simulation from dGCMs must thus be used with caution in hydrological applications, particularly for design hydrology, as extreme high and low flows are still poorly represented. This, arguably calls for the further improvement of downscaling techniques in order to generate climate data more relevant and useful for hydrological applications such as in design hydrology. Nevertheless, the availability of downscaled climatic output provide the potential of exploring climate model uncertainties in different hydro climatic regions at local scales where forcing data is often less accessible but more accurate at finer spatial scales and with adequate spatial detail.

Effect of flour particle size on microstructural, rheological and physico-sensory characteristics of bread and south Indian parotta.

PubMed

Sakhare, Suresh D; Inamdar, Aashitosh A; Soumya, C; Indrani, D; Rao, G Venkateswara

2014-12-01

Wheat flour fractioned by sieving into four different particle size fractions namely finer fractions (<75 and 75-118 μm), coarser fractions (118-150 and >150 μm) were analyzed for their chemical, rheological, bread & parotta making characteristics. The finer fractions had lower ash, higher dry gluten, damaged starch and sodium dodecysulphate (SDS)-sedimentation value than the coarser fractions. The flour from finer fractions gave bread with best sensory and textural attributes. The parottas from finer fractions showed significantly higher sensory scores for colour, texture, layers, mouthfeel and overall quality score than the coarser fractions. In the micrograph of finer flour fractions, higher number of loosened single starch granules than the aggregates of starch and protein matrix were seen as compared to coarser fractions. These studies indicate that the flour from the finer fractions produce higher quality bread, parotta owing to the presence of higher damaged starch content, quantity and quality of protein in these fractions than coarser fractions.

Global mapping of ecosystem services and conservation priorities

PubMed Central

Naidoo, R.; Balmford, A.; Costanza, R.; Fisher, B.; Green, R. E.; Lehner, B.; Malcolm, T. R.; Ricketts, T. H.

2008-01-01

Global efforts to conserve biodiversity have the potential to deliver economic benefits to people (i.e., “ecosystem services”). However, regions for which conservation benefits both biodiversity and ecosystem services cannot be identified unless ecosystem services can be quantified and valued and their areas of production mapped. Here we review the theory, data, and analyses needed to produce such maps and find that data availability allows us to quantify imperfect global proxies for only four ecosystem services. Using this incomplete set as an illustration, we compare ecosystem service maps with the global distributions of conventional targets for biodiversity conservation. Our preliminary results show that regions selected to maximize biodiversity provide no more ecosystem services than regions chosen randomly. Furthermore, spatial concordance among different services, and between ecosystem services and established conservation priorities, varies widely. Despite this lack of general concordance, “win–win” areas—regions important for both ecosystem services and biodiversity—can be usefully identified, both among ecoregions and at finer scales within them. An ambitious interdisciplinary research effort is needed to move beyond these preliminary and illustrative analyses to fully assess synergies and trade-offs in conserving biodiversity and ecosystem services. PMID:18621701

Satellite, climatological, and theoretical inputs for modeling of the diurnal cycle of fire emissions

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Reid, J. S.; Schmidt, C. C.; Giglio, L.; Prins, E.

2009-12-01

The diurnal cycle of fire activity is crucial for accurate simulation of atmospheric effects of fire emissions, especially at finer spatial and temporal scales. Estimating diurnal variability in emissions is also a critical problem for construction of emissions estimates from multiple sensors with variable coverage patterns. An optimal diurnal emissions estimate will use as much information as possible from satellite fire observations, compensate known biases in those observations, and use detailed theoretical models of the diurnal cycle to fill in missing information. As part of ongoing improvements to the Fire Location and Monitoring of Burning Emissions (FLAMBE) fire monitoring system, we evaluated several different methods of integrating observations with different temporal sampling. We used geostationary fire detections from WF_ABBA, fire detection data from MODIS, empirical diurnal cycles from TRMM, and simple theoretical diurnal curves based on surface heating. Our experiments integrated these data in different combinations to estimate the diurnal cycles of emissions for each location and time. Hourly emissions estimates derived using these methods were tested using an aerosol transport model. We present results of this comparison, and discuss the implications of our results for the broader problem of multi-sensor data fusion in fire emissions modeling.

Delineating wetland catchments and modeling hydrologic ...

EPA Pesticide Factsheets

In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling–spilling–merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that

Disaggregating census data for population mapping using random forests with remotely-sensed and ancillary data.

PubMed

Stevens, Forrest R; Gaughan, Andrea E; Linard, Catherine; Tatem, Andrew J

2015-01-01

High resolution, contemporary data on human population distributions are vital for measuring impacts of population growth, monitoring human-environment interactions and for planning and policy development. Many methods are used to disaggregate census data and predict population densities for finer scale, gridded population data sets. We present a new semi-automated dasymetric modeling approach that incorporates detailed census and ancillary data in a flexible, "Random Forest" estimation technique. We outline the combination of widely available, remotely-sensed and geospatial data that contribute to the modeled dasymetric weights and then use the Random Forest model to generate a gridded prediction of population density at ~100 m spatial resolution. This prediction layer is then used as the weighting surface to perform dasymetric redistribution of the census counts at a country level. As a case study we compare the new algorithm and its products for three countries (Vietnam, Cambodia, and Kenya) with other common gridded population data production methodologies. We discuss the advantages of the new method and increases over the accuracy and flexibility of those previous approaches. Finally, we outline how this algorithm will be extended to provide freely-available gridded population data sets for Africa, Asia and Latin America.

New algorithms for field-theoretic block copolymer simulations: Progress on using adaptive-mesh refinement and sparse matrix solvers in SCFT calculations

NASA Astrophysics Data System (ADS)

Sides, Scott; Jamroz, Ben; Crockett, Robert; Pletzer, Alexander

2012-02-01

Self-consistent field theory (SCFT) for dense polymer melts has been highly successful in describing complex morphologies in block copolymers. Field-theoretic simulations such as these are able to access large length and time scales that are difficult or impossible for particle-based simulations such as molecular dynamics. The modified diffusion equations that arise as a consequence of the coarse-graining procedure in the SCF theory can be efficiently solved with a pseudo-spectral (PS) method that uses fast-Fourier transforms on uniform Cartesian grids. However, PS methods can be difficult to apply in many block copolymer SCFT simulations (eg. confinement, interface adsorption) in which small spatial regions might require finer resolution than most of the simulation grid. Progress on using new solver algorithms to address these problems will be presented. The Tech-X Chompst project aims at marrying the best of adaptive mesh refinement with linear matrix solver algorithms. The Tech-X code PolySwift++ is an SCFT simulation platform that leverages ongoing development in coupling Chombo, a package for solving PDEs via block-structured AMR calculations and embedded boundaries, with PETSc, a toolkit that includes a large assortment of sparse linear solvers.

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space.

PubMed

Lagomasino, David; Fatoyinbo, Temilola; Lee, SeungKuk; Feliciano, Emanuelle; Trettin, Carl; Simard, Marc

2016-04-01

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement, and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 m were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes.

Statistical Evaluation of Combined Daily Gauge Observations and Rainfall Satellite Estimations over Continental South America

NASA Technical Reports Server (NTRS)

Vila, Daniel; deGoncalves, Luis Gustavo; Toll, David L.; Rozante, Jose Roberto

2008-01-01

This paper describes a comprehensive assessment of a new high-resolution, high-quality gauge-satellite based analysis of daily precipitation over continental South America during 2004. This methodology is based on a combination of additive and multiplicative bias correction schemes in order to get the lowest bias when compared with the observed values. Inter-comparisons and cross-validations tests have been carried out for the control algorithm (TMPA real-time algorithm) and different merging schemes: additive bias correction (ADD), ratio bias correction (RAT) and TMPA research version, for different months belonging to different seasons and for different network densities. All compared merging schemes produce better results than the control algorithm, but when finer temporal (daily) and spatial scale (regional networks) gauge datasets is included in the analysis, the improvement is remarkable. The Combined Scheme (CoSch) presents consistently the best performance among the five techniques. This is also true when a degraded daily gauge network is used instead of full dataset. This technique appears a suitable tool to produce real-time, high-resolution, high-quality gauge-satellite based analyses of daily precipitation over land in regional domains.

Predicting breeding bird occurrence by stand- and microhabitat-scale features in even-aged stands in the Central Appalachians

USGS Publications Warehouse

McDermott, M.E.; Wood, P.B.; Miller, G.W.; Simpson, B.T.

2011-01-01

Spatial scale is an important consideration when managing forest wildlife habitat, and models can be used to improve our understanding of these habitats at relevant scales. Our objectives were to determine whether stand- or microhabitat-scale variables better predicted bird metrics (diversity, species presence, and abundance) and to examine breeding bird response to clearcut size and age in a highly forested landscape. In 2004-2007, vegetation data were collected from 62 even-aged stands that were 3.6-34.6. ha in size and harvested in 1963-1990 on the Monongahela National Forest, WV, USA. In 2005-2007, we also surveyed birds at vegetation plots. We used classification and regression trees to model breeding bird habitat use with a suite of stand and microhabitat variables. Among stand variables, elevation, stand age, and stand size were most commonly retained as important variables in guild and species models. Among microhabitat variables, medium-sized tree density and tree species diversity most commonly predicted bird presence or abundance. Early successional and generalist bird presence, abundance, and diversity were better predicted by microhabitat variables than stand variables. Thus, more intensive field sampling may be required to predict habitat use for these species, and management may be needed at a finer scale. Conversely, stand-level variables had greater utility in predicting late-successional species occurrence and abundance; thus management decisions and modeling at this scale may be suitable in areas with a uniform landscape, such as our study area. Our study suggests that late-successional breeding bird diversity can be maximized long-term by including harvests >10. ha in size into our study area and by increasing tree diversity. Some harvesting will need to be incorporated regularly, because after 15 years, the study stands did not provide habitat for most early successional breeding specialists. ?? 2010 Elsevier B.V.

Environmental Gap Analysis to Prioritize Conservation Efforts in Eastern Africa

PubMed Central

van Breugel, Paulo; Kindt, Roeland; Lillesø, Jens-Peter Barnekow; van Breugel, Michiel

2015-01-01

Countries in eastern Africa have set aside significant proportions of their land for protection. But are these areas representative of the diverse range of species and habitats found in the region? And do conservation efforts include areas where the state of biodiversity is likely to deteriorate without further interventions? Various studies have addressed these questions at global and continental scales. However, meaningful conservation decisions are required at finer geographical scales. To operate more effectively at the national level, finer scale baseline data on species and on higher levels of biological organization such as the eco-regions are required, among other factors. Here we adopted a recently developed high-resolution potential natural vegetation (PNV) map for eastern Africa as a baseline to more effectively identify conservation priorities. We examined how well different potential natural vegetations (PNVs) are represented in the protected area (PA) network of eastern Africa and used a multivariate environmental similarity index to evaluate biases in PA versus PNV coverage. We additionally overlaid data of anthropogenic factors that potentially influence the natural vegetation to assess the level of threat to different PNVs. Our results indicate substantial differences in the conservation status of PNVs. In addition, particular PNVs in which biodiversity protection and ecological functions are at risk due to human influences are revealed. The data and approach presented here provide a step forward in developing more transparent and better informed translation from global priorities to regional or national implementation in eastern Africa, and are valid for other geographic regions. PMID:25855968

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

El-Khoury, Patrick Z.; Ueltschi, Tyler W.; Mifflin, Amanda L.

Non-resonant tip-enhanced Raman images of 4,4'-dimercaptostilbene on silver reveal that different vibrational resonances of the reporter are selectively enhanced at different sites on the metal substrate. Sequentially recorded images track molecular diffusion within the diffraction-limited laser spot which illuminates the substrate. In effect, the recorded time resolved (Δt = 10 s) pixelated images (25 nm x 8 cm-1) broadcast molecule-local field interactions which take place on much finer scales.

Morphological evidence for discrete stocks of yellow perch in Lake Erie

USGS Publications Warehouse

Kocovsky, Patrick M.; Knight, Carey T.

2012-01-01

Identification and management of unique stocks of exploited fish species are high-priority management goals in the Laurentian Great Lakes. We analyzed whole-body morphometrics of 1430 yellow perch Perca flavescens captured during 2007–2009 from seven known spawning areas in Lake Erie to determine if morphometrics vary among sites and management units to assist in identification of spawning stocks of this heavily exploited species. Truss-based morphometrics (n = 21 measurements) were analyzed using principal component analysis followed by ANOVA of the first three principal components to determine whether yellow perch from the several sampling sites varied morphometrically. Duncan's multiple range test was used to determine which sites differed from one another to test whether morphometrics varied at scales finer than management unit. Morphometrics varied significantly among sites and annually, but differences among sites were much greater. Sites within the same management unit typically differed significantly from one another, indicating morphometric variation at a scale finer than management unit. These results are largely congruent with recently-published studies on genetic variation of yellow perch from many of the same sampling sites. Thus, our results provide additional evidence that there are discrete stocks of yellow perch in Lake Erie and that management units likely comprise multiple stocks.

A Rapidly Prototyped Vegetation Dryness Index Evaluated for Wildfire Risk Assessment at Stennis Space Center

NASA Technical Reports Server (NTRS)

Ross, Kenton; Graham, William; Prados, Don; Spruce, Joseph

2007-01-01

MVDI, which effectively involves the differencing of NDMI and NDVI, appears to display increased noise that is consistent with a differencing technique. This effect masks finer variations in vegetation moisture, preventing MVDI from fulfilling the requirement of giving decision makers insight into spatial variation of fire risk. MVDI shows dependencies on land cover and phenology which also argue against its use as a fire risk proxy in an area of diverse and fragmented land covers. The conclusion of the rapid prototyping effort is that MVDI should not be implemented for SSC decision support.

The Importance and Current Limitations of Planetary Boundary Layer (PBL) Retrieval from Space for Land-Atmosphere Coupling Studies

NASA Astrophysics Data System (ADS)

Santanello, J. A., Jr.; Schaefer, A.

2016-12-01

There is an established need for improved PBL remote sounding over land for hydrology, land-atmosphere (L-A), PBL, cloud/convection, pollution/chemistry studies and associated model evaluation and development. Most notably, the connection of surface hydrology (through soil moisture) to clouds and precipitation relies on proper quantification of water's transport through the coupled system, which is modulated strongly by PBL structure, growth, and feedback processes such as entrainment. In-situ (ground-based or radiosonde) measurements will be spatially limited to small field campaigns for the foreseeable future, so satellite data is a must in order to understand these processes globally. The scales of these applications require diurnal resolution (e.g. 3-hourly or finer) at <100m vertical and 1-10km spatial resolutions in order to assess processes driving land-PBL coupling and water and energy cycles at their native scales. Today's satellite sensors (e.g. advanced IR, GEO, lidar, GPS-RO) do not reach close to these targets in terms of accuracy or resolution, and each of these sensors has some advantages but even more limitations that make them impractical for PBL and L-A studies. Unfortunately, there is very little attention or planning (short or long-term) in place for improving lower tropospheric sounding over land, and as a result PBL and L-A interactions have been identified as `gaps' in current programmatic focal areas. It is therefore timely to assess how these technologies can be leveraged, combined, or evolved in order to form a dedicated mission or sub-mission to routinely monitor the PBL on diurnal timescales. In addition, improved PBL monitoring from space needs to be addressed in the next Decadal Survey. In this talk, the importance of PBL information (structure, evolution) for L-A coupling diagnostics and model development will be summarized. The current array of PBL retrieval methods and products from space will then be assessed in terms of meeting the needs of these models, diagnostics, and scales, with a look forward as to how this can and must be improved through future mission and sensor design.

Snow driven Radiative Forcing in High Latitude Areas of Disturbance Using Higher Resolution Albedo Products from Landsat and Sentinel-2

NASA Astrophysics Data System (ADS)

Erb, A.; Li, Z.; Schaaf, C.; Wang, Z.; Rogers, B. M.

2017-12-01

Land surface albedo plays an important role in the surface energy budget and radiative forcing by determining the proportion of absorbed incoming solar radiation available to drive photosynthesis and surface heating. In Arctic regions, albedo is particularly sensitive to land cover and land use change (LCLUC) and modeling efforts have shown it to be the primary driver of effective radiative forcing from the biogeophysical effects of LCLUC. In boreal forests, the effects of these changes are complicated during snow covered periods when newly exposed, highly reflective snow can serve as the primary driver of radiative forcing. In Arctic biomes disturbance scars from fire, pest and harvest can remain in the landscape for long periods of time. As such, understanding the magnitude and persistence of these disturbances, especially in the shoulder seasons, is critical. The Landsat and Sentinel-2 Albedo Products couple 30m and 20m surface reflectances with concurrent 500m BRDF Products from the MODerate resolution Imaging Spectroradiometer (MODIS). The 12 bit radiometric fidelity of Sentinel-2 and Landsat-8 allow for the inclusion of high-quality, unsaturated albedo calculations over snow covered surfaces at scales more compatible with fragmented landscapes. Recent work on the early spring albedo of fire scars has illustrated significant post-fire spatial heterogeneity of burn severity at the landscape scale and highlights the need for a finer spatial resolution albedo record. The increased temporal resolution provided by multiple satellite instruments also allows for a better understanding of albedo dynamics during the dynamic shoulder seasons and in historically difficult high latitude locations where persistent cloud cover limits high quality retrievals. Here we present how changes in the early spring albedo of recent boreal forest disturbance in Alaska and central Canada affects landscape-scale radiative forcing. We take advantage of the long historical Landsat record to examine pre-disturbance albedo trends and to link historical land cover and disturbance history to post-disturbance early spring albedo values. We examine the impact of landscape heterogeneity on albedo in the growing and dormant seasons and quantify the effects of snow exposure changes from over-story canopy loss.

Conserving tigers in working landscapes.

PubMed

Chanchani, Pranav; Noon, Barry R; Bailey, Larissa L; Warrier, Rekha A

2016-06-01

Tiger (Panthera tigris) conservation efforts in Asia are focused on protected areas embedded in human-dominated landscapes. A system of protected areas is an effective conservation strategy for many endangered species if the network is large enough to support stable metapopulations. The long-term conservation of tigers requires that the species be able to meet some of its life-history needs beyond the boundaries of small protected areas and within the working landscape, including multiple-use forests with logging and high human use. However, understanding of factors that promote or limit the occurrence of tigers in working landscapes is incomplete. We assessed the relative influence of protection status, prey occurrence, extent of grasslands, intensity of human use, and patch connectivity on tiger occurrence in the 5400 km(2) Central Terai Landscape of India, adjacent to Nepal. Two observer teams independently surveyed 1009 km of forest trails and water courses distributed across 60 166-km(2) cells. In each cell, the teams recorded detection of tiger signs along evenly spaced trail segments. We used occupancy models that permitted multiscale analysis of spatially correlated data to estimate cell-scale occupancy and segment-scale habitat use by tigers as a function of management and environmental covariates. Prey availability and habitat quality, rather than protected-area designation, influenced tiger occupancy. Tiger occupancy was low in some protected areas in India that were connected to extensive areas of tiger habitat in Nepal, which brings into question the efficacy of current protection and management strategies in both India and Nepal. At a finer spatial scale, tiger habitat use was high in trail segments associated with abundant prey and large grasslands, but it declined as human and livestock use increased. We speculate that riparian grasslands may provide tigers with critical refugia from human activity in the daytime and thereby promote tiger occurrence in some multiple-use forests. Restrictions on human-use in high-quality tiger habitat in multiple-use forests may complement existing protected areas and collectively promote the persistence of tiger populations in working landscapes. © 2015 Society for Conservation Biology.

The impact of wave number selection and spin up time when using spectral nudging for dynamical downscaling applications

NASA Astrophysics Data System (ADS)

Gómez, Breogán; Miguez-Macho, Gonzalo

2017-04-01

Nudging techniques are commonly used to constrain the evolution of numerical models to a reference dataset that is typically of a lower resolution. The nudged model retains some of the features of the reference field while incorporating its own dynamics to the solution. These characteristics have made nudging very popular in dynamic downscaling applications that cover from shot range, single case studies, to multi-decadal regional climate simulations. Recently, a variation of this approach called Spectral Nudging, has gained popularity for its ability to maintain the higher temporal and spatial variability of the model results, while forcing the large scales in the solution with a coarser resolution field. In this work, we focus on a not much explored aspect of this technique: the impact of selecting different cut-off wave numbers and spin-up times. We perform four-day long simulations with the WRF model, daily for three different one-month periods that include a free run and several Spectral Nudging experiments with cut-off wave numbers ranging from the smallest to the largest possible (full Grid Nudging). Results show that Spectral Nudging is very effective at imposing the selected scales onto the solution, while allowing the limited area model to incorporate finer scale features. The model error diminishes rapidly as the nudging expands over broader parts of the spectrum, but this decreasing trend ceases sharply at cut-off wave numbers equivalent to a length scale of about 1000 km, and the error magnitude changes minimally thereafter. This scale corresponds to the Rossby Radius of deformation, separating synoptic from convective scales in the flow. When nudging above this value is applied, a shifting of the synoptic patterns can occur in the solution, yielding large model errors. However, when selecting smaller scales, the fine scale contribution of the model is damped, thus making 1000 km the appropriate scale threshold to nudge in order to balance both effects. Finally, we note that longer spin-up times are needed for model errors to stabilize when using Spectral Nudging than with Grid Nudging. Our results suggest that this time is between 36 and 48 hours.

Forest Loss in Protected Areas and Intact Forest Landscapes: A Global Analysis

PubMed Central

Heino, Matias; Kummu, Matti; Makkonen, Marika; Mulligan, Mark; Verburg, Peter H.; Jalava, Mika; Räsänen, Timo A.

2015-01-01

In spite of the high importance of forests, global forest loss has remained alarmingly high during the last decades. Forest loss at a global scale has been unveiled with increasingly finer spatial resolution, but the forest extent and loss in protected areas (PAs) and in large intact forest landscapes (IFLs) have not so far been systematically assessed. Moreover, the impact of protection on preserving the IFLs is not well understood. In this study we conducted a consistent assessment of the global forest loss in PAs and IFLs over the period 2000–2012. We used recently published global remote sensing based spatial forest cover change data, being a uniform and consistent dataset over space and time, together with global datasets on PAs’ and IFLs’ locations. Our analyses revealed that on a global scale 3% of the protected forest, 2.5% of the intact forest, and 1.5% of the protected intact forest were lost during the study period. These forest loss rates are relatively high compared to global total forest loss of 5% for the same time period. The variation in forest losses and in protection effect was large among geographical regions and countries. In some regions the loss in protected forests exceeded 5% (e.g. in Australia and Oceania, and North America) and the relative forest loss was higher inside protected areas than outside those areas (e.g. in Mongolia and parts of Africa, Central Asia, and Europe). At the same time, protection was found to prevent forest loss in several countries (e.g. in South America and Southeast Asia). Globally, high area-weighted forest loss rates of protected and intact forests were associated with high gross domestic product and in the case of protected forests also with high proportions of agricultural land. Our findings reinforce the need for improved understanding of the reasons for the high forest losses in PAs and IFLs and strategies to prevent further losses. PMID:26466348

A Search for Temporal Changes on Pluto and Charon

NASA Astrophysics Data System (ADS)

Hofgartner, Jason D.; Buratti, Bonnie J.; Devins, Spencer; Beyer, Ross A.; Schenk, Paul M.; Stern, S. Alan; Weaver, Harold A.; Olkin, Catherine; Cheng, Andrew F.; Ennico, Kimberly; Lauer, Tod R.; Spencer, John R.; Young, Leslie; New Horizons Science Team

2017-10-01

A search for temporal changes on Pluto and Charon was motivated by (1) the discovery of young surfaces in the Pluto system that imply ongoing or recent geologic activity, (2) the detection of active plumes on Triton during the Voyager 2 flyby, and (3) the abundant and detailed information that observing geologic processes in action provides about the processes. A thorough search for temporal changes using New Horizons images was completed. Images that covered the same region were blinked and manually inspected for any differences in appearance. The search included full-disk images such that all illuminated regions of both bodies were investigated and also higher resolution images such that parts of the encounter hemispheres were investigated at finer spatial scales. Changes of appearance between different images were observed but in all cases were attributed to variability of the imaging parameters (especially geometry) or artifacts. No differences of appearance that are strongly indicative of a temporal change were found on the surface or in the atmosphere of either Pluto or Charon. Limits on temporal changes as a function of spatial scale and temporal interval during the New Horizons encounter are determined. The longest time interval constraint is one Pluto/Charon rotation period (~6.4 Earth days). Contrast reversal and high-phase bright features that change in appearance with solar phase angle are identified. The change of appearance of these features is most likely due to the change in phase angle rather than a temporal change. Had active plumes analogous to the plumes discovered on Triton been present on the encounter hemispheres of either Pluto or Charon, they would have been detected. Several dark streak features that may be deposits from past plumes are identified. The absence of active plumes may be due to temporal variability or because the process that generates Triton’s plumes does not occur on Pluto.

A search for temporal changes on Pluto and Charon

NASA Astrophysics Data System (ADS)

Hofgartner, J. D.; Buratti, B. J.; Devins, S. L.; Beyer, R. A.; Schenk, P.; Stern, S. A.; Weaver, H. A.; Olkin, C. B.; Cheng, A.; Ennico, K.; Lauer, T. R.; McKinnon, W. B.; Spencer, J.; Young, L. A.; New Horizons Science Team

2018-03-01

A search for temporal changes on Pluto and Charon was motivated by (1) the discovery of young surfaces in the Pluto system that imply ongoing or recent geologic activity, (2) the detection of active plumes on Triton during the Voyager 2 flyby, and (3) the abundant and detailed information that observing geologic processes in action provides about the processes. A thorough search for temporal changes using New Horizons images was completed. Images that covered the same region were blinked and manually inspected for any differences in appearance. The search included full-disk images such that all illuminated regions of both bodies were investigated and higher resolution images such that parts of the encounter hemispheres were investigated at finer spatial scales. Changes of appearance between different images were observed but in all cases were attributed to variability of the imaging parameters (especially geometry) or artifacts. No differences of appearance that are strongly indicative of a temporal change were found on the surface or in the atmosphere of either Pluto or Charon. Limits on temporal changes as a function of spatial scale and temporal interval during the New Horizons encounter are determined. The longest time interval constraint is one Pluto/Charon rotation period (∼6.4 Earth days). Contrast reversal and high-phase bright features that change in appearance with solar phase angle are identified. The change of appearance of these features is most likely due to the change in phase angle rather than a temporal change. Had active plumes analogous to the plumes discovered on Triton been present on the encounter hemispheres of either Pluto or Charon, they would have been detected. The absence of active plumes may be due to temporal variability (i.e., plumes do occur but none were active on the encounter hemispheres during the epoch of the New Horizons encounter) or because plumes do not occur. Several dark streak features that may be deposits from past plumes are identified.

The Influence of Physical Factors on Kelp and Sea Urchin Distribution in Previously and Still Grazed Areas in the NE Atlantic

PubMed Central

Rinde, Eli; Christie, Hartvig; Fagerli, Camilla W.; Bekkby, Trine; Gundersen, Hege; Norderhaug, Kjell Magnus; Hjermann, Dag Ø.

2014-01-01

The spatial distribution of kelp (Laminaria hyperborea) and sea urchins (Strongylocentrotus droebachiensis) in the NE Atlantic are highly related to physical factors and to temporal changes in temperature. On a large scale, we identified borders for kelp recovery and sea urchin persistence along the north-south gradient. Sea urchin persistence was also related to the coast-ocean gradient. The southern border corresponds to summer temperatures exceeding about 10°C, a threshold value known to be critical for sea urchin recruitment and development. The outer border along the coast-ocean gradient is related to temperature, wave exposure and salinity. On a finer scale, kelp recovery occurs mainly at ridges in outer, wave exposed, saline and warm areas whereas sea urchins still dominate in inner, shallow and cold areas, particularly in areas with optimal current speed for sea urchin foraging. In contrast to other studies in Europe, we here show a positive influence of climate change to presence of a long-lived climax canopy-forming kelp. The extent of the coast-ocean gradient varies within the study area, and is especially wide in the southern part where the presence of islands and skerries increases the area of the shallow coastal zone. This creates a large area with intermediate physical conditions for the two species and a mosaic of kelp and sea urchin dominated patches. The statistical models (GAM and BRT) show high performance and indicate recovery of kelp in 45–60% of the study area. The study shows the value of combining a traditional (GAM) and a more complex (BRT) modeling approach to gain insight into complex spatial patterns of species or habitats. The results, methods and approaches are of general ecological relevance regardless of ecosystems and species, although they are particularly relevant for understanding and exploring the corresponding changes between algae and grazers in different coastal areas. PMID:24949954

The influence of physical factors on kelp and sea urchin distribution in previously and still grazed areas in the NE Atlantic.

PubMed

Rinde, Eli; Christie, Hartvig; Fagerli, Camilla W; Bekkby, Trine; Gundersen, Hege; Norderhaug, Kjell Magnus; Hjermann, Dag Ø

2014-01-01

The spatial distribution of kelp (Laminaria hyperborea) and sea urchins (Strongylocentrotus droebachiensis) in the NE Atlantic are highly related to physical factors and to temporal changes in temperature. On a large scale, we identified borders for kelp recovery and sea urchin persistence along the north-south gradient. Sea urchin persistence was also related to the coast-ocean gradient. The southern border corresponds to summer temperatures exceeding about 10°C, a threshold value known to be critical for sea urchin recruitment and development. The outer border along the coast-ocean gradient is related to temperature, wave exposure and salinity. On a finer scale, kelp recovery occurs mainly at ridges in outer, wave exposed, saline and warm areas whereas sea urchins still dominate in inner, shallow and cold areas, particularly in areas with optimal current speed for sea urchin foraging. In contrast to other studies in Europe, we here show a positive influence of climate change to presence of a long-lived climax canopy-forming kelp. The extent of the coast-ocean gradient varies within the study area, and is especially wide in the southern part where the presence of islands and skerries increases the area of the shallow coastal zone. This creates a large area with intermediate physical conditions for the two species and a mosaic of kelp and sea urchin dominated patches. The statistical models (GAM and BRT) show high performance and indicate recovery of kelp in 45-60% of the study area. The study shows the value of combining a traditional (GAM) and a more complex (BRT) modeling approach to gain insight into complex spatial patterns of species or habitats. The results, methods and approaches are of general ecological relevance regardless of ecosystems and species, although they are particularly relevant for understanding and exploring the corresponding changes between algae and grazers in different coastal areas.

Spatial patterns of simulated transpiration response to climate variability in a snow dominated mountain ecosystem

USGS Publications Warehouse

Christensen, L.; Tague, C.L.; Baron, Jill S.

2008-01-01

Transpiration is an important component of soil water storage and stream-flow and is linked with ecosystem productivity, species distribution, and ecosystem health. In mountain environments, complex topography creates heterogeneity in key controls on transpiration as well as logistical challenges for collecting representative measurements. In these settings, ecosystem models can be used to account for variation in space and time of the dominant controls on transpiration and provide estimates of transpiration patterns and their sensitivity to climate variability and change. The Regional Hydro-Ecological Simulation System (RHESSys) model was used to assess elevational differences in sensitivity of transpiration rates to the spatiotemporal variability of climate variables across the Upper Merced River watershed, Yosemite Valley, California, USA. At the basin scale, predicted annual transpiration was lowest in driest and wettest years, and greatest in moderate precipitation years (R2 = 0.32 and 0.29, based on polynomial regression of maximum snow depth and annual precipitation, respectively). At finer spatial scales, responsiveness of transpiration rates to climate differed along an elevational gradient. Low elevations (1200-1800 m) showed little interannual variation in transpiration due to topographically controlled high soil moistures along the river corridor. Annual conifer stand transpiration at intermediate elevations (1800-2150 m) responded more strongly to precipitation, resulting in a unimodal relationship between transpiration and precipitation where highest transpiration occurred during moderate precipitation levels, regardless of annual air temperatures. Higher elevations (2150-2600 m) maintained this trend, but air temperature sensitivities were greater. At these elevations, snowfall provides enough moisture for growth, and increased temperatures influenced transpiration. Transpiration at the highest elevations (2600-4000 m) showed strong sensitivity to air temperature, little sensitivity to precipitation. Model results suggest elevational differences in vegetation water use and sensitivity to climate were significant and will likely play a key role in controlling responses and vulnerability of Sierra Nevada ecosystems to climate change. Copyright ?? 2008 John Wiley & Sons, Ltd.

Mapping global surface water inundation dynamics using synergistic information from SMAP, AMSR2 and Landsat

NASA Astrophysics Data System (ADS)

Du, J.; Kimball, J. S.; Galantowicz, J. F.; Kim, S.; Chan, S.; Reichle, R. H.; Jones, L. A.; Watts, J. D.

2017-12-01

A method to monitor global land surface water (fw) inundation dynamics was developed by exploiting the enhanced fw sensitivity of L-band (1.4 GHz) passive microwave observations from the Soil Moisture Active Passive (SMAP) mission. The L-band fw (fwLBand) retrievals were derived using SMAP H-polarization brightness temperature (Tb) observations and predefined L-band reference microwave emissivities for water and land endmembers. Potential soil moisture and vegetation contributions to the microwave signal were represented from overlapping higher frequency Tb observations from AMSR2. The resulting fwLBand global record has high temporal sampling (1-3 days) and 36-km spatial resolution. The fwLBand annual averages corresponded favourably (R=0.84, p<0.001) with a 250-m resolution static global water map (MOD44W) aggregated at the same spatial scale, while capturing significant inundation variations worldwide. The monthly fwLBand averages also showed seasonal inundation changes consistent with river discharge records within six major US river basins. An uncertainty analysis indicated generally reliable fwLBand performance for major land cover areas and under low to moderate vegetation cover, but with lower accuracy for detecting water bodies covered by dense vegetation. Finer resolution (30-m) fwLBand results were obtained for three sub-regions in North America using an empirical downscaling approach and ancillary global Water Occurrence Dataset (WOD) derived from the historical Landsat record. The resulting 30-m fwLBand retrievals showed favourable classification accuracy for water (commission error 31.84%; omission error 28.08%) and land (commission error 0.82%; omission error 0.99%) and seasonal wet and dry periods when compared to independent water maps derived from Landsat-8 imagery. The new fwLBand algorithms and continuing SMAP and AMSR2 operations provide for near real-time, multi-scale monitoring of global surface water inundation dynamics, potentially benefiting hydrological monitoring, flood assessments, and global climate and carbon modeling.

Patterns of surface burrow plugging in a colony of black-tailed prairie dogs occupied by black-footed ferrets

USGS Publications Warehouse

Eads, David E.; Biggins, Dean E.

2012-01-01

Black-tailed prairie dogs (Cynomys ludovicianus) can surface-plug openings to a burrow occupied by a black-footed ferret (Mustela nigripes). At a coarse scale, surface plugs are more common in colonies of prairie dogs occupied by ferrets than in colonies without ferrets. However, little is known about spatial and temporal patterns of surface plugging in a colony occupied by ferrets. In a 452-ha colony of black-tailed prairie dogs in South Dakota, we sampled burrow openings for surface plugs and related those data to locations of ferrets observed during spotlight surveys. Of 67,574 burrow openings in the colony between June and September 2007, 3.7% were plugged. In a colony-wide grid of 80 m × 80 m cells, the occurrence of surface plugging (≥1 opening plugged) was greater in cells used by ferrets (93.3% of cells) than in cells not observably used by ferrets (70.6%). Rates of surface plugging (percentages of openings plugged) were significantly higher in cells used by ferrets (median = 3.7%) than in cells without known ferret use (median = 3.2%). Also, numbers of ferret locations in cells correlated positively with numbers of mapped surface plugs in the cells. To investigate surface plugging at finer temporal and spatial scales, we compared rates of surface plugging in 20-m-radius circle-plots centered on ferret locations and in random plots 1–4 days after observing a ferret (Jun–Oct 2007 and 2008). Rates of surface plugging were greater in ferret-plots (median = 12.0%) than in random plots (median = 0%). For prairie dogs and their associates, the implications of surface plugging could be numerous. For instance, ferrets must dig to exit or enter plugged burrows (suggesting energetic costs), and surface plugs might influence microclimates in burrows and consequently influence species that cannot excavate soil (e.g., fleas that transmit the plague bacterium Yersinia pestis).

Saturn B Ring, Finer Than Ever

NASA Image and Video Library

2017-01-30

This image shows a region in Saturn's outer B ring. NASA's Cassini spacecraft viewed this area at a level of detail twice as high as it had ever been observed before. And from this view, it is clear that there are still finer details to uncover. Researchers have yet to determine what generated the rich structure seen in this view, but they hope detailed images like this will help them unravel the mystery. In order to preserve the finest details, this image has not been processed to remove the many small bright blemishes, which are created by cosmic rays and charged particle radiation near the planet. The image was taken in visible light with the Cassini spacecraft wide-angle camera on Dec. 18, 2016. The view was obtained at a distance of approximately 32,000 miles (51,000 kilometers) from the rings, and looks toward the unilluminated side of the rings. Image scale is about a quarter-mile (360 meters) per pixel. http://photojournal.jpl.nasa.gov/catalog/PIA21058

Nanotechnology in Dental Sciences: Moving towards a Finer Way of Doing Dentistry

PubMed Central

Uskoković, Vuk; Bertassoni, Luiz Eduardo

2010-01-01

Nanotechnologies are predicted to revolutionize: (a) the control over materials properties at ultrafine scales; and (b) the sensitivity of tools and devices applied in various scientific and technological fields. In this short review, we argue that dentistry will be no exception to this trend. Here, we present a dynamic view of dental tissues, an adoption of which may lead to finer, more effective and minimally invasive reparation approaches. By doing so, we aim at providing insights into some of the breakthroughs relevant to understanding the genesis of dental tissues at the nanostructural level or generating dental materials with nanoscale critical boundaries. The lineage of the progress of dental science, including the projected path along the presumed nanotechnological direction of research and clinical application is mentioned too. We conclude by claiming that dentistry should follow the trend of probing matter at nanoscale that currently dominates both materials and biological sciences in order to improve on the research strategies and clinical techniques that have traditionally rested on mechanistic assumptions. PMID:27103959

Statistical downscaling and future scenario generation of temperatures for Pakistan Region

NASA Astrophysics Data System (ADS)

Kazmi, Dildar Hussain; Li, Jianping; Rasul, Ghulam; Tong, Jiang; Ali, Gohar; Cheema, Sohail Babar; Liu, Luliu; Gemmer, Marco; Fischer, Thomas

2015-04-01

Finer climate change information on spatial scale is required for impact studies than that presently provided by global or regional climate models. It is especially true for regions like South Asia with complex topography, coastal or island locations, and the areas of highly heterogeneous land-cover. To deal with the situation, an inexpensive method (statistical downscaling) has been adopted. Statistical DownScaling Model (SDSM) employed for downscaling of daily minimum and maximum temperature data of 44 national stations for base time (1961-1990) and then the future scenarios generated up to 2099. Observed as well as Predictors (product of National Oceanic and Atmospheric Administration) data were calibrated and tested on individual/multiple basis through linear regression. Future scenario was generated based on HadCM3 daily data for A2 and B2 story lines. The downscaled data has been tested, and it has shown a relatively strong relationship with the observed in comparison to ECHAM5 data. Generally, the southern half of the country is considered vulnerable in terms of increasing temperatures, but the results of this study projects that in future, the northern belt in particular would have a possible threat of increasing tendency in air temperature. Especially, the northern areas (hosting the third largest ice reserves after the Polar Regions), an important feeding source for Indus River, are projected to be vulnerable in terms of increasing temperatures. Consequently, not only the hydro-agricultural sector but also the environmental conditions in the area may be at risk, in future.

Identification and simulation of space-time variability of past hydrological drought events in the Limpopo River basin, southern Africa

NASA Astrophysics Data System (ADS)

Trambauer, P.; Maskey, S.; Werner, M.; Pappenberger, F.; van Beek, L. P. H.; Uhlenbrook, S.

2014-08-01

Droughts are widespread natural hazards and in many regions their frequency seems to be increasing. A finer-resolution version (0.05° × 0.05°) of the continental-scale hydrological model PCRaster Global Water Balance (PCR-GLOBWB) was set up for the Limpopo River basin, one of the most water-stressed basins on the African continent. An irrigation module was included to account for large irrigated areas of the basin. The finer resolution model was used to analyse hydrological droughts in the Limpopo River basin in the period 1979-2010 with a view to identifying severe droughts that have occurred in the basin. Evaporation, soil moisture, groundwater storage and runoff estimates from the model were derived at a spatial resolution of 0.05° (approximately 5 km) on a daily timescale for the entire basin. PCR-GLOBWB was forced with daily precipitation and temperature obtained from the ERA-Interim global atmospheric reanalysis product from the European Centre for Medium-Range Weather Forecasts. Two agricultural drought indicators were computed: the Evapotranspiration Deficit Index (ETDI) and the Root Stress Anomaly Index (RSAI). Hydrological drought was characterised using the Standardized Runoff Index (SRI) and the Groundwater Resource Index (GRI), which make use of the streamflow and groundwater storage resulting from the model. Other more widely used meteorological drought indicators, such as the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evaporation Index (SPEI), were also computed for different aggregation periods. Results show that a carefully set-up, process-based model that makes use of the best available input data can identify hydrological droughts even if the model is largely uncalibrated. The indicators considered are able to represent the most severe droughts in the basin and to some extent identify the spatial variability of droughts. Moreover, results show the importance of computing indicators that can be related to hydrological droughts, and how these add value to the identification of hydrological droughts and floods and the temporal evolution of events that would otherwise not have been apparent when considering only meteorological indicators. In some cases, meteorological indicators alone fail to capture the severity of the hydrological drought. Therefore, a combination of some of these indicators (e.g. SPEI-3, SRI-6 and SPI-12 computed together) is found to be a useful measure for identifying agricultural to long-term hydrological droughts in the Limpopo River basin. Additionally, it was possible to undertake a characterisation of the drought severity in the basin, indicated by its time of occurrence, duration and intensity.

Multiscale properties of weighted total variation flow with applications to denoising and registration.

PubMed

Athavale, Prashant; Xu, Robert; Radau, Perry; Nachman, Adrian; Wright, Graham A

2015-07-01

Images consist of structures of varying scales: large scale structures such as flat regions, and small scale structures such as noise, textures, and rapidly oscillatory patterns. In the hierarchical (BV, L(2)) image decomposition, Tadmor, et al. (2004) start with extracting coarse scale structures from a given image, and successively extract finer structures from the residuals in each step of the iterative decomposition. We propose to begin instead by extracting the finest structures from the given image and then proceed to extract increasingly coarser structures. In most images, noise could be considered as a fine scale structure. Thus, starting the image decomposition with finer scales, rather than large scales, leads to fast denoising. We note that our approach turns out to be equivalent to the nonstationary regularization in Scherzer and Weickert (2000). The continuous limit of this procedure leads to a time-scaled version of total variation flow. Motivated by specific clinical applications, we introduce an image depending weight in the regularization functional, and study the corresponding weighted TV flow. We show that the edge-preserving property of the multiscale representation of an input image obtained with the weighted TV flow can be enhanced and localized by appropriate choice of the weight. We use this in developing an efficient and edge-preserving denoising algorithm with control on speed and localization properties. We examine analytical properties of the weighted TV flow that give precise information about the denoising speed and the rate of change of energy of the images. An additional contribution of the paper is to use the images obtained at different scales for robust multiscale registration. We show that the inherently multiscale nature of the weighted TV flow improved performance for registration of noisy cardiac MRI images, compared to other methods such as bilateral or Gaussian filtering. A clinical application of the multiscale registration algorithm is also demonstrated for aligning viability assessment magnetic resonance (MR) images from 8 patients with previous myocardial infarctions. Copyright © 2015. Published by Elsevier B.V.

Mechanisms of Cottonwood Establishment in Gravel-Bed Rivers, across Scales from the Bar to the Reach

NASA Astrophysics Data System (ADS)

Meier, C. I.

2017-12-01

Riparian cottonwoods are pioneer trees adapted to colonizing fluvial corridors, with strong effects on ecosystem structure and function. As their populations are being affected by flow alterations and invasive species, their recruitment mechanisms need to be understood, to support scientifically-based restoration efforts. I propose new concepts for cottonwood establishment in gravelly streams, from the local to the reach scale. These notions complement the currently-accepted ideas, which apply only to the landscape scale, and whose basic assumptions (existence of an alluvial water table, which is planar, almost horizontal, and linked to the river stage, with a parallel, spatially-uniform capillary fringe) seem to be based on a physical template that is only valid in the case of sand-bed streams. At the local, within-the-bar scale, two concepts drive establishment success. First, a finer matrix material helps retain more capillary water after the yearly snowmelt flood or a precipitation event. Second, the coarse surface layer of clean gravel and cobble acts as rock mulch, strongly decreasing evaporative losses. At the reach scale, we find that the commonly reported arcuate bands of cottonwoods do not depend on groundwater, but are caused by water dispersal (hydrochory). Wind-dispersed seeds fall into the river, are entrained into the drift, and start germinating as they travel under water. Some of the seeds and germinants find their way into the shallow, high relative roughness flow along the cobble shoreline. They are able to deposit in this environment, where they start growing, also under water. As waters recede, during the period of seed availability in the drift, the river seeds its banks and bars. Thus, the boundaries of observed bands and patches with successful seedling recruitment correspond to the location of flow profiles at different dates during the flood recession.

Multiscale skeletal representation of images via Voronoi diagrams

NASA Astrophysics Data System (ADS)

Marston, R. E.; Shih, Jian C.

1995-08-01

Polygonal approximations to skeletal or stroke-based representations of 2D objects may consume less storage and be sufficient to describe their shape for many applications. Multi- scale descriptions of object outlines are well established but corresponding methods for skeletal descriptions have been slower to develop. In this paper we offer a method of generating scale-based skeletal representation via the Voronoi diagram. The method has the advantages of less time complexity, a closer relationship between the skeletons at each scale and better control over simplification of the skeleton at lower scales. This is because the algorithm starts by generating the skeleton at the coarsest scale first, then it produces each finer scale, in an iterative manner, directly from the level below. The skeletal approximations produced by the algorithm also benefit from a strong relationship with the object outline, due to the structure of the Voronoi diagram.

Neural mechanisms of coarse-to-fine discrimination in the visual cortex.

PubMed

Purushothaman, Gopathy; Chen, Xin; Yampolsky, Dmitry; Casagrande, Vivien A

2014-12-01

Vision is a dynamic process that refines the spatial scale of analysis over time, as evidenced by a progressive improvement in the ability to detect and discriminate finer details. To understand coarse-to-fine discrimination, we studied the dynamics of spatial frequency (SF) response using reverse correlation in the primary visual cortex (V1) of the primate. In a majority of V1 cells studied, preferred SF either increased monotonically with time (group 1) or changed nonmonotonically, with an initial increase followed by a decrease (group 2). Monotonic shift in preferred SF occurred with or without an early suppression at low SFs. Late suppression at high SFs always accompanied nonmonotonic SF dynamics. Bayesian analysis showed that SF discrimination performance and best discriminable SF frequencies changed with time in different ways in the two groups of neurons. In group 1 neurons, SF discrimination performance peaked on both left and right flanks of the SF tuning curve at about the same time. In group 2 neurons, peak discrimination occurred on the right flank (high SFs) later than on the left flank (low SFs). Group 2 neurons were also better discriminators of high SFs. We examined the relationship between the time at which SF discrimination performance peaked on either flank of the SF tuning curve and the corresponding best discriminable SFs in both neuronal groups. This analysis showed that the population best discriminable SF increased with time in V1. These results suggest neural mechanisms for coarse-to-fine discrimination behavior and that this process originates in V1 or earlier. Copyright © 2014 the American Physiological Society.

Evaluating DEM conditioning techniques, elevation source data, and grid resolution for field-scale hydrological parameter extraction

NASA Astrophysics Data System (ADS)

Woodrow, Kathryn; Lindsay, John B.; Berg, Aaron A.

2016-09-01

Although digital elevation models (DEMs) prove useful for a number of hydrological applications, they are often the end result of numerous processing steps that each contains uncertainty. These uncertainties have the potential to greatly influence DEM quality and to further propagate to DEM-derived attributes including derived surface and near-surface drainage patterns. This research examines the impacts of DEM grid resolution, elevation source data, and conditioning techniques on the spatial and statistical distribution of field-scale hydrological attributes for a 12,000 ha watershed of an agricultural area within southwestern Ontario, Canada. Three conditioning techniques, including depression filling (DF), depression breaching (DB), and stream burning (SB), were examined. The catchments draining to each boundary of 7933 agricultural fields were delineated using the surface drainage patterns modeled from LiDAR data, interpolated to a 1 m, 5 m, and 10 m resolution DEMs, and from a 10 m resolution photogrammetric DEM. The results showed that variation in DEM grid resolution resulted in significant differences in the spatial and statistical distributions of contributing areas and the distributions of downslope flowpath length. Degrading the grid resolution of the LiDAR data from 1 m to 10 m resulted in a disagreement in mapped contributing areas of between 29.4% and 37.3% of the study area, depending on the DEM conditioning technique. The disagreements among the field-scale contributing areas mapped from the 10 m LiDAR DEM and photogrammetric DEM were large, with nearly half of the study area draining to alternate field boundaries. Differences in derived contributing areas and flowpaths among various conditioning techniques increased substantially at finer grid resolutions, with the largest disagreement among mapped contributing areas occurring between the 1 m resolution DB DEM and the SB DEM (37% disagreement) and the DB-DF comparison (36.5% disagreement in mapped areas). These results demonstrate that the decision to use one DEM conditioning technique over another, and the constraints of available DEM data resolution and source, can greatly impact the modeled surface drainage patterns at the scale of individual fields. This work has significance for applications that attempt to optimize best-management practices (BMPs) for reducing soil erosion and runoff contamination within agricultural watersheds.

Distribution of melt along the East Pacific Rise from 9°30' to 10°N from an amplitude variation with angle of incidence (AVA) technique

NASA Astrophysics Data System (ADS)

Marjanović, Milena; Carton, Hélène; Carbotte, Suzanne M.; Nedimović, Mladen R.; Mutter, John C.; Canales, J. Pablo

2015-10-01

We examine along-axis variations in melt content of the axial magma lens (AML) beneath the fast-spreading East Pacific Rise (EPR) using an amplitude variation with angle of incidence (AVA) crossplotting method applied to multichannel seismic data acquired in 2008. The AVA crossplotting method, which has been developed for and, so far, applied for hydrocarbon prospection in sediments, is for the first time applied to a hardrock environment. We focus our analysis on 2-D data collected along the EPR axis from 9°29.8'N to 9°58.4'N, a region which encompasses the sites of two well-documented submarine volcanic eruptions (1991-1992 and 2005-2006). AVA crossplotting is performed for a ˜53 km length of the EPR spanning nine individual AML segments (ranging in length from ˜3.2 to 8.5 km) previously identified from the geometry of the AML and disruptions in continuity. Our detailed analyses conducted at 62.5 m interval show that within most of the analysed segments melt content varies at spatial scales much smaller (a few hundred of metres) than the length of the fine-scale AML segments, suggesting high heterogeneity in melt concentration. At the time of our survey, about 2 yr after the eruption, our results indicate that the three AML segments that directly underlie the 2005-2006 lava flow are on average mostly molten. However, detailed analysis at finer-scale intervals for these three segments reveals AML pockets (from >62.5 to 812.5 m long) with a low melt fraction. The longest such mushy section is centred beneath the main eruption site at ˜9°50.4'N, possibly reflecting a region of primary melt drainage during the 2005-2006 event. The complex geometry of fluid flow pathways within the crust above the AML and the different response times of fluid flow and venting to eruption and magma reservoir replenishment may contribute to the poor spatial correlation between incidence of hydrothermal vents and presence of highly molten AML. The presented results are an important step forward in our ability to resolve small-scale characteristics of the AML and recommend the AVA crossplotting as a tool for examining mid-ocean ridge magma-systems elsewhere.

Geologic exploration: The contribution of LANDSAT-4 thematic mapper data

NASA Technical Reports Server (NTRS)

Everett, J. R.; Dykstra, J. D.; Sheffield, C. A.

1983-01-01

The major advantages of the TM data over that of MSS systems are increased spatial resolution and a greater number of narrow, strategically placed spectral bands. The 30 meter pixel size permits finer definition of ground features and improves reliability of the photointerpretation of geologic structure. The value of the spatial data increases relative to the value of the spectral data as soil and vegetation cover increase. In arid areas with good exposure, it is possible with careful digital processing and some inventive color compositing to produce enough spectral differentiation of rock types and thereby produce facsimiles of standard geologic maps with a minimum of field work or reference to existing maps. Hue-saturation value images are compared with geological maps of Death Valley, California, the Big Horn/Wind River Basin of Wyoming, the area around Cement, Oklahoma, and Detroit. False color composites of the Ontario region are also examined.

Population at risk: using areal interpolation and Twitter messages to create population models for burglaries and robberies

PubMed Central

2018-01-01

ABSTRACT Population at risk of crime varies due to the characteristics of a population as well as the crime generator and attractor places where crime is located. This establishes different crime opportunities for different crimes. However, there are very few efforts of modeling structures that derive spatiotemporal population models to allow accurate assessment of population exposure to crime. This study develops population models to depict the spatial distribution of people who have a heightened crime risk for burglaries and robberies. The data used in the study include: Census data as source data for the existing population, Twitter geo-located data, and locations of schools as ancillary data to redistribute the source data more accurately in the space, and finally gridded population and crime data to evaluate the derived population models. To create the models, a density-weighted areal interpolation technique was used that disaggregates the source data in smaller spatial units considering the spatial distribution of the ancillary data. The models were evaluated with validation data that assess the interpolation error and spatial statistics that examine their relationship with the crime types. Our approach derived population models of a finer resolution that can assist in more precise spatial crime analyses and also provide accurate information about crime rates to the public. PMID:29887766

Microparticles controllable accumulation, arrangement, and spatial shaping performed by tapered-fiber-based laser-induced convection flow.

PubMed

Zhang, Yu; Lei, Jiaojie; Zhang, Yaxun; Liu, Zhihai; Zhang, Jianzhong; Yang, Xinghua; Yang, Jun; Yuan, Libo

2017-10-30

The ability to arrange cells and/or microparticles into the desired pattern is critical in biological, chemical, and metamaterial studies and other applications. Researchers have developed a variety of patterning techniques, which either have a limited capacity to simultaneously trap massive particles or lack the spatial resolution necessary to manipulate individual particle. Several approaches have been proposed that combine both high spatial selectivity and high throughput simultaneously. However, those methods are complex and difficult to fabricate. In this article, we propose and demonstrate a simple method that combines the laser-induced convection flow and fiber-based optical trapping methods to perform both regular and special spatial shaping arrangement. Essentially, we combine a light field with a large optical intensity gradient distribution and a thermal field with a large temperature gradient distribution to perform the microparticles shaping arrangement. The tapered-fiber-based laser-induced convection flow provides not only the batch manipulation of massive particles, but also the finer manipulation of special one or several particles, which break out the limit of single-fiber-based massive/individual particles photothermal manipulation. The combination technique allows for microparticles quick accumulation, single-layer and multilayer arrangement; special spatial shaping arrangement/adjustment, and microparticles sorting.

Finescale turbulence and seabed scouring around pneumatophores in a wave-exposed mangrove forest

NASA Astrophysics Data System (ADS)

Mullarney, J. C.; Norris, B. K.; Henderson, S. M.; Bryan, K. R.

2015-12-01

Coastal mangroves provide a barrier between the coast and lower energy intertidal environments. The presence of mangrove roots (pneumatophores) alters local hydrodynamics by slowing currents, dissipating waves, enhancing within-canopy turbulence, and introducing significant spatial variability to the flow, particularly on the stem scale. To date, limited measurements exist within pneumatophore regions owing to the difficulties of measuring on sufficiently small scales. Hence, little is known about the turbulence controlling sediment transport within these regions. We report unique field observations near the seaward edge of a mangrove forest in the Mekong Delta, Vietnam. This forest is exposed to moderate wave energy (maximum heights of around 1 m), with waves observed to propagate and break up to 100 m inside the forest. Our measurements focus on a rapidly prograding area with a relatively sandy substrate and a gentle topographic slope. We resolved millimeter-scale turbulent flows within and above the pneumatophore canopy. Precise measurements of vegetation densities as a function of height were obtained using photogrammetry techniques. The dissipation rate of turbulent kinetic energy was enhanced at the canopy edge (ɛ ~ 10-4 W/kg), and decreased with distance into the forest (ɛ ~ 10-5 W/kg), although rates remained elevated above values measured on the tidal flat immediately offshore of the mangroves (ɛ ~ 10-6 W/kg). The dependence of turbulence on vegetation characteristics and on the stage of the tidal cycle is explored. The hydrodynamic measurements are then linked with changes in bathymetric features noted after a large wave event. Finer mud sediments were deposited outside the forest on the intertidal mudflat, whereas sandy sediments in the fringe region were significant scoured around regions of dense pneumatophores, and sediment mounds developed in the gaps between pneumatophores.

Mapping Forest Structure From Tree Clump And Opening Patterns Across Landscapes With Airborne Lidar To Study Response To Disturbances And Map Habitat

NASA Astrophysics Data System (ADS)

Kane, V. R.; McGaughey, R. J.; Asner, G. P.; Kane, J. T.; Churchill, D.; Vaughn, N.

2016-12-01

Most natural forests are structured as mosaics of tree clumps and openings. These mosaics reflect both the underlying patterns of the biophysical environment and the finer scale patterns of disturbance and regrowth. We have developed methods to quantify and map patterns of tree clumps and openings at scales from within stands to landscapes using airborne LiDAR. While many studies have used LiDAR data to identify individual trees, we also identify clumps as adjacent trees with similar heights within a stand that likely established at a similar time following a disturbance. We characterize openings by both size class and shape complexity. Spatial statistics are used to identify patterns of tree clumps and openings at the local (0.81 ha) scale, and these patterns are then mapped across entire landscapes. We use LiDAR data acquired over Sequoia National Park, California, USA, to show how forest structure varies with patterns of productivity driven by the biophysical environment. We then show how clump and opening patterns vary with different fire histories and how recent drought mortality correlates with different tree clump and opening structural mosaics. We also demonstrate that nesting sites for the California spotted owl, a species of concern, are associated with clumps of large (>32 and especially >48 m) trees but that the surrounding foraging areas consist of a heterogeneous pattern of forest structure. These methods are especially useful for studying clumps of large trees, which dominate above ground forest biomass, and the effects of disturbance on the abundance and pattern of large trees as key forest structures.

An introductory analysis of digital infrared thermal imaging guided oral cancer detection using multiresolution rotation invariant texture features

NASA Astrophysics Data System (ADS)

Chakraborty, M.; Das Gupta, R.; Mukhopadhyay, S.; Anjum, N.; Patsa, S.; Ray, J. G.

2017-03-01

This manuscript presents an analytical treatment on the feasibility of multi-scale Gabor filter bank response for non-invasive oral cancer pre-screening and detection in the long infrared spectrum. Incapability of present healthcare technology to detect oral cancer in budding stage manifests in high mortality rate. The paper contributes a step towards automation in non-invasive computer-aided oral cancer detection using an amalgamation of image processing and machine intelligence paradigms. Previous works have shown the discriminative difference of facial temperature distribution between a normal subject and a patient. The proposed work, for the first time, exploits this difference further by representing the facial Region of Interest(ROI) using multiscale rotation invariant Gabor filter bank responses followed by classification using Radial Basis Function(RBF) kernelized Support Vector Machine(SVM). The proposed study reveals an initial increase in classification accuracy with incrementing image scales followed by degradation of performance; an indication that addition of more and more finer scales tend to embed noisy information instead of discriminative texture patterns. Moreover, the performance is consistently better for filter responses from profile faces compared to frontal faces.This is primarily attributed to the ineptness of Gabor kernels to analyze low spatial frequency components over a small facial surface area. On our dataset comprising of 81 malignant, 59 pre-cancerous, and 63 normal subjects, we achieve state-of-the-art accuracy of 85.16% for normal v/s precancerous and 84.72% for normal v/s malignant classification. This sets a benchmark for further investigation of multiscale feature extraction paradigms in IR spectrum for oral cancer detection.

Color-tuned neurons are spatially clustered according to color preference within alert macaque posterior inferior temporal cortex

PubMed Central

Conway, Bevil R.; Tsao, Doris Y.

2009-01-01

Large islands of extrastriate cortex that are enriched for color-tuned neurons have recently been described in alert macaque using a combination of functional magnetic resonance imaging (fMRI) and single-unit recording. These millimeter-sized islands, dubbed “globs,” are scattered throughout the posterior inferior temporal cortex (PIT), a swath of brain anterior to area V3, including areas V4, PITd, and posterior TEO. We investigated the micro-organization of neurons within the globs. We used fMRI to identify the globs and then used MRI-guided microelectrodes to test the color properties of single glob cells. We used color stimuli that sample the CIELUV perceptual color space at regular intervals to test the color tuning of single units, and make two observations. First, color-tuned neurons of various color preferences were found within single globs. Second, adjacent glob cells tended to have the same color tuning, demonstrating that glob cells are clustered by color preference and suggesting that they are arranged in color columns. Neurons separated by 50 μm, measured parallel to the cortical sheet, had more similar color tuning than neurons separated by 100 μm, suggesting that the scale of the color columns is <100 μm. These results show that color-tuned neurons in PIT are organized by color preference on a finer scale than the scale of single globs. Moreover, the color preferences of neurons recorded sequentially along a given electrode penetration shifted gradually in many penetrations, suggesting that the color columns are arranged according to a chromotopic map reflecting perceptual color space. PMID:19805195

Paleo-environmental Setting of the Murray Formation of Aeolis Mons, Gale Crater, Mars, as Explored by the Curiosity Rover

NASA Astrophysics Data System (ADS)

Lewis, K. W.; Fedo, C.; Grotzinger, J. P.; Gupta, S.; Stein, N.; Rivera-Hernandez, F.; Watkins, J. A.; Banham, S.; Edgett, K. S.; Minitti, M. E.; Schieber, J.; Edgar, L. A.; Siebach, K. L.; Stack, K.; Newsom, H. E.; House, C. H.; Sumner, D. Y.; Vasavada, A. R.

2017-12-01

Since landing, the Mars Science Laboratory Curiosity rover climbed 300 meters in elevation from the floor of north Gale crater up the lower northwest flank of Aeolis Mons ("Mount Sharp"). Nearly 200 meters of this ascent was accomplished in the 1.5 years alone, as the rover was driven up-section through the sedimentary rocks of the informally designated "Murray" formation. This unit comprises a large fraction of the lower strata of Mt. Sharp along the rover traverse. Our exploration of the Murray formation reveals a diverse suite of fine-grained facies. Grain sizes range from finer grains than can be resolved by the MAHLI imager (particles <62.5 microns) up to medium sand; the finer fraction comprises the bulk of the stratigraphy. Layering occurs at a range of scales; the majority is expressed as parallel laminae of mm-scale. Some sandy stratigraphic intervals exhibit cross-stratification at ripple (cm) and dune (m and larger) scales; the inferred bedforms are consistent with a range of subaqueous and aeolian depositional settings. Diagenetic features include locally variable occurrences of concretions and near-ubiquitous Ca-sulfate veins; these attest to extended interaction of the sediment with aqueous fluids in the subsurface. As a whole, the sedimentary facies of the Murray formation have been interpreted to record a predominately lacustrine paleo-environment, with likely subaerial aeolian and fluvial intervals. Further exploration, including the campaign at the hematite-bearing Vera Rubin Ridge, continues to reveal the complex and long-lived depositional history of the Gale crater basin.

Decadal Variability of Temperature and Salinity in the Northwest Atlantic Ocean

NASA Astrophysics Data System (ADS)

Mishonov, A. V.; Seidov, D.; Reagan, J. R.; Boyer, T.; Parsons, A. R.

2017-12-01

There are only a few regions in the World Ocean where the density of observations collected over the past 60 years is sufficient for reliable data mapping with spatial resolutions finer than one-degree. The Northwest Atlantic basin is one such regions where a spatial resolution of gridded temperature and salinity fields, comparable to those generated by eddy-resolving numerical models of ocean circulation, has recently becomes available. Using the new high-resolution Northwest Atlantic Regional Climatology, built on quarter-degree and one-tenth-degree resolution fields, we analyzed decadal variability and trends of temperature and salinity over 60 years in the Northwest Atlantic, and two 30-year ocean climates of 1955-1984 and 1985-2012 to evaluate the oceanic climate shift in this region. The 30-year climate shift is demonstrated using an innovative 3-D visualization of temperature and salinity. Spatial and temporal variability of heat accumulation found in previous research of the entire North Atlantic Ocean persists in the Northwest Atlantic Ocean. Salinity changes between two 30-year climates were also computed and are discussed.

Evidence of differentiated near-surface plutons on Vesta in integrated Dawn color images and spectral datasets

NASA Astrophysics Data System (ADS)

Cheek, L.; Sunshine, J.

2014-07-01

Introduction: Recent analyses of Visible and Infrared Mapping Spectrometer (VIR) data from the Dawn mission [1] revealed isolated areas on the asteroid (4) Vesta that contain enhanced abundances of olivine [2,3]. However, this olivine component is only subtly expressed in the VIR data, superimposed on spectrally dominant pyroxene absorptions. The highly ''mixed'' nature of these spectra is likely due, in part, to the relatively coarse spatial resolution of VIR (˜190 m/pixel in HAMO-2) [4], which averages the spectral characteristics of potentially heterogeneous meter-scale outcrops. The capability to resolve the olivine-enhanced regions at a finer scale may reveal a spectrally-dominant olivine component that would facilitate characterization of 1) the distribution and context of the olivine-enhanced exposures, and 2) the spectral properties of the olivine component, providing clues to mineral composition. In order to access finer spatial scales while preserving the detailed mineralogic information offered by the hyperspectral VIR instrument, we use an approach developed for the Moon by [5] that is based on an inversion of the Spectral Mixture Analysis (SMA) framework [6]. Here, we project the VIR data onto co-located, multispectral Framing Camera (FC) data with a spatial resolution of ˜50 m/pixel (HAMO-2) [7]. The analysis was carried out using georeferenced VIR and FC calibrated mosaics for the olivine-enhanced region containing Bellicia and Arruntia craters in the northern hemisphere of Vesta. The approach produces a set of four calculated VIR end members, as well as a projected image cube that contains a calculated VIR spectrum for each FC pixel in the scene. An important advantage of this approach is that it can be applied to co-located multi- and hyperspectral datasets on other planetary bodies. Initial Results: We find that VIR observations for diverse areas across the scene are well described by the following hyperspectral end members: two spectra resembling pyroxenes, one of which has a subtle ˜600-nm absorption; one spectrum that resembles a pyroxene but displays a somewhat distorted 1000-nm band shape that may be indicative of residual calibration issues in the VIR data; and one spectrum strongly resembling a pure olivine. The olivine-like calculated end member spectrum provides important validation of the interpretation that the spectral character of VIR data in the Bellicia/Arruntia region is due to the spectral influence of an olivine component. In addition, the ˜600-nm feature in one of the calculated pyroxene end members is an unexpected and compelling result. Coordinated petrologic and spectral analyses of unbrecciated eucrites by [8] indicate that a similar ˜600-nm absorption is observable in relatively primitive, Cr-rich pyroxenes. This observation suggested that the presence of a ˜600-nm absorption in remote-sensing data for Dawn may be a straightforward indicator of the presence of primitive materials - a prediction that is borne out in these results. Evaluation of the hyperspectral projected cube reveals that discrete regions of spectrally pure olivine are indeed present throughout the walls of Bellicia and, to a lesser extent, Arruntia. Spectra of the Arruntia ejecta in the projected cube contain less of an olivine component than the walls, but important spatial variations are apparent. In particular, the proximal Arruntia ejecta (< 1 crater radius) appear to contain very little olivine, whereas spectra of the more distal ejecta (> 1 crater radius) do display an apparent olivine component. This observation strongly suggests that the Arruntia impact has revealed a compositionally stratified subsurface, with an enhanced olivine component occurring at slightly deeper levels. Projected spectra displaying pyroxene bands with a superimposed ˜600-nm feature occur primarily on crater walls, often in association with olivine- dominated spectra. The co-occurrence of Cr-rich pyroxene and olivine in this unique region of Vesta suggests that a primitive lithology is locally exposed at the surface. We interpret these observations as indicating the presence of one or more differentiated plutons in the Bellicia/Arruntia region.

A Multiscale Surface Water Temperature Data Acquisition Platform: Tests on Lake Geneva, Switzerland

NASA Astrophysics Data System (ADS)

Barry, D. A.; Irani Rahaghi, A.; Lemmin, U.; Riffler, M.; Wunderle, S.

2015-12-01

An improved understanding of surface transport processes is necessary to predict sediment, pollutant and phytoplankton patterns in large lakes. Lake surface water temperature (LSWT), which varies in space and time, reflects meteorological and climatological forcing more than any other physical lake parameter. There are different data sources for LSWT mapping, including remote sensing and in situ measurements. Satellite data can be suitable for detecting large-scale thermal patterns, but not meso- or small scale processes. Lake surface thermography, investigated in this study, has finer resolution compared to satellite images. Thermography at the meso-scale provides the ability to ground-truth satellite imagery over scales of one to several satellite image pixels. On the other hand, thermography data can be used as a control in schemes to upscale local measurements that account for surface energy fluxes and the vertical energy budget. Independently, since such data can be collected at high frequency, they can be also useful in capturing changes in the surface signatures of meso-scale eddies and thus to quantify mixing processes. In the present study, we report results from a Balloon Launched Imaging and Monitoring Platform (BLIMP), which was developed in order to measure the LSWT at meso-scale. The BLIMP consists of a small balloon that is tethered to a boat and equipped with thermal and RGB cameras, as well as other instrumentation for location and communication. Several deployments were carried out on Lake Geneva. In a typical deployment, the BLIMP is towed by a boat, and collects high frequency data from different heights (i.e., spatial resolutions) and locations. Simultaneous ground-truthing of the BLIMP data is achieved using an autonomous craft that collects a variety of data, including in situ surface/near surface temperatures, radiation and meteorological data in the area covered by the BLIMP images. With suitable scaling, our results show good consistency between in situ, BLIMP and concurrent satellite data. In addition, the BLIMP thermography reveals (hydrodynamically-driven) structures in the LSWT - an obvious example being mixing of river discharges.

Accelerated thermal and mechanical testing of CSP assemblies

NASA Technical Reports Server (NTRS)

Ghaffarian, R.

2000-01-01

Chip Scale Packages (CSP) are now widely used for many electronic applications including portable and telecommunication products. A test vehicle (TV-1) with eleven package types and pitches was built and tested by the JPL MicrotypeBGA Consortium during 1997 to 1999. Lessons learned by the team were published as a guidelines document for industry use. The finer pitch CSP packages which recently became available were indluded in the next test vehicle of the JPL CSP Consortium.

Frequency Resolved Nanoscale Chemical Imaging of 4,4'-Dimercaptostilbene on Silver

DOE PAGES

El-Khoury, Patrick Z.; Ueltschi, Tyler W.; Mifflin, Amanda L.; ...

2014-11-26

Non-resonant tip-enhanced Raman images of 4,4'-dimercaptostilbene on silver reveal that different vibrational resonances of the reporter are selectively enhanced at different sites on the metal substrate. Sequentially recorded images track molecular diffusion within the diffraction-limited laser spot which illuminates the substrate. In effect, the recorded time resolved (Δt = 10 s) pixelated images (25 nm x 8 cm-1) broadcast molecule-local field interactions which take place on much finer scales.

Spectral Mixture Analysis to map burned areas in Brazil's deforestation arc from 1992 to 2011

NASA Astrophysics Data System (ADS)

Antunes Daldegan, G.; Ribeiro, F.; Roberts, D. A.

2017-12-01

The two most extensive biomes in South America, the Amazon and the Cerrado, are subject to several fire events every dry season. Both are known for their ecological and environmental importance. However, due to the intensive human occupation over the last four decades, they have been facing high deforestation rates. The Cerrado biome is adapted to fire and is considered a fire-dependent landscape. In contrast, the Amazon as a tropical moist broadleaf forest does not display similar characteristics and is classified as a fire-sensitive landscape. Nonetheless, studies have shown that forest areas that have already been burned become more prone to experience recurrent burns. Remote sensing has been extensively used by a large number of researchers studying fire occurrence at a global scale, as well as in both landscapes aforementioned. Digital image processing aiming to map fire activity has been applied to a number of imagery from sensors of various spatial, temporal, and spectral resolutions. More specifically, several studies have used Landsat data to map fire scars in the Amazon forest and in the Cerrado. An advantage of using Landsat data is the potential to map fire scars at a finer spatial resolution, when compared to products derived from imagery of sensors featuring better temporal resolution but coarser spatial resolution, such as MODIS (Moderate Resolution Imaging Spectrometer) and GOES (Geostationary Operational Environmental Satellite). This study aimed to map burned areas present in the Amazon-Cerrado transition zone by applying Spectral Mixture Analysis on Landsat imagery for a period of 20 years (1992-2011). The study area is a subset of this ecotone, centered at the State of Mato Grosso. By taking advantage of the Landsat 5TM and Landsat 7ETM+ imagery collections available in Google Earth Engine platform and applying Spectral Mixture Analysis (SMA) techniques over them permitted to model fire scar fractions and delimitate burned areas. Overlaying yearly burned areas allowed to identify areas with high fire recurrence.

A global map of mangrove forest soil carbon at 30 m spatial resolution

NASA Astrophysics Data System (ADS)

Sanderman, Jonathan; Hengl, Tomislav; Fiske, Greg; Solvik, Kylen; Adame, Maria Fernanda; Benson, Lisa; Bukoski, Jacob J.; Carnell, Paul; Cifuentes-Jara, Miguel; Donato, Daniel; Duncan, Clare; Eid, Ebrahem M.; Ermgassen, Philine zu; Ewers Lewis, Carolyn J.; Macreadie, Peter I.; Glass, Leah; Gress, Selena; Jardine, Sunny L.; Jones, Trevor G.; Ndemem Nsombo, Eugéne; Mizanur Rahman, Md; Sanders, Christian J.; Spalding, Mark; Landis, Emily

2018-05-01

With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30 m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250 m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kg m‑3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha‑1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies.

Diversity and distribution of deep-sea shrimps in the Ross Sea region of Antarctica.

PubMed

Basher, Zeenatul; Bowden, David A; Costello, Mark J

2014-01-01

Although decapod crustaceans are widespread in the oceans, only Natantia (shrimps) are common in the Antarctic. Because remoteness, depth and ice cover restrict sampling in the South Ocean, species distribution modelling is a useful tool for evaluating distributions. We used physical specimen and towed camera data to describe the diversity and distribution of shrimps in the Ross Sea region of Antarctica. Eight shrimp species were recorded: Chorismus antarcticus; Notocrangon antarcticus; Nematocarcinus lanceopes; Dendrobranchiata; Pasiphaea scotiae; Pasiphaea cf. ledoyeri; Petalidium sp., and a new species of Lebbeus. For the two most common species, N. antarcticus and N. lanceopes, we used maximum entropy modelling, based on records of 60 specimens and over 1130 observations across 23 sites in depths from 269 m to 3433 m, to predict distributions in relation to environmental variables. Two independent sets of environmental data layers at 0.05° and 0.5° resolution respectively, showed how spatial resolution affected the model. Chorismus antarcticus and N. antarcticus were found only on the continental shelf and upper slopes, while N. lanceopes, Lebbeus n. sp., Dendrobranchiata, Petalidium sp., Pasiphaea cf. ledoyeri, and Pasiphaea scotiae were found on the slopes, seamounts and abyssal plain. The environmental variables that contributed most to models for N. antarcticus were depth, chlorophyll-a concentration, temperature, and salinity, and for N. lanceopes were depth, ice concentration, seabed slope/rugosity, and temperature. The relative ranking, but not the composition of these variables changed in models using different spatial resolutions, and the predicted extent of suitable habitat was smaller in models using the finer-scale environmental layers. Our modelling indicated that shrimps were widespread throughout the Ross Sea region and were thus likely to play important functional role in the ecosystem, and that the spatial resolution of data needs to be considered both in the use of species distribution models.

Diversity and Distribution of Deep-Sea Shrimps in the Ross Sea Region of Antarctica

PubMed Central

Basher, Zeenatul; Bowden, David A.; Costello, Mark J.

2014-01-01

Although decapod crustaceans are widespread in the oceans, only Natantia (shrimps) are common in the Antarctic. Because remoteness, depth and ice cover restrict sampling in the South Ocean, species distribution modelling is a useful tool for evaluating distributions. We used physical specimen and towed camera data to describe the diversity and distribution of shrimps in the Ross Sea region of Antarctica. Eight shrimp species were recorded: Chorismus antarcticus; Notocrangon antarcticus; Nematocarcinus lanceopes; Dendrobranchiata; Pasiphaea scotiae; Pasiphaea cf. ledoyeri; Petalidium sp., and a new species of Lebbeus. For the two most common species, N. antarcticus and N. lanceopes, we used maximum entropy modelling, based on records of 60 specimens and over 1130 observations across 23 sites in depths from 269 m to 3433 m, to predict distributions in relation to environmental variables. Two independent sets of environmental data layers at 0.05° and 0.5° resolution respectively, showed how spatial resolution affected the model. Chorismus antarcticus and N. antarcticus were found only on the continental shelf and upper slopes, while N. lanceopes, Lebbeus n. sp., Dendrobranchiata, Petalidium sp., Pasiphaea cf. ledoyeri, and Pasiphaea scotiae were found on the slopes, seamounts and abyssal plain. The environmental variables that contributed most to models for N. antarcticus were depth, chlorophyll-a concentration, temperature, and salinity, and for N. lanceopes were depth, ice concentration, seabed slope/rugosity, and temperature. The relative ranking, but not the composition of these variables changed in models using different spatial resolutions, and the predicted extent of suitable habitat was smaller in models using the finer-scale environmental layers. Our modelling indicated that shrimps were widespread throughout the Ross Sea region and were thus likely to play important functional role in the ecosystem, and that the spatial resolution of data needs to be considered both in the use of species distribution models. PMID:25051333

Spatially explicit assessment of heat health risk by using multi-sensor remote sensing images and socioeconomic data in Yangtze River Delta, China.

PubMed

Chen, Qian; Ding, Mingjun; Yang, Xuchao; Hu, Kejia; Qi, Jiaguo

2018-05-25

The increase in the frequency and intensity of extreme heat events, which are potentially associated with climate change in the near future, highlights the importance of heat health risk assessment, a significant reference for heat-related death reduction and intervention. However, a spatiotemporal mismatch exists between gridded heat hazard and human exposure in risk assessment, which hinders the identification of high-risk areas at finer scales. A human settlement index integrated by nighttime light images, enhanced vegetation index, and digital elevation model data was utilized to assess the human exposure at high spatial resolution. Heat hazard and vulnerability index were generated by land surface temperature and demographic and socioeconomic census data, respectively. Spatially explicit assessment of heat health risk and its driving factors was conducted in the Yangtze River Delta (YRD), east China at 250 m pixel level. High-risk areas were mainly distributed in the urbanized areas of YRD, which were mostly driven by high human exposure and heat hazard index. In some less-urbanized cities and suburban and rural areas of mega-cities, the heat health risks are in second priority. The risks in some less-developed areas were high despite the low human exposure index because of high heat hazard and vulnerability index. This study illustrated a methodology for identifying high-risk areas by combining freely available multi-source data. Highly urbanized areas were considered hotspots of high heat health risks, which were largely driven by the increasing urban heat island effects and population density in urban areas. Repercussions of overheating were weakened due to the low social vulnerability in some central areas benefitting from the low proportion of sensitive population or the high level of socioeconomic development. By contrast, high social vulnerability intensifies heat health risks in some less-urbanized cities and suburban areas of mega-cities.

Application of the WEAP model in strategic environmental assessment: Experiences from a case study in an arid/semi-arid area in China.

PubMed

Gao, Jingjing; Christensen, Per; Li, Wei

2017-08-01

This article investigated how the use of a water resources assessment model contributed to one of the first strategic environmental assessments (SEA) conducted for arid/semi-arid regions in China. The study was based on the SEA of a coal industry development plan in Ordos, an arid/semi-arid region of northwest China, where a temporally and spatially simplified version of the WEAP (Water Evaluation And Planning System) model was applied for assessing the impact of the planned activities on local water resource system. Four scenarios were developed to simulate various alternatives using a diverse range of water utilisation measures such as irrigation efficiency, treatment and the reuse of water. The WEAP model itself was found to be a useful tool for efficient water resources assessment in SEA: 1) WEAP provides built-in simulation modules for water assessment, which improve the SEA's efficiency significantly; 2) WEAP temporally has the flexibility in both delivering information on a reasonably aggregated level by evaluating water resource on an annual time step, which fits most SEA cases, and being possible to take a finer time step analysis monthly, weekly even daily; 3) Spatially, WEAP has advantage in dealing with distributed demand sites in large spatial scale. However, although WEAP appears as a useful tool in providing support for decision-making, in this SEA case we experienced difficulty in building a feasible scenario to mitigate the impact of the proposed activities on the local water system, so that solution had to be found outside of the assessed scenarios - which led to the discussion on the fact that the proposed activities in SEA cases are rarely regarded as an uncertainty. Therefore future research on the scope of SEA scenarios could be valuable. Copyright © 2017 Elsevier Ltd. All rights reserved.

Delineating wetland catchments and modeling hydrologic connectivity using lidar data and aerial imagery

NASA Astrophysics Data System (ADS)

Wu, Qiusheng; Lane, Charles R.

2017-07-01

In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling-spilling-merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow simulation and hydrologic connectivity analysis.

Simulating future residential property losses from wildfire in Flathead County, Montana: Chapter 1

USGS Publications Warehouse

Prato, Tony; Paveglio, Travis B; Barnett, Yan; Silverstein, Robin; Hardy, Michael; Keane, Robert; Loehman, Rachel A.; Clark, Anthony; Fagre, Daniel B.; Venn, Tyron; Stockmann, Keith

2014-01-01

Wildfire damages to private residences in the United States and elsewhere have increased as a result of expansion of the wildland-urban interface (WUI) and other factors. Understanding this unwelcome trend requires analytical frameworks that simulate how various interacting social, economic, and biophysical factors influence those damages. A methodological framework is developed for simulating expected residential property losses from wildfire [E(RLW)], which is a probabilistic monetary measure of wildfire risk to residential properties in the WUI. E(RLW) is simulated for Flathead County, Montana for five, 10-year subperiods covering the period 2010-2059, under various assumptions about future climate change, economic growth, land use policy, and forest management. Results show statistically significant increases in the spatial extent of WUI properties, the number of residential structures at risk from wildfire, and E(RLW) over the 50-year evaluation period for both the county and smaller subareas (i.e., neighborhoods and parcels). The E(RLW) simulation framework presented here advances the field of wildfire risk assessment by providing a finer-scale tool that incorporates a set of dynamic, interacting processes. The framework can be applied using other scenarios for climate change, economic growth, land use policy, and forest management, and in other areas.

Occupancy as a surrogate for abundance estimation

USGS Publications Warehouse

MacKenzie, D.I.; Nichols, J.D.

2004-01-01

In many monitoring programmes it may be prohibitively expensive to estimate the actual abundance of a bird species in a defined area, particularly at large spatial scales, or where birds occur at very low densities. Often it may be appropriate to consider the proportion of area occupied by the species as an alternative state variable. However, as with abundance estimation, issues of detectability must be taken into account in order to make accurate inferences: the non?detection of the species does not imply the species is genuinely absent. Here we review some recent modelling developments that permit unbiased estimation of the proportion of area occupied, colonization and local extinction probabilities. These methods allow for unequal sampling effort and enable covariate information on sampling locations to be incorporated. We also describe how these models could be extended to incorporate information from marked individuals, which would enable finer questions of population dynamics (such as turnover rate of nest sites by specific breeding pairs) to be addressed. We believe these models may be applicable to a wide range of bird species and may be useful for investigating various questions of ecological interest. For example, with respect to habitat quality, we might predict that a species is more likely to have higher local extinction probabilities, or higher turnover rates of specific breeding pairs, in poor quality habitats.

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

NASA Technical Reports Server (NTRS)

Lagomasino, David; Fatoyinbo, Temilola; Lee, SeungKuk; Feliciano, Emanuelle; Trettin, Carl; Simard, Marc

2016-01-01

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement (DEM), and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 meters were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes.

Disaggregating Census Data for Population Mapping Using Random Forests with Remotely-Sensed and Ancillary Data

PubMed Central

Stevens, Forrest R.; Gaughan, Andrea E.; Linard, Catherine; Tatem, Andrew J.

2015-01-01

High resolution, contemporary data on human population distributions are vital for measuring impacts of population growth, monitoring human-environment interactions and for planning and policy development. Many methods are used to disaggregate census data and predict population densities for finer scale, gridded population data sets. We present a new semi-automated dasymetric modeling approach that incorporates detailed census and ancillary data in a flexible, “Random Forest” estimation technique. We outline the combination of widely available, remotely-sensed and geospatial data that contribute to the modeled dasymetric weights and then use the Random Forest model to generate a gridded prediction of population density at ~100 m spatial resolution. This prediction layer is then used as the weighting surface to perform dasymetric redistribution of the census counts at a country level. As a case study we compare the new algorithm and its products for three countries (Vietnam, Cambodia, and Kenya) with other common gridded population data production methodologies. We discuss the advantages of the new method and increases over the accuracy and flexibility of those previous approaches. Finally, we outline how this algorithm will be extended to provide freely-available gridded population data sets for Africa, Asia and Latin America. PMID:25689585

A Comparison of Mangrove Canopy Height Using Multiple Independent Measurements from Land, Air, and Space

PubMed Central

Lagomasino, David; Fatoyinbo, Temilola; Lee, SeungKuk; Feliciano, Emanuelle; Trettin, Carl; Simard, Marc

2017-01-01

Canopy height is one of the strongest predictors of biomass and carbon in forested ecosystems. Additionally, mangrove ecosystems represent one of the most concentrated carbon reservoirs that are rapidly degrading as a result of deforestation, development, and hydrologic manipulation. Therefore, the accuracy of Canopy Height Models (CHM) over mangrove forest can provide crucial information for monitoring and verification protocols. We compared four CHMs derived from independent remotely sensed imagery and identified potential errors and bias between measurement types. CHMs were derived from three spaceborne datasets; Very-High Resolution (VHR) stereophotogrammetry, TerraSAR-X add-on for Digital Elevation Measurement, and Shuttle Radar Topography Mission (TanDEM-X), and lidar data which was acquired from an airborne platform. Each dataset exhibited different error characteristics that were related to spatial resolution, sensitivities of the sensors, and reference frames. Canopies over 10 m were accurately predicted by all CHMs while the distributions of canopy height were best predicted by the VHR CHM. Depending on the guidelines and strategies needed for monitoring and verification activities, coarse resolution CHMs could be used to track canopy height at regional and global scales with finer resolution imagery used to validate and monitor critical areas undergoing rapid changes. PMID:29629207

Seabed mapping and characterization of sediment variability using the usSEABED data base

USGS Publications Warehouse

Goff, J.A.; Jenkins, C.J.; Jeffress, Williams S.

2008-01-01

We present a methodology for statistical analysis of randomly located marine sediment point data, and apply it to the US continental shelf portions of usSEABED mean grain size records. The usSEABED database, like many modern, large environmental datasets, is heterogeneous and interdisciplinary. We statistically test the database as a source of mean grain size data, and from it provide a first examination of regional seafloor sediment variability across the entire US continental shelf. Data derived from laboratory analyses ("extracted") and from word-based descriptions ("parsed") are treated separately, and they are compared statistically and deterministically. Data records are selected for spatial analysis by their location within sample regions: polygonal areas defined in ArcGIS chosen by geography, water depth, and data sufficiency. We derive isotropic, binned semivariograms from the data, and invert these for estimates of noise variance, field variance, and decorrelation distance. The highly erratic nature of the semivariograms is a result both of the random locations of the data and of the high level of data uncertainty (noise). This decorrelates the data covariance matrix for the inversion, and largely prevents robust estimation of the fractal dimension. Our comparison of the extracted and parsed mean grain size data demonstrates important differences between the two. In particular, extracted measurements generally produce finer mean grain sizes, lower noise variance, and lower field variance than parsed values. Such relationships can be used to derive a regionally dependent conversion factor between the two. Our analysis of sample regions on the US continental shelf revealed considerable geographic variability in the estimated statistical parameters of field variance and decorrelation distance. Some regional relationships are evident, and overall there is a tendency for field variance to be higher where the average mean grain size is finer grained. Surprisingly, parsed and extracted noise magnitudes correlate with each other, which may indicate that some portion of the data variability that we identify as "noise" is caused by real grain size variability at very short scales. Our analyses demonstrate that by applying a bias-correction proxy, usSEABED data can be used to generate reliable interpolated maps of regional mean grain size and sediment character. 

Roadmap for Scaling and Multifractals in Geosciences: still a long way to go ?

NASA Astrophysics Data System (ADS)

Schertzer, Daniel; Lovejoy, Shaun

2010-05-01

The interest in scale symmetries (scaling) in Geosciences has never lessened since the first pioneering EGS session on chaos and fractals 22 years ago. The corresponding NP activities have been steadily increasing, covering a wider and wider diversity of geophysical phenomena and range of space-time scales. Whereas interest was initially largely focused on atmospheric turbulence, rain and clouds at small scales, it has quickly broadened to much larger scales and to much wider scale ranges, to include ocean sciences, solid earth and space physics. Indeed, the scale problem being ubiquitous in Geosciences, it is indispensable to share the efforts and the resulting knowledge as much as possible. There have been numerous achievements which have followed from the exploration of larger and larger datasets with finer and finer resolutions, from both modelling and theoretical discussions, particularly on formalisms for intermittency, anisotropy and scale symmetry, multiple scaling (multifractals) vs. simple scaling,. We are now way beyond the early pioneering but tentative attempts using crude estimates of unique scaling exponents to bring some credence to the fact that scale symmetries are key to most nonlinear geoscience problems. Nowadays, we need to better demonstrate that scaling brings effective solutions to geosciences and therefore to society. A large part of the answer corresponds to our capacity to create much more universal and flexible tools to multifractally analyse in straightforward and reliable manners complex and complicated systems such as the climate. Preliminary steps in this direction are already quite encouraging: they show that such approaches explain both the difficulty of classical techniques to find trends in climate scenarios (particularly for extremes) and resolve them with the help of scaling estimators. The question of the reliability and accuracy of these methods is not trivial. After discussing these important, but rather short term issues, we will point out more general questions, which can be put together into the following provocative question: how to convert the classical time evolving deterministic PDE's into dynamical multifractal systems? We will argue that this corresponds to an already active field of research, which include: multifractals as generic solutions of nonlinear PDE (exact results for 1D Burgers equation and a few other caricatures of Navier-Stokes equations, prospects for 3D Burgers equations), cascade structures of numerical weather models, links between multifractal processes and random dynamical systems, and the challenging debate on the most relevant stochastic multifractal formalism, whereas there is already a rather general consent about the deterministic one.

Mapping and exploring variation in post-fire vegetation recovery following mixed severity wildfire using airborne LiDAR.

PubMed

Gordon, Christopher E; Price, Owen F; Tasker, Elizabeth M

2017-07-01

There is a public perception that large high-severity wildfires decrease biodiversity and increase fire hazard by homogenizing vegetation composition and increasing the cover of mid-story vegetation. But a growing literature suggests that vegetation responses are nuanced. LiDAR technology provides a promising remote sensing tool to test hypotheses about post-fire vegetation regrowth because vegetation cover can be quantified within different height strata at fine scales over large areas. We assess the usefulness of airborne LiDAR data for measuring post-fire mid-story vegetation regrowth over a range of spatial resolutions (10 × 10 m, 30 × 30 m, 50 × 50 m, 100 × 100 m cell size) and investigate the effect of fire severity on regrowth amount and spatial pattern following a mixed severity wildfire in Warrumbungle National Park, Australia. We predicted that recovery would be more vigorous in areas of high fire severity, because park managers observed dense post-fire regrowth in these areas. Moderate to strong positive associations were observed between LiDAR and field surveys of mid-story vegetation cover between 0.5-3.0 m. Thus our LiDAR survey was an apt representation of on-ground vegetation cover. LiDAR-derived mid-story vegetation cover was 22-40% lower in areas of low and moderate than high fire severity. Linear mixed-effects models showed that fire severity was among the strongest biophysical predictors of mid-story vegetation cover irrespective of spatial resolution. However much of the variance associated with these models was unexplained, presumably because soil seed banks varied at finer scales than our LiDAR maps. Dense patches of mid-story vegetation regrowth were small (median size 0.01 ha) and evenly distributed between areas of low, moderate and high fire severity, demonstrating that high-severity fires do not homogenize vegetation cover. Our results are relevant for ecosystem conservation and fire management because they: indicate that native vegetation are responsive and resilient to high-severity fire, and show the usefulness of remote sensing tools such as LiDAR to monitor post-fire vegetation recovery over large areas in situ. © 2017 by the Ecological Society of America.

Topographic Controls on Spatial Patterns of Soil Texture and Moisture in a Semi-arid Montane Catchment with Aspect-Dependent Vegetation

NASA Astrophysics Data System (ADS)

Lehman, B. M.; Niemann, J. D.

2008-12-01

Soil moisture exerts significant control over the partitioning of latent and sensible energy fluxes, the magnitude of both vertical and lateral water fluxes, the physiological and water-use characteristics of vegetation, and nutrient cycling. Considerable progress has been made in determining how soil characteristics, topography, and vegetation influence spatial patterns of soil moisture in humid environments at the catchment, hillslope, and plant scales. However, understanding of the controls on soil moisture patterns beyond the plant scale in semi-arid environments remains more limited. This study examines the relationships between the spatial patterns of near surface soil moisture (upper 5 cm), terrain indices, and soil properties in a small, semi-arid, montane catchment. The 8 ha catchment, located in the Cache La Poudre River Canyon in north-central Colorado, has a total relief of 115 m and an average elevation of 2193 m. It is characterized by steep slopes and shallow, gravelly/sandy soils with scattered granite outcroppings. Depth to bedrock ranges from 0 m to greater than 1 m. Vegetation in the catchment is highly correlated with topographic aspect. In particular, north-facing hillslopes are predominately vegetated by ponderosa pines, while south-facing slopes are mostly vegetated by several shrub species. Soil samples were collected at a 30 m resolution to characterize soil texture and bulk density, and several datasets consisting of more than 300 point measurements of soil moisture were collected using time domain reflectometry (TDR) between Fall 2007 and Summer 2008 at a 15 m resolution. Results from soil textural analysis performed with sieving and the ASTM standard hydrometer method show that soil texture is finer on the north-facing hillslope than on the south-facing hillslope. Cos(aspect) is the best univariate predictor of silts, while slope is the best predictor of coarser fractions up to fine gravel. Bulk density increases with depth but shows no significant relationship with topographic indices. When the catchment average soil moisture is low, the variance of soil moisture increases with the average. When the average is high, the variance remains relatively constant. Little of the variation in soil moisture is explained by topographic indices when the catchment is either very wet or dry; however, when the average soil moisture takes on intermediate values, cos(aspect) is consistently the best predictor among the terrain indices considered.

Phylogeography in Response to Reproductive Strategies and Ecogeographic Isolation in Ant Species on Madagascar: Genus Mystrium (Formicidae: Amblyoponinae)

PubMed Central

Graham, Natalie R.; Fisher, Brian L.; Girman, Derek J.

2016-01-01

The bulk of models used to understand the species diversification on Madagascar have been constructed using vertebrate taxa. It is not clear how these models affect less vagile species that may interact at a variety of spatial scales. Several studies on vertebrates have divided Madagascar into east-west bioclimatic regions, suggesting there is a fundamental division between eastern wet-adapted and western dry-adapted taxa. An alternative model of ecogeographic constraints shows a north-south division. We test whether the diversification in a small arthropod with variable degrees of dispersal conform to either model of ecogeographic constraints proposed for vertebrate taxa. We employ a molecular taxonomic dataset using ~2 kilobases nuDNA (Wg, LW Rh, Abd-A, 28s) and 790 basepairs mtDNA (CO1), along with geographic and habitat data, to examine the diversification patterns of the ant genus Mystrium Roger, 1862, (Subfamily Amblyoponinae) from Madagascar. The nuclear and mitochondrial phylogenies were both congruent with morphospecies as indicated in a recent revision of the genus. Species of Mystrium practice different colony reproductive strategies (winged queens vs non-winged queens). Alternate reproductive strategies led to inequalities in female dispersal ability among species, providing an additional layer for examination of the impacts of vagility on divergence, especially when measured using a maternally inherited locus. Mystrium species distribution patterns support these models of ecogeographic constraints. Reproductive strategy effected how Mystrium mtDNA lineages were associated with large-scale habitat distinctions and various topographical features. Furthermore, in some cases we find microgeographic population structure which appears to have been impacted by localized habitat differences (tsingy limestone formations, littoral forest) on a scale much smaller than that found in vertebrates. The current system offers a finer scale look at species diversification on the island, and helps achieve a more universal understanding of the generation of biodiversity on Madagascar. PMID:26800442

Phylogeography in Response to Reproductive Strategies and Ecogeographic Isolation in Ant Species on Madagascar: Genus Mystrium (Formicidae: Amblyoponinae).

PubMed

Graham, Natalie R; Fisher, Brian L; Girman, Derek J

2016-01-01

The bulk of models used to understand the species diversification on Madagascar have been constructed using vertebrate taxa. It is not clear how these models affect less vagile species that may interact at a variety of spatial scales. Several studies on vertebrates have divided Madagascar into east-west bioclimatic regions, suggesting there is a fundamental division between eastern wet-adapted and western dry-adapted taxa. An alternative model of ecogeographic constraints shows a north-south division. We test whether the diversification in a small arthropod with variable degrees of dispersal conform to either model of ecogeographic constraints proposed for vertebrate taxa. We employ a molecular taxonomic dataset using ~2 kilobases nuDNA (Wg, LW Rh, Abd-A, 28s) and 790 basepairs mtDNA (CO1), along with geographic and habitat data, to examine the diversification patterns of the ant genus Mystrium Roger, 1862, (Subfamily Amblyoponinae) from Madagascar. The nuclear and mitochondrial phylogenies were both congruent with morphospecies as indicated in a recent revision of the genus. Species of Mystrium practice different colony reproductive strategies (winged queens vs non-winged queens). Alternate reproductive strategies led to inequalities in female dispersal ability among species, providing an additional layer for examination of the impacts of vagility on divergence, especially when measured using a maternally inherited locus. Mystrium species distribution patterns support these models of ecogeographic constraints. Reproductive strategy effected how Mystrium mtDNA lineages were associated with large-scale habitat distinctions and various topographical features. Furthermore, in some cases we find microgeographic population structure which appears to have been impacted by localized habitat differences (tsingy limestone formations, littoral forest) on a scale much smaller than that found in vertebrates. The current system offers a finer scale look at species diversification on the island, and helps achieve a more universal understanding of the generation of biodiversity on Madagascar.

Development of a local-scale urban stream assessment method using benthic macroinvertebrates: An example from the Santa Clara Basin, California

USGS Publications Warehouse

Carter, J.L.; Purcell, A.H.; Fend, S.V.; Resh, V.H.

2009-01-01

Research that explores the biological response to urbanization on a site-specific scale is necessary for management of urban basins. Recent studies have proposed a method to characterize the biological response of benthic macroinvertebrates along an urban gradient for several climatic regions in the USA. Our study demonstrates how this general framework can be refined and applied on a smaller scale to an urbanized basin, the Santa Clara Basin (surrounding San Jose, California, USA). Eighty-four sampling sites on 14 streams in the Santa Clara Basin were used for assessing local stream conditions. First, an urban index composed of human population density, road density, and urban land cover was used to determine the extent of urbanization upstream from each sampling site. Second, a multimetric biological index was developed to characterize the response of macroinvertebrate assemblages along the urban gradient. The resulting biological index included metrics from 3 ecological categories: taxonomic composition ( Ephemeroptera, Plecoptera, and Trichoptera), functional feeding group (shredder richness), and habit ( clingers). The 90th-quantile regression line was used to define the best available biological conditions along the urban gradient, which we define as the predicted biological potential. This descriptor was then used to determine the relative condition of sites throughout the basin. Hierarchical partitioning of variance revealed that several site-specific variables (dissolved O2 and temperature) were significantly related to a site's deviation from its predicted biological potential. Spatial analysis of each site's deviation from its biological potential indicated geographic heterogeneity in the distribution of impaired sites. The presence and operation of local dams optimize water use, but modify natural flow regimes, which in turn influence stream habitat, dissolved O2, and temperature. Current dissolved O2 and temperature regimes deviate from natural conditions and appear to affect benthic macroinvertebrate assemblages. The assessment methods presented in our study provide finer-scale assessment tools for managers in urban basins. ?? North American Benthological Society.

Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology

USGS Publications Warehouse

Cross, Paul C.; Klaver, Robert W.; Brennan, Angela; Creel, Scott; Beckmann, Jon P.; Higgs, Megan D.; Scurlock, Brandon M.

2013-01-01

Abstract. It is increasingly common for studies of animal ecology to use model-based predictions of environmental variables as explanatory or predictor variables, even though model prediction uncertainty is typically unknown. To demonstrate the potential for misleading inferences when model predictions with error are used in place of direct measurements, we compared snow water equivalent (SWE) and snow depth as predicted by the Snow Data Assimilation System (SNODAS) to field measurements of SWE and snow depth. We examined locations on elk (Cervus canadensis) winter ranges in western Wyoming, because modeled data such as SNODAS output are often used for inferences on elk ecology. Overall, SNODAS predictions tended to overestimate field measurements, prediction uncertainty was high, and the difference between SNODAS predictions and field measurements was greater in snow shadows for both snow variables compared to non-snow shadow areas. We used a simple simulation of snow effects on the probability of an elk being killed by a predator to show that, if SNODAS prediction uncertainty was ignored, we might have mistakenly concluded that SWE was not an important factor in where elk were killed in predatory attacks during the winter. In this simulation, we were interested in the effects of snow at finer scales (2) than the resolution of SNODAS. If bias were to decrease when SNODAS predictions are averaged over coarser scales, SNODAS would be applicable to population-level ecology studies. In our study, however, averaging predictions over moderate to broad spatial scales (9–2200 km2) did not reduce the differences between SNODAS predictions and field measurements. This study highlights the need to carefully evaluate two issues when using model output as an explanatory variable in subsequent analysis: (1) the model’s resolution relative to the scale of the ecological question of interest and (2) the implications of prediction uncertainty on inferences when using model predictions as explanatory or predictor variables.

Verification Test of the SURF and SURFplus Models in xRage: Part II

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

Menikoff, Ralph

2016-06-20

The previous study used an underdriven detonation wave (steady ZND reaction zone profile followed by a scale invariant rarefaction wave) for PBX 9502 as a validation test of the implementation of the SURF and SURFplus models in the xRage code. Even with a fairly fine uniform mesh (12,800 cells for 100mm) the detonation wave profile had limited resolution due to the thin reaction zone width (0.18mm) for the fast SURF burn rate. Here we study the effect of finer resolution by comparing results of simulations with cell sizes of 8, 2 and 1 μm, which corresponds to 25, 100 andmore » 200 points within the reaction zone. With finer resolution the lead shock pressure is closer to the von Neumann spike pressure, and there is less noise in the rarefaction wave due to fluctuations within the reaction zone. As a result the average error decreases. The pointwise error is still dominated by the smearing the pressure kink in the vicinity of the sonic point which occurs at the end of the reaction zone.« less

Optical instruments synergy in determination of optical depth of thin clouds

NASA Astrophysics Data System (ADS)

Viviana Vlăduţescu, Daniela; Schwartz, Stephen E.; Huang, Dong

2018-04-01

Optically thin clouds have a strong radiative effect and need to be represented accurately in climate models. Cloud optical depth of thin clouds was retrieved using high resolution digital photography, lidar, and a radiative transfer model. The Doppler Lidar was operated at 1.5 μm, minimizing return from Rayleigh scattering, emphasizing return from aerosols and clouds. This approach examined cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opening new avenues for examination of cloud structure and evolution.

Optical Instruments Synergy in Determination of Optical Depth of Thin Clouds

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

Vladutescu, Daniela V.; Schwartz, Stephen E.

Optically thin clouds have a strong radiative effect and need to be represented accurately in climate models. Cloud optical depth of thin clouds was retrieved using high resolution digital photography, lidar, and a radiative transfer model. The Doppler Lidar was operated at 1.5 μm, minimizing return from Rayleigh scattering, emphasizing return from aerosols and clouds. This approach examined cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opening new avenues for examination of cloud structure and evolution.

Grid Sensitivity Study for Slat Noise Simulations

NASA Technical Reports Server (NTRS)

Lockard, David P.; Choudhari, Meelan M.; Buning, Pieter G.

2014-01-01

The slat noise from the 30P/30N high-lift system is being investigated through computational fluid dynamics simulations in conjunction with a Ffowcs Williams-Hawkings acoustics solver. Many previous simulations have been performed for the configuration, and the case was introduced as a new category for the Second AIAA workshop on Benchmark problems for Airframe Noise Configurations (BANC-II). However, the cost of the simulations has restricted the study of grid resolution effects to a baseline grid and coarser meshes. In the present study, two different approaches are being used to investigate the effect of finer resolution of near-field unsteady structures. First, a standard grid refinement by a factor of two is used, and the calculations are performed by using the same CFL3D solver employed in the majority of the previous simulations. Second, the OVERFLOW code is applied to the baseline grid, but with a 5th-order upwind spatial discretization as compared with the second-order discretization used in the CFL3D simulations. In general, the fine grid CFL3D simulation and OVERFLOW calculation are in very good agreement and exhibit the lowest levels of both surface pressure fluctuations and radiated noise. Although the smaller scales resolved by these simulations increase the velocity fluctuation levels, they appear to mitigate the influence of the larger scales on the surface pressure. These new simulations are used to investigate the influence of the grid on unsteady high-lift simulations and to gain a better understanding of the physics responsible for the noise generation and radiation.

Global patterns of terrestrial vertebrate diversity and conservation

PubMed Central

Jenkins, Clinton N.; Pimm, Stuart L.; Joppa, Lucas N.

2013-01-01

Identifying priority areas for biodiversity is essential for directing conservation resources. Fundamentally, we must know where individual species live, which ones are vulnerable, where human actions threaten them, and their levels of protection. As conservation knowledge and threats change, we must reevaluate priorities. We mapped priority areas for vertebrates using newly updated data on >21,000 species of mammals, amphibians, and birds. For each taxon, we identified centers of richness for all species, small-ranged species, and threatened species listed with the International Union for the Conservation of Nature. Importantly, all analyses were at a spatial grain of 10 × 10 km, 100 times finer than previous assessments. This fine scale is a significant methodological improvement, because it brings mapping to scales comparable with regional decisions on where to place protected areas. We also mapped recent species discoveries, because they suggest where as-yet-unknown species might be living. To assess the protection of the priority areas, we calculated the percentage of priority areas within protected areas using the latest data from the World Database of Protected Areas, providing a snapshot of how well the planet’s protected area system encompasses vertebrate biodiversity. Although the priority areas do have more protection than the global average, the level of protection still is insufficient given the importance of these areas for preventing vertebrate extinctions. We also found substantial differences between our identified vertebrate priorities and the leading map of global conservation priorities, the biodiversity hotspots. Our findings suggest a need to reassess the global allocation of conservation resources to reflect today’s improved knowledge of biodiversity and conservation. PMID:23803854

Validation of satellite daily rainfall estimates in complex terrain of Bali Island, Indonesia

NASA Astrophysics Data System (ADS)

Rahmawati, Novi; Lubczynski, Maciek W.

2017-11-01

Satellite rainfall products have different performances in different geographic regions under different physical and climatological conditions. In this study, the objective was to select the most reliable and accurate satellite rainfall products for specific, environmental conditions of Bali Island. The performances of four spatio-temporal satellite rainfall products, i.e., CMORPH25, CMORPH8, TRMM, and PERSIANN, were evaluated at the island, zonation (applying elevation and climatology as constraints), and pixel scales, using (i) descriptive statistics and (ii) categorical statistics, including bias decomposition. The results showed that all the satellite products had low accuracy because of spatial scale effect, daily resolution and the island complexity. That accuracy was relatively lower in (i) dry seasons and dry climatic zones than in wet seasons and wet climatic zones; (ii) pixels jointly covered by sea and mountainous land than in pixels covered by land or by sea only; and (iii) topographically diverse than uniform terrains. CMORPH25, CMORPH8, and TRMM underestimated and PERSIANN overestimated rainfall when comparing them to gauged rain. The CMORPH25 had relatively the best performance and the PERSIANN had the worst performance in the Bali Island. The CMORPH25 had the lowest statistical errors, the lowest miss, and the highest hit rainfall events; it also had the lowest miss rainfall bias and was relatively the most accurate in detecting, frequent in Bali, ≤ 20 mm day-1 rain events. Lastly, the CMORPH25 coarse grid better represented rainfall events from coastal to inlands areas than other satellite products, including finer grid CMORPH8.

Using NextRAD sequencing to infer movement of herbivores among host plants.

PubMed

Fu, Zhen; Epstein, Brendan; Kelley, Joanna L; Zheng, Qi; Bergland, Alan O; Castillo Carrillo, Carmen I; Jensen, Andrew S; Dahan, Jennifer; Karasev, Alexander V; Snyder, William E

2017-01-01

Herbivores often move among spatially interspersed host plants, tracking high-quality resources through space and time. This dispersal is of particular interest for vectors of plant pathogens. Existing molecular tools to track such movement have yielded important insights, but often provide insufficient genetic resolution to infer spread at finer spatiotemporal scales. Here, we explore the use of Nextera-tagmented reductively-amplified DNA (NextRAD) sequencing to infer movement of a highly-mobile winged insect, the potato psyllid (Bactericera cockerelli), among host plants. The psyllid vectors the pathogen that causes zebra chip disease in potato (Solanum tuberosum), but understanding and managing the spread of this pathogen is limited by uncertainty about the insect's host plant(s) outside of the growing season. We identified 1,978 polymorphic loci among psyllids separated spatiotemporally on potato or in patches of bittersweet nightshade (S. dulcumara), a weedy plant proposed to be the source of potato-colonizing psyllids. A subset of the psyllids on potato exhibited genetic similarity to insects on nightshade, consistent with regular movement between these two host plants. However, a second subset of potato-collected psyllids was genetically distinct from those collected on bittersweet nightshade; this suggests that a currently unrecognized source, i.e., other nightshade patches or a third host-plant species, could be contributing to psyllid populations in potato. Oftentimes, dispersal of vectors of pathogens must be tracked at a fine scale in order to understand, predict, and manage disease spread. We demonstrate that emerging sequencing technologies that detect genome-wide SNPs of a vector can be used to infer such localized movement.

Classification of the alterations of beaver dams to headwater streams in northeastern Connecticut, U.S.A.

NASA Astrophysics Data System (ADS)

Burchsted, Denise; Daniels, Melinda D.

2014-01-01

Of the many types of barriers to water flow, beaver dams are among the smallest, typically lasting less than a decade and rarely exceeding 1.5 m in height. They are also among the most frequent and common obstructions in rivers, with a density often exceeding ten dams per km, a frequency of construction within a given network on a time scale of years, and a historic extent covering most of North America. Past quantification of the geomorphologic impact of beaver dams has primarily been limited to local impacts within individual impoundments and is of limited geographic scope. To assess the impact of beaver dams at larger scales, this study examines channel shape and sediment distribution in thirty river reaches in northeastern Connecticut, U.S.A. The study reaches fall within the broader categories of impounded and free-flowing segments, leaving a third segment class of beaver meadows requiring additional study. Each of the study reaches were classified at the reach scale as free-flowing, valley-wide beaver pond, in-channel beaver pond, and downstream of beaver dam. The bankfull channel width to depth ratios and channel widths normalized by watershed area vary significantly across the study reach classes. Additionally, reaches modified by beaver dams have finer sediment distributions. This paper provides the first quantitative geomorphic descriptions of the in-channel beaver pond and reaches downstream of beaver dams. Given the different channel shapes and sediment distributions, we infer that geomorphic processes are longitudinally decoupled by these frequent barriers that control local base level. These barriers generate heterogeneity within a river network by greatly increasing the range of channel morphology and by generating patches controlled by different processes. Therefore, in spite of the small size of individual beaver dams, the cumulative effect of multiple dams has the potential to modify processes at larger spatial scales. To improve assessment of the larger-scale impacts, we propose a hierarchical classification scheme based on discontinuities, place the reach classes of this study within that scheme, and suggest that further research should continue investigation of discontinuity at the network scale and quantification of the cumulative impacts.

Flash flooding: Toward an Interdisciplinary and Integrated Strategy for Disaster Reduction in a Global Environmental Change Perspective

NASA Astrophysics Data System (ADS)

Ruin, Isabelle

2014-05-01

How do people answer to heavy precipitation and flood warnings? How do they adapt their daily schedule and activity to the fast evolution of the environmental circumstances? More generally, how do social processes interact with physical ones? Such questions address the dynamical interactions between hydro-meteorological variables, human perception and representation of the environment, and actual individual and social behavioral responses. It also poses the question of scales and hierarchy issues through seamless interactions between smaller and larger scales. These questions are relevant for both social and physical scientists. They are more and more pertinently addressed in the Global Environmental Change perspective through the concepts of Coupled Human And Natural Systems (CHANS), resilience or panarchy developped in the context of interdisciplinary collaborations. Nevertheless those concepts are complex and not easy to handle, specially when facing with operational goals. One of the main difficulty to advance these integrated approaches is the access to empirical data informing the processes at various scales. In fact, if physical and social processes are well studied by distinct disciplines, they are rarely jointly explored within similar spatial and temporal resolutions. Such coupled observation and analysis poses methodological challenges, specially when dealing with responses to short-fuse and extreme weather events. In fact, if such coupled approach is quite common to study large scale phenomenon like global change (for instance using historical data on green house gaz emissions and the evolution of temperatures worldwide), it is rarer for studing smaller nested sets of scales of human-nature systems where finer resolution data are sparse. Another problem arise from the need to produce comparable analysis on different case studies where social, physical and even cultural contexts may be diverse. Generic and robust framework for data collection, modeling and analysis are needed to allow cross comparison and deeper understanding of the processes accross scales. This presentation will address these issues based on concrete exemples from empirical studies on past flash flooding events across Europe and USA.

Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Gutmann, Ethan D.; Mendoza, Pablo A.; Newman, Andrew J.; Nijssen, Bart; Livneh, Ben; Hay, Lauren E.; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.

A Review of distribution and quantity of lingering subsurface oil from the Exxon Valdez Oil Spill

NASA Astrophysics Data System (ADS)

Nixon, Zachary; Michel, Jacqueline

2018-01-01

Remaining lingering subsurface oil residues from the Exxon Valdez oil spill (EVOS) are, at present, patchily distributed across the geologically complex and spatially extensive shorelines of Prince William Sound and the Gulf of Alaska. We review and synthesize previous literature describing the causal geomorphic and physical mechanisms for persistence of oil in the intertidal subsurface sediments of these areas. We also summarize previous sampling and modeling efforts, and refine previously presented models with additional data to characterize the present-day linear and areal spatial extent, and quantity of lingering subsurface oil. In the weeks after the spill in March of 1989, approximately 17,750 t of oil were stranded along impacted shorelines, and by October of 1992, only 2% of the mass of spilled oil was estimated to remain in intertidal areas. We estimate that lingering subsurface residues, generally between 5 and 20 cm thick and sequestered below 10-20 cm of clean sediment, are present over 30 ha of intertidal area, along 11.4 km of shoreline, and represent approximately 227 t or 0.6% of the total mass of spilled oil. These residues are typically located in finer-grained sand and gravel sediments, often under an armor of cobble- or boulder-sized clasts, in areas with limited groundwater flow and porosity. Persistence of these residues is correlated with heavy initial oil loading together with localized sheltering from physical disturbance such as wave energy within the beach face. While no longer generally bioavailable and increasingly chemically weathered, present removal rates for these remaining subsurface oil residues have slowed to nearly zero. The only remaining plausible removal mechanisms will operate over time scales of decades.

High-Resolution Soil Moisture Retrieval using SMAP-L Band Radiometer and RISAT-C band Radar Data for the Indian Subcontinent

NASA Astrophysics Data System (ADS)

Singh, G.; Das, N. N.; Panda, R. K.; Mohanty, B.; Entekhabi, D.; Bhattacharya, B. K.

2016-12-01

Soil moisture status at high resolution (1-10 km) is vital for hydrological, agricultural and hydro-metrological applications. The NASA Soil Moisture Active Passive (SMAP) mission had potential to provide reliable soil moisture estimate at finer spatial resolutions (3 km and 9 km) at the global extent, but suffered a malfunction of its radar, consequently making the SMAP mission observations only from radiometer that are of coarse spatial resolution. At present, the availability of high-resolution soil moisture product is limited, especially in developing countries like India, which greatly depends on agriculture for sustaining a huge population. Therefore, an attempt has been made in the reported study to combine the C-band synthetic aperture radar (SAR) data from Radar Imaging Satellite (RISAT) of the Indian Space Research Organization (ISRO) with the SMAP mission L-band radiometer data to obtain high-resolution (1 km and 3 km) soil moisture estimates. In this study, a downscaling approach (Active-Passive Algorithm) implemented for the SMAP mission was used to disaggregate the SMAP radiometer brightness temperature (Tb) using the fine resolution SAR backscatter (σ0) from RISAT. The downscaled high-resolution Tb was then subjected to tau-omega model in conjunction with high-resolution ancillary data to retrieve soil moisture at 1 and 3 km scale. The retrieved high-resolution soil moisture estimates were then validated with ground based soil moisture measurement under different hydro-climatic regions of India. Initial results show tremendous potential and reasonable accuracy for the retrieved soil moisture at 1 km and 3 km. It is expected that ISRO will implement this approach to produce high-resolution soil moisture estimates for the Indian subcontinent.

The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware

USGS Publications Warehouse

Vanderhoof, Melanie; Distler, Hayley; Lang, Megan W.; Alexander, Laurie C.

2018-01-01

The dependence of downstream waters on upstream ecosystems necessitates an improved understanding of watershed-scale hydrological interactions including connections between wetlands and streams. An evaluation of such connections is challenging when, (1) accurate and complete datasets of wetland and stream locations are often not available and (2) natural variability in surface-water extent influences the frequency and duration of wetland/stream connectivity. The Upper Choptank River watershed on the Delmarva Peninsula in eastern Maryland and Delaware is dominated by a high density of small, forested wetlands. In this analysis, wetland/stream surface water connections were quantified using multiple wetland and stream datasets, including headwater streams and depressions mapped from a lidar-derived digital elevation model. Surface-water extent was mapped across the watershed for spring 2015 using Landsat-8, Radarsat-2 and Worldview-3 imagery. The frequency of wetland/stream connections increased as a more complete and accurate stream dataset was used and surface-water extent was included, in particular when the spatial resolution of the imagery was finer (i.e., <10 m). Depending on the datasets used, 12–60% of wetlands by count (21–93% of wetlands by area) experienced surface-water interactions with streams during spring 2015. This translated into a range of 50–94% of the watershed contributing direct surface water runoff to streamflow. This finding suggests that our interpretation of the frequency and duration of wetland/stream connections will be influenced not only by the spatial and temporal characteristics of wetlands, streams and potential flowpaths, but also by the completeness, accuracy and resolution of input datasets.