Spatial discretization of large watersheds and its influence on the estimation of hillslope sediment yield

USDA-ARS?s Scientific Manuscript database

The combined use of water erosion models and geographic information systems (GIS) has facilitated soil loss estimation at the watershed scale. Tools such as the Geo-spatial interface for the Water Erosion Prediction Project (GeoWEPP) model provide a convenient spatially distributed soil loss estimat...

Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways

DOE PAGES

Jones, B.; O’Neill, B. C.

2016-07-29

Here we report that the projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatiallymore » explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.« less

Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways

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

Jones, B.; O’Neill, B. C.

Here we report that the projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatiallymore » explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.« less

A Method for Mapping Future Urbanization in the United States

NASA Technical Reports Server (NTRS)

Bounoua, Lahouari; Nigro, Joseph; Thome, Kurtis; Zhang, Ping; Fathi, Najlaa; Lachir, Asia

2018-01-01

Cities are poised to absorb additional people. Their sustainability, or ability to accommodate a population increase without depleting resources or compromising future growth, depends on whether they harness the efficiency gains from urban land management. Population is often projected as a bulk national number without details about spatial distribution. We use Landsat and population data in a methodology to project and map U.S. urbanization for the year 2020 and document its spatial pattern. This methodology is important to spatially disaggregate projected population and assist land managers to monitor land use, assess infrastructure and distribute resources. We found the U.S. west coast urban areas to have the fastest population growth with relatively small land consumption resulting in future decrease in per capita land use. Except for Miami (FL), most other U.S. large urban areas, especially in the Midwest, are growing spatially faster than their population and inadvertently consuming land needed for ecosystem services. In large cities, such as New York, Chicago, Houston and Miami, land development is expected more in suburban zones than urban cores. In contrast, in Los Angeles land development within the city core is greater than in its suburbs.

Spatial distribution of citizen science casuistic observations for different taxonomic groups.

PubMed

Tiago, Patrícia; Ceia-Hasse, Ana; Marques, Tiago A; Capinha, César; Pereira, Henrique M

2017-10-16

Opportunistic citizen science databases are becoming an important way of gathering information on species distributions. These data are temporally and spatially dispersed and could have limitations regarding biases in the distribution of the observations in space and/or time. In this work, we test the influence of landscape variables in the distribution of citizen science observations for eight taxonomic groups. We use data collected through a Portuguese citizen science database (biodiversity4all.org). We use a zero-inflated negative binomial regression to model the distribution of observations as a function of a set of variables representing the landscape features plausibly influencing the spatial distribution of the records. Results suggest that the density of paths is the most important variable, having a statistically significant positive relationship with number of observations for seven of the eight taxa considered. Wetland coverage was also identified as having a significant, positive relationship, for birds, amphibians and reptiles, and mammals. Our results highlight that the distribution of species observations, in citizen science projects, is spatially biased. Higher frequency of observations is driven largely by accessibility and by the presence of water bodies. We conclude that efforts are required to increase the spatial evenness of sampling effort from volunteers.

Extended Shared Socioeconomic Pathways for Coastal Impact Assessment: Spatial Coastal Population Scenarios

NASA Astrophysics Data System (ADS)

Merkens, Jan-Ludolf; Reimann, Lena; Hinkel, Jochen; Vafeidis, Athanasios T.

2016-04-01

This work extends the Shared Socioeconomic Pathways (SSPs) by developing spatial projections of global coastal population distribution for the five basic SSPs. Based on a series of coastal migration drivers, which were identified from existing literature, we develop coastal narratives for the five basic SSPs (SSP1-5). These narratives account for differences in coastal versus inland population development in urban and rural areas. To spatially distribute population we use the International Institute for Applied Systems Analysis (IIASA) national population and urbanisation projections and employ country-specific growth rates which differ for coastal and inland as well as for urban and rural regions. These rates are derived from spatial analysis of historical population data. We then adjust these rates for each SSP based on the coastal narratives. The resulting global population grids depict the projected distribution of coastal population for each SSP, until the end of the 21st century, at a spatial resolution of 30 arc seconds. These grids exhibit a three- to four-fold increase in coastal population compared to the basic SSPs. Across all SSPs, except for SSP3, coastal population peaks by the middle of the 21st century and declines afterwards. In SSP3 the coastal population grows continuously until 2100. Compared to the base year 2000 the coastal population increases considerably in all SSPs. The extended SSPs are intended to be utilised in Impact, Adaptation and Vulnerability (IAV) assessments as they allow for improved analysis of exposure to sea-level rise and coastal flooding under different physical and socioeconomic scenarios.

Spatial variability of soil moisture retrieved by SMOS satellite

NASA Astrophysics Data System (ADS)

Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy

2015-04-01

Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies ergodicity and quasi-stationarity assumptions, required for geostatistical analysis. The semivariograms examinations revealed that spatial dependences occurring in the surface soil moisture distributions for the selected area were more or less 200 km. The exception was the driest of the studied days, when the spatial correlations of soil moisture were not disturbed for a long time by any rainfall. Spatial correlation length on that day was about 400 km. Because of zonal character of frost, the spatial dependences in the examined surface soil moisture distributions during freezing/thawing found to be disturbed. Probably, the amount of water remains the same, but it is not detected by SMOS, hence analysing dielectric constant instead of soil moisture would be more appropriate. Some spatial relations of soil moisture and freezing distribution with existing maps of soil granulometric fractions and soil specific surface area for Poland have also been found. The work was partially funded under the ELBARA_PD (Penetration Depth) project No. 4000107897/13/NL/KML. ELBARA_PD project is funded by the Government of Poland through an ESA (European Space Agency) Contract under the PECS (Plan for European Cooperating States).

SIMPPLLE, version 2.5 user's guide

Treesearch

Jimmie D. Chew; Kirk Moeller; Christine Stalling

2012-01-01

SIMPPLLE is a spatially-interactive, dynamic landscape modeling system for projecting temporal changes in the spatial distribution of vegetation in response to insects, disease, wildland fire, and other natural and management-caused disturbances. SIMPPLLE is designed to provide a balance between incorporating enough complexity and interactions in modeling ecosystem...

The Filtered Abel Transform and Its Application in Combustion Diagnostics

NASA Technical Reports Server (NTRS)

Simons, Stephen N. (Technical Monitor); Yuan, Zeng-Guang

2003-01-01

Many non-intrusive combustion diagnosis methods generate line-of-sight projections of a flame field. To reconstruct the spatial field of the measured properties, these projections need to be deconvoluted. When the spatial field is axisymmetric, commonly used deconvolution method include the Abel transforms, the onion peeling method and the two-dimensional Fourier transform method and its derivatives such as the filtered back projection methods. This paper proposes a new approach for performing the Abel transform method is developed, which possesses the exactness of the Abel transform and the flexibility of incorporating various filters in the reconstruction process. The Abel transform is an exact method and the simplest among these commonly used methods. It is evinced in this paper that all the exact reconstruction methods for axisymmetric distributions must be equivalent to the Abel transform because of its uniqueness and exactness. Detailed proof is presented to show that the two dimensional Fourier methods when applied to axisymmetric cases is identical to the Abel transform. Discrepancies among various reconstruction method stem from the different approximations made to perform numerical calculations. An equation relating the spectrum of a set of projection date to that of the corresponding spatial distribution is obtained, which shows that the spectrum of the projection is equal to the Abel transform of the spectrum of the corresponding spatial distribution. From the equation, if either the projection or the distribution is bandwidth limited, the other is also bandwidth limited, and both have the same bandwidth. If the two are not bandwidth limited, the Abel transform has a bias against low wave number components in most practical cases. This explains why the Abel transform and all exact deconvolution methods are sensitive to high wave number noises. The filtered Abel transform is based on the fact that the Abel transform of filtered projection data is equal to an integral transform of the original projection data with the kernel function being the Abel transform of the filtering function. The kernel function is independent of the projection data and can be obtained separately when the filtering function is selected. Users can select the best filtering function for a particular set of experimental data. When the kernal function is obtained, it can be used repeatedly to a number of projection data sets (rovs) from the same experiment. When an entire flame image that contains a large number of projection lines needs to be processed, the new approach significantly reduces computational effort in comparison with the conventional approach in which each projection data set is deconvoluted separately. Computer codes have been developed to perform the filter Abel transform for an entire flame field. Measured soot volume fraction data of a jet diffusion flame are processed as an example.

Modeling nonbreeding distributions of shorebirds and waterfowl in response to climate change

USGS Publications Warehouse

Reese, Gordon; Skagen, Susan K.

2017-01-01

To identify areas on the landscape that may contribute to a robust network of conservation areas, we modeled the probabilities of occurrence of several en route migratory shorebirds and wintering waterfowl in the southern Great Plains of North America, including responses to changing climate. We predominantly used data from the eBird citizen-science project to model probabilities of occurrence relative to land-use patterns, spatial distribution of wetlands, and climate. We projected models to potential future climate conditions using five representative general circulation models of the Coupled Model Intercomparison Project 5 (CMIP5). We used Random Forests to model probabilities of occurrence and compared the time periods 1981–2010 (hindcast) and 2041–2070 (forecast) in “model space.” Projected changes in shorebird probabilities of occurrence varied with species-specific general distribution pattern, migration distance, and spatial extent. Species using the western and northern portion of the study area exhibited the greatest likelihoods of decline, whereas species with more easterly occurrences, mostly long-distance migrants, had the greatest projected increases in probability of occurrence. At an ecoregional extent, differences in probabilities of shorebird occurrence ranged from −0.015 to 0.045 when averaged across climate models, with the largest increases occurring early in migration. Spatial shifts are predicted for several shorebird species. Probabilities of occurrence of wintering Mallards and Northern Pintail are predicted to increase by 0.046 and 0.061, respectively, with northward shifts projected for both species. When incorporated into partner land management decision tools, results at ecoregional extents can be used to identify wetland complexes with the greatest potential to support birds in the nonbreeding season under a wide range of future climate scenarios.

Space, relations, and the learning of science

NASA Astrophysics Data System (ADS)

Roth, Wolff-Michael; Hsu, Pei-Ling

2014-03-01

In the literature on the situated and distributed nature of cognition, the coordination of spatial organization and the structure of human practices and relations is accepted as a fact. To date, science educators have yet to build on such research. Drawing on an ethnographic study of high school students during an internship in a scientific research laboratory, which we understand as a "perspicuous setting" and a "smart setting," in which otherwise invisible dimensions of human practices become evident, we analyze the relationship between spatial configurations of the setting and the nature and temporal organization of knowing and learning in science. Our analyses show that spatial aspects of the laboratory projectively organize how participants act and can serve as resources to help the novices to participate in difficult and unfamiliar tasks. First, existing spatial relations projectively organize the language involving interns and lab members. In particular, spatial relations projectively organize where and when pedagogical language should happen; and there are specific discursive mechanisms that produce cohesion in language across different places in the laboratory. Second, the spatial arrangements projectively organize the temporal dimensions of action. These findings allow science educators to think explicitly about organizing "smart contexts" that help learners participate in and learn complex scientific laboratory practices.

Data Publishing Services in a Scientific Project Platform

NASA Astrophysics Data System (ADS)

Schroeder, Matthias; Stender, Vivien; Wächter, Joachim

2014-05-01

Data-intensive science lives from data. More and more interdisciplinary projects are aligned to mutually gain access to their data, models and results. In order to achieving this, an umbrella project GLUES is established in the context of the "Sustainable Land Management" (LAMA) initiative funded by the German Federal Ministry of Education and Research (BMBF). The GLUES (Global Assessment of Land Use Dynamics, Greenhouse Gas Emissions and Ecosystem Services) project supports several different regional projects of the LAMA initiative: Within the framework of GLUES a Spatial Data Infrastructure (SDI) is implemented to facilitate publishing, sharing and maintenance of distributed global and regional scientific data sets as well as model results. The GLUES SDI supports several OGC webservices like the Catalog Service Web (CSW) which enables it to harvest data from varying regional projects. One of these regional projects is SuMaRiO (Sustainable Management of River Oases along the Tarim River) which aims to support oasis management along the Tarim River (PR China) under conditions of climatic and societal changes. SuMaRiO itself is an interdisciplinary and spatially distributed project. Working groups from twelve German institutes and universities are collecting data and driving their research in disciplines like Hydrology, Remote Sensing, and Agricultural Sciences among others. Each working group is dependent on the results of another working group. Due to the spatial distribution of participating institutes the data distribution is solved by using the eSciDoc infrastructure at the German Research Centre for Geosciences (GFZ). Further, the metadata based data exchange platform PanMetaDocs will be used by participants collaborative. PanMetaDocs supports an OAI-PMH interface which enables an Open Source metadata portal like GeoNetwork to harvest the information. The data added in PanMetaDocs can be labeled with a DOI (Digital Object Identifier) to publish the data and to harvest this information subsequently by the GLUES SDI. Our contribution will show the architecture of this new established SuMaRiO infrastructure node in a superordinate network of the GLUES infrastructure.

The Effect of Stereoscopic ("3D") vs. 2D Presentation on Learning through Video and Film

NASA Astrophysics Data System (ADS)

Price, Aaron; Kasal, E.

2014-01-01

Two Eyes, 3D is a NSF-funded research project into the effects of stereoscopy on learning of highly spatial concepts. We report final results on one study of the project which tested the effect of stereoscopic presentation on learning outcomes of two short films about Type 1a supernovae and the morphology of the Milky Way. 986 adults watched either film, randomly distributed between stereoscopic and 2D presentation. They took a pre-test and post-test that included multiple choice and drawing tasks related to the spatial nature of the topics in the film. Orientation of the answering device was also tracked and a spatial cognition pre-test was given to control for prior spatial ability. Data collection took place at the Adler Planetarium's Space Visualization Lab and the project is run through the AAVSO.

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

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

Predicted altitudinal shifts and reduced spatial distribution of Leishmania infantum vector species under climate change scenarios in Colombia.

PubMed

González, Camila; Paz, Andrea; Ferro, Cristina

2014-01-01

Visceral leishmaniasis (VL) is caused by the trypanosomatid parasite Leishmania infantum (=Leishmania chagasi), and is epidemiologically relevant due to its wide geographic distribution, the number of annual cases reported and the increase in its co-infection with HIV. Two vector species have been incriminated in the Americas: Lutzomyia longipalpis and Lutzomyia evansi. In Colombia, L. longipalpis is distributed along the Magdalena River Valley while L. evansi is only found in the northern part of the Country. Regarding the epidemiology of the disease, in Colombia the incidence of VL has decreased over the last few years without any intervention being implemented. Additionally, changes in transmission cycles have been reported with urban transmission occurring in the Caribbean Coast. In Europe and North America climate change seems to be driving a latitudinal shift of leishmaniasis transmission. Here, we explored the spatial distribution of the two known vector species of L. infantum in Colombia and projected its future distribution into climate change scenarios to establish the expansion potential of the disease. An updated database including L. longipalpis and L. evansi collection records from Colombia was compiled. Ecological niche models were performed for each species using the Maxent software and 13 Worldclim bioclimatic coverages. Projections were made for the pessimistic CSIRO A2 scenario, which predicts the higher increase in temperature due to non-emission reduction, and the optimistic Hadley B2 Scenario predicting the minimum increase in temperature. The database contained 23 records for L. evansi and 39 records for L. longipalpis, distributed along the Magdalena River Valley and the Caribbean Coast, where the potential distribution areas of both species were also predicted by Maxent. Climate change projections showed a general overall reduction in the spatial distribution of the two vector species, promoting a shift in altitudinal distribution for L. longipalpis and confining L. evansi to certain regions in the Caribbean Coast. Altitudinal shifts have been reported for cutaneous leishmaniasis vectors in Colombia and Peru. Here, we predict the same outcome for VL vectors in Colombia. Changes in spatial distribution patterns could be affecting local abundances due to climatic pressures on vector populations thus reducing the incidence of human cases. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

GIS-and Web-based Water Resource Geospatial Infrastructure for Oil Shale Development

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

Zhou, Wei; Minnick, Matthew; Geza, Mengistu

2012-09-30

The Colorado School of Mines (CSM) was awarded a grant by the National Energy Technology Laboratory (NETL), Department of Energy (DOE) to conduct a research project en- titled GIS- and Web-based Water Resource Geospatial Infrastructure for Oil Shale Development in October of 2008. The ultimate goal of this research project is to develop a water resource geo-spatial infrastructure that serves as “baseline data” for creating solutions on water resource management and for supporting decisions making on oil shale resource development. The project came to the end on September 30, 2012. This final project report will report the key findings frommore » the project activity, major accomplishments, and expected impacts of the research. At meantime, the gamma version (also known as Version 4.0) of the geodatabase as well as other various deliverables stored on digital storage media will be send to the program manager at NETL, DOE via express mail. The key findings from the project activity include the quantitative spatial and temporal distribution of the water resource throughout the Piceance Basin, water consumption with respect to oil shale production, and data gaps identified. Major accomplishments of this project include the creation of a relational geodatabase, automated data processing scripts (Matlab) for database link with surface water and geological model, ArcGIS Model for hydrogeologic data processing for groundwater model input, a 3D geological model, surface water/groundwater models, energy resource development systems model, as well as a web-based geo-spatial infrastructure for data exploration, visualization and dissemination. This research will have broad impacts of the devel- opment of the oil shale resources in the US. The geodatabase provides a “baseline” data for fur- ther study of the oil shale development and identification of further data collection needs. The 3D geological model provides better understanding through data interpolation and visualization techniques of the Piceance Basin structure spatial distribution of the oil shale resources. The sur- face water/groundwater models quantify the water shortage and better understanding the spatial distribution of the available water resources. The energy resource development systems model reveals the phase shift of water usage and the oil shale production, which will facilitate better planning for oil shale development. Detailed descriptions about the key findings from the project activity, major accomplishments, and expected impacts of the research will be given in the sec- tion of “ACCOMPLISHMENTS, RESULTS, AND DISCUSSION” of this report.« less

Age-related changes in rostral basal forebrain cholinergic and GABAergic projection neurons: Relationship with spatial impairment

PubMed Central

Bañuelos, C.; LaSarge, C. L.; McQuail, J. A.; Hartman, J. J.; Gilbert, R. J.; Ormerod, B. K.; Bizon, J. L.

2013-01-01

Both cholinergic and GABAergic projections from the rostral basal forebrain have been implicated in hippocampal function and mnemonic abilities. While dysfunction of cholinergic neurons has been heavily implicated in age-related memory decline, significantly less is known regarding how age-related changes in co-distributed GABAergic projection neurons contribute to a decline in hippocampal-dependent spatial learning. In the current study, confocal stereology was used to quantify cholinergic (choline acetyltransferase (ChAT) immunopositive) neurons, GABAergic projection (glutamic decarboxylase 67 (GAD67) immunopositive) neurons, and total (NeuN immunopositive) neurons in the rostral basal forebrain of young and aged rats that were first characterized on a spatial learning task. ChAT immunopositive neurons were significantly but modestly reduced in aged rats. Although ChAT immunopositive neuron number was strongly correlated with spatial learning abilities among young rats, the reduction of ChAT immunopositive neurons was not associated with impaired spatial learning in aged rats. In contrast, the number of GAD67 immunopositive neurons was robustly and selectively elevated in aged rats that exhibited impaired spatial learning. Interestingly, the total number of rostral basal forebrain neurons was comparable in young and aged rats, regardless of their cognitive status. These data demonstrate differential effects of age on phenotypically distinct rostral basal forebrain projection neurons, and implicate dysregulated cholinergic and GABAergic septohippocampal circuitry in age-related mnemonic decline. PMID:22817834

Modelling climate change effects on benthos: Distributional shifts in the North Sea from 2001 to 2099

NASA Astrophysics Data System (ADS)

Weinert, Michael; Mathis, Moritz; Kröncke, Ingrid; Neumann, Hermann; Pohlmann, Thomas; Reiss, Henning

2016-06-01

In the marine realm, climate change can affect a variety of physico-chemical properties with wide-ranging biological effects, but the knowledge of how climate change affects benthic distributions is limited and mainly restricted to coastal environments. To project the response of benthic species of a shelf sea (North Sea) to the expected climate change, the distributions of 75 marine benthic species were modelled and the spatial changes in distribution were projected for 2099 based on modelled bottom temperature and salinity changes using the IPCC scenario A1B. Mean bottom temperature was projected to increase between 0.15 and 5.4 °C, while mean bottom salinity was projected to moderately increase by 1.7. The spatial changes in species distribution were modelled with Maxent and the direction and extent of these changes were assessed. The results showed a latitudinal northward shift for 64% of the species (maximum 109 km; brittle star Ophiothrix fragilis) and a southward shift for 36% (maximum 101 km; hermit crab Pagurus prideaux and the associated cloak anemone Adamsia carciniopados; 105 km). The relatively low rates of distributional shifts compared to fish or plankton species were probably influenced by the regional topography. The environmental gradients in the central North Sea along the 50 m depth contour might act as a 'barrier', possibly resulting in a compression of distribution range and hampering further shifts to the north. For 49 species this resulted in a habitat loss up to 100%, while only 11 species could benefit from the warming in terms of habitat gain. Particularly the benthic communities of the southern North Sea, where the strongest temperature increase was projected, would be strongly affected by the distributional changes, since key species showed northward shifts and high rates of habitat loss, with potential ramifications for the functioning of the ecosystem.

Transit time distributions to assess present and future contamination risk of karst aquifers over Europe and the Mediterranean

NASA Astrophysics Data System (ADS)

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

2016-04-01

Karst develops through the dissolution of carbonate rock. Karst groundwater in Europe is a major source of fresh water contributing up to half of the total drinking water supply in some countries. Climate model projections suggest that in the next 100 years, karst regions will experience a strong increase in temperature and a serious decrease of precipitation - especially in the Mediterranean region. Previous work showed that the karstic preferential recharge processes result in enhanced recharge rates and future climate sensitivity. But as there is fast water flow form the surface to the aquifer, there is also an enhanced risk of groundwater contamination. In this study we will assess the contamination risk of karst aquifers over Europe and the Mediterranean using simulated transit time distributions. Using a new type of semi-distributed model that considers the spatial heterogeneity of the karst system by distribution functions we simulated a range of spatially variable pathways of karstic groundwater recharge. The model is driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). Transit time distributions are calculated by virtual tracer experiments. These are repeated several times in the present (1991-2010) and the future (2080-2099). We can show that regions with larger fractions of preferential recharge show higher risks of contamination and that spatial patterns of contamination risk change towards the future.

Projecting changes in the distribution and productivity of living marine resources: A critical review of the suite of modelling approaches used in the large European project VECTORS

NASA Astrophysics Data System (ADS)

Peck, Myron A.; Arvanitidis, Christos; Butenschön, Momme; Canu, Donata Melaku; Chatzinikolaou, Eva; Cucco, Andrea; Domenici, Paolo; Fernandes, Jose A.; Gasche, Loic; Huebert, Klaus B.; Hufnagl, Marc; Jones, Miranda C.; Kempf, Alexander; Keyl, Friedemann; Maar, Marie; Mahévas, Stéphanie; Marchal, Paul; Nicolas, Delphine; Pinnegar, John K.; Rivot, Etienne; Rochette, Sébastien; Sell, Anne F.; Sinerchia, Matteo; Solidoro, Cosimo; Somerfield, Paul J.; Teal, Lorna R.; Travers-Trolet, Morgan; van de Wolfshaar, Karen E.

2018-02-01

We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

Spatial modeling to project Southern Appalachian Trout distribution in warmer climate

Treesearch

Patrica A. Flebbe; Laura D. Roghair; Jennifer L. Bruggink

2006-01-01

In the southern Appalachian Mountains, the distributions of native brook trout Salvelinus fontinalis and introduced rainbow trout Oncorhynchus mykiss and brown trout Salmo trutta are presently limited by temperature and are expected to be limited further by a warmer climate. To estimate trout habitat in a future...

Microclimate predicts within-season distribution dynamics of montane forest birds

Treesearch

Sarah J.K. Frey; Adam S. Hadley; Matthew G. Betts; Mark Robertson

2016-01-01

Aim: Climate changes are anticipated to have pervasive negative effects on biodiversity and are expected to necessitate widespread range shifts or contractions. Such projections are based upon the assumptions that (1) species respond primarily to broad-scale climatic regimes, or (2) that variation in climate at fine spatial scales is less relevant at coarse spatial...

Legacies of Lead in Charm City's Soil: Lessons from the Baltimore Ecosystem Study

Treesearch

Kirsten Schwarz; Richard Pouyat; Ian Yesilonis

2016-01-01

Understanding the spatial distribution of soil lead has been a focus of the Baltimore Ecosystem Study since its inception in 1997. Through multiple research projects that span spatial scales and use different methodologies, three overarching patterns have been identified: (1) soil lead concentrations often exceed state and federal regulatory limits; (2) the variability...

Spatial patterns of carbon, biodiversity, deforestation threat, and REDD+ projects in Indonesia.

PubMed

Murray, Josil P; Grenyer, Richard; Wunder, Sven; Raes, Niels; Jones, Julia P G

2015-10-01

There are concerns that Reduced Emissions from Deforestation and forest Degradation (REDD+) may fail to deliver potential biodiversity cobenefits if it is focused on high carbon areas. We explored the spatial overlaps between carbon stocks, biodiversity, projected deforestation threats, and the location of REDD+ projects in Indonesia, a tropical country at the forefront of REDD+ development. For biodiversity, we assembled data on the distribution of terrestrial vertebrates (ranges of amphibians, mammals, birds, reptiles) and plants (species distribution models for 8 families). We then investigated congruence between different measures of biodiversity richness and carbon stocks at the national and subnational scales. Finally, we mapped active REDD+ projects and investigated the carbon density and potential biodiversity richness and modeled deforestation pressures within these forests relative to protected areas and unprotected forests. There was little internal overlap among the different hotspots (richest 10% of cells) of species richness. There was also no consistent spatial congruence between carbon stocks and the biodiversity measures: a weak negative correlation at the national scale masked highly variable and nonlinear relationships island by island. Current REDD+ projects were preferentially located in areas with higher total species richness and threatened species richness but lower carbon densities than protected areas and unprotected forests. Although a quarter of the total area of these REDD+ projects is under relatively high deforestation pressure, the majority of the REDD+ area is not. In Indonesia at least, first-generation REDD+ projects are located where they are likely to deliver biodiversity benefits. However, if REDD+ is to deliver additional gains for climate and biodiversity, projects will need to focus on forests with the highest threat to deforestation, which will have cost implications for future REDD+ implementation. © 2015 The Authors. Conservation Biology published by Wiley Periodicals, Inc., on behalf of Society for Conservation Biology.

Capturing spatial heterogeneity of soil organic carbon under changing climate

NASA Astrophysics Data System (ADS)

Mishra, U.; Fan, Z.; Jastrow, J. D.; Matamala, R.; Vitharana, U.

2015-12-01

The spatial heterogeneity of the land surface affects water, energy, and greenhouse gas exchanges with the atmosphere. Designing observation networks that capture land surface spatial heterogeneity is a critical scientific challenge. Here, we present a geospatial approach to capture the existing spatial heterogeneity of soil organic carbon (SOC) stocks across Alaska, USA. We used the standard deviation of 556 georeferenced SOC profiles previously compiled in Mishra and Riley (2015, Biogeosciences, 12:3993-4004) to calculate the number of observations that would be needed to reliably estimate Alaskan SOC stocks. This analysis indicated that 906 randomly distributed observation sites would be needed to quantify the mean value of SOC stocks across Alaska at a confidence interval of ± 5 kg m-2. We then used soil-forming factors (climate, topography, land cover types, surficial geology) to identify the locations of appropriately distributed observation sites by using the conditioned Latin hypercube sampling approach. Spatial correlation and variogram analyses demonstrated that the spatial structures of soil-forming factors were adequately represented by these 906 sites. Using the spatial correlation length of existing SOC observations, we identified 484 new observation sites would be needed to provide the best estimate of the present status of SOC stocks in Alaska. We then used average decadal projections (2020-2099) of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change to investigate whether the location of identified observation sites will shift/change under future climate. Our results showed 12-41 additional observation sites (depending on emission scenarios) will be required to capture the impact of projected climatic conditions by 2100 on the spatial heterogeneity of Alaskan SOC stocks. Our results represent an ideal distribution of observation sites across Alaska that captures the land surface spatial heterogeneity and can be used in efforts to quantify SOC stocks, monitor greenhouse gas emissions, and benchmark Earth System Model results.

A spatially distributed model for assessment of the effects of changing land use and climate on urban stream quality: Development of a Spatially Distributed Urban Water Quality Model

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

Sun, Ning; Yearsley, John; Baptiste, Marisa

While the effects of land use change in urban areas have been widely examined, the combined effects of climate and land use change on the quality of urban and urbanizing streams have received much less attention. We describe a modeling framework that is applicable to the evaluation of potential changes in urban water quality and associated hydrologic changes in response to ongoing climate and landscape alteration. The grid-based spatially distributed model, DHSVM-WQ, is an outgrowth of the Distributed Hydrology-Soil-Vegetation Model (DHSVM) that incorporates modules for assessing hydrology and water quality in urbanized watersheds at a high spatial and temporal resolution.more » DHSVM-WQ simulates surface runoff quality and in-stream processes that control the transport of nonpoint-source (NPS) pollutants into urban streams. We configure DHSVM-WQ for three partially urbanized catchments in the Puget Sound region to evaluate the water quality responses to current conditions and projected changes in climate and/or land use over the next century. Here we focus on total suspended solids (TSS) and total phosphorus (TP) from nonpoint sources (runoff), as well as stream temperature. The projection of future land use is characterized by a combination of densification in existing urban or partially urban areas, and expansion of the urban footprint. The climate change scenarios consist of individual and concurrent changes in temperature and precipitation. Future precipitation is projected to increase in winter and decrease in summer, while future temperature is projected to increase throughout the year. Our results show that urbanization has a much greater effect than climate change on both the magnitude and seasonal variability of streamflow, TSS and TP loads largely due to substantially increased streamflow, and particularly winter flow peaks. Water temperature is more sensitive to climate warming scenarios than to urbanization and precipitation changes. Future urbanization and climate change together are predicted to significantly increase annual mean streamflow (up to 55%), water temperature (up to 1.9 ºC), TSS load (up to 182%), and TP load (up to 74%).« less

Climate suitability for European ticks: assessing species distribution models against null models and projection under AR5 climate.

PubMed

Williams, Hefin Wyn; Cross, Dónall Eoin; Crump, Heather Louise; Drost, Cornelis Jan; Thomas, Christopher James

2015-08-28

There is increasing evidence that the geographic distribution of tick species is changing. Whilst correlative Species Distribution Models (SDMs) have been used to predict areas that are potentially suitable for ticks, models have often been assessed without due consideration for spatial patterns in the data that may inflate the influence of predictor variables on species distributions. This study used null models to rigorously evaluate the role of climate and the potential for climate change to affect future climate suitability for eight European tick species, including several important disease vectors. We undertook a comparative assessment of the performance of Maxent and Mahalanobis Distance SDMs based on observed data against those of null models based on null species distributions or null climate data. This enabled the identification of species whose distributions demonstrate a significant association with climate variables. Latest generation (AR5) climate projections were subsequently used to project future climate suitability under four Representative Concentration Pathways (RCPs). Seven out of eight tick species exhibited strong climatic signals within their observed distributions. Future projections intimate varying degrees of northward shift in climate suitability for these tick species, with the greatest shifts forecasted under the most extreme RCPs. Despite the high performance measure obtained for the observed model of Hyalomma lusitanicum, it did not perform significantly better than null models; this may result from the effects of non-climatic factors on its distribution. By comparing observed SDMs with null models, our results allow confidence that we have identified climate signals in tick distributions that are not simply a consequence of spatial patterns in the data. Observed climate-driven SDMs for seven out of eight species performed significantly better than null models, demonstrating the vulnerability of these tick species to the effects of climate change in the future.

Projected Irrigation Requirement Under Climate Change in Korean Peninsula by Apply Global Hydrologic Model to Local Scale.

NASA Astrophysics Data System (ADS)

Yang, B.; Lee, D. K.

2016-12-01

Understanding spatial distribution of irrigation requirement is critically important for agricultural water management. However, many studies considering future agricultural water management in Korea assessed irrigation requirement on watershed or administrative district scale, but have not accounted the spatial distribution. Lumped hydrologic model has typically used in Korea for simulating watershed scale irrigation requirement, while distribution hydrologic model can simulate the spatial distribution grid by grid. To overcome this shortcoming, here we applied a grid base global hydrologic model (H08) into local scale to estimate spatial distribution under future irrigation requirement of Korean Peninsula. Korea is one of the world's most densely populated countries, with also high produce and demand of rice which requires higher soil moisture than other crops. Although, most of the precipitation concentrate in particular season and disagree with crop growth season. This precipitation character makes management of agricultural water which is approximately 60% of total water usage critical issue in Korea. Furthermore, under future climate change, the precipitation predicted to be more concentrated and necessary need change of future water management plan. In order to apply global hydrological model into local scale, we selected appropriate major crops under social and local climate condition in Korea to estimate cropping area and yield, and revised the cropping area map more accurately. As a result, future irrigation requirement estimation varies under each projection, however, slightly decreased in most case. The simulation reveals, evapotranspiration increase slightly while effective precipitation also increase to balance the irrigation requirement. This finding suggest practical guideline to decision makers for further agricultural water management plan including future development of water supply plan to resolve water scarcity.

Spatially distributed evapotranspiration and recharge estimation for sand regions of Hungary in the context of climate change

NASA Astrophysics Data System (ADS)

Csáki, Péter; Kalicz, Péter; Gribovszki, Zoltán

2016-04-01

Water balance of sand regions of Hungary was analysed using remote-sensing based evapotranspiration (ET) maps (1*1 km spatial resolution) by CREMAP model over the 2000-2008 period. The mean annual (2000-2008) net groundwater recharge (R) estimated as the difference in mean annual precipitation (P) and ET, taking advantage that for sand regions the surface runoff is commonly negligible. For the examined nine-year period (2000-2008) the ET and R were about 90 percent and 10 percent of the P. The mean annual ET and R were analysed in the context of land cover types. A Budyko-model was used in spatially-distributed mode for the climate change impact analysis. The parameters of the Budyko-model (α) was calculated for pixels without surplus water. For the extra-water affected pixels a linear model with β-parameters (actual evapotranspiration / pan-evapotranspiration) was used. These parameter maps can be used for evaluating future ET and R in spatially-distributed mode (1*1 km resolution). By using the two parameter maps (α and β) and data of regional climate models (mean annual temperature and precipitation) evapotranspiration and net groundwater recharge projections have been done for three future periods (2011-2040, 2041-2070, 2071-2100). The expected ET and R changes have been determined relative to a reference period (1981-2010). According to the projections, by the end of the 21th century, ET may increase while in case of R a heavy decrease can be detected for the sand regions of Hungary. This research has been supported by Agroclimate.2 VKSZ_12-1-2013-0034 project. Keywords: evapotranspiration, net groundwater recharge, climate change, Budyko-model

The Estrada Real project and endemic diseases: the case of schistosomiasis, geoprocessing and tourism.

PubMed

Carvalho, Omar S; Scholte, Ronaldo G C; Guimarães, Ricardo J P S; Freitas, Corina C; Drummond, Sandra C; Amaral, Ronaldo S; Dutra, Luciano V; Oliveira, Guilherme; Massara, Cristiano L; Enk, Martin J

2010-07-01

Geographical Information System (GIS) is a tool that has recently been applied to better understand spatial disease distributions. Using meteorological, social, sanitation, mollusc distribution data and remote sensing variables, this study aimed to further develop the GIS technology by creating a model for the spatial distribution of schistosomiasis and to apply this model to an area with rural tourism in the Brazilian state of Minas Gerais (MG). The Estrada Real, covering about 1,400 km, is the largest and most important Brazilian tourism project, involving 163 cities in MG with different schistosomiasis prevalence rates. The model with three variables showed a R(2) = 0.34, with a standard deviation of risk estimated adequate for public health needs. The main variables selected for modelling were summer vegetation, summer minimal temperature and winter minimal temperature. The results confirmed the importance of Remote Sensing data and the valuable contribution of GIS in identifying priority areas for intervention in tourism regions which are endemic to schistosomiasis.

A probabilistic approach to modeling erosion for spatially-varied conditions

Treesearch

William J. Elliot; Peter R. Robichaud; C. D. Pannkuk

2001-01-01

In the years following a major forest disturbance, such as fire, the erosion rate is greatly influenced by variability in weather, in soil properties, and in spatial distribution. This paper presents a method to incorporate these variabilities into the erosion rate predicted by the Water Erosion Prediction Project model. It appears that it is not necessary to describe...

Multi-criteria decision analysis in conservation planning: Designing conservation area networks in San Diego County

NASA Astrophysics Data System (ADS)

MacDonald, Garrick Richard

To limit biodiversity loss caused by human activity, conservation planning must protect biodiversity while considering socio-economic cost criteria. This research aimed to determine the effects of socio-economic criteria and spatial configurations on the development of CANs for three species with different distribution patterns, while simultaneously attempting to address the uncertainty and sensitivity of CANs produced by ConsNet. The socio-economic factors and spatial criteria included the cost of land, population density, agricultural output value, area, average cluster area, number of clusters, shape, and perimeter. Three sensitive mammal species with different distribution patterns were selected and included the Bobcat, Ringtail, and a custom created mammal distribution. Forty problems and the corresponding number of CANs were formulated and computed by running each predicted presence species model with and without the four different socioeconomic threshold groups at two different resolutions. Thirty-two percent less area was conserved after considering multiple socio-economic constraints and spatial configurations in comparison to CANs that did not consider multiple socio-economic constraints and spatial configurations. Without including socio-economic costs, ConsNet's ALL_CELLS heuristic solution was the highest ranking CAN. After considering multiple socio-economic costs, the number one ranking CAN was no longer the ALL_CELLS heuristic solution, but a spatially different meta-heuristic solution. The effects of multiple constraints and objectives on the design of CANs with different distribution patterns did not vary significantly across the criteria. The CANs produced by ConsNet appeared to demonstrate some uncertainty surrounding particular criteria, but did not demonstrate substantial uncertainty across all criteria used to rank the CANs. Similarly, the range of socio-economic criteria thresholds did not have a substantial impact. ConsNet was very applicable to the research project, however, it did exhibit a few limitations. Both the advantages and disadvantages of ConsNet should be considered before using ConsNet for future conservation planning projects. The research project is an example of a large data scenario undertaken with a multiple criteria decision analysis (MCDA) approach.

Does scale matter? A systematic review of incorporating biological realism when predicting changes in species distributions.

PubMed

Record, Sydne; Strecker, Angela; Tuanmu, Mao-Ning; Beaudrot, Lydia; Zarnetske, Phoebe; Belmaker, Jonathan; Gerstner, Beth

2018-01-01

There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species' responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. We systematically reviewed SDM studies published from 2003-2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis.

High resolution population distribution maps for Southeast Asia in 2010 and 2015.

PubMed

Gaughan, Andrea E; Stevens, Forrest R; Linard, Catherine; Jia, Peng; Tatem, Andrew J

2013-01-01

Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org.

High Resolution Population Distribution Maps for Southeast Asia in 2010 and 2015

PubMed Central

Gaughan, Andrea E.; Stevens, Forrest R.; Linard, Catherine; Jia, Peng; Tatem, Andrew J.

2013-01-01

Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org. PMID:23418469

Tracing the assembly history of NGC 1395 through its Globular Cluster System

NASA Astrophysics Data System (ADS)

Escudero, Carlos G.; Faifer, Favio R.; Smith Castelli, Analía V.; Forte, Juan C.; Sesto, Leandro A.; González, Nélida M.; Scalia, María C.

2018-03-01

We used deep Gemini-South/GMOS g΄r΄i΄z΄ images to study the globular cluster (GC) system of the massive elliptical galaxy NGC 1395, located in the Eridanus supergroup. The photometric analysis of the GC candidates reveals a clear colour bimodality distribution, indicating the presence of `blue' and `red' GC subpopulations. While a negative radial colour gradient is detected in the projected spatial distribution of the red GCs, the blue GCs display a shallow colour gradient. The blue GCs also display a remarkable shallow and extended surface density profile, suggesting a significant accretion of low-mass satellites in the outer halo of the galaxy. In addition, the slope of the projected spatial distribution of the blue GCs in the outer regions of the galaxy, is similar to that of the X-ray halo emission. Integrating up to 165 kpc the profile of the projected spatial distribution of the GCs, we estimated a total GC population and specific frequency of 6000 ± 1100 and SN = 7.4 ± 1.4, respectively. Regarding NGC 1395 itself, the analysis of the deep Gemini/GMOS images shows a low surface brightness umbrella-like structure indicating, at least, one recent merger event. Through relations recently published in the literature, we obtained global parameters, such as Mstellar = 9.32 × 1011 M⊙ and Mh = 6.46 × 1013 M⊙. Using public spectroscopic data, we derive stellar population parameters of the central region of the galaxy by the full spectral fitting technique. We have found that this region seems to be dominated for an old stellar population, in contrast to findings of young stellar populations from the literature.

THE SIZE DIFFERENCE BETWEEN RED AND BLUE GLOBULAR CLUSTERS IS NOT DUE TO PROJECTION EFFECTS

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

Webb, Jeremy J.; Harris, William E.; Sills, Alison, E-mail: webbjj@mcmaster.ca

Metal-rich (red) globular clusters in massive galaxies are, on average, smaller than metal-poor (blue) globular clusters. One of the possible explanations for this phenomenon is that the two populations of clusters have different spatial distributions. We test this idea by comparing clusters observed in unusually deep, high signal-to-noise images of M87 with a simulated globular cluster population in which the red and blue clusters have different spatial distributions, matching the observations. We compare the overall distribution of cluster effective radii as well as the relationship between effective radius and galactocentric distance for both the observed and simulated red and bluemore » sub-populations. We find that the different spatial distributions does not produce a significant size difference between the red and blue sub-populations as a whole or at a given galactocentric distance. These results suggest that the size difference between red and blue globular clusters is likely due to differences during formation or later evolution.« less

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.

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.

Projected climate-induced habitat loss for salmonids in the John Day River network, Oregon, U.S.A.

USGS Publications Warehouse

Ruesch, Aaron S.; Torgersen, Christian E.; Lawler, Joshua J.; Olden, Julian D.; Peterson, Erin E.; Volk, Carol J.; Lawrence, David J.

2012-01-01

Climate change will likely have profound effects on cold-water species of freshwater fishes. As temperatures rise, cold-water fish distributions may shift and contract in response. Predicting the effects of projected stream warming in stream networks is complicated by the generally poor correlation between water temperature and air temperature. Spatial dependencies in stream networks are complex because the geography of stream processes is governed by dimensions of flow direction and network structure. Therefore, forecasting climate-driven range shifts of stream biota has lagged behind similar terrestrial modeling efforts. We predicted climate-induced changes in summer thermal habitat for 3 cold-water fish species—juvenile Chinook salmon, rainbow trout, and bull trout (Oncorhynchus tshawytscha, O. mykiss, and Salvelinus confluentus, respectively)—in the John Day River basin, northwestern United States. We used a spatially explicit statistical model designed to predict water temperature in stream networks on the basis of flow and spatial connectivity. The spatial distribution of stream temperature extremes during summers from 1993 through 2009 was largely governed by solar radiation and interannual extremes of air temperature. For a moderate climate change scenario, estimated declines by 2100 in the volume of habitat for Chinook salmon, rainbow trout, and bull trout were 69–95%, 51–87%, and 86–100%, respectively. Although some restoration strategies may be able to offset these projected effects, such forecasts point to how and where restoration and management efforts might focus.

An open source platform for multi-scale spatially distributed simulations of microbial ecosystems

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

Segre, Daniel

2014-08-14

The goal of this project was to develop a tool for facilitating simulation, validation and discovery of multiscale dynamical processes in microbial ecosystems. This led to the development of an open-source software platform for Computation Of Microbial Ecosystems in Time and Space (COMETS). COMETS performs spatially distributed time-dependent flux balance based simulations of microbial metabolism. Our plan involved building the software platform itself, calibrating and testing it through comparison with experimental data, and integrating simulations and experiments to address important open questions on the evolution and dynamics of cross-feeding interactions between microbial species.

Decadal application of WRF/chem for regional air quality and climate modeling over the U.S. under the representative concentration pathways scenarios. Part 2: Current vs. future simulations

NASA Astrophysics Data System (ADS)

Yahya, Khairunnisa; Campbell, Patrick; Zhang, Yang

2017-03-01

Following a comprehensive model evaluation, this Part II paper presents projected changes in future (2046-2055) climate, air quality, and their interactions under the RCP4.5 and RCP8.5 scenarios using the Weather, Research and Forecasting model with Chemistry (WRF/Chem). In general, both WRF/Chem RCP4.5 and RCP8.5 simulations predict similar increases on average (∼2 °C) for 2-m temperature (T2) but different spatial distributions of the projected changes in T2, 2-m relative humidity, 10-m wind speed, precipitation, and planetary boundary layer height, due to differences in the spatial distributions of projected emissions, and their feedbacks into climate. Future O3 mixing ratios will decrease for most parts of the U.S. under the RCP4.5 scenario but increase for all areas under the RCP8.5 scenario due to higher projected temperature, greenhouse gas concentrations and biogenic volatile organic compounds (VOC) emissions, higher O3 values for boundary conditions, and disbenefit of NOx reduction and decreased NO titration over VOC-limited O3 chemistry regions. Future PM2.5 concentrations will decrease for both RCP4.5 and RCP8.5 scenarios with different trends in projected concentrations of individual PM species. Total cloud amounts decrease under both scenarios in the future due to decreases in PM and cloud droplet number concentration thus increased radiation. Those results illustrate the impacts of carbon policies with different degrees of emission reductions on future climate and air quality. The WRF/Chem and WRF simulations show different spatial patterns for projected changes in T2 for future decade, indicating different impacts of prognostic and prescribed gas/aerosol concentrations, respectively, on climate change.

Long-term impact of the World Bank Loan Project for schistosomiasis control: a comparison of the spatial distribution of schistosomiasis risk in China.

PubMed

Zhang, Zhijie; Zhu, Rong; Ward, Michael P; Xu, Wanghong; Zhang, Lijuan; Guo, Jiagang; Zhao, Fei; Jiang, Qingwu

2012-01-01

The World Bank Loan Project (WBLP) for controlling schistosomiasis in China was implemented during 1992-2001. Its short-term impact has been assessed from non-spatial perspective, but its long-term impact remains unclear and a spatial evaluation has not previously been conducted. Here we compared the spatial distribution of schistosomiasis risk using national datasets in the lake and marshland regions from 1999-2001 and 2007-2008 to evaluate the long-term impact of WBLP strategy on China's schistosomiasis burden. A hierarchical Poisson regression model was developed in a Bayesian framework with spatially correlated and uncorrelated heterogeneities at the county-level, modeled using a conditional autoregressive prior structure and a spatially unstructured Gaussian distribution, respectively. There were two important findings from this study. The WBLP strategy was found to have a good short-term impact on schistosomiasis control, but its long-term impact was not ideal. It has successfully reduced the morbidity of schistosomiasis to a low level, but can not contribute further to China's schistosomiasis control because of the current low endemic level. A second finding is that the WBLP strategy could not effectively compress the spatial distribution of schistosomiasis risk. To achieve further reductions in schistosomiasis-affected areas, and for sustainable control, focusing on the intermediate host snail should become the next step to interrupt schistosomiasis transmission within the two most affected regions surrounding the Dongting and Poyang Lakes. Furthermore, in the lower reaches of the Yangtze River, the WBLP's morbidity control strategy may need to continue for some time until snails in the upriver provinces have been well controlled. It is difficult to further reduce morbidity due to schistosomiasis using a chemotherapy-based control strategy in the lake and marshland regions of China because of the current low endemic levels of infection. The future control strategy for schistosomiasis should instead focus on a snail-based integrated control strategy to maintain the program achievements and sustainably reduce the burden of schistosomiasis in China.

Utilizing a scale model solar system project to visualize important planetary science concepts and develop technology and spatial reasoning skills

NASA Astrophysics Data System (ADS)

Kortenkamp, Stephen J.; Brock, Laci

2016-10-01

Scale model solar systems have been used for centuries to help educate young students and the public about the vastness of space and the relative sizes of objects. We have adapted the classic scale model solar system activity into a student-driven project for an undergraduate general education astronomy course at the University of Arizona. Students are challenged to construct and use their three dimensional models to demonstrate an understanding of numerous concepts in planetary science, including: 1) planetary obliquities, eccentricities, inclinations; 2) phases and eclipses; 3) planetary transits; 4) asteroid sizes, numbers, and distributions; 5) giant planet satellite and ring systems; 6) the Pluto system and Kuiper belt; 7) the extent of space travel by humans and robotic spacecraft; 8) the diversity of extrasolar planetary systems. Secondary objectives of the project allow students to develop better spatial reasoning skills and gain familiarity with technology such as Excel formulas, smart-phone photography, and audio/video editing.During our presentation we will distribute a formal description of the project and discuss our expectations of the students as well as present selected highlights from preliminary submissions.

Into the environment of mosquito-borne disease: A spatial analysis of vector distribution using traditional and remotely sensed methods

NASA Astrophysics Data System (ADS)

Brown, Heidi E.

Spatially explicit information is increasingly available for infectious disease modeling. However, such information is reluctantly or inappropriately incorporated. My dissertation research uses spatially explicit data to assess relationships between landscape and mosquito species distribution and discusses challenges regarding accurate predictive risk modeling. The goal of my research is to use remotely sensed environmental information and spatial statistical methods to better understand mosquito-borne disease epidemiology for improvement of public health responses. In addition to reviewing the progress of spatial infectious disease modeling, I present four research projects. I begin by evaluating the biases in surveillance data and build up to predictive modeling of mosquito species presence. In the first study I explore how mosquito surveillance trap types influence estimations of mosquito populations. Then. I use county-based human surveillance data and landscape variables to identify risk factors for West Nile virus disease. The third study uses satellite-based vegetation indices to identify spatial variation among West Nile virus vectors in an urban area and relates the variability to virus transmission dynamics. Finally, I explore how information from three satellite sensors of differing spatial and spectral resolution can be used to identify and distinguish mosquito habitat across central Connecticut wetlands. Analyses presented here constitute improvements to the prediction of mosquito distribution and therefore identification of disease risk factors. Current methods for mosquito surveillance data collection are labor intensive and provide an extremely limited, incomplete picture of the species composition and abundance. Human surveillance data offers additional challenges with respect to reporting bias and resolution, but is nonetheless informative in identifying environmental risk factors and disease transmission dynamics. Remotely sensed imagery supports mosquito and human disease surveillance data by providing spatially explicit, line resolution information about environmental factors relevant to vector-borne disease processes. Together, surveillance and remotely sensed environmental data facilitate improved description and modeling of disease transmission. Remote sensing can be used to develop predictive maps of mosquito distribution in relation to disease risk. This has implications for increased accuracy of mosquito control efforts. The projects presented in this dissertation enhance current public health capacities by examining the applications of spatial modeling with respect to mosquito-borne disease.

Prioritizing abandoned coal mine reclamation projects within the contiguous United States using geographic information system extrapolation.

PubMed

Gorokhovich, Yuri; Reid, Matthew; Mignone, Erica; Voros, Andrew

2003-10-01

Coal mine reclamation projects are very expensive and require coordination of local and federal agencies to identify resources for the most economic way of reclaiming mined land. Location of resources for mine reclamation is a spatial problem. This article presents a methodology that allows the combination of spatial data on resources for the coal mine reclamation and uses GIS analysis to develop a priority list of potential mine reclamation sites within contiguous United States using the method of extrapolation. The extrapolation method in this study was based on the Bark Camp reclamation project. The mine reclamation project at Bark Camp, Pennsylvania, USA, provided an example of the beneficial use of fly ash and dredged material to reclaim 402,600 sq mi of a mine abandoned in the 1980s. Railroads provided transportation of dredged material and fly ash to the site. Therefore, four spatial elements contributed to the reclamation project at Bark Camp: dredged material, abandoned mines, fly ash sources, and railroads. Using spatial distribution of these data in the contiguous United States, it was possible to utilize GIS analysis to prioritize areas where reclamation projects similar to Bark Camp are feasible. GIS analysis identified unique occurrences of all four spatial elements used in the Bark Camp case for each 1 km of the United States territory within 20, 40, 60, 80, and 100 km radii from abandoned mines. The results showed the number of abandoned mines for each state and identified their locations. The federal or state governments can use these results in mine reclamation planning.

Onondaga Lake Watershed – A Geographic Information System Project Phase I – Needs assessment and spatial data framework

USGS Publications Warehouse

Freehafer, Douglas A.; Pierson, Oliver

2004-01-01

In the fall of 2002, the Onondaga Lake Partnership (OLP) formed a Geographic Information System (GIS) Planning Committee to begin the process of developing a comprehensive watershed geographic information system for Onondaga Lake. The goal of the Onondaga Lake Partnership geographic information system is to integrate the various types of spatial data used for scientific investigations, resource management, and planning and design of improvement projects in the Onondaga Lake Watershed. A needs-assessment survey was conducted and a spatial data framework developed to support the Onondaga Lake Partnership use of geographic information system technology. The design focused on the collection, management, and distribution of spatial data, maps, and internet mapping applications. A geographic information system library of over 100 spatial datasets and metadata links was assembled on the basis of the results of the needs assessment survey. Implementation options were presented, and the Geographic Information System Planning Committee offered recommendations for the management and distribution of spatial data belonging to Onondaga Lake Partnership members. The Onondaga Lake Partnership now has a strong foundation for building a comprehensive geographic information system for the Onondaga Lake watershed. The successful implementation of a geographic information system depends on the Onondaga Lake Partnership’s determination of: (1) the design and plan for a geographic information system, including the applications and spatial data that will be provided and to whom, (2) the level of geographic information system technology to be utilized and funded, and (3) the institutional issues of operation and maintenance of the system.

Complex Network Simulation of Forest Network Spatial Pattern in Pearl River Delta

NASA Astrophysics Data System (ADS)

Zeng, Y.

2017-09-01

Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network's power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network's degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network's main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc.) for networking a standard and base datum.

High-Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

NASA Astrophysics Data System (ADS)

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.; Kotamarthi, V. Rao

2017-12-01

The aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary conditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal-length time slices (2045-2054 and 2085-2094) are compared with a historical decade (1995-2004). Probability density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm-side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm-side shift with decreased variability. Using "business-as-usual" scenario, 5-day heat waves are projected to occur at least 5-10 times per year in most CONUS and ≥95°F days will increase by 1-2 months by the end of the century.

Spatiotemporal analysis of the agricultural drought risk in Heilongjiang Province, China

NASA Astrophysics Data System (ADS)

Pei, Wei; Fu, Qiang; Liu, Dong; Li, Tian-xiao; Cheng, Kun; Cui, Song

2017-06-01

Droughts are natural disasters that pose significant threats to agricultural production as well as living conditions, and a spatial-temporal difference analysis of agricultural drought risk can help determine the spatial distribution and temporal variation of the drought risk within a region. Moreover, this type of analysis can provide a theoretical basis for the identification, prevention, and mitigation of drought disasters. In this study, the overall dispersion and local aggregation of projection points were based on research by Friedman and Tukey (IEEE Trans on Computer 23:881-890, 1974). In this work, high-dimensional samples were clustered by cluster analysis. The clustering results were represented by the clustering matrix, which determined the local density in the projection index. This method avoids the problem of determining a cutoff radius. An improved projection pursuit model is proposed that combines cluster analysis and the projection pursuit model, which offer advantages for classification and assessment, respectively. The improved model was applied to analyze the agricultural drought risk of 13 cities in Heilongjiang Province over 6 years (2004, 2006, 2008, 2010, 2012, and 2014). The risk of an agricultural drought disaster was characterized by 14 indicators and the following four aspects: hazard, exposure, sensitivity, and resistance capacity. The spatial distribution and temporal variation characteristics of the agricultural drought risk in Heilongjiang Province were analyzed. The spatial distribution results indicated that Suihua, Qigihar, Daqing, Harbin, and Jiamusi are located in high-risk areas, Daxing'anling and Yichun are located in low-risk areas, and the differences among the regions were primarily caused by the aspects exposure and resistance capacity. The temporal variation results indicated that the risk of agricultural drought in most areas presented an initially increasing and then decreasing trend. A higher value for the exposure aspect increased the risk of drought, whereas a higher value for the resistance capacity aspect reduced the risk of drought. Over the long term, the exposure level of the region presented limited increases, whereas the resistance capacity presented considerable increases. Therefore, the risk of agricultural drought in Heilongjiang Province will continue to exhibit a decreasing trend.

Optical phase distribution evaluation by using zero order Generalized Morse Wavelet

NASA Astrophysics Data System (ADS)

Kocahan, Özlem; Elmas, Merve Naz; Durmuş, ćaǧla; Coşkun, Emre; Tiryaki, Erhan; Özder, Serhat

2017-02-01

When determining the phase from the projected fringes by using continuous wavelet transform (CWT), selection of wavelet is an important step. A new wavelet for phase retrieval from the fringe pattern with the spatial carrier frequency in the x direction is presented. As a mother wavelet, zero order generalized Morse wavelet (GMW) is chosen because of the flexible spatial and frequency localization property, and it is exactly analytic. In this study, GMW method is explained and numerical simulations are carried out to show the validity of this technique for finding the phase distributions. Results for the Morlet and Paul wavelets are compared with the results of GMW analysis.

Gulf Coast megaregion evacuation traffic simulation modeling and analysis.

DOT National Transportation Integrated Search

2015-12-01

This paper describes a project to develop a micro-level traffic simulation for a megaregion. To : accomplish this, a mass evacuation event was modeled using a traffic demand generation process that : created a spatial and temporal distribution of dep...

Gridded population projections for the coastal zone under the Shared Socioeconomic Pathways

NASA Astrophysics Data System (ADS)

Merkens, Jan-Ludolf; Reimann, Lena; Hinkel, Jochen; Vafeidis, Athanasios T.

2016-10-01

Existing quantifications of the Shared Socioeconomic Pathways (SSP) used for climate impact assessment do not account for subnational population dynamics such as coastward-migration that can be critical for coastal impact assessment. This paper extends the SSPs by developing spatial projections of global coastal population distribution for the five basic SSPs. Based on a series of coastal migration drivers we develop coastal narratives for each SSP. These narratives account for differences in coastal and inland population developments in urban and rural areas. To spatially distribute population, we use the International Institute for Applied Systems Analysis (IIASA) national population and urbanisation projections and employ country-specific growth rates, which differ for coastal and inland as well as for urban and rural regions, to project coastal population for each SSP. These rates are derived from spatial analysis of historical population data and adjusted for each SSP based on the coastal narratives. Our results show that, compared to the year 2000 (638 million), the population living in the Low Elevated Coastal Zone (LECZ) increases by 58% to 71% until 2050 and exceeds one billion in all SSPs. By the end of the 21st century, global coastal population declines to 830-907 million in all SSPs except for SSP3, where coastal population growth continues and reaches 1.184 billion. Overall, the population living in the LECZ is higher by 85 to 239 million compared to the original IIASA projections. Asia expects the highest absolute growth (238-303 million), Africa the highest relative growth (153% to 218%). Our results highlight regions where high coastal population growth is expected and will therefore face an increased exposure to coastal flooding.

Niches, models, and climate change: Assessing the assumptions and uncertainties

PubMed Central

Wiens, John A.; Stralberg, Diana; Jongsomjit, Dennis; Howell, Christine A.; Snyder, Mark A.

2009-01-01

As the rate and magnitude of climate change accelerate, understanding the consequences becomes increasingly important. Species distribution models (SDMs) based on current ecological niche constraints are used to project future species distributions. These models contain assumptions that add to the uncertainty in model projections stemming from the structure of the models, the algorithms used to translate niche associations into distributional probabilities, the quality and quantity of data, and mismatches between the scales of modeling and data. We illustrate the application of SDMs using two climate models and two distributional algorithms, together with information on distributional shifts in vegetation types, to project fine-scale future distributions of 60 California landbird species. Most species are projected to decrease in distribution by 2070. Changes in total species richness vary over the state, with large losses of species in some “hotspots” of vulnerability. Differences in distributional shifts among species will change species co-occurrences, creating spatial variation in similarities between current and future assemblages. We use these analyses to consider how assumptions can be addressed and uncertainties reduced. SDMs can provide a useful way to incorporate future conditions into conservation and management practices and decisions, but the uncertainties of model projections must be balanced with the risks of taking the wrong actions or the costs of inaction. Doing this will require that the sources and magnitudes of uncertainty are documented, and that conservationists and resource managers be willing to act despite the uncertainties. The alternative, of ignoring the future, is not an option. PMID:19822750

Reducing Sensor Noise in MEG and EEG Recordings Using Oversampled Temporal Projection.

PubMed

Larson, Eric; Taulu, Samu

2018-05-01

Here, we review the theory of suppression of spatially uncorrelated, sensor-specific noise in electro- and magentoencephalography (EEG and MEG) arrays, and introduce a novel method for suppression. Our method requires only that the signals of interest are spatially oversampled, which is a reasonable assumption for many EEG and MEG systems. Our method is based on a leave-one-out procedure using overlapping temporal windows in a mathematical framework to project spatially uncorrelated noise in the temporal domain. This method, termed "oversampled temporal projection" (OTP), has four advantages over existing methods. First, sparse channel-specific artifacts are suppressed while limiting mixing with other channels, whereas existing linear, time-invariant spatial operators can spread such artifacts to other channels with a spatial distribution which can be mistaken for one produced by an electrophysiological source. Second, OTP minimizes distortion of the spatial configuration of the data. During source localization (e.g., dipole fitting), many spatial methods require corresponding modification of the forward model to avoid bias, while OTP does not. Third, noise suppression factors at the sensor level are maintained during source localization, whereas bias compensation removes the denoising benefit for spatial methods that require such compensation. Fourth, OTP uses a time-window duration parameter to control the tradeoff between noise suppression and adaptation to time-varying sensor characteristics. OTP efficiently optimizes noise suppression performance while controlling for spatial bias of the signal of interest. This is important in applications where sensor noise significantly limits the signal-to-noise ratio, such as high-frequency brain oscillations.

Matching species traits to projected threats and opportunities from climate change

PubMed Central

Garcia, Raquel A; Araújo, Miguel B; Burgess, Neil D; Foden, Wendy B; Gutsche, Alexander; Rahbek, Carsten; Cabeza, Mar

2014-01-01

Aim Climate change can lead to decreased climatic suitability within species' distributions, increased fragmentation of climatically suitable space, and/or emergence of newly suitable areas outside present distributions. Each of these extrinsic threats and opportunities potentially interacts with specific intrinsic traits of species, yet this specificity is seldom considered in risk assessments. We present an analytical framework for examining projections of climate change-induced threats and opportunities with reference to traits that are likely to mediate species' responses, and illustrate the applicability of the framework. Location Sub-Saharan Africa. Methods We applied the framework to 195 sub-Saharan African amphibians with both available bioclimatic envelope model projections for the mid-21st century and trait data. Excluded were 500 narrow-ranging species mainly from montane areas. For each of projected losses, increased fragmentation and gains of climate space, we selected potential response-mediating traits and examined the spatial overlap with vulnerability due to these traits. We examined the overlap for all species, and individually for groups of species with different combinations of threats and opportunities. Results In the Congo Basin and arid Southern Africa, projected losses for wide-ranging amphibians were compounded by sensitivity to climatic variation, and expected gains were precluded by poor dispersal ability. The spatial overlap between exposure and vulnerability was more pronounced for species projected to have their climate space contracting in situ or shifting to distant geographical areas. Our results exclude the potential exposure of narrow-ranging species to shrinking climates in the African tropical mountains. Main conclusions We illustrate the application of a framework combining spatial projections of climate change exposure with traits that are likely to mediate species' responses. Although the proposed framework carries several assumptions that require further scrutiny, its application adds a degree of realism to familiar assessments that consider all species to be equally affected by climate change-induced threats and opportunities. PMID:25505356

A Big Spatial Data Processing Framework Applying to National Geographic Conditions Monitoring

NASA Astrophysics Data System (ADS)

Xiao, F.

2018-04-01

In this paper, a novel framework for spatial data processing is proposed, which apply to National Geographic Conditions Monitoring project of China. It includes 4 layers: spatial data storage, spatial RDDs, spatial operations, and spatial query language. The spatial data storage layer uses HDFS to store large size of spatial vector/raster data in the distributed cluster. The spatial RDDs are the abstract logical dataset of spatial data types, and can be transferred to the spark cluster to conduct spark transformations and actions. The spatial operations layer is a series of processing on spatial RDDs, such as range query, k nearest neighbor and spatial join. The spatial query language is a user-friendly interface which provide people not familiar with Spark with a comfortable way to operation the spatial operation. Compared with other spatial frameworks, it is highlighted that comprehensive technologies are referred for big spatial data processing. Extensive experiments on real datasets show that the framework achieves better performance than traditional process methods.

Geoarchaeological approaches to Palaeolithic surface artefact distributions and hominin landscape use in SW Saudi Arabia

NASA Astrophysics Data System (ADS)

Inglis, Robyn; Sinclair, Anthony; Fanning, Patricia; Alsharekh, Abdullah; Bailey, Geoff

2017-04-01

The vast majority of Palaeolithic archaeological material in arid and semi-arid regions exists in the form of scatters of stone tools across the surface of present-day landscapes. This is particularly the case in the Saharo-Arabian desert belt, a region vital to understanding the global dispersal of hominins from Africa. These surface artefacts possess little stratigraphic context, but comprise the only record we possess to examine spatial behavioural patterning and landscape use by hominin populations. Interpretation of the observed spatial distribution of artefacts is far from straightforward. Surface artefact distributions result from a complex interplay of varying human behaviours over time. Also, geomorphological processes affect the preservation, exposure and visibility of the artefacts, as well as alter the presence and location of attractive resources. The SURFACE project employs an interdisciplinary approach to understanding the distribution of Palaeolithic artefacts in SW Saudi Arabia. By combining remote sensing, geomorphological fieldwork, archaeological survey and GIS analyses, the project is developing a geomorphological context for the artefacts that guides survey to areas of high archaeological potential, as well as allowing the robust interpretation of the observed artefact distribution in a dynamic landscape in terms of past landscape use. This paper will present the ongoing multi-scalar approaches employed by the project to Palaeolithic landscapes, particularly focussing on the site of Wadi Dabsa, Asir Province, where Lower and Middle Palaeolithic artefacts have been found in association with extensive tufa deposits. Investigation in early 2017 at the site will apply SURFACE's methods to understand the present-day artefact distributions at the exposure, and their relationship to the tufa deposition, as well as their potential to inform on Palaeolithic activity and landscape use at the site.

A high resolution spatial population database of Somalia for disease risk mapping.

PubMed

Linard, Catherine; Alegana, Victor A; Noor, Abdisalan M; Snow, Robert W; Tatem, Andrew J

2010-09-14

Millions of Somali have been deprived of basic health services due to the unstable political situation of their country. Attempts are being made to reconstruct the health sector, in particular to estimate the extent of infectious disease burden. However, any approach that requires the use of modelled disease rates requires reasonable information on population distribution. In a low-income country such as Somalia, population data are lacking, are of poor quality, or become outdated rapidly. Modelling methods are therefore needed for the production of contemporary and spatially detailed population data. Here land cover information derived from satellite imagery and existing settlement point datasets were used for the spatial reallocation of populations within census units. We used simple and semi-automated methods that can be implemented with free image processing software to produce an easily updatable gridded population dataset at 100 × 100 meters spatial resolution. The 2010 population dataset was matched to administrative population totals projected by the UN. Comparison tests between the new dataset and existing population datasets revealed important differences in population size distributions, and in population at risk of malaria estimates. These differences are particularly important in more densely populated areas and strongly depend on the settlement data used in the modelling approach. The results show that it is possible to produce detailed, contemporary and easily updatable settlement and population distribution datasets of Somalia using existing data. The 2010 population dataset produced is freely available as a product of the AfriPop Project and can be downloaded from: http://www.afripop.org.

A high resolution spatial population database of Somalia for disease risk mapping

PubMed Central

2010-01-01

Background Millions of Somali have been deprived of basic health services due to the unstable political situation of their country. Attempts are being made to reconstruct the health sector, in particular to estimate the extent of infectious disease burden. However, any approach that requires the use of modelled disease rates requires reasonable information on population distribution. In a low-income country such as Somalia, population data are lacking, are of poor quality, or become outdated rapidly. Modelling methods are therefore needed for the production of contemporary and spatially detailed population data. Results Here land cover information derived from satellite imagery and existing settlement point datasets were used for the spatial reallocation of populations within census units. We used simple and semi-automated methods that can be implemented with free image processing software to produce an easily updatable gridded population dataset at 100 × 100 meters spatial resolution. The 2010 population dataset was matched to administrative population totals projected by the UN. Comparison tests between the new dataset and existing population datasets revealed important differences in population size distributions, and in population at risk of malaria estimates. These differences are particularly important in more densely populated areas and strongly depend on the settlement data used in the modelling approach. Conclusions The results show that it is possible to produce detailed, contemporary and easily updatable settlement and population distribution datasets of Somalia using existing data. The 2010 population dataset produced is freely available as a product of the AfriPop Project and can be downloaded from: http://www.afripop.org. PMID:20840751

Soil organic matter dynamics and CO2 fluxes in relation to landscape scale processes: linking process understanding to regional scale carbon mass-balances

NASA Astrophysics Data System (ADS)

Van Oost, Kristof; Nadeu, Elisabet; Wiaux, François; Wang, Zhengang; Stevens, François; Vanclooster, Marnik; Tran, Anh; Bogaert, Patrick; Doetterl, Sebastian; Lambot, Sébastien; Van wesemael, Bas

2014-05-01

In this paper, we synthesize the main outcomes of a collaborative project (2009-2014) initiated at the UCL (Belgium). The main objective of the project was to increase our understanding of soil organic matter dynamics in complex landscapes and use this to improve predictions of regional scale soil carbon balances. In a first phase, the project characterized the emergent spatial variability in soil organic matter storage and key soil properties at the regional scale. Based on the integration of remote sensing, geomorphological and soil analysis techniques, we quantified the temporal and spatial variability of soil carbon stock and pool distribution at the local and regional scales. This work showed a linkage between lateral fluxes of C in relation with sediment transport and the spatial variation in carbon storage at multiple spatial scales. In a second phase, the project focused on characterizing key controlling factors and process interactions at the catena scale. In-situ experiments of soil CO2 respiration showed that the soil carbon response at the catena scale was spatially heterogeneous and was mainly controlled by the catenary variation of soil physical attributes (soil moisture, temperature, C quality). The hillslope scale characterization relied on advanced hydrogeophysical techniques such as GPR (Ground Penetrating Radar), EMI (Electromagnetic induction), ERT (Electrical Resistivity Tomography), and geophysical inversion and data mining tools. Finally, we report on the integration of these insights into a coupled and spatially explicit model and its application. Simulations showed that C stocks and redistribution of mass and energy fluxes are closely coupled, they induce structured spatial and temporal patterns with non negligible attached uncertainties. We discuss the main outcomes of these activities in relation to sink-source behavior and relevance of erosion processes for larger-scale C budgets.

Spatial dynamics of action potentials estimated by dendritic Ca(2+) signals in insect projection neurons.

PubMed

Ogawa, Hiroto; Mitani, Ruriko

2015-11-13

The spatial dynamics of action potentials, including their propagation and the location of spike initiation zone (SIZ), are crucial for the computation of a single neuron. Compared with mammalian central neurons, the spike dynamics of invertebrate neurons remain relatively unknown. Thus, we examined the spike dynamics based on single spike-induced Ca(2+) signals in the dendrites of cricket mechanosensory projection neurons, known as giant interneurons (GIs). The Ca(2+) transients induced by a synaptically evoked single spike were larger than those induced by an antidromic spike, whereas subthreshold synaptic potentials caused no elevation of Ca(2+). These results indicate that synaptic activity enhances the dendritic Ca(2+) influx through voltage-gated Ca(2+) channels. Stimulation of the presynaptic sensory afferents ipsilateral to the recording site evoked a dendritic spike with higher amplitude than contralateral stimulation, thereby suggesting that alteration of the spike waveform resulted in synaptic enhancement of the dendritic Ca(2+) transients. The SIZ estimated from the spatial distribution of the difference in the Ca(2+) amplitude was distributed throughout the right and left dendritic branches across the primary neurite connecting them in GIs. Copyright © 2015 Elsevier Inc. All rights reserved.

Forecasting the impact of transport improvements on commuting and residential choice

NASA Astrophysics Data System (ADS)

Elhorst, J. Paul; Oosterhaven, Jan

2006-03-01

This paper develops a probabilistic, competing-destinations, assignment model that predicts changes in the spatial pattern of the working population as a result of transport improvements. The choice of residence is explained by a new non-parametric model, which represents an alternative to the popular multinominal logit model. Travel times between zones are approximated by a normal distribution function with different mean and variance for each pair of zones, whereas previous models only use average travel times. The model’s forecast error of the spatial distribution of the Dutch working population is 7% when tested on 1998 base-year data. To incorporate endogenous changes in its causal variables, an almost ideal demand system is estimated to explain the choice of transport mode, and a new economic geography inter-industry model (RAEM) is estimated to explain the spatial distribution of employment. In the application, the model is used to forecast the impact of six mutually exclusive Dutch core-periphery railway proposals in the projection year 2020.

Winners and losers of national and global efforts to reconcile agricultural intensification and biodiversity conservation.

PubMed

Egli, Lukas; Meyer, Carsten; Scherber, Christoph; Kreft, Holger; Tscharntke, Teja

2018-05-01

Closing yield gaps within existing croplands, and thereby avoiding further habitat conversions, is a prominently and controversially discussed strategy to meet the rising demand for agricultural products, while minimizing biodiversity impacts. The agricultural intensification associated with such a strategy poses additional threats to biodiversity within agricultural landscapes. The uneven spatial distribution of both yield gaps and biodiversity provides opportunities for reconciling agricultural intensification and biodiversity conservation through spatially optimized intensification. Here, we integrate distribution and habitat information for almost 20,000 vertebrate species with land-cover and land-use datasets. We estimate that projected agricultural intensification between 2000 and 2040 would reduce the global biodiversity value of agricultural lands by 11%, relative to 2000. Contrasting these projections with spatial land-use optimization scenarios reveals that 88% of projected biodiversity loss could be avoided through globally coordinated land-use planning, implying huge efficiency gains through international cooperation. However, global-scale optimization also implies a highly uneven distribution of costs and benefits, resulting in distinct "winners and losers" in terms of national economic development, food security, food sovereignty or conservation. Given conflicting national interests and lacking effective governance mechanisms to guarantee equitable compensation of losers, multinational land-use optimization seems politically unlikely. In turn, 61% of projected biodiversity loss could be avoided through nationally focused optimization, and 33% through optimization within just 10 countries. Targeted efforts to improve the capacity for integrated land-use planning for sustainable intensification especially in these countries, including the strengthening of institutions that can arbitrate subnational land-use conflicts, may offer an effective, yet politically feasible, avenue to better reconcile future trade-offs between agriculture and conservation. The efficiency gains of optimization remained robust when assuming that yields could only be increased to 80% of their potential. Our results highlight the need to better integrate real-world governance, political and economic challenges into sustainable development and global change mitigation research. © 2018 John Wiley & Sons Ltd.

Uncertainty Analysis of Downscaled CMIP5 Precipitation Data for Louisiana, USA

NASA Astrophysics Data System (ADS)

Sumi, S. J.; Tamanna, M.; Chivoiu, B.; Habib, E. H.

2014-12-01

The downscaled CMIP3 and CMIP5 Climate and Hydrology Projections dataset contains fine spatial resolution translations of climate projections over the contiguous United States developed using two downscaling techniques (monthly Bias Correction Spatial Disaggregation (BCSD) and daily Bias Correction Constructed Analogs (BCCA)). The objective of this study is to assess the uncertainty of the CMIP5 downscaled general circulation models (GCM). We performed an analysis of the daily, monthly, seasonal and annual variability of precipitation downloaded from the Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections website for the state of Louisiana, USA at 0.125° x 0.125° resolution. A data set of daily gridded observations of precipitation of a rectangular boundary covering Louisiana is used to assess the validity of 21 downscaled GCMs for the 1950-1999 period. The following statistics are computed using the CMIP5 observed dataset with respect to the 21 models: the correlation coefficient, the bias, the normalized bias, the mean absolute error (MAE), the mean absolute percentage error (MAPE), and the root mean square error (RMSE). A measure of variability simulated by each model is computed as the ratio of its standard deviation, in both space and time, to the corresponding standard deviation of the observation. The correlation and MAPE statistics are also computed for each of the nine climate divisions of Louisiana. Some of the patterns that we observed are: 1) Average annual precipitation rate shows similar spatial distribution for all the models within a range of 3.27 to 4.75 mm/day from Northwest to Southeast. 2) Standard deviation of summer (JJA) precipitation (mm/day) for the models maintains lower value than the observation whereas they have similar spatial patterns and range of values in winter (NDJ). 3) Correlation coefficients of annual precipitation of models against observation have a range of -0.48 to 0.36 with variable spatial distribution by model. 4) Most of the models show negative correlation coefficients in summer and positive in winter. 5) MAE shows similar spatial distribution for all the models within a range of 5.20 to 7.43 mm/day from Northwest to Southeast of Louisiana. 6) Highest values of correlation coefficients are found at seasonal scale within a range of 0.36 to 0.46.

Socio-economic and Climate Factors Associated with Dengue Fever Spatial Heterogeneity: A Worked Example in New Caledonia.

PubMed

Teurlai, Magali; Menkès, Christophe Eugène; Cavarero, Virgil; Degallier, Nicolas; Descloux, Elodie; Grangeon, Jean-Paul; Guillaumot, Laurent; Libourel, Thérèse; Lucio, Paulo Sergio; Mathieu-Daudé, Françoise; Mangeas, Morgan

2015-12-01

Understanding the factors underlying the spatio-temporal distribution of infectious diseases provides useful information regarding their prevention and control. Dengue fever spatio-temporal patterns result from complex interactions between the virus, the host, and the vector. These interactions can be influenced by environmental conditions. Our objectives were to analyse dengue fever spatial distribution over New Caledonia during epidemic years, to identify some of the main underlying factors, and to predict the spatial evolution of dengue fever under changing climatic conditions, at the 2100 horizon. We used principal component analysis and support vector machines to analyse and model the influence of climate and socio-economic variables on the mean spatial distribution of 24,272 dengue cases reported from 1995 to 2012 in thirty-three communes of New Caledonia. We then modelled and estimated the future evolution of dengue incidence rates using a regional downscaling of future climate projections. The spatial distribution of dengue fever cases is highly heterogeneous. The variables most associated with this observed heterogeneity are the mean temperature, the mean number of people per premise, and the mean percentage of unemployed people, a variable highly correlated with people's way of life. Rainfall does not seem to play an important role in the spatial distribution of dengue cases during epidemics. By the end of the 21st century, if temperature increases by approximately 3 °C, mean incidence rates during epidemics could double. In New Caledonia, a subtropical insular environment, both temperature and socio-economic conditions are influencing the spatial spread of dengue fever. Extension of this study to other countries worldwide should improve the knowledge about climate influence on dengue burden and about the complex interplay between different factors. This study presents a methodology that can be used as a step by step guide to model dengue spatial heterogeneity in other countries.

Socio-economic and Climate Factors Associated with Dengue Fever Spatial Heterogeneity: A Worked Example in New Caledonia

PubMed Central

Teurlai, Magali; Menkès, Christophe Eugène; Cavarero, Virgil; Degallier, Nicolas; Descloux, Elodie; Grangeon, Jean-Paul; Guillaumot, Laurent; Libourel, Thérèse; Lucio, Paulo Sergio; Mathieu-Daudé, Françoise; Mangeas, Morgan

2015-01-01

Background/Objectives Understanding the factors underlying the spatio-temporal distribution of infectious diseases provides useful information regarding their prevention and control. Dengue fever spatio-temporal patterns result from complex interactions between the virus, the host, and the vector. These interactions can be influenced by environmental conditions. Our objectives were to analyse dengue fever spatial distribution over New Caledonia during epidemic years, to identify some of the main underlying factors, and to predict the spatial evolution of dengue fever under changing climatic conditions, at the 2100 horizon. Methods We used principal component analysis and support vector machines to analyse and model the influence of climate and socio-economic variables on the mean spatial distribution of 24,272 dengue cases reported from 1995 to 2012 in thirty-three communes of New Caledonia. We then modelled and estimated the future evolution of dengue incidence rates using a regional downscaling of future climate projections. Results The spatial distribution of dengue fever cases is highly heterogeneous. The variables most associated with this observed heterogeneity are the mean temperature, the mean number of people per premise, and the mean percentage of unemployed people, a variable highly correlated with people's way of life. Rainfall does not seem to play an important role in the spatial distribution of dengue cases during epidemics. By the end of the 21st century, if temperature increases by approximately 3°C, mean incidence rates during epidemics could double. Conclusion In New Caledonia, a subtropical insular environment, both temperature and socio-economic conditions are influencing the spatial spread of dengue fever. Extension of this study to other countries worldwide should improve the knowledge about climate influence on dengue burden and about the complex interplay between different factors. This study presents a methodology that can be used as a step by step guide to model dengue spatial heterogeneity in other countries. PMID:26624008

Evaluation of induced seismicity forecast models in the Induced Seismicity Test Bench

NASA Astrophysics Data System (ADS)

Király, Eszter; Gischig, Valentin; Zechar, Jeremy; Doetsch, Joseph; Karvounis, Dimitrios; Wiemer, Stefan

2016-04-01

Induced earthquakes often accompany fluid injection, and the seismic hazard they pose threatens various underground engineering projects. Models to monitor and control induced seismic hazard with traffic light systems should be probabilistic, forward-looking, and updated as new data arrive. Here, we propose an Induced Seismicity Test Bench to test and rank such models. We apply the test bench to data from the Basel 2006 and Soultz-sous-Forêts 2004 geothermal stimulation projects, and we assess forecasts from two models that incorporate a different mix of physical understanding and stochastic representation of the induced sequences: Shapiro in Space (SiS) and Hydraulics and Seismics (HySei). SiS is based on three pillars: the seismicity rate is computed with help of the seismogenic index and a simple exponential decay of the seismicity; the magnitude distribution follows the Gutenberg-Richter relation; and seismicity is distributed in space based on smoothing seismicity during the learning period with 3D Gaussian kernels. The HySei model describes seismicity triggered by pressure diffusion with irreversible permeability enhancement. Our results show that neither model is fully superior to the other. HySei forecasts the seismicity rate well, but is only mediocre at forecasting the spatial distribution. On the other hand, SiS forecasts the spatial distribution well but not the seismicity rate. The shut-in phase is a difficult moment for both models in both reservoirs: the models tend to underpredict the seismicity rate around, and shortly after, shut-in. Ensemble models that combine HySei's rate forecast with SiS's spatial forecast outperform each individual model.

Past and future effects of climate change on spatially heterogeneous vegetation activity in China

NASA Astrophysics Data System (ADS)

Gao, Jiangbo; Jiao, Kewei; Wu, Shaohong; Ma, Danyang; Zhao, Dongsheng; Yin, Yunhe; Dai, Erfu

2017-07-01

Climate change is a major driver of vegetation activity but its complex ecological relationships impede research efforts. In this study, the spatial distribution and dynamic characteristics of climate change effects on vegetation activity in China from the 1980s to the 2010s and from 2021 to 2050 were investigated using a geographically weighted regression (GWR) model. The GWR model was based on combined datasets of satellite vegetation index, climate observation and projection, and future vegetation productivity simulation. Our results revealed that the significantly positive precipitation-vegetation relationship was and will be mostly distributed in North China. However, the regions with temperature-dominated distribution of vegetation activity were and will be mainly located in South China. Due to the varying climate features and vegetation cover, the spatial correlation between vegetation activity and climate change may be altered. There will be different dominant climatic factors for vegetation activity distribution in some regions such as Northwest China, and even opposite correlations in Northeast China. Additionally, the response of vegetation activity to precipitation will move southward in the next three decades. In contrast, although the high warming rate will restrain the vegetation activity, precipitation variability could modify hydrothermal conditions for vegetation activity. This observation is exemplified in the projected future enhancement of vegetation activity in the Tibetan Plateau and weakened vegetation activity in East and Middle China. Furthermore, the vegetation in most parts of North China may adapt to an arid environment, whereas in many southern areas, vegetation will be repressed by water shortage in the future.

Changes in projected spatial and seasonal groundwater recharge in the upper Colorado River Basin

USGS Publications Warehouse

Tillman, Fred; Gangopadhyay, Subhrendu; Pruitt, Tom

2017-01-01

The Colorado River is an important source of water in the western United States, supplying the needs of more than 38 million people in the United States and Mexico. Groundwater discharge to streams has been shown to be a critical component of streamflow in the Upper Colorado River Basin (UCRB), particularly during low-flow periods. Understanding impacts on groundwater in the basin from projected climate change will assist water managers in the region in planning for potential changes in the river and groundwater system. A previous study on changes in basin-wide groundwater recharge in the UCRB under projected climate change found substantial increases in temperature, moderate increases in precipitation, and mostly periods of stable or slight increases in simulated groundwater recharge through 2099. This study quantifies projected spatial and seasonal changes in groundwater recharge within the UCRB from recent historical (1950 to 2015) through future (2016 to 2099) time periods, using a distributed-parameter groundwater recharge model with downscaled climate data from 97 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate projections. Simulation results indicate that projected increases in basin-wide recharge of up to 15% are not distributed uniformly within the basin or throughout the year. Northernmost subregions within the UCRB are projected an increase in groundwater recharge, while recharge in other mainly southern subregions will decline. Seasonal changes in recharge also are projected within the UCRB, with decreases of 50% or more in summer months and increases of 50% or more in winter months for all subregions, and increases of 10% or more in spring months for many subregions.

Changes in Projected Spatial and Seasonal Groundwater Recharge in the Upper Colorado River Basin.

PubMed

Tillman, Fred D; Gangopadhyay, Subhrendu; Pruitt, Tom

2017-07-01

The Colorado River is an important source of water in the western United States, supplying the needs of more than 38 million people in the United States and Mexico. Groundwater discharge to streams has been shown to be a critical component of streamflow in the Upper Colorado River Basin (UCRB), particularly during low-flow periods. Understanding impacts on groundwater in the basin from projected climate change will assist water managers in the region in planning for potential changes in the river and groundwater system. A previous study on changes in basin-wide groundwater recharge in the UCRB under projected climate change found substantial increases in temperature, moderate increases in precipitation, and mostly periods of stable or slight increases in simulated groundwater recharge through 2099. This study quantifies projected spatial and seasonal changes in groundwater recharge within the UCRB from recent historical (1950 to 2015) through future (2016 to 2099) time periods, using a distributed-parameter groundwater recharge model with downscaled climate data from 97 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate projections. Simulation results indicate that projected increases in basin-wide recharge of up to 15% are not distributed uniformly within the basin or throughout the year. Northernmost subregions within the UCRB are projected an increase in groundwater recharge, while recharge in other mainly southern subregions will decline. Seasonal changes in recharge also are projected within the UCRB, with decreases of 50% or more in summer months and increases of 50% or more in winter months for all subregions, and increases of 10% or more in spring months for many subregions. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Can We "Future-Proof" Marine Conservation Planning?

NASA Astrophysics Data System (ADS)

Pinsky, M. L.; Rogers, L. A.

2016-02-01

Marine conservation and marine spatial planning strategies worldwide are designed around biogeographic patterns, often under the assumption that these patterns are relatively stable. With climate change, however, distributions are shifting rapidly as species seek more suitable conditions. Here, we use distribution projections from 2006-2100 for 360 marine species in North America to evaluate the effectiveness of the current marine protected area (MPA) network and to test climate-ready planning approaches. We consider both expected community changes and the uncertainty in those projections. We find that existing MPAs are likely to lose more species over the coming century than other locations on the continental shelf. We also find substantial shifts in the location of high- and low-value regions, which can complicate conservation planning. However, planning portfolios can be developed that perform much better in the face of changes expected over the coming century. The theory and practice of marine spatial planning and marine conservation can be substantially more responsive to our dynamic ocean.

High-Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

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

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.

The aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary con- ditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal-length time slices (2045–2054 and 2085–2094) are compared with a historical decade (1995–2004). Probabilitymore » density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm-side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm-side shift with decreased variability. Finally, using "business-as-usual" scenario, 5-day heat waves are projected to occur at least 5–10 times per year in most CONUS and ≥ 95°F days will increase by 1–2 months by the end of the century.« less

High-Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

DOE PAGES

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.; ...

2017-11-20

The aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary con- ditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal-length time slices (2045–2054 and 2085–2094) are compared with a historical decade (1995–2004). Probabilitymore » density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm-side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm-side shift with decreased variability. Finally, using "business-as-usual" scenario, 5-day heat waves are projected to occur at least 5–10 times per year in most CONUS and ≥ 95°F days will increase by 1–2 months by the end of the century.« less

An ecoregion assessment of projected tree species vulnerabilities in western North America through the 21st century.

PubMed

Mathys, Amanda S; Coops, Nicholas C; Waring, Richard H

2017-02-01

Forest ecosystems across western North America will likely see shifts in both tree species dominance and composition over the rest of this century in response to climate change. Our objective in this study was to identify which ecological regions might expect the greatest changes to occur. We used the process-based growth model 3-PG, to provide estimates of tree species responses to changes in environmental conditions and to evaluate the extent that species are resilient to shifts in climate over the rest of this century. We assessed the vulnerability of 20 tree species in western North America using the Canadian global circulation model under three different emission scenarios. We provided detailed projections of species shifts by including soil maps that account for the spatial variation in soil water availability and soil fertility as well as by utilizing annual climate projections of monthly changes in air temperature, precipitation, solar radiation, vapor pressure deficit and frost at a spatial resolution of one km. Projected suitable areas for tree species were compared to their current ranges based on observations at >40 000 field survey plots. Tree species were classified as vulnerable if environmental conditions projected in the future appear outside that of their current distribution ≥70% of the time. We added a migration constraint that limits species dispersal to <200 m yr -1 to provide more realistic projections on species distributions. Based on these combinations of constraints, we predicted the greatest changes in the distribution of dominant tree species to occur within the Northwest Forested Mountains and the highest number of tree species stressed will likely be in the North American Deserts. Projected climatic changes appear especially unfavorable for species in the subalpine zone, where major shifts in composition may lead to the emergence of new forest types. © 2016 John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Remote-sensing based approach to forecast habitat quality under climate change scenarios.

PubMed

Requena-Mullor, Juan M; López, Enrique; Castro, Antonio J; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios.

Remote-sensing based approach to forecast habitat quality under climate change scenarios

PubMed Central

Requena-Mullor, Juan M.; López, Enrique; Castro, Antonio J.; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios. PMID:28257501

Assessing air quality and climate impacts of future ground freight choice in United States

NASA Astrophysics Data System (ADS)

Liu, L.; Bond, T. C.; Smith, S.; Lee, B.; Ouyang, Y.; Hwang, T.; Barkan, C.; Lee, S.; Daenzer, K.

2013-12-01

The demand for freight transportation has continued to increase due to the growth of domestic and international trade. Emissions from ground freight (truck and railways) account for around 7% of the greenhouse gas emissions, 4% of the primary particulate matter emission and 25% of the NOx emissions in the U.S. Freight railways are generally more fuel efficient than trucks and cause less congestion. Freight demand and emissions are affected by many factors, including economic activity, the spatial distribution of demand, freight modal choice and routing decision, and the technology used in each modal type. This work links these four critical aspects of freight emission system to project the spatial distribution of emissions and pollutant concentration from ground freight transport in the U.S. between 2010 and 2050. Macroeconomic scenarios are used to forecast economic activities. Future spatial structure of employment and commodity demand in major metropolitan areas are estimated using spatial models and a shift-share model, respectively. Freight flow concentration and congestion patterns in inter-regional transportation networks are predicted from a four-step freight demand forecasting model. An asymptotic vehicle routing model is also developed to estimate delivery ton-miles for intra-regional freight shipment in metropolitan areas. Projected freight activities are then converted into impacts on air quality and climate. CO2 emissions are determined using a simple model of freight activity and fuel efficiency, and compared with the projected CO2 emissions from the Second Generation Model. Emissions of air pollutants including PM, NOx and CO are calculated with a vehicle fleet model SPEW-Trend, which incorporates the dynamic change of technologies. Emissions are projected under three economic scenarios to represent different plausible futures. Pollutant concentrations are then estimated using tagged chemical tracers in an atmospheric model with the emissions serving as input.

Mapping species of submerged aquatic vegetation with multi-seasonal satellite images and considering life history information

NASA Astrophysics Data System (ADS)

Luo, Juhua; Duan, Hongtao; Ma, Ronghua; Jin, Xiuliang; Li, Fei; Hu, Weiping; Shi, Kun; Huang, Wenjiang

2017-05-01

Spatial information of the dominant species of submerged aquatic vegetation (SAV) is essential for restoration projects in eutrophic lakes, especially eutrophic Taihu Lake, China. Mapping the distribution of SAV species is very challenging and difficult using only multispectral satellite remote sensing. In this study, we proposed an approach to map the distribution of seven dominant species of SAV in Taihu Lake. Our approach involved information on the life histories of the seven SAV species and eight distribution maps of SAV from February to October. The life history information of the dominant SAV species was summarized from the literature and field surveys. Eight distribution maps of the SAV were extracted from eight 30 m HJ-CCD images from February to October in 2013 based on the classification tree models, and the overall classification accuracies for the SAV were greater than 80%. Finally, the spatial distribution of the SAV species in Taihu in 2013 was mapped using multilayer erasing approach. Based on validation, the overall classification accuracy for the seven species was 68.4%, and kappa was 0.6306, which suggests that larger differences in life histories between species can produce higher identification accuracies. The classification results show that Potamogeton malaianus was the most widely distributed species in Taihu Lake, followed by Myriophyllum spicatum, Potamogeton maackianus, Potamogeton crispus, Elodea nuttallii, Ceratophyllum demersum and Vallisneria spiralis. The information is useful for planning shallow-water habitat restoration projects.

Characterizing the heterogeneity of tumor tissues from spatially resolved molecular measures

PubMed Central

Zavodszky, Maria I.

2017-01-01

Background Tumor heterogeneity can manifest itself by sub-populations of cells having distinct phenotypic profiles expressed as diverse molecular, morphological and spatial distributions. This inherent heterogeneity poses challenges in terms of diagnosis, prognosis and efficient treatment. Consequently, tools and techniques are being developed to properly characterize and quantify tumor heterogeneity. Multiplexed immunofluorescence (MxIF) is one such technology that offers molecular insight into both inter-individual and intratumor heterogeneity. It enables the quantification of both the concentration and spatial distribution of 60+ proteins across a tissue section. Upon bioimage processing, protein expression data can be generated for each cell from a tissue field of view. Results The Multi-Omics Heterogeneity Analysis (MOHA) tool was developed to compute tissue heterogeneity metrics from MxIF spatially resolved tissue imaging data. This technique computes the molecular state of each cell in a sample based on a pathway or gene set. Spatial states are then computed based on the spatial arrangements of the cells as distinguished by their respective molecular states. MOHA computes tissue heterogeneity metrics from the distributions of these molecular and spatially defined states. A colorectal cancer cohort of approximately 700 subjects with MxIF data is presented to demonstrate the MOHA methodology. Within this dataset, statistically significant correlations were found between the intratumor AKT pathway state diversity and cancer stage and histological tumor grade. Furthermore, intratumor spatial diversity metrics were found to correlate with cancer recurrence. Conclusions MOHA provides a simple and robust approach to characterize molecular and spatial heterogeneity of tissues. Research projects that generate spatially resolved tissue imaging data can take full advantage of this useful technique. The MOHA algorithm is implemented as a freely available R script (see supplementary information). PMID:29190747

Future malaria spatial pattern based on the potential global warming impact in South and Southeast Asia.

PubMed

Khormi, Hassan M; Kumar, Lalit

2016-11-21

We used the Model for Interdisciplinary Research on Climate-H climate model with the A2 Special Report on Emissions Scenarios for the years 2050 and 2100 and CLIMEX software for projections to illustrate the potential impact of climate change on the spatial distributions of malaria in China, India, Indochina, Indonesia, and The Philippines based on climate variables such as temperature, moisture, heat, cold and dryness. The model was calibrated using data from several knowledge domains, including geographical distribution records. The areas in which malaria has currently been detected are consistent with those showing high values of the ecoclimatic index in the CLIMEX model. The match between prediction and reality was found to be high. More than 90% of the observed malaria distribution points were associated with the currently known suitable climate conditions. Climate suitability for malaria is projected to decrease in India, southern Myanmar, southern Thailand, eastern Borneo, and the region bordering Cambodia, Malaysia and the Indonesian islands, while it is expected to increase in southern and south-eastern China and Taiwan. The climatic models for Anopheles mosquitoes presented here should be useful for malaria control, monitoring, and management, particularly considering these future climate scenarios.

Building hydrologic information systems to promote climate resilience in the Blue Nile/Abay higlands

USDA-ARS?s Scientific Manuscript database

Climate adaptation requires information about climate and land-surface conditions – spatially distributed, and at scales of human influence (the field scale). This article describes a project aimed at combining meteorological data, satellite remote sensing, hydrologic modeling, and downscaled clima...

Soil carbon dynamics of tree plantings for woody biomass feedstock

USDA-ARS?s Scientific Manuscript database

Agroforestry practices are being considered for their bioenergy potential as the wood could be harvested for direct combustion, cellulose to ethanol conversion, or pyrolysis to bio-oils. The objective of this project was to use spatially-distributed soil sampling and soil profile descriptions to det...

RIPARIAN TREE SEEDLING DISTRIBUTION ON WISCONSIN RIVER SANDBARS: CONTROLS AT DIFFERENT SPATIAL SCALES. (R826600)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Mapping plant species ranges in the Hawaiian Islands: developing a methodology and associated GIS layers

USGS Publications Warehouse

Price, Jonathan P.; Jacobi, James D.; Gon, Samuel M.; Matsuwaki, Dwight; Mehrhoff, Loyal; Wagner, Warren; Lucas, Matthew; Rowe, Barbara

2012-01-01

This report documents a methodology for projecting the geographic ranges of plant species in the Hawaiian Islands. The methodology consists primarily of the creation of several geographic information system (GIS) data layers depicting attributes related to the geographic ranges of plant species. The most important spatial-data layer generated here is an objectively defined classification of climate as it pertains to the distribution of plant species. By examining previous zonal-vegetation classifications in light of spatially detailed climate data, broad zones of climate relevant to contemporary concepts of vegetation in the Hawaiian Islands can be explicitly defined. Other spatial-data layers presented here include the following: substrate age, as large areas of the island of Hawai'i, in particular, are covered by very young lava flows inimical to the growth of many plant species; biogeographic regions of the larger islands that are composites of multiple volcanoes, as many of their species are restricted to a given topographically isolated mountain or a specified group of them; and human impact, which can reduce the range of many species relative to where they formerly were found. Other factors influencing the geographic ranges of species that are discussed here but not developed further, owing to limitations in rendering them spatially, include topography, soils, and disturbance. A method is described for analyzing these layers in a GIS, in conjunction with a database of species distributions, to project the ranges of plant species, which include both the potential range prior to human disturbance and the projected present range. Examples of range maps for several species are given as case studies that demonstrate different spatial characteristics of range. Several potential applications of species-range maps are discussed, including facilitating field surveys, informing restoration efforts, studying range size and rarity, studying biodiversity, managing invasive species, and planning of conservation efforts.

Implications of Web Mercator and its Use in Online Mapping

USGS Publications Warehouse

Battersby, Sarah E.; Finn, Michael P.; Usery, E. Lynn; Yamamoto, Kristina H.

2014-01-01

Online interactive maps have become a popular means of communicating with spatial data. In most online mapping systems, Web Mercator has become the dominant projection. While the Mercator projection has a long history of discussion about its inappropriateness for general-purpose mapping, particularly at the global scale, and seems to have been virtually phased out for general-purpose global-scale print maps, it has seen a resurgence in popularity in Web Mercator form. This article theorizes on how Web Mercator came to be widely used for online maps and what this might mean in terms of data display, technical aspects of map generation and distribution, design, and cognition of spatial patterns. The authors emphasize details of where the projection excels and where it does not, as well as some of its advantages and disadvantages for cartographic communication, and conclude with some research directions that may help to develop better solutions to the problem of projections for general-purpose, multi-scale Web mapping.

The seven sisters DANCe. III. Projected spatial distribution

NASA Astrophysics Data System (ADS)

Olivares, J.; Moraux, E.; Sarro, L. M.; Bouy, H.; Berihuete, A.; Barrado, D.; Huelamo, N.; Bertin, E.; Bouvier, J.

2018-04-01

Context. Membership analyses of the DANCe and Tycho + DANCe data sets provide the largest and least contaminated sample of Pleiades candidate members to date. Aims: We aim at reassessing the different proposals for the number surface density of the Pleiades in the light of the new and most complete list of candidate members, and inferring the parameters of the most adequate model. Methods: We compute the Bayesian evidence and Bayes Factors for variations of the classical radial models. These include elliptical symmetry, and luminosity segregation. As a by-product of the model comparison, we obtain posterior distributions for each set of model parameters. Results: We find that the model comparison results depend on the spatial extent of the region used for the analysis. For a circle of 11.5 parsecs around the cluster centre (the most homogeneous and complete region), we find no compelling reason to abandon King's model, although the Generalised King model introduced here has slightly better fitting properties. Furthermore, we find strong evidence against radially symmetric models when compared to the elliptic extensions. Finally, we find that including mass segregation in the form of luminosity segregation in the J band is strongly supported in all our models. Conclusions: We have put the question of the projected spatial distribution of the Pleiades cluster on a solid probabilistic framework, and inferred its properties using the most exhaustive and least contaminated list of Pleiades candidate members available to date. Our results suggest however that this sample may still lack about 20% of the expected number of cluster members. Therefore, this study should be revised when the completeness and homogeneity of the data can be extended beyond the 11.5 parsecs limit. Such a study will allow for more precise determination of the Pleiades spatial distribution, its tidal radius, ellipticity, number of objects and total mass.

The Spatial Distribution and Kinematics of the Circumgalactic Medium

NASA Astrophysics Data System (ADS)

Churchill, Christopher W.; Nielsen, Nikole M.; Kacprzak, Glenn; Charlton, Jane C.; Muzahid, Sowgat

2017-01-01

We have examined the spatial distribution and kinematics of the circumgalactic medium (CGM) within 200 kpc of galaxies in the redshift range 0.1 to 1.0. The galaxies are resolved in HST images and are selected to have background quasars with sightlines that probe their CGM. We measured the cool/warm CGM in MgII absorption and the warm/hot CGM in OVI absorption using Keck/HIRES, VLT/UVES, and HST/COS. We have found that the CGM gas is highly organized such that: (1) gas is concentrated along the galaxy polar axes with high velocity dispersion, and (2) gas is concentrated along the galaxy major axes with smaller velocity dispersion. We constrain the geometry of the gas to reside between 20-40 degrees of the projected major axis and within 60 degrees of the projected minor axis, with little-to-no gas found in between. Furthermore, strongest absorption and largest velocity spreads are found for highly inclined (face on) galaxies with the bluest colors, suggesting outflows along the minor axes of star-forming galaxies. The major axis of bluer galaxies have similar velocity spreads to those of the gas surrouncding redder galaxies, which show little spatial preference in the distribution of the gas dynamics. Our results are consistent with the current view of the CGM originating from major axis (co-planer) inflows/recycled gas and from minor axis wind-driven outflows. We address how our results place strong contraints on the baryon cycle.

Forest defoliators and climatic change: Potential changes in spatial distribution of outbreaks of western spruce budworm (Lepidoptera: Tortricidae) and gypsy moth (Lepidoptera: Lymantriidae)

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

Williams, D.W.; Liebhold, A.M.

1995-02-01

Changes in geographical ranges and spatial extent of outbreaks of pest species are likely consequences of climatic change. We investigated potential changes in spatial distribution of outbreaks of western spruce budworm, Choristoneura occidentalis Freeman, and gypsy moth, Lymantria dispar (L.), in Oregon and Pennsylvania, respectively using maps of historial defoliation, climate, and forest type in a geographic information system. Maps of defoliation frequency at a resolution of 2 x 2 km were assembled from historical aerial survey data. Weather maps for mean monthly temperature maxima and minima and precipitation over 30 yr were developed by interpolation. Relationships between defoliation statusmore » and environmental variables were estimated using linear discriminant analysis. Five climatic change scenarios were investigated: an increase of 2{degrees}C, a 2{degrees}C increase with a small increase and a small decrease in precipitation, and projections of two general circulation models (GCMs) after 100 yr at doubled carbon dioxide. With an increase in temperature alone, the projected defoliated area decreased relative to ambient conditions for budworm and increased slightly for gypsy moth. With an increase in temperature and precipitation, defoliated area increased for both species. Conversely, defoliated area decreased for both when temperature increased and precipitation decreased. Results for the GCM scenarios contrasted sharply. For one GCM, defoliation by budworm was projected to cover Oregon completely, whereas no defoliation was projected by gypsy moth in Pennsylvania. For the other, defoliation disappeared completely for budworm and slightly exceeded that under ambient conditions for gypsy moth. The results are discussed in terms of current forest composition and its potential changes. 36 refs., 5 figs., 4 tabs.« less

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

NASA Astrophysics Data System (ADS)

Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.

2013-12-01

Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at fine-spatial scales (sub-meter to 10-meter) shows greater temperature variability with warmer mean temperatures. This is inconsistent with the inherent assumption made in current species distribution models that fine-scale variability is static, implying that current projections of future species ranges may be biased -- the direction and magnitude requiring further study. While we focus our findings on the cross-scaling characteristics of temporal and spatial variability, we also compare the mean-variance relationship between 1) experimental climate manipulations and observed conditions and 2) temporal versus spatial variance, i.e., variability in a time-series at one location vs. variability across a landscape at a single time. The former informs the rich debate concerning the ability to experimentally mimic a warmer future. The latter informs space-for-time study design and analyses, as well as species persistence via a combined spatiotemporal probability of suitable future habitat.

SOURCE ATTRIBUTION OF RADIATIVE FORCING FROM SHORT LIVED CLIMATE FORCING AGENTS

EPA Science Inventory

The immediate project result is quantification of the pre-industrial to present forcing for anthropogenic emissions, the radiative effects of natural emissions, and spatial distribution of the radiative forcing efficiency for key aerosol and O3 precursors (i.e., mW/m^2<...

Simulating the Interactions Among Land Use, Transportation, and Economy to Inform Light Rail Transit Decisions

EPA Science Inventory

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic a...

Simulating the Interactions Among Land Use, Transportation, and Economy to Inform Light Rail Transit Decisions (proceedings)

EPA Science Inventory

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic a...

An analysis of historic and projected climate scenarios in the Western United States using hydrologic landscape classification.

EPA Science Inventory

: Identifying areas of similar hydrology within the United States and its regions (hydrologic landscapes - HLs) is an active area of research. HLs are being used to construct spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, a...

An analysis of historic and projected climate scenarios in the Western united States using hydrologic landscape classification

EPA Science Inventory

Identifying areas of similar hydrology within the United States and its regions (Hydrologic landscapes - HLs) is an active area of research. HLs have been used to make spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, and the ...

TEMPORAL TRENDS AND SPATIAL DISTRIBUTIONS OF BROMINATED FLAME RETARDANTS IN ARCHIVED FISHES FROM THE GREAT LAKES. (R830397)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Spatial And Temporal Distribution Of Microbial Communities In A TCE DNAPL Site: SABRE Field Studies

EPA Science Inventory

The SABRE (Source Area BioREmediation) project was conducted to evaluate accelerated anaerobic bioremediation of chlorinated solvents in areas of high concentration, such as DNAPL source areas. To study performance of this technology, a test cell was constructed with a longitudi...

SPATIAL METHODS FOR ASSESSING THE DISTRIBUTION AND IMPACT OF SOIL PHOSPHORUS IN A SUB-TROPICAL FRESHWATER WETLAND. (R827641)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

The Evolution of Galaxies Through the Spatial Distribution of Their Globular Clusters: the Brightest Galaxies in Fornax

NASA Astrophysics Data System (ADS)

Zegeye, David W.

2018-01-01

We present a study of the evolution of the 10 brightest galaxies in the Fornax Cluster, as reconstructed through their Globular Cluster (GC) populations. GCs can be characterized by their projected two-dimensional (2D) spatial distribution. Over- or under-densities in the GC distribution, can be linked to events in the host galaxy assembly history, and used to constrain the properties of their progenitors. With HST/ACS imaging, we identified significant structures in the GC distribution of the 10 galaxies investigated, with some of the galaxies possessing structures with >10-sigma significance. GC over-densities have been found within the galaxies, with significant differences between the red and blue GC population. For elongated galaxies, structures are preferentially to be aligned along the major axis. Fornax Cluster galaxies appear to be more dynamically relaxed than the Virgo Cluster galaxies previously investigated with the same methodology by D'Abrusco et al. (2016). However, from these observations, the evident imprints left in the spatial distribution of GCs in these galaxies suggest a similarly intense history of interactions.The SAO REU program is funded by the National Science Foundation REU and Department of Defense ASSURE programs under NSF Grant AST-1659473, and by the Smithsonian Institution.

Nonmydriatic fluorescence-based quantitative imaging of human macular pigment distributions

NASA Astrophysics Data System (ADS)

Sharifzadeh, Mohsen; Bernstein, Paul S.; Gellermann, Werner

2006-10-01

We have developed a CCD-camera-based nonmydriatic instrument that detects fluorescence from retinal lipofuscin chromophores ("autofluorescence") as a means to indirectly quantify and spatially image the distribution of macular pigment (MP). The lipofuscin fluorescence intensity is reduced at all retinal locations containing MP, since MP has a competing absorption in the blue-green wavelength region. Projecting a large diameter, 488 nm excitation spot onto the retina, centered on the fovea, but extending into the macular periphery, and comparing lipofuscin fluorescence intensities outside and inside the foveal area, it is possible to spatially map out the distribution of MP. Spectrally selective detection of the lipofuscin fluorescence reveals an important wavelength dependence of the obtainable image contrast and deduced MP optical density levels, showing that it is important to block out interfering fluorescence contributions in the detection setup originating from ocular media such as the lens. Measuring 70 healthy human volunteer subjects with no ocular pathologies, we find widely varying spatial extent of MP, distinctly differing distribution patterns of MP, and strongly differing absolute MP levels among individuals. Our population study suggests that MP imaging based on lipofuscin fluorescence is useful as a relatively simple, objective, and quantitative noninvasive optical technique suitable to rapidly screen MP levels and distributions in healthy humans with undilated pupils.

Pluto: Distribution of ices and coloring agents from New Horizons LEISA observations

NASA Astrophysics Data System (ADS)

Cruikshank, Dale P.; Grundy, William M.; Stern, S. Alan; Olkin, Catherine B.; Cook, Jason C.; Dalle Ore, Cristina M.; Binzel, Richard P.; Earle, Alissa M.; Ennico, Kimberly; Jennings, Donald E.; Howett, Carly J. A.; Linscott, Ivan R.; Lunsford, Allen W.; Parker, Alex H.; Parker, Joel W.; Protopapa, Silvia; Reuter, Dennis C.; Singer, Kelsi N.; Spencer, John R.; Tsang, Constantine C. C.; Verbiscer, Anne J.; Weaver, Harold A.; Young, Leslie A.

2015-11-01

Pluto was observed at high spatial resolution (maximum ~3 km/px) by the New Horizons LEISA imaging spectrometer. LEISA is a component of the Ralph instrument (Reuter, D.C., Stern, S.A., Scherrer, J., et al. 2008, Space Sci. Rev. 140, 129) and affords a spectral resolving power of 240 in the wavelength range 1.25-2.5 µm, and 560 in the range 2.1-2.25 µm. Spatially resolved spectra with LEISA are used to map the distributions of the known ices on Pluto (N2, CH4, CO) and to search for other surface components. The spatial distribution of volatile ices is compared with the distribution of the coloring agent(s) on Pluto's surface. The correlation of ice abundance and the degree of color (ranging from yellow to orange to dark red) is consistent with the presence of tholins, which are refractory organic solids of complex structure and high molecular weight, with colors consistent with those observed on Pluto. Tholins are readily synthesized in the laboratory by energetic processing of mixtures of the ices (N2, CH4, CO) known on Pluto's surface. We present results returned from the spacecraft to date obtained from the analysis of the high spatial resolution dataset obtained near the time of closest approach to the planet. Supported by NASA’s New Horizons project.

Interbasin water transfer, riverine connectivity, and spatial controls on fish biodiversity

USGS Publications Warehouse

Grant, Evan H. Campbell; Lynch, Heather J.; Muneepeerakul, Rachata; Muthukumarasamy, Arunachalam; Rodríguez-Iturbe, Ignacio; Fagan, William F.

2012-01-01

Background Large-scale inter-basin water transfer (IBWT) projects are commonly proposed as solutions to water distribution and supply problems. These problems are likely to intensify under future population growth and climate change scenarios. Scarce data on the distribution of freshwater fishes frequently limits the ability to assess the potential implications of an IBWT project on freshwater fish communities. Because connectivity in habitat networks is expected to be critical to species' biogeography, consideration of changes in the relative isolation of riverine networks may provide a strategy for controlling impacts of IBWTs on freshwater fish communities Methods/Principal Findings Using empirical data on the current patterns of freshwater fish biodiversity for rivers of peninsular India, we show here how the spatial changes alone under an archetypal IBWT project will (1) reduce freshwater fish biodiversity system-wide, (2) alter patterns of local species richness, (3) expand distributions of widespread species throughout peninsular rivers, and (4) decrease community richness by increasing inter-basin similarity (a mechanism for the observed decrease in biodiversity). Given the complexity of the IBWT, many paths to partial or full completion of the project are possible. We evaluate two strategies for step-wise implementation of the 11 canals, based on economic or ecological considerations. We find that for each step in the project, the impacts on freshwater fish communities are sensitive to which canal is added to the network. Conclusions/Significance Importantly, ecological impacts can be reduced by associating the sequence in which canals are added to characteristics of the links, except for the case when all 11 canals are implemented simultaneously (at which point the sequence of canal addition is inconsequential). By identifying the fundamental relationship between the geometry of riverine networks and freshwater fish biodiversity, our results will aid in assessing impacts of IBWT projects and balancing ecosystem and societal demands for freshwater, even in cases where biodiversity data are limited.

Interbasin Water Transfer, Riverine Connectivity, and Spatial Controls on Fish Biodiversity

PubMed Central

Grant, Evan H. Campbell; Lynch, Heather J.; Muneepeerakul, Rachata; Arunachalam, Muthukumarasamy; Rodríguez-Iturbe, Ignacio; Fagan, William F.

2012-01-01

Background Large-scale inter-basin water transfer (IBWT) projects are commonly proposed as solutions to water distribution and supply problems. These problems are likely to intensify under future population growth and climate change scenarios. Scarce data on the distribution of freshwater fishes frequently limits the ability to assess the potential implications of an IBWT project on freshwater fish communities. Because connectivity in habitat networks is expected to be critical to species' biogeography, consideration of changes in the relative isolation of riverine networks may provide a strategy for controlling impacts of IBWTs on freshwater fish communities. Methods/Principal Findings Using empirical data on the current patterns of freshwater fish biodiversity for rivers of peninsular India, we show here how the spatial changes alone under an archetypal IBWT project will (1) reduce freshwater fish biodiversity system-wide, (2) alter patterns of local species richness, (3) expand distributions of widespread species throughout peninsular rivers, and (4) decrease community richness by increasing inter-basin similarity (a mechanism for the observed decrease in biodiversity). Given the complexity of the IBWT, many paths to partial or full completion of the project are possible. We evaluate two strategies for step-wise implementation of the 11 canals, based on economic or ecological considerations. We find that for each step in the project, the impacts on freshwater fish communities are sensitive to which canal is added to the network. Conclusions/Significance Importantly, ecological impacts can be reduced by associating the sequence in which canals are added to characteristics of the links, except for the case when all 11 canals are implemented simultaneously (at which point the sequence of canal addition is inconsequential). By identifying the fundamental relationship between the geometry of riverine networks and freshwater fish biodiversity, our results will aid in assessing impacts of IBWT projects and balancing ecosystem and societal demands for freshwater, even in cases where biodiversity data are limited. PMID:22470533

Interbasin water transfer, riverine connectivity, and spatial controls on fish biodiversity.

PubMed

Grant, Evan H Campbell; Lynch, Heather J; Muneepeerakul, Rachata; Arunachalam, Muthukumarasamy; Rodríguez-Iturbe, Ignacio; Fagan, William F

2012-01-01

Large-scale inter-basin water transfer (IBWT) projects are commonly proposed as solutions to water distribution and supply problems. These problems are likely to intensify under future population growth and climate change scenarios. Scarce data on the distribution of freshwater fishes frequently limits the ability to assess the potential implications of an IBWT project on freshwater fish communities. Because connectivity in habitat networks is expected to be critical to species' biogeography, consideration of changes in the relative isolation of riverine networks may provide a strategy for controlling impacts of IBWTs on freshwater fish communities. Using empirical data on the current patterns of freshwater fish biodiversity for rivers of peninsular India, we show here how the spatial changes alone under an archetypal IBWT project will (1) reduce freshwater fish biodiversity system-wide, (2) alter patterns of local species richness, (3) expand distributions of widespread species throughout peninsular rivers, and (4) decrease community richness by increasing inter-basin similarity (a mechanism for the observed decrease in biodiversity). Given the complexity of the IBWT, many paths to partial or full completion of the project are possible. We evaluate two strategies for step-wise implementation of the 11 canals, based on economic or ecological considerations. We find that for each step in the project, the impacts on freshwater fish communities are sensitive to which canal is added to the network. Importantly, ecological impacts can be reduced by associating the sequence in which canals are added to characteristics of the links, except for the case when all 11 canals are implemented simultaneously (at which point the sequence of canal addition is inconsequential). By identifying the fundamental relationship between the geometry of riverine networks and freshwater fish biodiversity, our results will aid in assessing impacts of IBWT projects and balancing ecosystem and societal demands for freshwater, even in cases where biodiversity data are limited.

Response of Sierra Nevada forests to projected climate-wildfire interactions.

PubMed

Liang, Shuang; Hurteau, Matthew D; Westerling, Anthony LeRoy

2017-05-01

Climate influences forests directly and indirectly through disturbance. The interaction of climate change and increasing area burned has the potential to alter forest composition and community assembly. However, the overall forest response is likely to be influenced by species-specific responses to environmental change and the scale of change in overstory species cover. In this study, we sought to quantify how projected changes in climate and large wildfire size would alter forest communities and carbon (C) dynamics, irrespective of competition from nontree species and potential changes in other fire regimes, across the Sierra Nevada, USA. We used a species-specific, spatially explicit forest landscape model (LANDIS-II) to evaluate forest response to climate-wildfire interactions under historical (baseline) climate and climate projections from three climate models (GFDL, CCSM3, and CNRM) forced by a medium-high emission scenario (A2) in combination with corresponding climate-specific large wildfire projections. By late century, we found modest changes in the spatial distribution of dominant species by biomass relative to baseline, but extensive changes in recruitment distribution. Although forest recruitment declined across much of the Sierra, we found that projected climate and wildfire favored the recruitment of more drought-tolerant species over less drought-tolerant species relative to baseline, and this change was greatest at mid-elevations. We also found that projected climate and wildfire decreased tree species richness across a large proportion of the study area and transitioned more area to a C source, which reduced landscape-level C sequestration potential. Our study, although a conservative estimate, suggests that by late century, forest community distributions may not change as intact units as predicted by biome-based modeling, but are likely to trend toward simplified community composition as communities gradually disaggregate and the least tolerant species are no longer able to establish. The potential exists for substantial community composition change and forest simplification beyond this century. © 2016 John Wiley & Sons Ltd.

The Shale Hills Critical Zone Observatory for Embedded Sensing and Simulation

NASA Astrophysics Data System (ADS)

Duffy, C.; Davis, K.; Kane, T.; Boyer, E.

2009-04-01

The future of environmental observing systems will utilize embedded sensor networks with continuous real-time measurement of hydrologic, atmospheric, biogeochemical, and ecological variables across diverse terrestrial environments. Embedded environmental sensors, benefitting from advances in information sciences, networking technology, materials science, computing capacity, and data synthesis methods, are undergoing revolutionary change. It is now possible to field spatially-distributed, multi-node sensor networks that provide density and spatial coverage previously accessible only via numerical simulation. At the same time, computational tools are advancing rapidly to the point where it is now possible to simulate the physical processes controlling individual parcels of water and solutes through the complete terrestrial water cycle. Our goal for the Penn State Critical Zone Observatory is to apply environmental sensor arrays, integrated hydrologic models deployed and coordinated at a testbed within the Penn State Experimental Forest. The NSF-funded CZO is designed to observe the detailed space and time complexities of the water and energy cycle for a watershed and ultimately the river basin for all physical states and fluxes (groundwater, soil moisture, temperature, streamflow, latent heat, snowmelt, chemistry, isotopes etc.). Presently fully-coupled physical models are being developed that link the atmosphere-land-vegetation-subsurface system into a fully-coupled distributed system. During the last 5 years the Penn State Integrated Hydrologic Modeling System has been under development as an open-source community modeling project funded by NSF EAR/GEO and NSF CBET/ENG. PIHM represents a strategy for the formulation and solution of fully-coupled process equations at the watershed and river basin scales, and includes a tightly coupled GIS tool for data handling, domain decomposition, optimal unstructured grid generation, and model parameterization. (PIHM; http://sourceforge.net/projects/pihmmodel/; http://sourceforge.net/projects/pihmgis/ ) The CZO sensor and simulation system is being developed to have the following elements: 1) extensive, spatially-distributed smart sensor networks to gather intensive soil, geologic, hydrologic, geochemical and isotopic data; 2) spatially-explicit multiphysics models/solutions of the land-subsurface-vegetation-atmosphere system; and 3) parallel/distributed, adaptive algorithms for rapidly simulating the states of the watershed at high resolution, and 4) signal processing tools for data mining and parameter estimation. The prototype proposed sensor array and simulation system proposed is demonstrated with preliminary results from our first year.

Vapor cell geometry effect on Rydberg atom-based microwave electric field measurement

NASA Astrophysics Data System (ADS)

Zhang, Linjie; Liu, Jiasheng; Jia, Yue; Zhang, Hao; Song, Zhenfei; Jia, Suotang

2018-03-01

The geometry effect of a vapor cell on the metrology of a microwave electric field is investigated. Based on the splitting of the electromagnetically induced transparency spectra of cesium Rydberg atoms in a vapor cell, high-resolution spatial distribution of the microwave electric field strength is achieved for both a cubic cell and a cylinder cell. The spatial distribution of the microwave field strength in two dimensions is measured with sub-wavelength resolution. The experimental results show that the shape of a vapor cell has a significant influence on the abnormal spatial distribution because of the Fabry–Pérot effect inside a vapor cell. A theoretical simulation is obtained for different vapor cell wall thicknesses and shows that a restricted wall thickness results in a measurement fluctuation smaller than 3% at the center of the vapor cell. Project supported by the National Key Research and Development Program of China (Grant Nos. 2017YFA03044200 and 2016YFF0200104), the National Natural Science Foundation of China (Grant Nos. 91536110, 61505099, and 61378013), and the Fund for Shanxi “331 Project” Key Subjects Construction, China.

Spatial interpolation of monthly mean air temperature data for Latvia

NASA Astrophysics Data System (ADS)

Aniskevich, Svetlana

2016-04-01

Temperature data with high spatial resolution are essential for appropriate and qualitative local characteristics analysis. Nowadays the surface observation station network in Latvia consists of 22 stations recording daily air temperature, thus in order to analyze very specific and local features in the spatial distribution of temperature values in the whole Latvia, a high quality spatial interpolation method is required. Until now inverse distance weighted interpolation was used for the interpolation of air temperature data at the meteorological and climatological service of the Latvian Environment, Geology and Meteorology Centre, and no additional topographical information was taken into account. This method made it almost impossible to reasonably assess the actual temperature gradient and distribution between the observation points. During this project a new interpolation method was applied and tested, considering auxiliary explanatory parameters. In order to spatially interpolate monthly mean temperature values, kriging with external drift was used over a grid of 1 km resolution, which contains parameters such as 5 km mean elevation, continentality, distance from the Gulf of Riga and the Baltic Sea, biggest lakes and rivers, population density. As the most appropriate of these parameters, based on a complex situation analysis, mean elevation and continentality was chosen. In order to validate interpolation results, several statistical indicators of the differences between predicted values and the values actually observed were used. Overall, the introduced model visually and statistically outperforms the previous interpolation method and provides a meteorologically reasonable result, taking into account factors that influence the spatial distribution of the monthly mean temperature.

Spatial and kinematic distributions of transition populations in intermediate redshift galaxy clusters

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

Crawford, Steven M.; Wirth, Gregory D.; Bershady, Matthew A., E-mail: crawford@saao.ac.za, E-mail: wirth@keck.hawaii.edu, E-mail: mab@astro.wisc.edu

2014-05-01

We analyze the spatial and velocity distributions of confirmed members in five massive clusters of galaxies at intermediate redshift (0.5 < z < 0.9) to investigate the physical processes driving galaxy evolution. Based on spectral classifications derived from broad- and narrow-band photometry, we define four distinct galaxy populations representing different evolutionary stages: red sequence (RS) galaxies, blue cloud (BC) galaxies, green valley (GV) galaxies, and luminous compact blue galaxies (LCBGs). For each galaxy class, we derive the projected spatial and velocity distribution and characterize the degree of subclustering. We find that RS, BC, and GV galaxies in these clusters havemore » similar velocity distributions, but that BC and GV galaxies tend to avoid the core of the two z ≈ 0.55 clusters. GV galaxies exhibit subclustering properties similar to RS galaxies, but their radial velocity distribution is significantly platykurtic compared to the RS galaxies. The absence of GV galaxies in the cluster cores may explain their somewhat prolonged star-formation history. The LCBGs appear to have recently fallen into the cluster based on their larger velocity dispersion, absence from the cores of the clusters, and different radial velocity distribution than the RS galaxies. Both LCBG and BC galaxies show a high degree of subclustering on the smallest scales, leading us to conclude that star formation is likely triggered by galaxy-galaxy interactions during infall into the cluster.« less

Evaluation of single and two-stage adaptive sampling designs for estimation of density and abundance of freshwater mussels in a large river

USGS Publications Warehouse

Smith, D.R.; Rogala, J.T.; Gray, B.R.; Zigler, S.J.; Newton, T.J.

2011-01-01

Reliable estimates of abundance are needed to assess consequences of proposed habitat restoration and enhancement projects on freshwater mussels in the Upper Mississippi River (UMR). Although there is general guidance on sampling techniques for population assessment of freshwater mussels, the actual performance of sampling designs can depend critically on the population density and spatial distribution at the project site. To evaluate various sampling designs, we simulated sampling of populations, which varied in density and degree of spatial clustering. Because of logistics and costs of large river sampling and spatial clustering of freshwater mussels, we focused on adaptive and non-adaptive versions of single and two-stage sampling. The candidate designs performed similarly in terms of precision (CV) and probability of species detection for fixed sample size. Both CV and species detection were determined largely by density, spatial distribution and sample size. However, designs did differ in the rate that occupied quadrats were encountered. Occupied units had a higher probability of selection using adaptive designs than conventional designs. We used two measures of cost: sample size (i.e. number of quadrats) and distance travelled between the quadrats. Adaptive and two-stage designs tended to reduce distance between sampling units, and thus performed better when distance travelled was considered. Based on the comparisons, we provide general recommendations on the sampling designs for the freshwater mussels in the UMR, and presumably other large rivers.

Investigation of the Reactions and Distribution of Polycyclic Aromatic Hydrocarbons and Fullerenes in Extraterrestrial Material

NASA Technical Reports Server (NTRS)

Zare, Richard N.

2005-01-01

The work funded by this research grant includes four specific projects: (1) Mapping the spatial distribution of polycyclic aromatic hydrocarbons (PAHs) in a variety of meteoritic samples and comparing this distribution with mineralogical features of the meteorite to determine whether a correlation exists between the two. (2) Developing a method for detection of fullerenes in extraterrestrial samples using microprobe laser-desorption laser-ionization mass spectrometry ( pL2MS) and utilizing this technique to investigate fullerene presence, while exploring the possibility of spatially mapping the fullerene distribution in these samples through in situ detection. (3) Investigating a possible formation pathway for meteoritic and ancient terrestrial kerogen involving the photochemical reactions of PAHs with alkanes under prebiotic and astrophysically relevant conditions. (4) Studying reaction pathways and identifying the photoproducts generated during the photochemical evolution of PAH-containing interstellar ice analogs as part of an ongoing collaboration with researchers at the Astrochemistry Lab at NASA Ames.

Current and Future Patterns of Global Marine Mammal Biodiversity

PubMed Central

Kaschner, Kristin; Tittensor, Derek P.; Ready, Jonathan; Gerrodette, Tim; Worm, Boris

2011-01-01

Quantifying the spatial distribution of taxa is an important prerequisite for the preservation of biodiversity, and can provide a baseline against which to measure the impacts of climate change. Here we analyse patterns of marine mammal species richness based on predictions of global distributional ranges for 115 species, including all extant pinnipeds and cetaceans. We used an environmental suitability model specifically designed to address the paucity of distributional data for many marine mammal species. We generated richness patterns by overlaying predicted distributions for all species; these were then validated against sightings data from dedicated long-term surveys in the Eastern Tropical Pacific, the Northeast Atlantic and the Southern Ocean. Model outputs correlated well with empirically observed patterns of biodiversity in all three survey regions. Marine mammal richness was predicted to be highest in temperate waters of both hemispheres with distinct hotspots around New Zealand, Japan, Baja California, the Galapagos Islands, the Southeast Pacific, and the Southern Ocean. We then applied our model to explore potential changes in biodiversity under future perturbations of environmental conditions. Forward projections of biodiversity using an intermediate Intergovernmental Panel for Climate Change (IPCC) temperature scenario predicted that projected ocean warming and changes in sea ice cover until 2050 may have moderate effects on the spatial patterns of marine mammal richness. Increases in cetacean richness were predicted above 40° latitude in both hemispheres, while decreases in both pinniped and cetacean richness were expected at lower latitudes. Our results show how species distribution models can be applied to explore broad patterns of marine biodiversity worldwide for taxa for which limited distributional data are available. PMID:21625431

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging.

PubMed

Lauzier, Pascal Theriault; Tang, Jie; Speidel, Michael A; Chen, Guang-Hong

2012-07-01

To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise and streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Images reconstructed using FBP showed a highly nonuniform spatial distribution of noise. This spatial nonuniformity led to large fluctuations in the temporal direction. In the numerical phantom study, the level of noise was shown to vary by as much as 87% within a given image, and as much as 110% between different time frames for a ROI far from isocenter. The spatially nonuniform noise pattern was shown to correlate with the source trajectory and the object structure. In contrast, images reconstructed using SIR showed a highly uniform spatial distribution of noise, leading to smaller unexpected noise fluctuations in the temporal direction when a short scan angular range was used. In the numerical phantom study, the noise varied by less than 37% within a given image, and by less than 20% between different time frames. Also, the noise standard deviation in SIR images was on average half of that of FBP images. In the in vivo studies, the deviation observed between quantitative perfusion metrics measured from low-dose scans and high-dose scans was mitigated when SIR was used instead of FBP to reconstruct images. (1) Images reconstructed using FBP suffered from nonuniform spatial noise levels. This nonuniformity is another manifestation of the detrimental effects caused by short-scan reconstruction in CT MPI. (2) Images reconstructed using SIR had a much lower and more uniform noise level and thus can be used as a potential solution to address the FBP nonuniformity. (3) Given the improvement in the accuracy of the perfusion metrics when using SIR, it may be desirable to use a statistical reconstruction framework to perform low-dose dynamic CT MPI.

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging

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

Lauzier, Pascal Theriault; Tang Jie; Speidel, Michael A.

Purpose: To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise andmore » streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Methods: Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Results: Images reconstructed using FBP showed a highly nonuniform spatial distribution of noise. This spatial nonuniformity led to large fluctuations in the temporal direction. In the numerical phantom study, the level of noise was shown to vary by as much as 87% within a given image, and as much as 110% between different time frames for a ROI far from isocenter. The spatially nonuniform noise pattern was shown to correlate with the source trajectory and the object structure. In contrast, images reconstructed using SIR showed a highly uniform spatial distribution of noise, leading to smaller unexpected noise fluctuations in the temporal direction when a short scan angular range was used. In the numerical phantom study, the noise varied by less than 37% within a given image, and by less than 20% between different time frames. Also, the noise standard deviation in SIR images was on average half of that of FBP images. In the in vivo studies, the deviation observed between quantitative perfusion metrics measured from low-dose scans and high-dose scans was mitigated when SIR was used instead of FBP to reconstruct images. Conclusions: (1) Images reconstructed using FBP suffered from nonuniform spatial noise levels. This nonuniformity is another manifestation of the detrimental effects caused by short-scan reconstruction in CT MPI. (2) Images reconstructed using SIR had a much lower and more uniform noise level and thus can be used as a potential solution to address the FBP nonuniformity. (3) Given the improvement in the accuracy of the perfusion metrics when using SIR, it may be desirable to use a statistical reconstruction framework to perform low-dose dynamic CT MPI.« less

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging

PubMed Central

Lauzier, Pascal Thériault; Tang, Jie; Speidel, Michael A.; Chen, Guang-Hong

2012-01-01

Purpose: To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise and streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Methods: Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Results: Images reconstructed using FBP showed a highly nonuniform spatial distribution of noise. This spatial nonuniformity led to large fluctuations in the temporal direction. In the numerical phantom study, the level of noise was shown to vary by as much as 87% within a given image, and as much as 110% between different time frames for a ROI far from isocenter. The spatially nonuniform noise pattern was shown to correlate with the source trajectory and the object structure. In contrast, images reconstructed using SIR showed a highly uniform spatial distribution of noise, leading to smaller unexpected noise fluctuations in the temporal direction when a short scan angular range was used. In the numerical phantom study, the noise varied by less than 37% within a given image, and by less than 20% between different time frames. Also, the noise standard deviation in SIR images was on average half of that of FBP images. In the in vivo studies, the deviation observed between quantitative perfusion metrics measured from low-dose scans and high-dose scans was mitigated when SIR was used instead of FBP to reconstruct images. Conclusions: (1) Images reconstructed using FBP suffered from nonuniform spatial noise levels. This nonuniformity is another manifestation of the detrimental effects caused by short-scan reconstruction in CT MPI. (2) Images reconstructed using SIR had a much lower and more uniform noise level and thus can be used as a potential solution to address the FBP nonuniformity. (3) Given the improvement in the accuracy of the perfusion metrics when using SIR, it may be desirable to use a statistical reconstruction framework to perform low-dose dynamic CT MPI. PMID:22830741

High-spatial-resolution nanoparticle x-ray fluorescence tomography

NASA Astrophysics Data System (ADS)

Larsson, Jakob C.; Vâgberg, William; Vogt, Carmen; Lundström, Ulf; Larsson, Daniel H.; Hertz, Hans M.

2016-03-01

X-ray fluorescence tomography (XFCT) has potential for high-resolution 3D molecular x-ray bio-imaging. In this technique the fluorescence signal from targeted nanoparticles (NPs) is measured, providing information about the spatial distribution and concentration of the NPs inside the object. However, present laboratory XFCT systems typically have limited spatial resolution (>1 mm) and suffer from long scan times and high radiation dose even at high NP concentrations, mainly due to low efficiency and poor signal-to-noise ratio. We have developed a laboratory XFCT system with high spatial resolution (sub-100 μm), low NP concentration and vastly decreased scan times and dose, opening up the possibilities for in-vivo small-animal imaging research. The system consists of a high-brightness liquid-metal-jet microfocus x-ray source, x-ray focusing optics and an energy-resolving photon-counting detector. By using the source's characteristic 24 keV line-emission together with carefully matched molybdenum nanoparticles the Compton background is greatly reduced, increasing the SNR. Each measurement provides information about the spatial distribution and concentration of the Mo nanoparticles. A filtered back-projection method is used to produce the final XFCT image.

Anticipating Forest and Range Land Development in Central Oregon (USA) for Landscape Analysis, with an Example Application Involving Mule Deer

NASA Astrophysics Data System (ADS)

Kline, Jeffrey D.; Moses, Alissa; Burcsu, Theresa

2010-05-01

Forest policymakers, public lands managers, and scientists in the Pacific Northwest (USA) seek ways to evaluate the landscape-level effects of policies and management through the multidisciplinary development and application of spatially explicit methods and models. The Interagency Mapping and Analysis Project (IMAP) is an ongoing effort to generate landscape-wide vegetation data and models to evaluate the integrated effects of disturbances and management activities on natural resource conditions in Oregon and Washington (USA). In this initial analysis, we characterized the spatial distribution of forest and range land development in a four-county pilot study region in central Oregon. The empirical model describes the spatial distribution of buildings and new building construction as a function of population growth, existing development, topography, land-use zoning, and other factors. We used the model to create geographic information system maps of likely future development based on human population projections to inform complementary landscape analyses underway involving vegetation, habitat, and wildfire interactions. In an example application, we use the model and resulting maps to show the potential impacts of future forest and range land development on mule deer ( Odocoileus hemionus) winter range. Results indicate significant development encroachment and habitat loss already in 2000 with development located along key migration routes and increasing through the projection period to 2040. The example application illustrates a simple way for policymakers and public lands managers to combine existing data and preliminary model outputs to begin to consider the potential effects of development on future landscape conditions.

Globular cluster systems and their host galaxies: comparison of spatial distributions and colors

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

Hargis, Jonathan R.; Rhode, Katherine L., E-mail: jhargis@haverford.edu

2014-11-20

We present a study of the spatial and color distributions of four early-type galaxies and their globular cluster (GC) systems observed as part of our ongoing wide-field imaging survey. We use BVR KPNO 4 m+MOSAIC imaging data to characterize the galaxies' GC populations, perform surface photometry of the galaxies, and compare the projected two-dimensional shape of the host galaxy light to that of the GC population. The GC systems of the ellipticals NGC 4406 and NGC 5813 both show an elliptical distribution consistent with that of the host galaxy light. Our analysis suggests a similar result for the giant ellipticalmore » NGC 4472, but a smaller GC candidate sample precludes a definite conclusion. For the S0 galaxy NGC 4594, the GCs have a circular projected distribution, in contrast to the host galaxy light, which is flattened in the inner regions. For NGC 4406 and NGC 5813, we also examine the projected shapes of the metal-poor and metal-rich GC subpopulations and find that both subpopulations have elliptical shapes that are consistent with those of the host galaxy light. Lastly, we use integrated colors and color profiles to compare the stellar populations of the galaxies to their GC systems. For each galaxy, we explore the possibility of color gradients in the individual metal-rich and metal-poor GC subpopulations. We find statistically significant color gradients in both GC subpopulations of NGC 4594 over the inner ∼5 effective radii (∼20 kpc). We compare our results to scenarios for the formation and evolution of giant galaxies and their GC systems.« less

Population exposure to heat-related extremes: Demographic change vs climate change

NASA Astrophysics Data System (ADS)

Jones, B.; O'Neill, B. C.; Tebaldi, C.; Oleson, K. W.

2014-12-01

Extreme heat events are projected to increase in frequency and intensity in the coming decades [1]. The physical effects of extreme heat on human populations are well-documented, and anticipating changes in future exposure to extreme heat is a key component of adequate planning/mitigation [2, 3]. Exposure to extreme heat depends not only on changing climate, but also on changes in the size and spatial distribution of the human population. Here we focus on systematically quantifying exposure to extreme heat as a function of both climate and population change. We compare exposure outcomes across multiple global climate and spatial population scenarios, and characterize the relative contributions of each to population exposure to extreme heat. We consider a 2 x 2 matrix of climate and population output, using projections of heat extremes corresponding to RCP 4.5 and RCP 8.5 from the NCAR community land model, and spatial population projections for SSP 3 and SSP 5 from the NCAR spatial population downscaling model. Our primary comparison is across RCPs - exposure outcomes from RCP 4.5 versus RCP 8.5 - paying particular attention to how variation depends on the choice of SSP in terms of aggregate global and regional exposure, as well as the spatial distribution of exposure. We assess how aggregate exposure changes based on the choice of SSP, and which driver is more important, population or climate change (i.e. does that outcome vary more as a result of RCP or SSP). We further decompose the population component to analyze the contributions of total population change, migration, and changes in local spatial structure. Preliminary results from a similar study of the US suggests a four-to-six fold increase in total exposure by the latter half of the 21st century. Changes in population are as important as changes in climate in driving this outcome, and there is regional variation in the relative importance of each. Aggregate population growth, as well as redistribution of the population across larger US regions, strongly affects outcomes while smaller-scale spatial patterns of population change have smaller effects. [1] Collins, M. et al. (2013) Contribution of WG I to the 5th AR of the IPCC[2] Romero-Lankao, P. et al (2014) Contribution of WG II to the 5th AR of the IPCC[3] Walsh, J. et al. (2014) The 3rd National Climate Assessment

Projecting distribution of the overwintering population of Sogatella furcifera (Hemiptera: Delphacidae), in Yunnan, China with analysis on key influencing climatic factors.

PubMed

Hu, Shao-Ji; Liu, Xiao-Fei; Fu, Da-Ying; Huang, Wei; Wang, Xue-Ying; Liu, Xiao-Jun; Lü, Jian-Ping; Ye, Hui

2015-01-01

Sogatella furcifera (Horváth) is the most threatening migratory rice pest in Yunnan, China. S. furcifera overwinters in low- altitude basins and valleys in southern Yunnan and migrates northward in spring and summer of the following year, causing serious damage during migration. The overwintering distribution, areas, and spatial pattern of S. furcifera are relevant to the migration and outbreak of this pest. Based on a 4-yr field survey (2010-2013), this study projected areas suitable for S. furcifera to overwinter using a species distribution model, and analyzed the key influencing climatic factors using principal component analysis (PCA) and ecological niche factor analysis (ENFA). Our field survey showed that the northern latitudinal- and upper elevation limits of overwintering S. furcifera was 25.4° N and 1,608 m in western Yunnan and 24.2° N and 1,563 m in eastern Yunnan. The species distribution model produced a fragmented distribution pattern, with most of which in western Yunnan and only a few in eastern Yunnan. The PCA and ENFA analyses showed that the mean temperature of the driest quarter and the precipitation of the coldest quarter significantly influenced the distribution of S. furcifera in winter. The results suggested that the complex topography, spatial differences in winter temperatures, and host availability altogether determined the distribution of overwintering S. furcifera. Compared with previous surveys, the northern latitudinal- and upper elevation limits of overwintering S. furcifera were higher, while the population became rarer in some suitable areas due to change of farmland utilization in winter and possibly climate change. © The Author 2015. Published by Oxford University Press on behalf of the Entomological Society of America.

Segregating animals in naturalistic surroundings: interaction of color distributions and mechanisms.

PubMed

Jansen, Michael; Giesel, Martin; Zaidi, Qasim

2016-03-01

Humans have been shown to rapidly detect animals in naturalistic scenes, but the role of color in this task is unclear. We first analyze the color information contained in a large number of images of salient and camouflaged animals in generic backgrounds. We found that color distributions of most animals and of their immediate backgrounds were oriented along other than the cardinal directions of color space. In addition, the maximum distances between animals and background distributions also tended to be along noncardinal directions, suggesting a role for higher-order cortical color mechanisms whose preferred axes are distributed widely in color space. We measured temporal thresholds for segmenting animal color distributions from background distributions in the absence of spatial cues. Combined over all observers and all images in our sample, thresholds for segmenting isoluminant projections of these distributions were lower than for segmenting the original distributions and considerably lower than for segmenting achromatic projections. Color information is thus likely to be useful in segregating animals in generic views, i.e., views not purposely chosen by the photographer to enhance the visibility of the animal. However, a comparison of thresholds with distances between distributions failed to reveal any advantage conferred by higher-order color mechanisms.

Improving Access to MODIS Biophysical Science Products for NACP Investigators

NASA Technical Reports Server (NTRS)

Wolfe, Robert E.; Gao, Feng; Morisette, Jeffrey T.; Ederer, Gregory A.; Pedelty, Jeffrey A.

2007-01-01

MODIS 4 NACP is a NASA-funded project supporting the North American Carbon Program (NACP). The purpose of this Advancing Collaborative Connections for Earth-Sun System Science (ACCESS) project is to provide researchers with Moderate Resolution Imaging Spectroradiometer (MODIS) biophysical data products that are custom tailored for use in NACP model studies. Standard MODIS biophysical products provide used to improve our understanding on the climate and ecosystem changes. However, direct uses of the MODIS biophysical parameters are constrained by retrieval quality and cloud contamination. Another challenge that NACP users face is acquiring MODIS data in formats and at spatial-temporal resolutions consistent with other data sets they use. We have been working closely with key NACP users to tailor the MODIS products to fit their needs. First, we provide new temporally smoothed and spatially continuous MODIS biophysical data sets. Second, we are distributing MODIS data at suitable spatial-temporal resolutions and in formats consistent with other data integration into model studies.

It’s our Fault: Immersing Young Learners in Authentic Practices of Seismology

NASA Astrophysics Data System (ADS)

Kilb, D. L.; Moher, T.; Wiley, J.

2009-12-01

The scalable RoomQuake seismology project uses a learning technology framework-embedded phenomena (Moher, 2006)—that simulates seismic phenomena mapped directly onto the physical space of classrooms. This project, aimed at the upper elementary level, situates students as the scientists engaged in an extended investigation designed to discover the spatial, temporal, and intensity distributions of a series of earthquakes. This project emulates earthquake occurrence over a condensed time and spatial span, with students mapping an earthquake fault imagined to be running through their classroom. The students learn: basic seismology terms; ability to identify seismic P- and S-waves; skills associated with trilateration; nomogram/graph reading skills; and the ability to recognize the emergence of a fault based on RoomQuake geometries. From the students’ perspectives, and similar to real-world earthquakes, RoomQuakes occur at unknown times over the course of several weeks. Multiple computers distributed around the perimeter of the classroom serve as simulated seismographs that depict continuous strip-chart seismic recordings. Most of the time the seismograms reflect background noise, but at (apparently) unpredictable times a crescendoing rumble (emanating from a subwoofer) signals a RoomQuake. Hearing this signal, students move to the seismic stations to read the strip charts. Next, the students trilaterate the RoomQuake epicenter by arcing calibrated strings of length proportional to S-P latencies from each seismic station until a common point is identified. Each RoomQuake epicenter is marked by hanging a Styrofoam ball (color-coded by magnitude) from the ceiling. The developing ‘fault’ within the classroom provides an immersive historic record of the RoomQuake’s spatial distribution. Students also maintain a temporal record of events on a large time-line on the wall (recognizing time-related phenomena like aftershocks) and a record of magnitude frequencies on another large wall chart (basis for a simplified version of Gutenberg-Richter). We have used Roomquake in 13 urban and suburban classrooms. We find students develop high levels of proficiency in the interpretation of seismograms and identification of epicenters. Pre-post assessments have yielded significant learning gains with respect to conceptual understandings of the causes and distributions of earthquakes and changes in attitudes self-efficacy.

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.

Mapping permafrost change hot-spots with Landsat time-series

NASA Astrophysics Data System (ADS)

Grosse, G.; Nitze, I.

2016-12-01

Recent and projected future climate warming strongly affects permafrost stability over large parts of the terrestrial Arctic with local, regional and global scale consequences. The monitoring and quantification of permafrost and associated land surface changes in these areas is crucial for the analysis of hydrological and biogeochemical cycles as well as vegetation and ecosystem dynamics. However, detailed knowledge of the spatial distribution and the temporal dynamics of these processes is scarce and likely key locations of permafrost landscape dynamics may remain unnoticed. As part of the ERC funded PETA-CARB and ESA GlobPermafrost projects, we developed an automated processing chain based on data from the entire Landsat archive (excluding MSS) for the detection of permafrost change related processes and hotspots. The automated method enables us to analyze thousands of Landsat scenes, which allows for a multi-scaled spatio-temporal analysis at 30 meter spatial resolution. All necessary processing steps are carried out automatically with minimal user interaction, including data extraction, masking, reprojection, subsetting, data stacking, and calculation of multi-spectral indices. These indices, e.g. Landsat Tasseled Cap and NDVI among others, are used as proxies for land surface conditions, such as vegetation status, moisture or albedo. Finally, a robust trend analysis is applied to each multi-spectral index and each pixel over the entire observation period of up to 30 years from 1985 to 2015, depending on data availability. Large transects of around 2 million km² across different permafrost types in Siberia and North America have been processed. Permafrost related or influencing landscape dynamics were detected within the trend analysis, including thermokarst lake dynamics, fires, thaw slumps, and coastal dynamics. The produced datasets will be distributed to the community as part of the ERC PETA-CARB and ESA GlobPermafrost projects. Users are encouraged to provide feedback and ground truth data for a continuous improvement of our methodology and datasets, which will lead to a better understanding of the spatial and temporal distribution of changes within the vulnerable permafrost zone.

Applications of Geomatics in Surface Mining

NASA Astrophysics Data System (ADS)

Blachowski, Jan; Górniak-Zimroz, Justyna; Milczarek, Wojciech; Pactwa, Katarzyna

2017-12-01

In terms of method of extracting mineral from deposit, mining can be classified into: surface, underground, and borehole mining. Surface mining is a form of mining, in which the soil and the rock covering the mineral deposits are removed. Types of surface mining include mainly strip and open-cast methods, as well as quarrying. Tasks associated with surface mining of minerals include: resource estimation and deposit documentation, mine planning and deposit access, mine plant development, extraction of minerals from deposits, mineral and waste processing, reclamation and reclamation of former mining grounds. At each stage of mining, geodata describing changes occurring in space during the entire life cycle of surface mining project should be taken into consideration, i.e. collected, analysed, processed, examined, distributed. These data result from direct (e.g. geodetic) and indirect (i.e. remote or relative) measurements and observations including airborne and satellite methods, geotechnical, geological and hydrogeological data, and data from other types of sensors, e.g. located on mining equipment and infrastructure, mine plans and maps. Management of such vast sources and sets of geodata, as well as information resulting from processing, integrated analysis and examining such data can be facilitated with geomatic solutions. Geomatics is a discipline of gathering, processing, interpreting, storing and delivering spatially referenced information. Thus, geomatics integrates methods and technologies used for collecting, management, processing, visualizing and distributing spatial data. In other words, its meaning covers practically every method and tool from spatial data acquisition to distribution. In this work examples of application of geomatic solutions in surface mining on representative case studies in various stages of mine operation have been presented. These applications include: prospecting and documenting mineral deposits, assessment of land accessibility for a potential large-scale surface mining project, modelling mineral deposit (granite) management, concept of a system for management of conveyor belt network technical condition, project of a geoinformation system of former mining terrains and objects, and monitoring and control of impact of surface mining on mine surroundings with satellite radar interferometry.

The Spatial Distribution of Resolved Young Stars in Blue Compact Dwarf Galaxies

NASA Astrophysics Data System (ADS)

Murphy, K.; Crone, M. M.

2002-12-01

We present the first results from a survey of the distribution of resolved young stars in Blue Compact Dwarf Galaxies. In order to identify the dominant physical processes driving star formation in these puzzling galaxies, we use a multi-scale cluster-finding algorithm to quantify the characteristic scales and properties of star-forming regions, from sizes smaller than 10 pc up to the size of each entire galaxy. This project was partially funded by the Lubin Chair at Skidmore College.

Projecting climate change impacts on hydrology: the potential role of daily GCM output

NASA Astrophysics Data System (ADS)

Maurer, E. P.; Hidalgo, H. G.; Das, T.; Dettinger, M. D.; Cayan, D.

2008-12-01

A primary challenge facing resource managers in accommodating climate change is determining the range and uncertainty in regional and local climate projections. This is especially important for assessing changes in extreme events, which will drive many of the more severe impacts of a changed climate. Since global climate models (GCMs) produce output at a spatial scale incompatible with local impact assessment, different techniques have evolved to downscale GCM output so locally important climate features are expressed in the projections. We compared skill and hydrologic projections using two statistical downscaling methods and a distributed hydrology model. The downscaling methods are the constructed analogues (CA) and the bias correction and spatial downscaling (BCSD). CA uses daily GCM output, and can thus capture GCM projections for changing extreme event occurrence, while BCSD uses monthly output and statistically generates historical daily sequences. We evaluate the hydrologic impacts projected using downscaled climate (from the NCEP/NCAR reanalysis as a surrogate GCM) for the late 20th century with both methods, comparing skill in projecting soil moisture, snow pack, and streamflow at key locations in the Western United States. We include an assessment of a new method for correcting for GCM biases in a hybrid method combining the most important characteristics of both methods.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe.

PubMed

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe

PubMed Central

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes. PMID:27074044

Taking a 'Big Data' approach to data quality in a citizen science project.

PubMed

Kelling, Steve; Fink, Daniel; La Sorte, Frank A; Johnston, Alison; Bruns, Nicholas E; Hochachka, Wesley M

2015-11-01

Data from well-designed experiments provide the strongest evidence of causation in biodiversity studies. However, for many species the collection of these data is not scalable to the spatial and temporal extents required to understand patterns at the population level. Only data collected from citizen science projects can gather sufficient quantities of data, but data collected from volunteers are inherently noisy and heterogeneous. Here we describe a 'Big Data' approach to improve the data quality in eBird, a global citizen science project that gathers bird observations. First, eBird's data submission design ensures that all data meet high standards of completeness and accuracy. Second, we take a 'sensor calibration' approach to measure individual variation in eBird participant's ability to detect and identify birds. Third, we use species distribution models to fill in data gaps. Finally, we provide examples of novel analyses exploring population-level patterns in bird distributions.

Spatial-temporal Evolution of Vegetation Coverage and Analysis of it’s Future Trends in Wujiang River Basin

NASA Astrophysics Data System (ADS)

Xiao, Jianyong; Bai, Xiaoyong; Zhou, Dequan; Qian, Qinghuan; Zeng, Cheng; Chen, Fei

2018-01-01

Vegetation coverage dynamics is affected by climatic, topography and human activities, which is an important indicator reflecting the regional ecological environment. Revealing the spatial-temporal characteristics of vegetation coverage is of great significance to the protection and management of ecological environment. Based on MODIS NDVI data and the Maximum Value Composites (MVC), we excluded soil spectrum interference to calculate Fractional Vegetation Coverage (FVC). Then the long-term FVC was used to calculate the spatial pattern and temporal variation of vegetation in Wujiang River Basin from 2000 to 2016 by using Trend analysis and Hurst index. The relationship between topography and spatial distribution of FVC was analyzed. The main conclusions are as follows: (1) The multi-annual mean vegetation coverage reveals a spatial distribution variation characteristic of low value in midstream and high level in other parts of the basin, owing a mean value of 0.6567. (2) From 2000 to 2016, the FVC of the Wujiang River Basin fluctuated between 0.6110 and 0.7380, and the overall growth rate of FVC was 0.0074/a. (3) The area of vegetation coverage tending to improve is more than that going to degrade in the future. Grass land, Arable land and Others improved significantly; karst rocky desertification comprehensive management project lead to persistent vegetation coverage improvement of Grass land, Arable land and Others. Residential land is covered with obviously degraded vegetation, resulting of urban sprawl; (4) The spatial distribution of FVC is positively correlated with TNI. Researches of spatial-temporal evolution of vegetation coverage have significant meaning for the ecological environment protection and management of the Wujiang River Basin.

Evaluation of Denoising Strategies to Address Motion-Correlated Artifacts in Resting-State Functional Magnetic Resonance Imaging Data from the Human Connectome Project

PubMed Central

Kandala, Sridhar; Nolan, Dan; Laumann, Timothy O.; Power, Jonathan D.; Adeyemo, Babatunde; Harms, Michael P.; Petersen, Steven E.; Barch, Deanna M.

2016-01-01

Abstract Like all resting-state functional connectivity data, the data from the Human Connectome Project (HCP) are adversely affected by structured noise artifacts arising from head motion and physiological processes. Functional connectivity estimates (Pearson's correlation coefficients) were inflated for high-motion time points and for high-motion participants. This inflation occurred across the brain, suggesting the presence of globally distributed artifacts. The degree of inflation was further increased for connections between nearby regions compared with distant regions, suggesting the presence of distance-dependent spatially specific artifacts. We evaluated several denoising methods: censoring high-motion time points, motion regression, the FMRIB independent component analysis-based X-noiseifier (FIX), and mean grayordinate time series regression (MGTR; as a proxy for global signal regression). The results suggest that FIX denoising reduced both types of artifacts, but left substantial global artifacts behind. MGTR significantly reduced global artifacts, but left substantial spatially specific artifacts behind. Censoring high-motion time points resulted in a small reduction of distance-dependent and global artifacts, eliminating neither type. All denoising strategies left differences between high- and low-motion participants, but only MGTR substantially reduced those differences. Ultimately, functional connectivity estimates from HCP data showed spatially specific and globally distributed artifacts, and the most effective approach to address both types of motion-correlated artifacts was a combination of FIX and MGTR. PMID:27571276

Comparison of WEPP and APEX runoff and erosion prediction at field scale in Goodwater Creek Experimental Watershed

USDA-ARS?s Scientific Manuscript database

The Water Erosion Prediction Project (WEPP) and the Agricultural Policy/Environmental eXtender (APEX) are process-based models that can predict spatial and temporal distributions of erosion for hillslopes and watersheds. This study applies the WEPP model to predict runoff and erosion for a 35-ha fie...

Pathogen-Host Associations and Predicted Range Shifts of Human Monkeypox in Response to Climate Change in Central Africa

PubMed Central

Thomassen, Henri A.; Fuller, Trevon; Asefi-Najafabady, Salvi; Shiplacoff, Julia A. G.; Mulembakani, Prime M.; Blumberg, Seth; Johnston, Sara C.; Kisalu, Neville K.; Kinkela, Timothée L.; Fair, Joseph N.; Wolfe, Nathan D.; Shongo, Robert L.; LeBreton, Matthew; Meyer, Hermann; Wright, Linda L.; Muyembe, Jean-Jacques; Buermann, Wolfgang; Okitolonda, Emile; Hensley, Lisa E.; Lloyd-Smith, James O.; Smith, Thomas B.; Rimoin, Anne W.

2013-01-01

Climate change is predicted to result in changes in the geographic ranges and local prevalence of infectious diseases, either through direct effects on the pathogen, or indirectly through range shifts in vector and reservoir species. To better understand the occurrence of monkeypox virus (MPXV), an emerging Orthopoxvirus in humans, under contemporary and future climate conditions, we used ecological niche modeling techniques in conjunction with climate and remote-sensing variables. We first created spatially explicit probability distributions of its candidate reservoir species in Africa's Congo Basin. Reservoir species distributions were subsequently used to model current and projected future distributions of human monkeypox (MPX). Results indicate that forest clearing and climate are significant driving factors of the transmission of MPX from wildlife to humans under current climate conditions. Models under contemporary climate conditions performed well, as indicated by high values for the area under the receiver operator curve (AUC), and tests on spatially randomly and non-randomly omitted test data. Future projections were made on IPCC 4th Assessment climate change scenarios for 2050 and 2080, ranging from more conservative to more aggressive, and representing the potential variation within which range shifts can be expected to occur. Future projections showed range shifts into regions where MPX has not been recorded previously. Increased suitability for MPX was predicted in eastern Democratic Republic of Congo. Models developed here are useful for identifying areas where environmental conditions may become more suitable for human MPX; targeting candidate reservoir species for future screening efforts; and prioritizing regions for future MPX surveillance efforts. PMID:23935820

Schistosomiasis Breeding Environment Situation Analysis in Dongting Lake Area

NASA Astrophysics Data System (ADS)

Li, Chuanrong; Jia, Yuanyuan; Ma, Lingling; Liu, Zhaoyan; Qian, Yonggang

2013-01-01

Monitoring environmental characteristics, such as vegetation, soil moisture et al., of Oncomelania hupensis (O. hupensis)’ spatial/temporal distribution is of vital importance to the schistosomiasis prevention and control. In this study, the relationship between environmental factors derived from remotely sensed data and the density of O. hupensis was analyzed by a multiple linear regression model. Secondly, spatial analysis of the regression residual was investigated by the semi-variogram method. Thirdly, spatial analysis of the regression residual and the multiple linear regression model were both employed to estimate the spatial variation of O. hupensis density. Finally, the approach was used to monitor and predict the spatial and temporal variations of oncomelania of Dongting Lake region, China. And the areas of potential O. hupensis habitats were predicted and the influence of Three Gorges Dam (TGB)project on the density of O. hupensis was analyzed.

The CLIMB Geoportal - A web-based dissemination and documentation platform for hydrological modelling data

NASA Astrophysics Data System (ADS)

Blaschek, Michael; Gerken, Daniel; Ludwig, Ralf; Duttmann, Rainer

2015-04-01

Geoportals are important elements of spatial data infrastructures (SDIs) that are strongly based on GIS-related web services. These services are basically meant for distributing, documenting and visualizing (spatial) data in a standardized manner; an important but challenging task especially in large scientific projects with a high number of data suppliers and producers from various countries. This presentation focuses on introducing the free and open-source based geoportal solution developed within the research project CLIMB (Climate Induced Changes on the Hydrology of Mediterranean Basins, www.climb-fp7.eu) that serves as the central platform for interchanging project-related spatial data and information. In this collaboration, financed by the EU-FP7-framework and coordinated at the LMU Munich, 21 partner institutions from nine European and non-European countries were involved. The CLIMB Geoportal (lgi-climbsrv.geographie.uni-kiel.de) stores and provides spatially distributed data about the current state and future changes of the hydrological conditions within the seven CLIMB test sites around the Mediterranean. Hydrological modelling outcome - validated by the CLIMB partners - is offered to the public in forms of Web Map Services (WMS), whereas downloading the underlying data itself through Web Coverage Services (WCS) is possible for registered users only. A selection of common indicators such as discharge, drought index as well as uncertainty measures including their changes over time were used in different spatial resolution. Besides map information, the portal enables the graphical display of time series of selected variables calculated by the individual models applied within the CLIMB-project. The implementation of the CLIMB Geoportal is finally based on version 2.0c5 of the open source geospatial content management system GeoNode. It includes a GeoServer instance for providing the OGC-compliant web services and comes with a metadata catalog (pycsw) as well as a built-in WebGIS-client based on GeoExt (GeoExplorer). PostgreSQL enhanced by PostGIS in versions 9.2.1/2.0.1 serves as database backend for all base data of the study sites and for the time series of relevant hydrological indicators. Spatial model results in raster-format are stored file-based as GeoTIFFs. Due to the high number of model outputs, the generation of metadata (xml) and graphical rendering instructions (sld) associated with each single layer of the WMS has been done automatically using the statistical software R. Additional applications that have been programmed during the project period include a Java-based interface for comfortable download of climate data that was initially needed as input data in hydrological modeling as well as a tool for displaying time series of selected risk indicators which is directly integrated into the portal structure implemented using Python (Django) and JavaScript. The presented CLIMB Geoportal shows that relevant results of even large international research projects involving many partners and varying national standards in data handling, can be effectively disseminated to stakeholders, policy makers and other interested parties. Thus, it is a successful example of using free and open-source software for providing long-term visibility and access to data produced within a particular (environmental) research project.

High spatiotemporal resolution monitoring of hydrological function across degraded peatlands in the south west UK.

NASA Astrophysics Data System (ADS)

Ashe, Josie; Luscombe, David; Grand-Clement, Emilie; Gatis, Naomi; Anderson, Karen; Brazier, Richard

2014-05-01

The Exmoor/Dartmoor Mires Project is a peatland restoration programme focused on the geoclimatically marginal blanket bogs of South West England. In order to better understand the hydrological functioning of degraded/restored peatlands and support land management decisions across these uplands, this study is providing robust spatially distributed, hydrological monitoring at a high temporal resolution and in near real time. This paper presents the conceptual framework and experimental design for three hydrological monitoring arrays situated in headwater catchments dominated by eroding and drained blanket peatland. Over 250 individual measurements are collected at a high temporal resolution (15 minute time-step) via sensors integrated within a remote telemetry system. These are sent directly to a dedicated server over VHF and GPRS mobile networks. Sensors arrays are distributed at varying spatial scales throughout the studied catchments and record multiple parameters including: water table depth, channel flow, temperature, conductivity and pH measurements. A full suite of meteorological sensors and ten spatially distributed automatic flow based water samplers are also connected to the telemetry system and controlled remotely. This paper will highlight the challenges and solutions to obtaining these data in exceptionally remote and harsh field conditions over long (multi annual) temporal scales.

An improved protocol for optical projection tomography imaging reveals lobular heterogeneities in pancreatic islet and β-cell mass distribution

PubMed Central

2011-01-01

Optical projection tomography (OPT) imaging is a powerful tool for three-dimensional imaging of gene and protein distribution patterns in biomedical specimens. We have previously demonstrated the possibility, by this technique, to extract information of the spatial and quantitative distribution of the islets of Langerhans in the intact mouse pancreas. In order to further increase the sensitivity of OPT imaging for this type of assessment, we have developed a protocol implementing a computational statistical approach: contrast limited adaptive histogram equalization (CLAHE). We demonstrate that this protocol significantly increases the sensitivity of OPT imaging for islet detection, helps preserve islet morphology and diminish subjectivity in thresholding for tomographic reconstruction. When applied to studies of the pancreas from healthy C57BL/6 mice, our data reveal that, at least in this strain, the pancreas harbors substantially more islets than has previously been reported. Further, we provide evidence that the gastric, duodenal and splenic lobes of the pancreas display dramatic differences in total and relative islet and β-cell mass distribution. This includes a 75% higher islet density in the gastric lobe as compared to the splenic lobe and a higher relative volume of insulin producing cells in the duodenal lobe as compared to the other lobes. Altogether, our data show that CLAHE substantially improves OPT based assessments of the islets of Langerhans and that lobular origin must be taken into careful consideration in quantitative and spatial assessments of the pancreas. PMID:21633198

Projecting malaria hazard from climate change in eastern Africa using large ensembles to estimate uncertainty.

PubMed

Leedale, Joseph; Tompkins, Adrian M; Caminade, Cyril; Jones, Anne E; Nikulin, Grigory; Morse, Andrew P

2016-03-31

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate- driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

A high-resolution, regional analysis of stormwater runoff for managed aquifer recharge site assessment

NASA Astrophysics Data System (ADS)

Young, K. S.; Fisher, A. T.; Beganskas, S.; Harmon, R. E.; Teo, E. K.; Weir, W. B.; Lozano, S.

2016-12-01

Distributed Stormwater Collection-Managed Aquifer Recharge (DSC-MAR) presents a cost-effective method of aquifer replenishment by collecting runoff and infiltrating it into underlying aquifers, but its successful implementation demands thorough knowledge of the distribution and availability of hillslope runoff. We applied a surface hydrology model to analyze the dynamics of hillslope runoff at high resolution (0.1 to 1.0 km2) across the 350 km2 San Lorenzo River Basin (SLRB) watershed, northern Santa Cruz County, CA. We used a 3 m digital elevation model to create a detailed model grid, which we parameterized with high-resolution geologic, hydrologic, and land use data. To analyze hillslope runoff under a range of precipitation regimes, we developed dry, normal, and wet climate scenarios from historic daily precipitation records (1981-2014). Simulation results show high spatial variability of hillslope runoff generation as a function of differences in precipitation and soil and land use conditions, and reveal a consistent increase in the spatial and temporal variability of runoff under wetter climate scenarios. Our results suggest that there may be opportunities to develop successful DSC-MAR projects that provide benefits during all climate scenarios. In the SLRB, our results indicate that annual hillslope runoff generation achieves a target minimum of 100 acre-ft, per 100 acres of drainage area, in approximately 15% of the region during dry climate scenarios and 60% of the region during wet climate scenarios. The high spatial and temporal resolution of our simulation output enables quantification of hillslope runoff at sub-watershed scales, commensurate with the spacing and operation of DSC-MAR. This study demonstrates a viable tool for screening of potential DSC-MAR project sites and assessing project performance under a range of climate and land use scenarios.

Exceedance probability map: a tool helping the definition of arsenic Natural Background Level (NBL) within the Drainage Basin to the Venice Lagoon (NE Italy)

NASA Astrophysics Data System (ADS)

Dalla Libera, Nico; Fabbri, Paolo; Mason, Leonardo; Piccinini, Leonardo; Pola, Marco

2017-04-01

Arsenic groundwater contamination affects worldwide shallower groundwater bodies. Starting from the actual knowledges around arsenic origin into groundwater, we know that the major part of dissolved arsenic is naturally occurring through the dissolution of As-bearing minerals and ores. Several studies on the shallow aquifers of both the regional Venetian Plain (NE Italy) and the local Drainage Basin to the Venice Lagoon (DBVL) show local high arsenic concentration related to peculiar geochemical conditions, which drive arsenic mobilization. The uncertainty of arsenic spatial distribution makes difficult both the evaluation of the processes involved in arsenic mobilization and the stakeholders' decision about environmental management. Considering the latter aspect, the present study treats the problem of the Natural Background Level (NBL) definition as the threshold discriminating the natural contamination from the anthropogenic pollution. Actually, the UE's Directive 2006/118/EC suggests the procedures and criteria to set up the water quality standards guaranteeing a healthy status and reversing any contamination trends. In addition, the UE's BRIDGE project proposes some criteria, based on the 90th percentile of the contaminant's concentrations dataset, to estimate the NBL. Nevertheless, these methods provides just a statistical NBL for the whole area without considering the spatial variation of the contaminant's concentration. In this sense, we would reinforce the NBL concept using a geostatistical approach, which is able to give some detailed information about the distribution of arsenic concentrations and unveiling zones with high concentrations referred to the Italian drinking water standard (IDWS = 10 µg/liter). Once obtained the spatial information about arsenic distribution, we can apply the 90th percentile methods to estimate some Local NBL referring to every zones with arsenic higher than IDWS. The indicator kriging method was considered because it estimates the spatial distribution of the exceedance probabilities respect some pre-defined thresholds. This approach is largely mentioned in literature to face similar environmental problems. To test the validity of the procedure, we used the dataset from "A.Li.Na" project (founded by the Regional Environmental Agency) that defined regional NBLs of As, Fe, Mn and NH4+ into DBVL's groundwater. Primarily, we defined two thresholds corresponding respectively to the IDWS and the median of the data over the IDWS. These values were decided basing on the dataset's statistical structure and the quality criteria of the GWD 2006/118/EC. Subsequently, we evaluated the spatial distribution of the probability to exceed the defined thresholds using the Indicator kriging. The results highlight different zones with high exceedance probability ranging from 75% to 95% respect both the IDWS and the median value. Considering the geological setting of the DBVL, these probability values correspond with the occurrence of both organic matter and reducing conditions. In conclusion, the spatial prediction of the exceedance probability could be useful to define the areas in which estimate the local NBLs, enhancing the procedure of NBL definition. In that way, the NBL estimation could be more realistic because it considers the spatial distribution of the studied contaminant, distinguishing areas with high natural concentrations from polluted ones.

Fabrication of Nonperiodic Metasurfaces by Microlens Projection Lithography.

PubMed

Gonidec, Mathieu; Hamedi, Mahiar M; Nemiroski, Alex; Rubio, Luis M; Torres, Cesar; Whitesides, George M

2016-07-13

This paper describes a strategy that uses template-directed self-assembly of micrometer-scale microspheres to fabricate arrays of microlenses for projection photolithography of periodic, quasiperiodic, and aperiodic infrared metasurfaces. This method of "template-encoded microlens projection lithography" (TEMPL) enables rapid prototyping of planar, multiscale patterns of similarly shaped structures with critical dimensions down to ∼400 nm. Each of these structures is defined by local projection lithography with a single microsphere acting as a lens. This paper explores the use of TEMPL for the fabrication of a broad range of two-dimensional lattices with varying types of nonperiodic spatial distribution. The matching optical spectra of the fabricated and simulated metasurfaces confirm that TEMPL can produce structures that conform to expected optical behavior.

Projecting the Global Distribution of the Emerging Amphibian Fungal Pathogen, Batrachochytrium dendrobatidis, Based on IPCC Climate Futures.

PubMed

Xie, Gisselle Yang; Olson, Deanna H; Blaustein, Andrew R

2016-01-01

Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest) with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary), including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific) and also separately per region (region-specific). One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas, especially for sensitive species and those vulnerable to multiple threats.

Deciphering Front-Side Complex Formation in SN2 Reactions via Dynamics Mapping.

PubMed

Szabó, István; Olasz, Balázs; Czakó, Gábor

2017-07-06

Due to their importance in organic chemistry, the atomistic understanding of bimolecular nucleophilic substitution (S N 2) reactions shows exponentially growing interest. In this publication, the effect of front-side complex (FSC) formation is uncovered via quasi-classical trajectory computations combined with a novel analysis method called trajectory orthogonal projection (TOP). For both F - + CH 3 Y [Y = Cl,I] reactions, the lifetime distributions of the F - ···YCH 3 front-side complex revealed weakly trapped nucleophiles (F - ). However, only the F - + CH 3 I reaction features strongly trapped nucleophiles in the front-side region of the prereaction well. Interestingly, both back-side and front-side attack show propensity to long-lived FSC formation. Spatial distributions of the nucleophile demonstrate more prominent FSC formation in case of the F - + CH 3 I reaction compared to F - + CH 3 Cl. The presence of front-side intermediates and the broad spatial distribution in the back-side region may explain the indirect nature of the F - + CH 3 I reaction.

Grain Growth and Precipitation Behavior of Iridium Alloy DOP-26 During Long Term Aging

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

Pierce, Dean T.; Muralidharan, Govindarajan; Fox, Ethan E.

The influence of long term aging on grain growth and precipitate sizes and spatial distribution in iridium alloy DOP-26 was studied. Samples of DOP-26 were fabricated using the new process, recrystallized for 1 hour (h) at 1375 C, then aged at either 1300, 1400, or 1500 C for times ranging from 50 to 10,000 h. Grain size measurements (vertical and horizontal mean linear intercept and horizontal and vertical projection) and analyses of iridium-thorium precipitates (size and spacing) were made on the longitudinal, transverse, and rolling surfaces of the as-recrystallized and aged specimens from which the two-dimensional spatial distribution and meanmore » sizes of the precipitates were obtained. The results obtained from this study are intended to provide input to grain growth models.« less

The role of tropical deforestation in the global carbon cycle: Spatial and temporal dynamics

NASA Technical Reports Server (NTRS)

Houghton, R. A.; Skole, David; Moore, Berrien; Melillo, Jerry; Steudler, Paul

1995-01-01

'The Role of Tropical Deforestation in the Global Carbon cycle: Spatial and Temporal Dynamics', was a joint project involving the University of New Hampshire, the Marine Biological Laboratory, and the Woods Hole Research Center. The contribution of the Woods Hole Research Center consisted of three tasks: (1) assist University of New Hampshire in determining the net flux of carbon between the Brazilian Amazon and the atmosphere by means of a terrestrial carbon model; (2) address the spatial distribution of biomass across the Amazon Basin; and (3) assist NASA Headquarters in development of a science plan for the Terrestrial Ecology component of the NASA-Brazilian field campaign (anticipated for 1997-2001). Progress on these three tasks is briefly described.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

PubMed

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

2013-09-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors

PubMed Central

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H.; Gambhir, Manoj; Fu, Joshua S.; Liu, Yang; Remais, Justin V.

2014-01-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. PMID:24772388

Modeling of Subsurface Lagrangian Sensor Swarms for Spatially Distributed Current Measurements in High Energy Coastal Environments

NASA Astrophysics Data System (ADS)

Harrison, T. W.; Polagye, B. L.

2016-02-01

Coastal ecosystems are characterized by spatially and temporally varying hydrodynamics. In marine renewable energy applications, these variations strongly influence project economics and in oceanographic studies, they impact accuracy of biological transport and pollutant dispersion models. While stationary point or profile measurements are relatively straight forward, spatial representativeness of point measurements can be poor due to strong gradients. Moving platforms, such as AUVs or surface vessels, offer better coverage, but suffer from energetic constraints (AUVs) and resolvable scales (vessels). A system of sub-surface, drifting sensor packages is being developed to provide spatially distributed, synoptic data sets of coastal hydrodynamics with meter-scale resolution over a regional extent of a kilometer. Computational investigation has informed system parameters such as drifter size and shape, necessary position accuracy, number of drifters, and deployment methods. A hydrodynamic domain with complex flow features was created using a computational fluid dynamics code. A simple model of drifter dynamics propagate the drifters through the domain in post-processing. System parameters are evaluated relative to their ability to accurately recreate domain hydrodynamics. Implications of these results for an inexpensive, depth-controlled Lagrangian drifter system is presented.

Complementary aspects of spatial resolution and signal-to-noise ratio in computational imaging

NASA Astrophysics Data System (ADS)

Gureyev, T. E.; Paganin, D. M.; Kozlov, A.; Nesterets, Ya. I.; Quiney, H. M.

2018-05-01

A generic computational imaging setup is considered which assumes sequential illumination of a semitransparent object by an arbitrary set of structured coherent illumination patterns. For each incident illumination pattern, all transmitted light is collected by a photon-counting bucket (single-pixel) detector. The transmission coefficients measured in this way are then used to reconstruct the spatial distribution of the object's projected transmission. It is demonstrated that the square of the spatial resolution of such a setup is usually equal to the ratio of the image area to the number of linearly independent illumination patterns. If the noise in the measured transmission coefficients is dominated by photon shot noise, then the ratio of the square of the mean signal to the noise variance is proportional to the ratio of the mean number of registered photons to the number of illumination patterns. The signal-to-noise ratio in a reconstructed transmission distribution is always lower if the illumination patterns are nonorthogonal, because of spatial correlations in the measured data. Examples of imaging methods relevant to the presented analysis include conventional imaging with a pixelated detector, computational ghost imaging, compressive sensing, super-resolution imaging, and computed tomography.

Two and three-dimensional quantitative neutron imaging of the water distribution during ponded infiltration

NASA Astrophysics Data System (ADS)

Sacha, Jan; Snehota, Michal; Jelinkova, Vladimira

2016-04-01

Information on spatial and temporal water and air distribution in a soil sample during hydrological processes is important for evaluating current and developing new water transport models. Modern imaging techniques such as neutron imaging (NI) allow relatively short acquisition times and high resolution of images. At the same time, the appropriate data processing has to be applied to obtain results free of bias and artifacts. In this study a ponded infiltration experiments were conducted on two soil samples packed into the quartz glass columns of inner diameter of 29 and 34 mm, respectively. First sample was prepared by packing of fine and coarse fractions of sand and the second sample was packed using coarse sand and disks of fine porous ceramic. Ponded infiltration experiments conducted on both samples were monitored by neutron radiography to produce two dimensional (2D) projection images during the transient phase of infiltration. During the steady state flow stage of experiments neutron tomography was utilized to obtain three-dimensional (3D) information on gradual water redistribution. The acquired radiographic images were normalized for background noise and spatial inhomogeneity of the detector, fluctuations of the neutron flux in time and for spatial inhomogeneity of the neutron beam. The radiograms of dry sample were subtracted from all subsequent radiograms to determine water thickness in the 2D projection images. All projections were corrected for beam hardening and neutron scattering by empirical method of Kang et al. (2013). Parameters of the correction method uses were identified by two different approaches. The first approach was based on fitting the NI derived water thickness representing the water filled region in the layer of water above the sample surface to actual water thickness. In the second approach the NI derived volume of water in the entire sample in given time was fitted to corresponding gravimetrically determined amount of water in the sample. Tomography images were reconstructed from the both corrected and uncorrected water thickness maps to obtain the 3D spatial distribution of water content within the sample. Without the correction the beam hardening and scattering effects overestimated the water content values close to the sample perimeter and underestimated the values close to the center of the sample, however the total water content of whole sample was the same in both cases.

High resolution simulations of aerosol microphysics in a global and regionally nested chemical transport model

NASA Astrophysics Data System (ADS)

Adams, P. J.; Marks, M.

2015-12-01

The aerosol indirect effect is the largest source of forcing uncertainty in current climate models. This effect arises from the influence of aerosols on the reflective properties and lifetimes of clouds, and its magnitude depends on how many particles can serve as cloud droplet formation sites. Assessing levels of this subset of particles (cloud condensation nuclei, or CCN) requires knowledge of aerosol levels and their global distribution, size distributions, and composition. A key tool necessary to advance our understanding of CCN is the use of global aerosol microphysical models, which simulate the processes that control aerosol size distributions: nucleation, condensation/evaporation, and coagulation. Previous studies have found important differences in CO (Chen, D. et al., 2009) and ozone (Jang, J., 1995) modeled at different spatial resolutions, and it is reasonable to believe that short-lived, spatially-variable aerosol species will be similarly - or more - susceptible to model resolution effects. The goal of this study is to determine how CCN levels and spatial distributions change as simulations are run at higher spatial resolution - specifically, to evaluate how sensitive the model is to grid size, and how this affects comparisons against observations. Higher resolution simulations are necessary supports for model/measurement synergy. Simulations were performed using the global chemical transport model GEOS-Chem (v9-02). The years 2008 and 2009 were simulated at 4ox5o and 2ox2.5o globally and at 0.5ox0.667o over Europe and North America. Results were evaluated against surface-based particle size distribution measurements from the European Supersites for Atmospheric Aerosol Research project. The fine-resolution model simulates more spatial and temporal variability in ultrafine levels, and better resolves topography. Results suggest that the coarse model predicts systematically lower ultrafine levels than does the fine-resolution model. Significant differences are also evident with respect to model-measurement comparisons, and will be discussed.

Climate change impacts on maritime mountain snowpack in the Oregon Cascades

Treesearch

E. Sproles; A.W. Nolin; K. Rittger; T.H. Painter

2013-01-01

This study investigates the effect of projected temperature increases on maritime mountain snowpack in the McKenzie River Basin (MRB; 3041 km2) in the Cascades Mountains of Oregon, USA. We simulated the spatial distribution of snow water equivalent (SWE) in the MRB for the period of 1989–2009 with SnowModel, a spatiallydistributed, process-based...

Estimating spread rates of non-native species: the gypsy moth as a case study

Treesearch

Patrick Tobin; Andrew M. Liebhold; E. Anderson Roberts; Laura M. Blackburn

2015-01-01

Estimating rates of spread and generating projections of future range expansion for invasive alien species is a key process in the development of management guidelines and policy. Critical needs to estimate spread rates include the availability of surveys to characterize the spatial distribution of an invading species and the application of analytical methods to...

Application of Advanced Sensor Technology to DoD Soil Vapor Intrusion Problems

DTIC Science & Technology

2012-10-01

19 Figure 10. Photographs of: a) Layton , Utah, ASU SERDP project study house and b) basement...relative to sub-slab; line). ..................... 24 Figure 18. Spatial distributions of TCE in Layton , Utah, house without VI and emplaced indoor...technical advice and use of ASU’s Strategic Environmental Research and Development Program (SERDP) VI study house in Layton , Utah, is very

Negligent and intentional fires in Portugal: the role of human and biophysical drivers on the spatial distribution

NASA Astrophysics Data System (ADS)

Parente, Joana; Pereira, Mário; Amraoui, Malik; Tedim, Fantina

2017-04-01

The European Mediterranean countries, such as Portugal, Spain, France, Italy and Greece, have the higher incidence of fire. Of these countries, Portugal present the highest average number of fires (NF) and one of the highest burnt area (BA), in spite of its relatively smaller land area. The study period is focused in the recent years of 2012 - 2014, when a total of 59 257 fires were recorded and the fire cause is known for more than 50% of the fire records. All fires with known causes were then classified into intentional (40% of the total number of fires) and negligent (60%), leading to a total of 45% of fires related with human factors and activities. Taking into account these values the authors believe it's necessary to better understand the fire regime of this type of fires for a better fire prevention, firefighting and crisis management. Accordingly, the use of statistical analysis and GIS techniques were used to assess the spatial distribution of the human caused fires in each of the NUTS (Nomenclature of Territorial Units for Statistics level I, which divides Portugal in 5 basic economic regions, namely Norte, Centro, Area Metropolitana de Lisboa, Alentejo, and Algarve. The number of fires distribution increases with latitude, making north of Portugal the region with the highest number of fires. The analysis will also aims to assess the role of the most important human and biophysical drivers of the spatial distribution, namely the population density, land use land cover (LULC), distance to communication routes (roads and railways) and topographic variables (altitude, slope). The results show that: a) population density is highly and positively correlated with the agglomeration of fire ignitions, but doesn't imply highest burned area; b) burnt area increase with the distance to roads and altitude; and, c) 58% of the fires occurred on agriculture areas and 33% of fires occurred in forest and scrubs areas. Acknowledgements: This work was supported by: (i) the project Interact - Integrative Research in Environment,Agro-Chain and Technology, NORTE-01-0145-FEDER-000017, research line BEST, cofinanced by FEDER/NORTE 2020; (ii) the FIREXTR project, PTDC/ATP¬GEO/0462/2014; and, (iii) European Investment Funds by FEDER/COMPETE/POCI-Operacional Competitiveness and Internacionalization Programme, under Project POCI-01-0145-FEDER-006958 and National Funds by FCT - Portuguese Foundation for Science and Technology, under the project UID/AGR/04033. We are especially grateful to ICNF for providing the fire data.

Environmental Information Management For Data Discovery and Access System

NASA Astrophysics Data System (ADS)

Giriprakash, P.

2011-01-01

Mercury is a federated metadata harvesting, search and retrieval tool based on both open source software and software developed at Oak Ridge National Laboratory. It was originally developed for NASA, and the Mercury development consortium now includes funding from NASA, USGS, and DOE. A major new version of Mercury was developed during 2007 and released in early 2008. This new version provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, support for RSS delivery of search results, and ready customization to meet the needs of the multiple projects which use Mercury. For the end users, Mercury provides a single portal to very quickly search for data and information contained in disparate data management systems. It collects metadata and key data from contributing project servers distributed around the world and builds a centralized index. The Mercury search interfaces then allow ! the users to perform simple, fielded, spatial and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data.

Modelling the spatial distribution of Fasciola hepatica in dairy cattle in Europe.

PubMed

Ducheyne, Els; Charlier, Johannes; Vercruysse, Jozef; Rinaldi, Laura; Biggeri, Annibale; Demeler, Janina; Brandt, Christina; De Waal, Theo; Selemetas, Nikolaos; Höglund, Johan; Kaba, Jaroslaw; Kowalczyk, Slawomir J; Hendrickx, Guy

2015-03-26

A harmonized sampling approach in combination with spatial modelling is required to update current knowledge of fasciolosis in dairy cattle in Europe. Within the scope of the EU project GLOWORM, samples from 3,359 randomly selected farms in 849 municipalities in Belgium, Germany, Ireland, Poland and Sweden were collected and their infection status assessed using an indirect bulk tank milk (BTM) enzyme-linked immunosorbent assay (ELISA). Dairy farms were considered exposed when the optical density ratio (ODR) exceeded the 0.3 cut-off. Two ensemble-modelling techniques, Random Forests (RF) and Boosted Regression Trees (BRT), were used to obtain the spatial distribution of the probability of exposure to Fasciola hepatica using remotely sensed environmental variables (1-km spatial resolution) and interpolated values from meteorological stations as predictors. The median ODRs amounted to 0.31, 0.12, 0.54, 0.25 and 0.44 for Belgium, Germany, Ireland, Poland and southern Sweden, respectively. Using the 0.3 threshold, 571 municipalities were categorized as positive and 429 as negative. RF was seen as capable of predicting the spatial distribution of exposure with an area under the receiver operation characteristic (ROC) curve (AUC) of 0.83 (0.96 for BRT). Both models identified rainfall and temperature as the most important factors for probability of exposure. Areas of high and low exposure were identified by both models, with BRT better at discriminating between low-probability and high-probability exposure; this model may therefore be more useful in practise. Given a harmonized sampling strategy, it should be possible to generate robust spatial models for fasciolosis in dairy cattle in Europe to be used as input for temporal models and for the detection of deviations in baseline probability. Further research is required for model output in areas outside the eco-climatic range investigated.

Co-occurrence patterns of trees along macro-climatic gradients and their potential influence on the present and future distribution of Fagus sylvatica L.

USGS Publications Warehouse

Meier, E.S.; Edwards, T.C.; Kienast, Felix; Dobbertin, M.; Zimmermann, N.E.

2011-01-01

Aim During recent and future climate change, shifts in large-scale species ranges are expected due to the hypothesized major role of climatic factors in regulating species distributions. The stress-gradient hypothesis suggests that biotic interactions may act as major constraints on species distributions under more favourable growing conditions, while climatic constraints may dominate under unfavourable conditions. We tested this hypothesis for one focal tree species having three major competitors using broad-scale environmental data. We evaluated the variation of species co-occurrence patterns in climate space and estimated the influence of these patterns on the distribution of the focal species for current and projected future climates.Location Europe.Methods We used ICP Forest Level 1 data as well as climatic, topographic and edaphic variables. First, correlations between the relative abundance of European beech (Fagus sylvatica) and three major competitor species (Picea abies, Pinus sylvestris and Quercus robur) were analysed in environmental space, and then projected to geographic space. Second, a sensitivity analysis was performed using generalized additive models (GAM) to evaluate where and how much the predicted F. sylvatica distribution varied under current and future climates if potential competitor species were included or excluded. We evaluated if these areas coincide with current species co-occurrence patterns.Results Correlation analyses supported the stress-gradient hypothesis: towards favourable growing conditions of F. sylvatica, its abundance was strongly linked to the abundance of its competitors, while this link weakened towards unfavourable growing conditions, with stronger correlations in the south and at low elevations than in the north and at high elevations. The sensitivity analysis showed a potential spatial segregation of species with changing climate and a pronounced shift of zones where co-occurrence patterns may play a major role.Main conclusions Our results demonstrate the importance of species co-occurrence patterns for calibrating improved species distribution models for use in projections of climate effects. The correlation approach is able to localize European areas where inclusion of biotic predictors is effective. The climate-induced spatial segregation of the major tree species could have ecological and economic consequences. ?? 2010 Blackwell Publishing Ltd.

Mercury Toolset for Spatiotemporal Metadata

NASA Technical Reports Server (NTRS)

Wilson, Bruce E.; Palanisamy, Giri; Devarakonda, Ranjeet; Rhyne, B. Timothy; Lindsley, Chris; Green, James

2010-01-01

Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily) harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

Mercury Toolset for Spatiotemporal Metadata

NASA Astrophysics Data System (ADS)

Devarakonda, Ranjeet; Palanisamy, Giri; Green, James; Wilson, Bruce; Rhyne, B. Timothy; Lindsley, Chris

2010-06-01

Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily)harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

Modeling Transport of Cesium in Grimsel Granodiorite With Micrometer Scale Heterogeneities and Dynamic Update of Kd

NASA Astrophysics Data System (ADS)

Voutilainen, Mikko; Kekäläinen, Pekka; Siitari-Kauppi, Marja; Sardini, Paul; Muuri, Eveliina; Timonen, Jussi; Martin, Andrew

2017-11-01

Transport and retardation of cesium in Grimsel granodiorite taking into account heterogeneity of mineral and pore structure was studied using rock samples overcored from an in situ diffusion test at the Grimsel Test Site. The field test was part of the Long-Term Diffusion (LTD) project designed to characterize retardation properties (diffusion and distribution coefficients) under in situ conditions. Results of the LTD experiment for cesium showed that in-diffusion profiles and spatial concentration distributions were strongly influenced by the heterogeneous pore structure and mineral distribution. In order to study the effect of heterogeneity on the in-diffusion profile and spatial concentration distribution, a Time Domain Random Walk (TDRW) method was applied along with a feature for modeling chemical sorption in geological materials. A heterogeneous mineral structure of Grimsel granodiorite was constructed using X-ray microcomputed tomography (X-μCT) and the map was linked to previous results for mineral specific porosities and distribution coefficients (Kd) that were determined using C-14-PMMA autoradiography and batch sorption experiments, respectively. After this the heterogeneous structure contains information on local porosity and Kd in 3-D. It was found that the heterogeneity of the mineral structure on the micrometer scale affects significantly the diffusion and sorption of cesium in Grimsel granodiorite at the centimeter scale. Furthermore, the modeled in-diffusion profiles and spatial concentration distributions show similar shape and pattern to those from the LTD experiment. It was concluded that the use of detailed structure characterization and quantitative data on heterogeneity can significantly improve the interpretation and evaluation of transport experiments.

Climate model uncertainty in impact assessments for agriculture: A multi-ensemble case study on maize in sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Dale, Amy; Fant, Charles; Strzepek, Kenneth; Lickley, Megan; Solomon, Susan

2017-03-01

We present maize production in sub-Saharan Africa as a case study in the exploration of how uncertainties in global climate change, as reflected in projections from a range of climate model ensembles, influence climate impact assessments for agriculture. The crop model AquaCrop-OS (Food and Agriculture Organization of the United Nations) was modified to run on a 2° × 2° grid and coupled to 122 climate model projections from multi-model ensembles for three emission scenarios (Coupled Model Intercomparison Project Phase 3 [CMIP3] SRES A1B and CMIP5 Representative Concentration Pathway [RCP] scenarios 4.5 and 8.5) as well as two "within-model" ensembles (NCAR CCSM3 and ECHAM5/MPI-OM) designed to capture internal variability (i.e., uncertainty due to chaos in the climate system). In spite of high uncertainty, most notably in the high-producing semi-arid zones, we observed robust regional and sub-regional trends across all ensembles. In agreement with previous work, we project widespread yield losses in the Sahel region and Southern Africa, resilience in Central Africa, and sub-regional increases in East Africa and at the southern tip of the continent. Spatial patterns of yield losses corresponded with spatial patterns of aridity increases, which were explicitly evaluated. Internal variability was a major source of uncertainty in both within-model and between-model ensembles and explained the majority of the spatial distribution of uncertainty in yield projections. Projected climate change impacts on maize production in different regions and nations ranged from near-zero or positive (upper quartile estimates) to substantially negative (lower quartile estimates), highlighting a need for risk management strategies that are adaptive and robust to uncertainty.

Projected impacts of climate change on farmers' extraction of groundwater from crystalline aquifers in South India

NASA Astrophysics Data System (ADS)

Ferrant, Sylvain; Caballero, Yvan; Perrin, Jérome; Gascoin, Simon; Dewandel, Benoit; Aulong, Stéphanie; Dazin, Fabrice; Ahmed, Shakeel; Maréchal, Jean-Christophe

2014-01-01

Local groundwater levels in South India are falling alarmingly. In the semi-arid crystalline Deccan plateau area, agricultural production relies on groundwater resources. Downscaled Global Climate Model (GCM) data are used to force a spatially distributed agro-hydrological model in order to evaluate Climate Change (CC) effects on local groundwater extraction (GWE). The slight increase of precipitation may alleviate current groundwater depletion on average, despite the increased evaporation due to warming. Nevertheless, projected climatic extremes create worse GWE shortages than for present climate. Local conditions may lead to opposing impacts on GWE, from increases to decreases (+/-20 mm/year), for a given spatially homogeneous CC forcing. Areas vulnerable to CC in terms of irrigation apportionment are thus identified. Our results emphasize the importance of accounting for local characteristics (water harvesting systems and maximal aquifer capacity versus GWE) in developing measures to cope with CC impacts in the South Indian region.

Projected impacts of climate change on farmers' extraction of groundwater from crystalline aquifers in South India.

PubMed

Ferrant, Sylvain; Caballero, Yvan; Perrin, Jérome; Gascoin, Simon; Dewandel, Benoit; Aulong, Stéphanie; Dazin, Fabrice; Ahmed, Shakeel; Maréchal, Jean-Christophe

2014-01-15

Local groundwater levels in South India are falling alarmingly. In the semi-arid crystalline Deccan plateau area, agricultural production relies on groundwater resources. Downscaled Global Climate Model (GCM) data are used to force a spatially distributed agro-hydrological model in order to evaluate Climate Change (CC) effects on local groundwater extraction (GWE). The slight increase of precipitation may alleviate current groundwater depletion on average, despite the increased evaporation due to warming. Nevertheless, projected climatic extremes create worse GWE shortages than for present climate. Local conditions may lead to opposing impacts on GWE, from increases to decreases (+/-20 mm/year), for a given spatially homogeneous CC forcing. Areas vulnerable to CC in terms of irrigation apportionment are thus identified. Our results emphasize the importance of accounting for local characteristics (water harvesting systems and maximal aquifer capacity versus GWE) in developing measures to cope with CC impacts in the South Indian region.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Projected distributions and diversity of flightless ground beetles within the Australian Wet Tropics and their environmental correlates.

PubMed

Staunton, Kyran M; Robson, Simon K A; Burwell, Chris J; Reside, April E; Williams, Stephen E

2014-01-01

With the impending threat of climate change, greater understanding of patterns of species distributions and richness and the environmental factors driving them are required for effective conservation efforts. Species distribution models enable us to not only estimate geographic extents of species and subsequent patterns of species richness, but also generate hypotheses regarding environmental factors determining these spatial patterns. Projected changes in climate can then be used to predict future patterns of species distributions and richness. We created distribution models for most of the flightless ground beetles (Carabidae) within the Wet Tropics World Heritage Area of Australia, a major component of regionally endemic invertebrates. Forty-three species were modelled and the environmental correlates of these distributions and resultant patterns of species richness were examined. Flightless ground beetles generally inhabit upland areas characterised by stable, cool and wet environmental conditions. These distribution and richness patterns are best explained using the time-stability hypothesis as this group's primary habitat, upland rainforest, is considered to be the most stable regional habitat. Projected changes in distributions indicate that as upward shifts in distributions occur, species currently confined to lower and drier mountain ranges will be more vulnerable to climate change impacts than those restricted to the highest and wettest mountains. Distribution models under projected future climate change suggest that there will be reductions in range size, population size and species richness under all emission scenarios. Eighty-eight per cent of species modelled are predicted to decline in population size by over 80%, for the most severe emission scenario by the year 2080. These results suggest that flightless ground beetles are among the most vulnerable taxa to climate change impacts so far investigated in the Wet Tropics World Heritage Area. These findings have dramatic implications for all other flightless insect taxa and the future biodiversity of this region.

Projected Distributions and Diversity of Flightless Ground Beetles within the Australian Wet Tropics and Their Environmental Correlates

PubMed Central

Staunton, Kyran M.; Robson, Simon K. A.; Burwell, Chris J.; Reside, April E.; Williams, Stephen E.

2014-01-01

With the impending threat of climate change, greater understanding of patterns of species distributions and richness and the environmental factors driving them are required for effective conservation efforts. Species distribution models enable us to not only estimate geographic extents of species and subsequent patterns of species richness, but also generate hypotheses regarding environmental factors determining these spatial patterns. Projected changes in climate can then be used to predict future patterns of species distributions and richness. We created distribution models for most of the flightless ground beetles (Carabidae) within the Wet Tropics World Heritage Area of Australia, a major component of regionally endemic invertebrates. Forty-three species were modelled and the environmental correlates of these distributions and resultant patterns of species richness were examined. Flightless ground beetles generally inhabit upland areas characterised by stable, cool and wet environmental conditions. These distribution and richness patterns are best explained using the time-stability hypothesis as this group’s primary habitat, upland rainforest, is considered to be the most stable regional habitat. Projected changes in distributions indicate that as upward shifts in distributions occur, species currently confined to lower and drier mountain ranges will be more vulnerable to climate change impacts than those restricted to the highest and wettest mountains. Distribution models under projected future climate change suggest that there will be reductions in range size, population size and species richness under all emission scenarios. Eighty-eight per cent of species modelled are predicted to decline in population size by over 80%, for the most severe emission scenario by the year 2080. These results suggest that flightless ground beetles are among the most vulnerable taxa to climate change impacts so far investigated in the Wet Tropics World Heritage Area. These findings have dramatic implications for all other flightless insect taxa and the future biodiversity of this region. PMID:24586362

The Influence of Emission Location on the Magnitude and Spatial Distribution of Aerosols' Climate Effects

NASA Astrophysics Data System (ADS)

Persad, G.; Caldeira, K.

2017-12-01

The global distribution of anthropogenic aerosol emissions has evolved continuously since the preindustrial era - from 20th century North American and Western European emissions hotspots to present-day South and East Asian ones. With this comes a relocation of the regional radiative, dynamical, and hydrological impacts of aerosol emissions, which may influence global climate differently depending on where they occur. A lack of understanding of this relationship between aerosol emissions' location and their global climate effects, however, obscures the potential influence that aerosols' evolving geographic distribution may have on global and regional climate change—a gap which we address in this work. Using a novel suite of experiments in the CESM CAM5 atmospheric general circulation model coupled to a slab ocean, we systematically test and analyze mechanisms behind the relative climate impact of identical black carbon and sulfate aerosol emissions located in each of 8 past, present, or projected future major emissions regions. Results indicate that historically high emissions regions, such as North America and Western Europe, produce a stronger cooling effect than current and projected future high emissions regions. Aerosol emissions located in Western Europe produce 3 times the global mean cooling (-0.34 °C) as those located in East Africa or India (-0.11 °C). The aerosols' in-situ radiative effects remain relatively confined near the emissions region, but large distal cooling results from remote feedback processes - such as ice albedo and cloud changes - that are excited more strongly by emissions from certain regions than others. Results suggest that aerosol emissions from different countries should not be considered equal in the context of climate mitigation accounting, and that the evolving geographic distribution of aerosol emissions may have a substantial impact on the magnitude and spatial distribution of global climate change.

Bayesian hierarchical models for regional climate reconstructions of the last glacial maximum

NASA Astrophysics Data System (ADS)

Weitzel, Nils; Hense, Andreas; Ohlwein, Christian

2017-04-01

Spatio-temporal reconstructions of past climate are important for the understanding of the long term behavior of the climate system and the sensitivity to forcing changes. Unfortunately, they are subject to large uncertainties, have to deal with a complex proxy-climate structure, and a physically reasonable interpolation between the sparse proxy observations is difficult. Bayesian Hierarchical Models (BHMs) are a class of statistical models that is well suited for spatio-temporal reconstructions of past climate because they permit the inclusion of multiple sources of information (e.g. records from different proxy types, uncertain age information, output from climate simulations) and quantify uncertainties in a statistically rigorous way. BHMs in paleoclimatology typically consist of three stages which are modeled individually and are combined using Bayesian inference techniques. The data stage models the proxy-climate relation (often named transfer function), the process stage models the spatio-temporal distribution of the climate variables of interest, and the prior stage consists of prior distributions of the model parameters. For our BHMs, we translate well-known proxy-climate transfer functions for pollen to a Bayesian framework. In addition, we can include Gaussian distributed local climate information from preprocessed proxy records. The process stage combines physically reasonable spatial structures from prior distributions with proxy records which leads to a multivariate posterior probability distribution for the reconstructed climate variables. The prior distributions that constrain the possible spatial structure of the climate variables are calculated from climate simulation output. We present results from pseudoproxy tests as well as new regional reconstructions of temperatures for the last glacial maximum (LGM, ˜ 21,000 years BP). These reconstructions combine proxy data syntheses with information from climate simulations for the LGM that were performed in the PMIP3 project. The proxy data syntheses consist either of raw pollen data or of normally distributed climate data from preprocessed proxy records. Future extensions of our method contain the inclusion of other proxy types (transfer functions), the implementation of other spatial interpolation techniques, the use of age uncertainties, and the extension to spatio-temporal reconstructions of the last deglaciation. Our work is part of the PalMod project funded by the German Federal Ministry of Education and Science (BMBF).

Combining dispersal, landscape connectivity and habitat suitability to assess climate-induced changes in the distribution of Cunningham's skink, Egernia cunninghami.

PubMed

Ofori, Benjamin Y; Stow, Adam J; Baumgartner, John B; Beaumont, Linda J

2017-01-01

The ability of species to track their climate niche is dependent on their dispersal potential and the connectivity of the landscape matrix linking current and future suitable habitat. However, studies modeling climate-driven range shifts rarely address the movement of species across landscapes realistically, often assuming "unlimited" or "no" dispersal. Here, we incorporate dispersal rate and landscape connectivity with a species distribution model (Maxent) to assess the extent to which the Cunningham's skink (Egernia cunninghami) may be capable of tracking spatial shifts in suitable habitat as climate changes. Our model was projected onto four contrasting, but equally plausible, scenarios describing futures that are (relative to now) hot/wet, warm/dry, hot/with similar precipitation and warm/wet, at six time horizons with decadal intervals (2020-2070) and at two spatial resolutions: 1 km and 250 m. The size of suitable habitat was projected to decline 23-63% at 1 km and 26-64% at 250 m, by 2070. Combining Maxent output with the dispersal rate of the species and connectivity of the intervening landscape matrix showed that most current populations in regions projected to become unsuitable in the medium to long term, will be unable to shift the distance necessary to reach suitable habitat. In particular, numerous populations currently inhabiting the trailing edge of the species' range are highly unlikely to be able to disperse fast enough to track climate change. Unless these populations are capable of adaptation they are likely to be extirpated. We note, however, that the core of the species distribution remains suitable across the broad spectrum of climate scenarios considered. Our findings highlight challenges faced by philopatric species and the importance of adaptation for the persistence of peripheral populations under climate change.

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

NASA Astrophysics Data System (ADS)

Ji, C.; Shao, G.

2007-12-01

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

Characterizing spatial uncertainty when integrating social data in conservation planning.

PubMed

Lechner, A M; Raymond, C M; Adams, V M; Polyakov, M; Gordon, A; Rhodes, J R; Mills, M; Stein, A; Ives, C D; Lefroy, E C

2014-12-01

Recent conservation planning studies have presented approaches for integrating spatially referenced social (SRS) data with a view to improving the feasibility of conservation action. We reviewed the growing conservation literature on SRS data, focusing on elicited or stated preferences derived through social survey methods such as choice experiments and public participation geographic information systems. Elicited SRS data includes the spatial distribution of willingness to sell, willingness to pay, willingness to act, and assessments of social and cultural values. We developed a typology for assessing elicited SRS data uncertainty which describes how social survey uncertainty propagates when projected spatially and the importance of accounting for spatial uncertainty such as scale effects and data quality. These uncertainties will propagate when elicited SRS data is integrated with biophysical data for conservation planning and may have important consequences for assessing the feasibility of conservation actions. To explore this issue further, we conducted a systematic review of the elicited SRS data literature. We found that social survey uncertainty was commonly tested for, but that these uncertainties were ignored when projected spatially. Based on these results we developed a framework which will help researchers and practitioners estimate social survey uncertainty and use these quantitative estimates to systematically address uncertainty within an analysis. This is important when using SRS data in conservation applications because decisions need to be made irrespective of data quality and well characterized uncertainty can be incorporated into decision theoretic approaches. © 2014 Society for Conservation Biology.

Drive by Soil Moisture Measurement: A Citizen Science Project

NASA Astrophysics Data System (ADS)

Senanayake, I. P.; Willgoose, G. R.; Yeo, I. Y.; Hancock, G. R.

2017-12-01

Two of the common attributes of soil moisture are that at any given time it varies quite markedly from point to point, and that there is a significant deterministic pattern that underlies this spatial variation and which is typically 50% of the spatial variability. The spatial variation makes it difficult to determine the time varying catchment average soil moisture using field measurements because any individual measurement is unlikely to be equal to the average for the catchment. The traditional solution to this is to make many measurements (e.g. with soil moisture probes) spread over the catchment, which is very costly and manpower intensive, particularly if we need a time series of soil moisture variation across a catchment. An alternative approach, explored in this poster is to use the deterministic spatial pattern of soil moisture to calibrate one site (e.g. a permanent soil moisture probe at a weather station) to the spatial pattern of soil moisture over the study area. The challenge is then to determine the spatial pattern of soil moisture. This poster will present results from a proof of concept project, where data was collected by a number of undergraduate engineering students, to estimate the spatial pattern. The approach was to drive along a series of roads in a catchment and collect soil moisture measurements at the roadside using field portable soil moisture probes. This drive was repeated a number of times over the semester, and the time variation and spatial persistence of the soil moisture pattern were examined. Provided that the students could return to exactly the same location on each collection day there was a strong persistent pattern in the soil moisture, even while the average soil moisture varied temporally as a result of preceding rainfall. The poster will present results and analysis of the student data, and compare these results with several field sites where we have spatially distributed permanently installed soil moisture probes. The poster will also outline an experimental design, based on our experience, that will underpin a proposed citizen science project involving community environment and farming groups, and high school students.

Spatial variation of statistical properties of extreme water levels along the eastern Baltic Sea

NASA Astrophysics Data System (ADS)

Pindsoo, Katri; Soomere, Tarmo; Rocha, Eugénio

2016-04-01

Most of existing projections of future extreme water levels rely on the use of classic generalised extreme value distributions. The choice to use a particular distribution is often made based on the absolute value of the shape parameter of the Generalise Extreme Value distribution. If this parameter is small, the Gumbel distribution is most appropriate while in the opposite case the Weibull or Frechet distribution could be used. We demonstrate that the alongshore variation in the statistical properties of numerically simulated high water levels along the eastern coast of the Baltic Sea is so large that the use of a single distribution for projections of extreme water levels is highly questionable. The analysis is based on two simulated data sets produced in the Swedish Meteorological and Hydrological Institute. The output of the Rossby Centre Ocean model is sampled with a resolution of 6 h and the output of the circulation model NEMO with a resolution of 1 h. As the maxima of water levels of subsequent years may be correlated in the Baltic Sea, we also employ maxima for stormy seasons. We provide a detailed analysis of spatial variation of the parameters of the family of extreme value distributions along an approximately 600 km long coastal section from the north-western shore of Latvia in the Baltic Proper until the eastern Gulf of Finland. The parameters are evaluated using maximum likelihood method and method of moments. The analysis also covers the entire Gulf of Riga. The core parameter of this family of distributions, the shape parameter of the Generalised Extreme Value distribution, exhibits extensive variation in the study area. Its values evaluated using the Hydrognomon software and maximum likelihood method, vary from about -0.1 near the north-western coast of Latvia in the Baltic Proper up to about 0.05 in the eastern Gulf of Finland. This parameter is very close to zero near Tallinn in the western Gulf of Finland. Thus, it is natural that the Gumbel distribution gives adequate projections of extreme water levels for the vicinity of Tallinn. More importantly, this feature indicates that the use of a single distribution for the projections of extreme water levels and their return periods for the entire Baltic Sea coast is inappropriate. The physical reason is the interplay of the complex shape of large subbasins (such as the Gulf of Riga and Gulf of Finland) of the sea and highly anisotropic wind regime. The 'impact' of this anisotropy on the statistics of water level is amplified by the overall anisotropy of the distributions of the frequency of occurrence of high and low water levels. The most important conjecture is that long-term behaviour of water level extremes in different coastal sections of the Baltic Sea may be fundamentally different.

Freeform array projection

NASA Astrophysics Data System (ADS)

Michaelis, D.; Schreiber, P.; Li, C.; Bräuer, A.; Gross, H.

2015-09-01

The concept of multichannel array projection is generalized in order to realize an ultraslim, highly efficient optical system for structured illumination with high lumen output, where additionally the Köhler illumination principle is utilized and source light homogenization occurs. The optical system consists of a multitude of neighboring optical channels. In each channel two optical freeforms generate a real or a virtual spatial light pattern and furthermore, the ray directions are modified to enable Köhler illumination of a subsequent projection lens. The internal light pattern may be additionally influenced by absorbing apertures or slides. The projection lens transfers the resulting light pattern to a target, where the total target distribution is produced by superposition of all individual channel output pattern. The optical system without absorbing apertures can be regarded as a generalization of a fly's eye condenser for structured illumination. In this case light pattern is exclusively generated by freeform light redistribution. The commonly occurring blurring effect for freeform beamshaping is reduced due to the creation of a virtual object light structure by means of the two freeform surfaces and its imaging towards the target. But, the remaining blurring inhibits very high spatial frequencies at the target. In order to create target features with very high spatial resolution the absorbing apertures can be utilized. In this case the freeform beamshaping can be used for an enhanced light transmission through the absorbing apertures. The freeform surfaces are designed by a generalized approach of Cartesian oval representation.

The Use of Convolutional Neural Network in Relating Precipitation to Circulation

NASA Astrophysics Data System (ADS)

Pan, B.; Hsu, K. L.; AghaKouchak, A.; Sorooshian, S.

2017-12-01

Precipitation prediction in dynamical weather and climate models depends on 1) the predictability of pressure or geopotential height for the forecasting period and 2) the successive work of interpreting the pressure field in terms of precipitation events. The later task is represented as parameterization schemes in numerical models, where detailed computing inevitably blurs the hidden cause-and-effect relationship in precipitation generation. The "big data" provided by numerical simulation, reanalysis and observation networks requires better causation analysis for people to digest and realize their use. While classic synoptical analysis methods are very-often insufficient for spatially distributed high dimensional data, a Convolutional Neural Network(CNN) is developed here to directly relate precipitation with circulation. Case study carried over west coast United States during boreal winter showed that CNN can locate and capture key pressure zones of different structures to project precipitation spatial distribution with high accuracy across hourly to monthly scales. This direct connection between atmospheric circulation and precipitation offers a probe for attributing precipitation to the coverage, location, intensity and spatial structure of characteristic pressure zones, which can be used for model diagnosis and improvement.

Studies for the Loss of Atomic and Molecular Species from Io

NASA Technical Reports Server (NTRS)

Smyth, William H.

1997-01-01

The general objective of this project is to advance our theoretical understanding of Io's atmosphere by studying how various atomic and molecular species are lost from this atmosphere and are distributed near the satellite and in the circumplanetary environment of Jupiter. The project is divided into well-defined studies described for the likely dominant atmospheric gases involving species of the SO2 family (SO2, SO, 02, 0, S) and for the trace atmospheric gas atomic sodium. The relative abundance of the members of the S02 family and Na (and its parent Na(x)) at the satellite exobase and their relative spatial densities beyond in the extended corona of lo are not well known but will depend upon a number of factors including the upward transport rate of gases from below, the velocity distribution and corresponding escape rate of gases at the exobase, and the operative magnetospheric/solar-photon driven chemistry for the different gases. This question of relative abundance will be studied in this project.

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

PubMed

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

2015-01-01

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

Simulated effects of climate change, fragmentation, and inter-specific competition on tree species migration in northern Wisconsin, USA

Treesearch

Robert M. Scheller; David J. Mladenoff

2008-01-01

The reproductive success, growth, and mortality rates of tree species in the northern United States will be differentially affected by projected climate change over the next century. As a consequence, the spatial distributions of tree species will expand or contract at differential rates. In addition, human fragmentation of the landscape may limit effective seed...

Climate change and natural disasters: integrating science and practice to protect health.

PubMed

Sauerborn, Rainer; Ebi, Kristie

2012-12-17

Hydro-meteorological disasters are the focus of this paper. The authors examine, to which extent climate change increases their frequency and intensity. Review of IPCC-projections of climate-change related extreme weather events and related literature on health effects. Projections show that climate change is likely to increase the frequency, intensity, duration, and spatial distribution of a range of extreme weather events over coming decades. There is a need for strengthened collaboration between climate scientists, the health researchers and policy-makers as well as the disaster community to jointly develop adaptation strategies to protect human.

Mock-up experiment at Birmingham University for BNCT project of Osaka University--Neutron flux measurement with gold foil.

PubMed

Tamaki, S; Sakai, M; Yoshihashi, S; Manabe, M; Zushi, N; Murata, I; Hoashi, E; Kato, I; Kuri, S; Oshiro, S; Nagasaki, M; Horiike, H

2015-12-01

Mock-up experiment for development of accelerator based neutron source for Osaka University BNCT project was carried out at Birmingham University, UK. In this paper, spatial distribution of neutron flux intensity was evaluated by foil activation method. Validity of the design code system was confirmed by comparing measured gold foil activities with calculations. As a result, it was found that the epi-thermal neutron beam was well collimated by our neutron moderator assembly. Also, the design accuracy was evaluated to have less than 20% error. Copyright © 2015 Elsevier Ltd. All rights reserved.

Electric field imaging of single atoms

PubMed Central

Shibata, Naoya; Seki, Takehito; Sánchez-Santolino, Gabriel; Findlay, Scott D.; Kohno, Yuji; Matsumoto, Takao; Ishikawa, Ryo; Ikuhara, Yuichi

2017-01-01

In scanning transmission electron microscopy (STEM), single atoms can be imaged by detecting electrons scattered through high angles using post-specimen, annular-type detectors. Recently, it has been shown that the atomic-scale electric field of both the positive atomic nuclei and the surrounding negative electrons within crystalline materials can be probed by atomic-resolution differential phase contrast STEM. Here we demonstrate the real-space imaging of the (projected) atomic electric field distribution inside single Au atoms, using sub-Å spatial resolution STEM combined with a high-speed segmented detector. We directly visualize that the electric field distribution (blurred by the sub-Å size electron probe) drastically changes within the single Au atom in a shape that relates to the spatial variation of total charge density within the atom. Atomic-resolution electric field mapping with single-atom sensitivity enables us to examine their detailed internal and boundary structures. PMID:28555629

Assessing the significance of global and local correlations under spatial autocorrelation: a nonparametric approach.

PubMed

Viladomat, Júlia; Mazumder, Rahul; McInturff, Alex; McCauley, Douglas J; Hastie, Trevor

2014-06-01

We propose a method to test the correlation of two random fields when they are both spatially autocorrelated. In this scenario, the assumption of independence for the pair of observations in the standard test does not hold, and as a result we reject in many cases where there is no effect (the precision of the null distribution is overestimated). Our method recovers the null distribution taking into account the autocorrelation. It uses Monte-Carlo methods, and focuses on permuting, and then smoothing and scaling one of the variables to destroy the correlation with the other, while maintaining at the same time the initial autocorrelation. With this simulation model, any test based on the independence of two (or more) random fields can be constructed. This research was motivated by a project in biodiversity and conservation in the Biology Department at Stanford University. © 2014, The International Biometric Society.

A parallel-processing approach to computing for the geographic sciences

USGS Publications Warehouse

Crane, Michael; Steinwand, Dan; Beckmann, Tim; Krpan, Greg; Haga, Jim; Maddox, Brian; Feller, Mark

2001-01-01

The overarching goal of this project is to build a spatially distributed infrastructure for information science research by forming a team of information science researchers and providing them with similar hardware and software tools to perform collaborative research. Four geographically distributed Centers of the U.S. Geological Survey (USGS) are developing their own clusters of low-cost personal computers into parallel computing environments that provide a costeffective way for the USGS to increase participation in the high-performance computing community. Referred to as Beowulf clusters, these hybrid systems provide the robust computing power required for conducting research into various areas, such as advanced computer architecture, algorithms to meet the processing needs for real-time image and data processing, the creation of custom datasets from seamless source data, rapid turn-around of products for emergency response, and support for computationally intense spatial and temporal modeling.

Spatial distribution estimation of malaria in northern China and its scenarios in 2020, 2030, 2040 and 2050.

PubMed

Song, Yongze; Ge, Yong; Wang, Jinfeng; Ren, Zhoupeng; Liao, Yilan; Peng, Junhuan

2016-07-07

Malaria is one of the most severe parasitic diseases in the world. Spatial distribution estimation of malaria and its future scenarios are important issues for malaria control and elimination. Furthermore, sophisticated nonlinear relationships for prediction between malaria incidence and potential variables have not been well constructed in previous research. This study aims to estimate these nonlinear relationships and predict future malaria scenarios in northern China. Nonlinear relationships between malaria incidence and predictor variables were constructed using a genetic programming (GP) method, to predict the spatial distributions of malaria under climate change scenarios. For this, the examples of monthly average malaria incidence were used in each county of northern China from 2004 to 2010. Among the five variables at county level, precipitation rate and temperature are used for projections, while elevation, water density index, and gross domestic product are held at their present-day values. Average malaria incidence was 0.107 ‰ per annum in northern China, with incidence characteristics in significant spatial clustering. A GP-based model fit the relationships with average relative error (ARE) = 8.127 % for training data (R(2) = 0.825) and 17.102 % for test data (R(2) = 0.532). The fitness of GP results are significantly improved compared with those by generalized additive models (GAM) and linear regressions. With the future precipitation rate and temperature conditions in Special Report on Emission Scenarios (SRES) family B1, A1B and A2 scenarios, spatial distributions and changes in malaria incidences in 2020, 2030, 2040 and 2050 were predicted and mapped. The GP method increases the precision of predicting the spatial distribution of malaria incidence. With the assumption of varied precipitation rate and temperature, and other variables controlled, the relationships between incidence and the varied variables appear sophisticated nonlinearity and spatially differentiation. Using the future fluctuated precipitation and the increased temperature, median malaria incidence in 2020, 2030, 2040 and 2050 would significantly increase that it might increase 19 to 29 % in 2020, but currently China is in the malaria elimination phase, indicating that the effective strategies and actions had been taken. While the mean incidences will not increase even reduce due to the incidence reduction in high-risk regions but the simultaneous expansion of the high-risk areas.

Data management with a landslide inventory of the Franconian Alb (Germany) using a spatial database and GIS tools

NASA Astrophysics Data System (ADS)

Bemm, Stefan; Sandmeier, Christine; Wilde, Martina; Jaeger, Daniel; Schwindt, Daniel; Terhorst, Birgit

2014-05-01

The area of the Swabian-Franconian cuesta landscape (Southern Germany) is highly prone to landslides. This was apparent in the late spring of 2013, when numerous landslides occurred as a consequence of heavy and long-lasting rainfalls. The specific climatic situation caused numerous damages with serious impact on settlements and infrastructure. Knowledge on spatial distribution of landslides, processes and characteristics are important to evaluate the potential risk that can occur from mass movements in those areas. In the frame of two projects about 400 landslides were mapped and detailed data sets were compiled during years 2011 to 2014 at the Franconian Alb. The studies are related to the project "Slope stability and hazard zones in the northern Bavarian cuesta" (DFG, German Research Foundation) as well as to the LfU (The Bavarian Environment Agency) within the project "Georisks and climate change - hazard indication map Jura". The central goal of the present study is to create a spatial database for landslides. The database should contain all fundamental parameters to characterize the mass movements and should provide the potential for secure data storage and data management, as well as statistical evaluations. The spatial database was created with PostgreSQL, an object-relational database management system and PostGIS, a spatial database extender for PostgreSQL, which provides the possibility to store spatial and geographic objects and to connect to several GIS applications, like GRASS GIS, SAGA GIS, QGIS and GDAL, a geospatial library (Obe et al. 2011). Database access for querying, importing, and exporting spatial and non-spatial data is ensured by using GUI or non-GUI connections. The database allows the use of procedural languages for writing advanced functions in the R, Python or Perl programming languages. It is possible to work directly with the (spatial) data entirety of the database in R. The inventory of the database includes (amongst others), informations on location, landslide types and causes, geomorphological positions, geometries, hazards and damages, as well as assessments related to the activity of landslides. Furthermore, there are stored spatial objects, which represent the components of a landslide, in particular the scarps and the accumulation areas. Besides, waterways, map sheets, contour lines, detailed infrastructure data, digital elevation models, aspect and slope data are included. Examples of spatial queries to the database are intersections of raster and vector data for calculating values for slope gradients or aspects of landslide areas and for creating multiple, overlaying sections for the comparison of slopes, as well as distances to the infrastructure or to the next receiving drainage. Furthermore, getting informations on landslide magnitudes, distribution and clustering, as well as potential correlations concerning geomorphological or geological conditions. The data management concept in this study can be implemented for any academic, public or private use, because it is independent from any obligatory licenses. The created spatial database offers a platform for interdisciplinary research and socio-economic questions, as well as for landslide susceptibility and hazard indication mapping. Obe, R.O., Hsu, L.S. 2011. PostGIS in action. - pp 492, Manning Publications, Stamford

Longterm and spatial variability of Aerosol optical properties measured by sky radiometer in Japan sites

NASA Astrophysics Data System (ADS)

Aoki, K.

2016-12-01

Aerosols and cloud play an important role in the climate change. We started the long-term monitoring of aerosol and cloud optical properties since 1990's by using sky radiometer (POM-01, 02; Prede Co. Ltd., Japan). We provide the information, in this presentation, on the aerosol optical properties with respect to their temporal and spatial variability in Japan site (ex. Sapporo, Toyama, Kasuga and etc). The global distributions of aerosols have been derived from earth observation satellite and have been simulated in numerical models, which assume optical parameters. However, these distributions are difficult to derive because of variability in time and space. Therefore, Aerosol optical properties were investigated using the measurements from ground-based and ship-borne sky radiometer. The sky radiometer is an automatic instrument that takes observations only in daytime under the clear sky conditions. Observation of diffuse solar intensity interval was made every ten or five minutes by once. The aerosol optical properties were computed using the SKYRAD.pack version 4.2. The obtained Aerosol optical properties (Aerosol optical thickness, Ångström exponent, Single scattering albedo, and etc.) and size distribution volume clearly showed spatial and temporal variability in Japan area. In this study, we present the temporal and spatial variability of Aerosol optical properties at several Japan sites, applied to validation of satellite and numerical models. This project is validation satellite of GCOM-C, JAXA. The GCOM-C satellite scheduled to be launched in early 2017.

Distributed watershed modeling of design storms to identify nonpoint source loading areas

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

Endreny, T.A.; Wood, E.F.

1999-03-01

Watershed areas that generate nonpoint source (NPS) polluted runoff need to be identified prior to the design of basin-wide water quality projects. Current watershed-scale NPS models lack a variable source area (VSA) hydrology routine, and are therefore unable to identify spatially dynamic runoff zones. The TOPLATS model used a watertable-driven VSA hydrology routine to identify runoff zones in a 17.5 km{sup 2} agricultural watershed in central Oklahoma. Runoff areas were identified in a static modeling framework as a function of prestorm watertable depth and also in a dynamic modeling framework by simulating basin response to 2, 10, and 25 yrmore » return period 6 h design storms. Variable source area expansion occurred throughout the duration of each 6 h storm and total runoff area increased with design storm intensity. Basin-average runoff rates of 1 mm h{sup {minus}1} provided little insight into runoff extremes while the spatially distributed analysis identified saturation excess zones with runoff rates equaling effective precipitation. The intersection of agricultural landcover areas with these saturation excess runoff zones targeted the priority potential NPS runoff zones that should be validated with field visits. These intersected areas, labeled as potential NPS runoff zones, were mapped within the watershed to demonstrate spatial analysis options available in TOPLATS for managing complex distributions of watershed runoff. TOPLATS concepts in spatial saturation excess runoff modelling should be incorporated into NPS management models.« less

The Contribution of Vegetation and Landscape Configuration for Predicting Environmental Change Impacts on Iberian Birds

PubMed Central

Triviño, Maria; Thuiller, Wilfried; Cabeza, Mar; Hickler, Thomas; Araújo, Miguel B.

2011-01-01

Although climate is known to be one of the key factors determining animal species distributions amongst others, projections of global change impacts on their distributions often rely on bioclimatic envelope models. Vegetation structure and landscape configuration are also key determinants of distributions, but they are rarely considered in such assessments. We explore the consequences of using simulated vegetation structure and composition as well as its associated landscape configuration in models projecting global change effects on Iberian bird species distributions. Both present-day and future distributions were modelled for 168 bird species using two ensemble forecasting methods: Random Forests (RF) and Boosted Regression Trees (BRT). For each species, several models were created, differing in the predictor variables used (climate, vegetation, and landscape configuration). Discrimination ability of each model in the present-day was then tested with four commonly used evaluation methods (AUC, TSS, specificity and sensitivity). The different sets of predictor variables yielded similar spatial patterns for well-modelled species, but the future projections diverged for poorly-modelled species. Models using all predictor variables were not significantly better than models fitted with climate variables alone for ca. 50% of the cases. Moreover, models fitted with climate data were always better than models fitted with landscape configuration variables, and vegetation variables were found to correlate with bird species distributions in 26–40% of the cases with BRT, and in 1–18% of the cases with RF. We conclude that improvements from including vegetation and its landscape configuration variables in comparison with climate only variables might not always be as great as expected for future projections of Iberian bird species. PMID:22216263

Efficient and Flexible Climate Analysis with Python in a Cloud-Based Distributed Computing Framework

NASA Astrophysics Data System (ADS)

Gannon, C.

2017-12-01

As climate models become progressively more advanced, and spatial resolution further improved through various downscaling projects, climate projections at a local level are increasingly insightful and valuable. However, the raw size of climate datasets presents numerous hurdles for analysts wishing to develop customized climate risk metrics or perform site-specific statistical analysis. Four Twenty Seven, a climate risk consultancy, has implemented a Python-based distributed framework to analyze large climate datasets in the cloud. With the freedom afforded by efficiently processing these datasets, we are able to customize and continually develop new climate risk metrics using the most up-to-date data. Here we outline our process for using Python packages such as XArray and Dask to evaluate netCDF files in a distributed framework, StarCluster to operate in a cluster-computing environment, cloud computing services to access publicly hosted datasets, and how this setup is particularly valuable for generating climate change indicators and performing localized statistical analysis.

Oscillatory flow in the cochlea visualized by a magnetic resonance imaging technique.

PubMed

Denk, W; Keolian, R M; Ogawa, S; Jelinski, L W

1993-02-15

We report a magnetic resonance imaging technique that directly measures motion of cochlear fluids. It uses oscillating magnetic field gradients phase-locked to an external stimulus to selectively visualize and quantify oscillatory fluid motion. It is not invasive, and it does not require optical line-of-sight access to the inner ear. It permits the detection of displacements far smaller than the spatial resolution. The method is demonstrated on a phantom and on living rats. It is projected to have applications for auditory research, for the visualization of vocal tract dynamics during speech and singing, and for determination of the spatial distribution of mechanical relaxations in materials.

Fusion of multichannel local and global structural cues for photo aesthetics evaluation.

PubMed

Luming Zhang; Yue Gao; Zimmermann, Roger; Qi Tian; Xuelong Li

2014-03-01

Photo aesthetic quality evaluation is a fundamental yet under addressed task in computer vision and image processing fields. Conventional approaches are frustrated by the following two drawbacks. First, both the local and global spatial arrangements of image regions play an important role in photo aesthetics. However, existing rules, e.g., visual balance, heuristically define which spatial distribution among the salient regions of a photo is aesthetically pleasing. Second, it is difficult to adjust visual cues from multiple channels automatically in photo aesthetics assessment. To solve these problems, we propose a new photo aesthetics evaluation framework, focusing on learning the image descriptors that characterize local and global structural aesthetics from multiple visual channels. In particular, to describe the spatial structure of the image local regions, we construct graphlets small-sized connected graphs by connecting spatially adjacent atomic regions. Since spatially adjacent graphlets distribute closely in their feature space, we project them onto a manifold and subsequently propose an embedding algorithm. The embedding algorithm encodes the photo global spatial layout into graphlets. Simultaneously, the importance of graphlets from multiple visual channels are dynamically adjusted. Finally, these post-embedding graphlets are integrated for photo aesthetics evaluation using a probabilistic model. Experimental results show that: 1) the visualized graphlets explicitly capture the aesthetically arranged atomic regions; 2) the proposed approach generalizes and improves four prominent aesthetic rules; and 3) our approach significantly outperforms state-of-the-art algorithms in photo aesthetics prediction.

Assessment of the Economic Potential of Distributed Wind in Colorado, Minnesota, and New York

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

Baring-Gould, Edward I; McCabe, Kevin; Sigrin, Benjamin O

Stakeholders in the small and distributed wind space require access to better tools and data for more informed decisions on high-impact topics, including project planning, policymaking, and funding allocation. A major challenge in obtaining improved information is in the identification of favorable sites - namely, the intersection of sufficient wind resource with economic parameters such as retail rates, incentives, and other policies. This presentation made at the AWEA WINDPOWER Conference and Exhibition in Chicago in 2018 explores the researchers' objective: To understand the spatial variance of key distributed wind parameters and identify where they intersect to form pockets of favorablemore » areas in Colorado, Minnesota, and New York.« less

Automatic Calibration of a Distributed Rainfall-Runoff Model, Using the Degree-Day Formulation for Snow Melting, Within DMIP2 Project

NASA Astrophysics Data System (ADS)

Frances, F.; Orozco, I.

2010-12-01

This work presents the assessment of the TETIS distributed hydrological model in mountain basins of the American and Carson rivers in Sierra Nevada (USA) at hourly time discretization, as part of the DMIP2 Project. In TETIS each cell of the spatial grid conceptualizes the water cycle using six tanks connected among them. The relationship between tanks depends on the case, although at the end in most situations, simple linear reservoirs and flow thresholds schemes are used with exceptional results (Vélez et al., 1999; Francés et al., 2002). In particular, within the snow tank, snow melting is based in this work on the simple degree-day method with spatial constant parameters. The TETIS model includes an automatic calibration module, based on the SCE-UA algorithm (Duan et al., 1992; Duan et al., 1994) and the model effective parameters are organized following a split structure, as presented by Francés and Benito (1995) and Francés et al. (2007). In this way, the calibration involves in TETIS up to 9 correction factors (CFs), which correct globally the different parameter maps instead of each parameter cell value, thus reducing drastically the number of variables to be calibrated. This strategy allows for a fast and agile modification in different hydrological processes preserving the spatial structure of each parameter map. With the snowmelt submodel, automatic model calibration was carried out in three steps, separating the calibration of rainfall-runoff and snowmelt parameters. In the first step, the automatic calibration of the CFs during the period 05/20/1990 to 07/31/1990 in the American River (without snow influence), gave a Nash-Sutcliffe Efficiency (NSE) index of 0.92. The calibration of the three degree-day parameters was done using all the SNOTEL stations in the American and Carson rivers. Finally, using previous calibrations as initial values, the complete calibration done in the Carson River for the period 10/01/1992 to 07/31/1993 gave a NSE index of 0.86. The temporal and spatial validation using five periods must be considered in both rivers excellent for discharges (NSEs higher than 0.76) and good for snow distribution (daily spatial coverage errors ranging from -10 to 27%). In conclusion, this work demonstrates: 1.- The viability of automatic calibration of distributed models, with the corresponding personal time saving and maximum exploitation of the available information. 2.- The good performance of the degree-day snowmelt formulation even at hourly time discretization, in spite of its simplicity.

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.

Revised spatially distributed global livestock emissions

NASA Astrophysics Data System (ADS)

Asrar, G.; Wolf, J.; West, T. O.

2015-12-01

Livestock play an important role in agricultural carbon cycling through consumption of biomass and emissions of methane. Quantification and spatial distribution of methane and carbon dioxide produced by livestock is needed to develop bottom-up estimates for carbon monitoring. These estimates serve as stand-alone international emissions estimates, as input to global emissions modeling, and as comparisons or constraints to flux estimates from atmospheric inversion models. Recent results for the US suggest that the 2006 IPCC default coefficients may underestimate livestock methane emissions. In this project, revised coefficients were calculated for cattle and swine in all global regions, based on reported changes in body mass, quality and quantity of feed, milk production, and management of living animals and manure for these regions. New estimates of livestock methane and carbon dioxide emissions were calculated using the revised coefficients and global livestock population data. Spatial distribution of population data and associated fluxes was conducted using the MODIS Land Cover Type 5, version 5.1 (i.e. MCD12Q1 data product), and a previously published downscaling algorithm for reconciling inventory and satellite-based land cover data at 0.05 degree resolution. Preliminary results for 2013 indicate greater emissions than those calculated using the IPCC 2006 coefficients. Global total enteric fermentation methane increased by 6%, while manure management methane increased by 38%, with variation among species and regions resulting in improved spatial distributions of livestock emissions. These new estimates of total livestock methane are comparable to other recently reported studies for the entire US and the State of California. These new regional/global estimates will improve the ability to reconcile top-down and bottom-up estimates of methane production as well as provide updated global estimates for use in development and evaluation of Earth system models.

Species Distribution Modelling: Contrasting presence-only models with plot abundance data.

PubMed

Gomes, Vitor H F; IJff, Stéphanie D; Raes, Niels; Amaral, Iêda Leão; Salomão, Rafael P; de Souza Coelho, Luiz; de Almeida Matos, Francisca Dionízia; Castilho, Carolina V; de Andrade Lima Filho, Diogenes; López, Dairon Cárdenas; Guevara, Juan Ernesto; Magnusson, William E; Phillips, Oliver L; Wittmann, Florian; de Jesus Veiga Carim, Marcelo; Martins, Maria Pires; Irume, Mariana Victória; Sabatier, Daniel; Molino, Jean-François; Bánki, Olaf S; da Silva Guimarães, José Renan; Pitman, Nigel C A; Piedade, Maria Teresa Fernandez; Mendoza, Abel Monteagudo; Luize, Bruno Garcia; Venticinque, Eduardo Martins; de Leão Novo, Evlyn Márcia Moraes; Vargas, Percy Núñez; Silva, Thiago Sanna Freire; Manzatto, Angelo Gilberto; Terborgh, John; Reis, Neidiane Farias Costa; Montero, Juan Carlos; Casula, Katia Regina; Marimon, Beatriz S; Marimon, Ben-Hur; Coronado, Euridice N Honorio; Feldpausch, Ted R; Duque, Alvaro; Zartman, Charles Eugene; Arboleda, Nicolás Castaño; Killeen, Timothy J; Mostacedo, Bonifacio; Vasquez, Rodolfo; Schöngart, Jochen; Assis, Rafael L; Medeiros, Marcelo Brilhante; Simon, Marcelo Fragomeni; Andrade, Ana; Laurance, William F; Camargo, José Luís; Demarchi, Layon O; Laurance, Susan G W; de Sousa Farias, Emanuelle; Nascimento, Henrique Eduardo Mendonça; Revilla, Juan David Cardenas; Quaresma, Adriano; Costa, Flavia R C; Vieira, Ima Célia Guimarães; Cintra, Bruno Barçante Ladvocat; Castellanos, Hernán; Brienen, Roel; Stevenson, Pablo R; Feitosa, Yuri; Duivenvoorden, Joost F; Aymard C, Gerardo A; Mogollón, Hugo F; Targhetta, Natalia; Comiskey, James A; Vicentini, Alberto; Lopes, Aline; Damasco, Gabriel; Dávila, Nállarett; García-Villacorta, Roosevelt; Levis, Carolina; Schietti, Juliana; Souza, Priscila; Emilio, Thaise; Alonso, Alfonso; Neill, David; Dallmeier, Francisco; Ferreira, Leandro Valle; Araujo-Murakami, Alejandro; Praia, Daniel; do Amaral, Dário Dantas; Carvalho, Fernanda Antunes; de Souza, Fernanda Coelho; Feeley, Kenneth; Arroyo, Luzmila; Pansonato, Marcelo Petratti; Gribel, Rogerio; Villa, Boris; Licona, Juan Carlos; Fine, Paul V A; Cerón, Carlos; Baraloto, Chris; Jimenez, Eliana M; Stropp, Juliana; Engel, Julien; Silveira, Marcos; Mora, Maria Cristina Peñuela; Petronelli, Pascal; Maas, Paul; Thomas-Caesar, Raquel; Henkel, Terry W; Daly, Doug; Paredes, Marcos Ríos; Baker, Tim R; Fuentes, Alfredo; Peres, Carlos A; Chave, Jerome; Pena, Jose Luis Marcelo; Dexter, Kyle G; Silman, Miles R; Jørgensen, Peter Møller; Pennington, Toby; Di Fiore, Anthony; Valverde, Fernando Cornejo; Phillips, Juan Fernando; Rivas-Torres, Gonzalo; von Hildebrand, Patricio; van Andel, Tinde R; Ruschel, Ademir R; Prieto, Adriana; Rudas, Agustín; Hoffman, Bruce; Vela, César I A; Barbosa, Edelcilio Marques; Zent, Egleé L; Gonzales, George Pepe Gallardo; Doza, Hilda Paulette Dávila; de Andrade Miranda, Ires Paula; Guillaumet, Jean-Louis; Pinto, Linder Felipe Mozombite; de Matos Bonates, Luiz Carlos; Silva, Natalino; Gómez, Ricardo Zárate; Zent, Stanford; Gonzales, Therany; Vos, Vincent A; Malhi, Yadvinder; Oliveira, Alexandre A; Cano, Angela; Albuquerque, Bianca Weiss; Vriesendorp, Corine; Correa, Diego Felipe; Torre, Emilio Vilanova; van der Heijden, Geertje; Ramirez-Angulo, Hirma; Ramos, José Ferreira; Young, Kenneth R; Rocha, Maira; Nascimento, Marcelo Trindade; Medina, Maria Natalia Umaña; Tirado, Milton; Wang, Ophelia; Sierra, Rodrigo; Torres-Lezama, Armando; Mendoza, Casimiro; Ferreira, Cid; Baider, Cláudia; Villarroel, Daniel; Balslev, Henrik; Mesones, Italo; Giraldo, Ligia Estela Urrego; Casas, Luisa Fernanda; Reategui, Manuel Augusto Ahuite; Linares-Palomino, Reynaldo; Zagt, Roderick; Cárdenas, Sasha; Farfan-Rios, William; Sampaio, Adeilza Felipe; Pauletto, Daniela; Sandoval, Elvis H Valderrama; Arevalo, Freddy Ramirez; Huamantupa-Chuquimaco, Isau; Garcia-Cabrera, Karina; Hernandez, Lionel; Gamarra, Luis Valenzuela; Alexiades, Miguel N; Pansini, Susamar; Cuenca, Walter Palacios; Milliken, William; Ricardo, Joana; Lopez-Gonzalez, Gabriela; Pos, Edwin; Ter Steege, Hans

2018-01-17

Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs. Here, we test how the distribution of NHCs and MaxEnt predictions relates to a spatial abundance model, based on a large plot dataset for Amazonian tree species, using inverse distance weighting (IDW). We also propose a new pipeline to deal with inconsistencies in NHCs and to limit the area of occupancy of the species. We found a significant but weak positive relationship between the distribution of NHCs and IDW for 66% of the species. The relationship between SDMs and IDW was also significant but weakly positive for 95% of the species, and sensitivity for both analyses was high. Furthermore, the pipeline removed half of the NHCs records. Presence-only SDM applications should consider this limitation, especially for large biodiversity assessments projects, when they are automatically generated without subsequent checking. Our pipeline provides a conservative estimate of a species' area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.

Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model

USGS Publications Warehouse

Byrd, Kristin B.; Windham-Myers, Lisamarie; Leeuw, Thomas; Downing, Bryan D.; Morris, James T.; Ferner, Matthew C.

2016-01-01

Reducing uncertainty in data inputs at relevant spatial scales can improve tidal marsh forecasting models, and their usefulness in coastal climate change adaptation decisions. The Marsh Equilibrium Model (MEM), a one-dimensional mechanistic elevation model, incorporates feedbacks of organic and inorganic inputs to project elevations under sea-level rise scenarios. We tested the feasibility of deriving two key MEM inputs—average annual suspended sediment concentration (SSC) and aboveground peak biomass—from remote sensing data in order to apply MEM across a broader geographic region. We analyzed the precision and representativeness (spatial distribution) of these remote sensing inputs to improve understanding of our study region, a brackish tidal marsh in San Francisco Bay, and to test the applicable spatial extent for coastal modeling. We compared biomass and SSC models derived from Landsat 8, DigitalGlobe WorldView-2, and hyperspectral airborne imagery. Landsat 8-derived inputs were evaluated in a MEM sensitivity analysis. Biomass models were comparable although peak biomass from Landsat 8 best matched field-measured values. The Portable Remote Imaging Spectrometer SSC model was most accurate, although a Landsat 8 time series provided annual average SSC estimates. Landsat 8-measured peak biomass values were randomly distributed, and annual average SSC (30 mg/L) was well represented in the main channels (IQR: 29–32 mg/L), illustrating the suitability of these inputs across the model domain. Trend response surface analysis identified significant diversion between field and remote sensing-based model runs at 60 yr due to model sensitivity at the marsh edge (80–140 cm NAVD88), although at 100 yr, elevation forecasts differed less than 10 cm across 97% of the marsh surface (150–200 cm NAVD88). Results demonstrate the utility of Landsat 8 for landscape-scale tidal marsh elevation projections due to its comparable performance with the other sensors, temporal frequency, and cost. Integration of remote sensing data with MEM should advance regional projections of marsh vegetation change by better parameterizing MEM inputs spatially. Improving information for coastal modeling will support planning for ecosystem services, including habitat, carbon storage, and flood protection.

Detection of the Velocity Shear Effect on the Spatial Distributions of the Galactic Satellites in Isolated Systems

NASA Astrophysics Data System (ADS)

Lee, Jounghun; Choi, Yun-Young

2015-02-01

We report a detection of the effect of the large-scale velocity shear on the spatial distributions of the galactic satellites around the isolated hosts. Identifying the isolated galactic systems, each of which consists of a single host galaxy and its satellites, from the Seventh Data Release of the Sloan Digital Sky Survey and reconstructing linearly the velocity shear field in the local universe, we measure the alignments between the relative positions of the satellites from their isolated hosts and the principal axes of the local velocity shear tensors projected onto the plane of sky. We find a clear signal that the galactic satellites in isolated systems are located preferentially along the directions of the minor principal axes of the large-scale velocity shear field. Those galactic satellites that are spirals, are brighter, are located at distances larger than the projected virial radii of the hosts, and belong to the spiral hosts yield stronger alignment signals, which implies that the alignment strength depends on the formation and accretion epochs of the galactic satellites. It is also shown that the alignment strength is quite insensitive to the cosmic web environment, as well as the size and luminosity of the isolated hosts. Although this result is consistent with the numerical finding of Libeskind et al. based on an N-body experiment, owing to the very low significance of the observed signals, it remains inconclusive whether or not the velocity shear effect on the satellite distribution is truly universal.

A neutral hydrogen survey of the Hydra 1 cluster

NASA Technical Reports Server (NTRS)

Mcmahon, Pauline; Vangorkom, Jacqueline; Richter, Otto; Ferguson, Henry

1993-01-01

We are undertaking a project to image the entire volume of the Hydra 1 cluster of galaxies in neutral hydrogen using the VLA. This involves making a series of pointings spaced 30 min. (the half power beam width) apart, each observed at three velocity settings in order to span the whole velocity range of the cluster. The purpose of this survey is to determine the true distribution, both in space and velocity, of gas-rich systems and hence, to deduce what effects a dense environment may have on the evolution of these systems. Most surveys of clusters to date have been performed on optically selected samples. However, optically selected samples may provide misleading views of the distribution of gas-rich systems, since many low surface brightness galaxies have an abundance of neutral gas (Bothun et al. 1987, Giovanelli & Haynes 1989). The Hydra project is providing the first unbiased view of the HI distribution in a cluster of galaxies. Our 5 sigma sensitivity is 4.1 x 10(exp 7) solar M/beam, (assuming H(sub 0) = 75 km s(exp -1) Mpc(exp -1)) and our velocity resolution is 42 km s(exp -1). We have a spatial resolution of 45 sec., which means that only the largest galaxies are spatially resolved enough to determine HI disk size. Our coverage is about 50 percent of the central region plus eight other fields centered on bright spirals within about 2 deg. of the center.

The influence of coarse-scale environmental features on current and predicted future distributions of narrow-range endemic crayfish populations

USGS Publications Warehouse

Dyer, Joseph J.; Brewer, Shannon K.; Worthington, Thomas A.; Bergey, Elizabeth A.

2013-01-01

1.A major limitation to effective management of narrow-range crayfish populations is the paucity of information on the spatial distribution of crayfish species and a general understanding of the interacting environmental variables that drive current and future potential distributional patterns. 2.Maximum Entropy Species Distribution Modeling Software (MaxEnt) was used to predict the current and future potential distributions of four endemic crayfish species in the Ouachita Mountains. Current distributions were modelled using climate, geology, soils, land use, landform and flow variables thought to be important to lotic crayfish. Potential changes in the distribution were forecast by using models trained on current conditions and projecting onto the landscape predicted under climate-change scenarios. 3.The modelled distribution of the four species closely resembled the perceived distribution of each species but also predicted populations in streams and catchments where they had not previously been collected. Soils, elevation and winter precipitation and temperature most strongly related to current distributions and represented 6587% of the predictive power of the models. Model accuracy was high for all models, and model predictions of new populations were verified through additional field sampling. 4.Current models created using two spatial resolutions (1 and 4.5km2) showed that fine-resolution data more accurately represented current distributions. For three of the four species, the 1-km2 resolution models resulted in more conservative predictions. However, the modelled distributional extent of Orconectes leptogonopodus was similar regardless of data resolution. Field validations indicated 1-km2 resolution models were more accurate than 4.5-km2 resolution models. 5.Future projected (4.5-km2 resolution models) model distributions indicated three of the four endemic species would have truncated ranges with low occurrence probabilities under the low-emission scenario, whereas two of four species would be severely restricted in range under moderatehigh emissions. Discrepancies in the two emission scenarios probably relate to the exclusion of behavioural adaptations from species-distribution models. 6.These model predictions illustrate possible impacts of climate change on narrow-range endemic crayfish populations. The predictions do not account for biotic interactions, migration, local habitat conditions or species adaptation. However, we identified the constraining landscape features acting on these populations that provide a framework for addressing habitat needs at a fine scale and developing targeted and systematic monitoring programmes.

Land use compounds habitat losses under projected climate change in a threatened California ecosystem.

PubMed

Riordan, Erin Coulter; Rundel, Philip W

2014-01-01

Given the rapidly growing human population in mediterranean-climate systems, land use may pose a more immediate threat to biodiversity than climate change this century, yet few studies address the relative future impacts of both drivers. We assess spatial and temporal patterns of projected 21(st) century land use and climate change on California sage scrub (CSS), a plant association of considerable diversity and threatened status in the mediterranean-climate California Floristic Province. Using a species distribution modeling approach combined with spatially-explicit land use projections, we model habitat loss for 20 dominant shrub species under unlimited and no dispersal scenarios at two time intervals (early and late century) in two ecoregions in California (Central Coast and South Coast). Overall, projected climate change impacts were highly variable across CSS species and heavily dependent on dispersal assumptions. Projected anthropogenic land use drove greater relative habitat losses compared to projected climate change in many species. This pattern was only significant under assumptions of unlimited dispersal, however, where considerable climate-driven habitat gains offset some concurrent climate-driven habitat losses. Additionally, some of the habitat gained with projected climate change overlapped with projected land use. Most species showed potential northern habitat expansion and southern habitat contraction due to projected climate change, resulting in sharply contrasting patterns of impact between Central and South Coast Ecoregions. In the Central Coast, dispersal could play an important role moderating losses from both climate change and land use. In contrast, high geographic overlap in habitat losses driven by projected climate change and projected land use in the South Coast underscores the potential for compounding negative impacts of both drivers. Limiting habitat conversion may be a broadly beneficial strategy under climate change. We emphasize the importance of addressing both drivers in conservation and resource management planning.

The California Baseline Methane Survey

NASA Astrophysics Data System (ADS)

Duren, R. M.; Thorpe, A. K.; Hopkins, F. M.; Rafiq, T.; Bue, B. D.; Prasad, K.; Mccubbin, I.; Miller, C. E.

2017-12-01

The California Baseline Methane Survey is the first systematic, statewide assessment of methane point source emissions. The objectives are to reduce uncertainty in the state's methane budget and to identify emission mitigation priorities for state and local agencies, utilities and facility owners. The project combines remote sensing of large areas with airborne imaging spectroscopy and spatially resolved bottom-up data sets to detect, quantify and attribute emissions from diverse sectors including agriculture, waste management, oil and gas production and the natural gas supply chain. Phase 1 of the project surveyed nearly 180,000 individual facilities and infrastructure components across California in 2016 - achieving completeness rates ranging from 20% to 100% per emission sector at < 5 meters spatial resolution. Additionally, intensive studies of key areas and sectors were performed to assess source persistence and variability at times scales ranging from minutes to months. Phase 2 of the project continues with additional data collection in Spring and Fall 2017. We describe the survey design and measurement, modeling and analysis methods. We present initial findings regarding the spatial, temporal and sectoral distribution of methane point source emissions in California and their estimated contribution to the state's total methane budget. We provide case-studies and lessons learned about key sectors including examples where super-emitters were identified and mitigated. We summarize challenges and recommendations for future methane research, inventories and mitigation guidance within and beyond California.

Structural sensitivity of x-ray Bragg projection ptychography to domain patterns in epitaxial thin films

NASA Astrophysics Data System (ADS)

Hruszkewycz, S. O.; Zhang, Q.; Holt, M. V.; Highland, M. J.; Evans, P. G.; Fuoss, P. H.

2016-10-01

Bragg projection ptychography (BPP) is a coherent diffraction imaging technique capable of mapping the spatial distribution of the Bragg structure factor in nanostructured thin films. Here, we show that, because these images are projections, the structural sensitivity of the resulting images depends on the film thickness and the aspect ratio and orientation of the features of interest and that image interpretation depends on these factors. We model changes in contrast in the BPP reconstructions of simulated PbTiO3 ferroelectric thin films with meandering 180∘ stripe domains as a function of film thickness, discuss their origin, and comment on the implication of these factors on the design of BPP experiments of general nanostructured films.

[Effect of terracing project on temporal-spatial variation of non-point source pollution load in Hujiashan watershed, China].

PubMed

Han, Qiang; Yu, Xing Xiu; Wang, Wei; Xu, Miao Miao; Ren, Rui; Zhang, Jia Peng

2017-04-18

Taking Hujiashan small watershed as the study area, based on the classified result of Landsat TM/ETM images of 2005, 2010 and 2015, combined with long-term field observation data, and used the export coefficient model, our study explored the effect of small watershed management project on temporal and spatial variation of total nitrogen (TN) load of non-point source pollution under the support of GIS technology. The results indicated that, due to the implementation of slope modification project, the area of cultivated land was significantly increased, while forest and bareland were decreased. The load of non-point source TN increased from 63208 kg in 2005 to 72778 kg in 2010, but reduced to 46876 kg in 2015. The contribution rate from residential areas was higher, the average contribution rate of the three periods was 53.5%, but it showed a decreasing trend year by year. The contribution rate of land use types was 45%, which showed an increasing trend year by year. The contribution rate of livestock was always low. From the spatial distribution, TN loading intensity was changed obviously after the terracing project. High load intensity zone was mainly concentrated on the slope of 5°-15° before terracing project. Nevertheless, high load intensity zone was concentrated on the slope of 15°-35° after terracing project, and 5°-8° had become a low load strength area. The TN load intensity changed little with time on the slope of 0°-8°, and it increased first and then decreased on the slope above 8°. With the treatment of sewage, garbage and livestock manure in rural areas, the output of nitrogen in the living and livestock breeding were significantly reduced. Due to the implementation of the project, the cultivated land area increased by 31%.

The Southern Oscillation, Hypoxia, and the Eastern Pacific Tuna Fishery

NASA Astrophysics Data System (ADS)

Webster, D.; Kiefer, D.; Lam, C. H.; Harrison, D. P.; Armstrong, E. M.; Hinton, M.; Luo, L.

2012-12-01

The Eastern Pacific tuna fishery, which is one of the world's major fisheries, covers thousands of square kilometers. The vessels of this fishery are registered in more than 30 nations and largely target bigeye (Thunnus obesus), skipjack (Katsuwonus pelamis), and yellowfin (T. albacores) tuna. In both the Pelagic Habitat Analysis Module project, which is sponsored by NASA, and the Fishscape project, which is sponsored by NSF, we have attempted to define the habitat of the three species by matching a 50 year time series on fish catch and effort with oceanographic information obtained from satellite imagery and from a global circulation model. The fishery time series, which was provided by the Inter-American Tropical Tuna Commission, provided spatial maps of catch and effort at monthly time steps; the satellite imagery of the region consisted of sea surface temperature, chlorophyll, and height from GHRSST, SEAWiFS, and AVISO products, and the modeled flow field at selected depths was output from ECCO-92 simulations from 1992 to present. All information was integrated and analyzed within the EASy marine geographic information system. This GIS will also provides a home for the Fishscape spatial simulation model of the coupled dynamics of the ocean, fish, fleets, and markets. This model will then be applied to an assessment of the potential ecological and economic impacts of climate change, technological advances in fleet operations, and increases in fuel costs. We have determined by application of EOF analysis that the ECCO-2 simulation of sea surface height fits well with that of AVISO imagery; thus, if driven properly by predictions of future air-sea exchange, the model should provide good estimates of circulation patterns. We have also found that strong El Nino events lead to strong recruitment of all three species and strong La Nina events lead to weak recruitment. Finally, we have found that the general spatial distribution of the Eastern Pacific fishing grounds matches well with the spatial distribution of the hypoxic waters at a depth of 150 meters and the surface concentration of chlorophyll a, and monthly variations in the spatial distribution of the catch and effort are closely tied to sea surface temperature. We will conclude by discussing the reasons for these relationships and speculation on how these relations will help guide assessments of the impact of global warming on the fishery.

Generation of future potential scenarios in an Alpine Catchment by applying bias-correction techniques, delta-change approaches and stochastic Weather Generators at different spatial scale. Analysis of their influence on basic and drought statistics.

NASA Astrophysics Data System (ADS)

Collados-Lara, Antonio-Juan; Pulido-Velazquez, David; Pardo-Iguzquiza, Eulogio

2017-04-01

Assessing impacts of potential future climate change scenarios in precipitation and temperature is essential to design adaptive strategies in water resources systems. The objective of this work is to analyze the possibilities of different statistical downscaling methods to generate future potential scenarios in an Alpine Catchment from historical data and the available climate models simulations performed in the frame of the CORDEX EU project. The initial information employed to define these downscaling approaches are the historical climatic data (taken from the Spain02 project for the period 1971-2000 with a spatial resolution of 12.5 Km) and the future series provided by climatic models in the horizon period 2071-2100 . We have used information coming from nine climate model simulations (obtained from five different Regional climate models (RCM) nested to four different Global Climate Models (GCM)) from the European CORDEX project. In our application we have focused on the Representative Concentration Pathways (RCP) 8.5 emissions scenario, which is the most unfavorable scenario considered in the fifth Assessment Report (AR5) by the Intergovernmental Panel on Climate Change (IPCC). For each RCM we have generated future climate series for the period 2071-2100 by applying two different approaches, bias correction and delta change, and five different transformation techniques (first moment correction, first and second moment correction, regression functions, quantile mapping using distribution derived transformation and quantile mapping using empirical quantiles) for both of them. Ensembles of the obtained series were proposed to obtain more representative potential future climate scenarios to be employed to study potential impacts. In this work we propose a non-equifeaseble combination of the future series giving more weight to those coming from models (delta change approaches) or combination of models and techniques that provides better approximation to the basic and drought statistic of the historical data. A multi-objective analysis using basic statistics (mean, standard deviation and asymmetry coefficient) and droughts statistics (duration, magnitude and intensity) has been performed to identify which models are better in terms of goodness of fit to reproduce the historical series. The drought statistics have been obtained from the Standard Precipitation index (SPI) series using the Theory of Runs. This analysis allows discriminate the best RCM and the best combination of model and correction technique in the bias-correction method. We have also analyzed the possibilities of using different Stochastic Weather Generators to approximate the basic and droughts statistics of the historical series. These analyses have been performed in our case study in a lumped and in a distributed way in order to assess its sensibility to the spatial scale. The statistic of the future temperature series obtained with different ensemble options are quite homogeneous, but the precipitation shows a higher sensibility to the adopted method and spatial scale. The global increment in the mean temperature values are 31.79 %, 31.79 %, 31.03 % and 31.74 % for the distributed bias-correction, distributed delta-change, lumped bias-correction and lumped delta-change ensembles respectively and in the precipitation they are -25.48 %, -28.49 %, -26.42 % and -27.35% respectively. Acknowledgments: This research work has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank Spain02 and CORDEX projects for the data provided for this study and the R package qmap.

Mercury: An Example of Effective Software Reuse for Metadata Management, Data Discovery and Access

NASA Astrophysics Data System (ADS)

Devarakonda, Ranjeet; Palanisamy, Giri; Green, James; Wilson, Bruce E.

2008-12-01

Mercury is a federated metadata harvesting, data discovery and access tool based on both open source packages and custom developed software. Though originally developed for NASA, the Mercury development consortium now includes funding from NASA, USGS, and DOE. Mercury supports the reuse of metadata by enabling searching across a range of metadata specification and standards including XML, Z39.50, FGDC, Dublin-Core, Darwin-Core, EML, and ISO-19115. Mercury provides a single portal to information contained in distributed data management systems. It collects metadata and key data from contributing project servers distributed around the world and builds a centralized index. The Mercury search interfaces then allow the users to perform simple, fielded, spatial and temporal searches across these metadata sources. One of the major goals of the recent redesign of Mercury was to improve the software reusability across the 12 projects which currently fund the continuing development of Mercury. These projects span a range of land, atmosphere, and ocean ecological communities and have a number of common needs for metadata searches, but they also have a number of needs specific to one or a few projects. To balance these common and project-specific needs, Mercury's architecture has three major reusable components; a harvester engine, an indexing system and a user interface component. The harvester engine is responsible for harvesting metadata records from various distributed servers around the USA and around the world. The harvester software was packaged in such a way that all the Mercury projects will use the same harvester scripts but each project will be driven by a set of project specific configuration files. The harvested files are structured metadata records that are indexed against the search library API consistently, so that it can render various search capabilities such as simple, fielded, spatial and temporal. This backend component is supported by a very flexible, easy to use Graphical User Interface which is driven by cascading style sheets, which make it even simpler for reusable design implementation. The new Mercury system is based on a Service Oriented Architecture and effectively reuses components for various services such as Thesaurus Service, Gazetteer Web Service and UDDI Directory Services. The software also provides various search services including: RSS, Geo-RSS, OpenSearch, Web Services and Portlets, integrated shopping cart to order datasets from various data centers (ORNL DAAC, NSIDC) and integrated visualization tools. Other features include: Filtering and dynamic sorting of search results, book- markable search results, save, retrieve, and modify search criteria.

Mercury: An Example of Effective Software Reuse for Metadata Management, Data Discovery and Access

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

Devarakonda, Ranjeet

2008-01-01

Mercury is a federated metadata harvesting, data discovery and access tool based on both open source packages and custom developed software. Though originally developed for NASA, the Mercury development consortium now includes funding from NASA, USGS, and DOE. Mercury supports the reuse of metadata by enabling searching across a range of metadata specification and standards including XML, Z39.50, FGDC, Dublin-Core, Darwin-Core, EML, and ISO-19115. Mercury provides a single portal to information contained in distributed data management systems. It collects metadata and key data from contributing project servers distributed around the world and builds a centralized index. The Mercury search interfacesmore » then allow the users to perform simple, fielded, spatial and temporal searches across these metadata sources. One of the major goals of the recent redesign of Mercury was to improve the software reusability across the 12 projects which currently fund the continuing development of Mercury. These projects span a range of land, atmosphere, and ocean ecological communities and have a number of common needs for metadata searches, but they also have a number of needs specific to one or a few projects. To balance these common and project-specific needs, Mercury's architecture has three major reusable components; a harvester engine, an indexing system and a user interface component. The harvester engine is responsible for harvesting metadata records from various distributed servers around the USA and around the world. The harvester software was packaged in such a way that all the Mercury projects will use the same harvester scripts but each project will be driven by a set of project specific configuration files. The harvested files are structured metadata records that are indexed against the search library API consistently, so that it can render various search capabilities such as simple, fielded, spatial and temporal. This backend component is supported by a very flexible, easy to use Graphical User Interface which is driven by cascading style sheets, which make it even simpler for reusable design implementation. The new Mercury system is based on a Service Oriented Architecture and effectively reuses components for various services such as Thesaurus Service, Gazetteer Web Service and UDDI Directory Services. The software also provides various search services including: RSS, Geo-RSS, OpenSearch, Web Services and Portlets, integrated shopping cart to order datasets from various data centers (ORNL DAAC, NSIDC) and integrated visualization tools. Other features include: Filtering and dynamic sorting of search results, book- markable search results, save, retrieve, and modify search criteria.« less

Verification of Spatial Forecasts of Continuous Meteorological Variables Using Categorical and Object-Based Methods

DTIC Science & Technology

2016-08-01

Using Categorical and Object-Based Methods by John W Raby and Huaqing Cai Approved for public release; distribution...by John W Raby and Huaqing Cai Computational and Information Sciences Directorate, ARL Approved for public release...AUTHOR(S) John W Raby and Huaqing Cai 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND

Validating induced seismicity forecast models—Induced Seismicity Test Bench

NASA Astrophysics Data System (ADS)

Király-Proag, Eszter; Zechar, J. Douglas; Gischig, Valentin; Wiemer, Stefan; Karvounis, Dimitrios; Doetsch, Joseph

2016-08-01

Induced earthquakes often accompany fluid injection, and the seismic hazard they pose threatens various underground engineering projects. Models to monitor and control induced seismic hazard with traffic light systems should be probabilistic, forward-looking, and updated as new data arrive. In this study, we propose an Induced Seismicity Test Bench to test and rank such models; this test bench can be used for model development, model selection, and ensemble model building. We apply the test bench to data from the Basel 2006 and Soultz-sous-Forêts 2004 geothermal stimulation projects, and we assess forecasts from two models: Shapiro and Smoothed Seismicity (SaSS) and Hydraulics and Seismics (HySei). These models incorporate a different mix of physics-based elements and stochastic representation of the induced sequences. Our results show that neither model is fully superior to the other. Generally, HySei forecasts the seismicity rate better after shut-in but is only mediocre at forecasting the spatial distribution. On the other hand, SaSS forecasts the spatial distribution better and gives better seismicity rate estimates before shut-in. The shut-in phase is a difficult moment for both models in both reservoirs: the models tend to underpredict the seismicity rate around, and shortly after, shut-in.

EnviroAtlas Cyanobacteria Assessment Network (CyAN) ...

EPA Pesticide Factsheets

Economic, health, and environmental impacts of cyanobacteria and associated harmful algal blooms are increasingly recognized by policymakers, managers, and scientific researchers. However, spatially-distributed, long-term data on cyanobacteria blooms are largely unavailable. The multiagency Cyanobacteria Assessment Network (CyAN) project helps address this data need by providing remote-sensing derived information on the concentration of cyanobacteria in fresh water bodies of the Continental United States. CyAN provides data for >1 ,800 lakes using 300x300 meter MERIS and Sentinel-3 satellite image data processed using a second-derivative spectral-shape cyanobacteria algorithm. CyAN includes weekly information for over 200,000 km2 of surface water for 2008-2012, a breadth of spatiotemporal information unprecedented in cyanobacteria research. Online distribution and effective communication of CyAN issues are high priorities for the project and sharing these data offer exceptional opportunities for research, management, and public awareness of cyanobacteria. Challenges that these data pose for webbased data visualization include uneven sampling intervals due to cloud cover, inconsistent spatial data coverage associated with spectral interference and lake "edge effects," and widely varying lake sizes prohibiting presentation of data at the waterbody scale. We present an approach that overcomes these challenges by incorporating a variety of data visualization techniq

The relationship between climate change and the endangered rainforest shrub Triunia robusta (Proteaceae) endemic to southeast Queensland, Australia

NASA Astrophysics Data System (ADS)

Shimizu-Kimura, Yoko; Accad, Arnon; Shapcott, Alison

2017-04-01

Threatened species in rainforests may be vulnerable to climate change, because of their potentially narrow thermal tolerances, small population sizes and restricted distributions. This study modelled climate induced changes on the habitat distribution of the endangered rainforest plant Triunia robusta, endemic to southeast Queensland, Australia. Species distribution models were developed for eastern Australia at 250 m grids and southeast Queensland at 25 m grids using ground-truthed presence records and environmental predictor data. The species’ habitat distribution under the current climate was modelled, and the future potential habitat distributions were projected for the epochs 2030, 2050 and 2070. The eastern Australia model identified several spatially disjunct, broad habitat areas of coastal eastern Australia consistent with the current distribution of rainforests, and projected a southward and upslope contraction driven mainly by average temperatures exceeding current range limits. The southeast Queensland models suggest a dramatic upslope contraction toward locations where the majority of known populations are found. Populations located in the Sunshine Coast hinterland, consistent with past rainforest refugia, are likely to persist long-term. Upgrading the level of protection for less formal nature reserves containing viable populations is a high priority to better protect refugial T. robusta populations with respect to climate change.

The relationship between climate change and the endangered rainforest shrub Triunia robusta (Proteaceae) endemic to southeast Queensland, Australia

PubMed Central

Shimizu-Kimura, Yoko; Accad, Arnon; Shapcott, Alison

2017-01-01

Threatened species in rainforests may be vulnerable to climate change, because of their potentially narrow thermal tolerances, small population sizes and restricted distributions. This study modelled climate induced changes on the habitat distribution of the endangered rainforest plant Triunia robusta, endemic to southeast Queensland, Australia. Species distribution models were developed for eastern Australia at 250 m grids and southeast Queensland at 25 m grids using ground-truthed presence records and environmental predictor data. The species’ habitat distribution under the current climate was modelled, and the future potential habitat distributions were projected for the epochs 2030, 2050 and 2070. The eastern Australia model identified several spatially disjunct, broad habitat areas of coastal eastern Australia consistent with the current distribution of rainforests, and projected a southward and upslope contraction driven mainly by average temperatures exceeding current range limits. The southeast Queensland models suggest a dramatic upslope contraction toward locations where the majority of known populations are found. Populations located in the Sunshine Coast hinterland, consistent with past rainforest refugia, are likely to persist long-term. Upgrading the level of protection for less formal nature reserves containing viable populations is a high priority to better protect refugial T. robusta populations with respect to climate change. PMID:28422136

Projecting the Global Distribution of the Emerging Amphibian Fungal Pathogen, Batrachochytrium dendrobatidis, Based on IPCC Climate Futures

PubMed Central

Olson, Deanna H.; Blaustein, Andrew R.

2016-01-01

Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest) with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary), including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific) and also separately per region (region-specific). One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas, especially for sensitive species and those vulnerable to multiple threats. PMID:27513565

Spatial distributions of Southern Ocean mesozooplankton communities have been resilient to long-term surface warming.

PubMed

Tarling, Geraint A; Ward, Peter; Thorpe, Sally E

2018-01-01

The biogeographic response of oceanic planktonic communities to climatic change has a large influence on the future stability of marine food webs and the functioning of global biogeochemical cycles. Temperature plays a pivotal role in determining the distribution of these communities and ocean warming has the potential to cause major distributional shifts, particularly in polar regions where the thermal envelope is narrow. We considered the impact of long-term ocean warming on the spatial distribution of Southern Ocean mesozooplankton communities through examining plankton abundance in relation to sea surface temperature between two distinct periods, separated by around 60 years. Analyses considered 16 dominant mesozooplankton taxa (in terms of biomass and abundance) in the southwest Atlantic sector of the Southern Ocean, from net samples and in situ temperature records collected during the Discovery Investigations (1926-1938) and contemporary campaigns (1996-2013). Sea surface temperature was found to have increased significantly by 0.74°C between the two eras. The corresponding sea surface temperature at which community abundance peaked was also significantly higher in contemporary times, by 0.98°C. Spatial projections indicated that the geographical location of community peak abundance had remained the same between the two eras despite the poleward advance of sea surface isotherms. If the community had remained within the same thermal envelope as in the 1920s-1930s, community peak abundance would be 500 km further south in the contemporary era. Studies in the northern hemisphere have found that dominant taxa, such as calanoid copepods, have conserved their thermal niches and tracked surface isotherms polewards. The fact that this has not occurred in the Southern Ocean suggests that other selective pressures, particularly food availability and the properties of underlying water masses, place greater constraints on spatial distributions in this region. It further demonstrates that this community is thermally resilient to present levels of sea surface warming. © 2017 John Wiley & Sons Ltd.

Image Reconstruction from Data Collected with an Imaging Interferometer

NASA Astrophysics Data System (ADS)

DeSantis, Z. J.; Thurman, S. T.; Hix, T. T.; Ogden, C. E.

The intensity distribution of an incoherent source and the spatial coherence function at some distance away are related by a Fourier transform, via the Van Cittert-Zernike theorem. Imaging interferometers measure the spatial coherence of light propagated from the incoherently illuminated object by combining light from spatially separated points to measure interference fringes. The contrast and phase of the fringe are the amplitude and phase of a Fourier component of the source’s intensity distribution. The Fiber-Coupled Interferometer (FCI) testbed is a visible light, lab-based imaging interferometer designed to test aspects of an envisioned ground-based interferometer for imaging geosynchronous satellites. The front half of the FCI testbed consists of the scene projection optics, which includes an incoherently backlit scene, located at the focus of a 1 m aperture f/100 telescope. The projected light was collected by the back half of the FCI testbed. The collection optics consisted of three 11 mm aperture fiber-coupled telescopes. Light in the fibers was combined pairwise and dispersed onto a sensor to measure the interference fringe as a function of wavelength, which produces a radial spoke of measurements in the Fourier domain. The visibility function was sampled throughout the Fourier domain by recording fringe data at many different scene rotations and collection telescope separations. Our image reconstruction algorithm successfully produced images for the three scenes we tested: asymmetric pair of pinholes, U.S. Air Force resolution bar target, and satellite scene. The bar target reconstruction shows detail and resolution near the predicted resolution limit. This research was developed with funding from the Defense Advanced Research Projects Agency (DARPA). The views, opinions and/or findings expressed are those of the author(s) and should not be interpreted as reflecting the official views or policies of the Department of Defense or the U.S. Government.

Onshore wind energy potential over Iberia: present and future projections

NASA Astrophysics Data System (ADS)

Rochinha, Carlos A.; Santos, João A.; Liberato, Margarida L. R.; Pinto, Joaquim G.

2014-05-01

Onshore grid-connected wind power generation has been explored for more than three decades in the Iberian Peninsula. Further, increasing attention has been devoted to renewable energy sources in a climate change context. While advantages of wind energy are widely recognized, its distribution is not spatially homogeneous and not uniform throughout the year. Hence, understanding these spatial-temporal distributions is critical in power system planning. The present study aims at assessing the potential power output estimated from 10 m wind components simulated by a regional climate model (CCLM), driven by ERA40 reanalysis. Datasets are available on a grid with a high spatial resolution (approximately 20 km) and over a 40-yr period (1961-2000). Furthermore, several target sites, located in areas with high installed wind generation capacity, are selected for local-to-regional scale assessments. The results show that potential wind power is higher over northern Iberia, mostly in Cantabria and Galicia, while Andalucía and Cataluña record the lowest values. With respect to the intra-annual variability, summer is by far the season with the lowest potential energy outputs. Furthermore, the inter-annual variability reveals an overall downward long-term trend over the 40-yr period, particularly in the winter time series. A CCLM transient experiment, forced by the SRES A1B emission scenario, is also discussed for a future period (2041-2070), after a model validation/calibration process (bias corrections). Significant changes in the wind power potential are projected for the future throughout Iberia, but their magnitude largely depends on the locations. This work was partially supported by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE (Programa Operacional Factores de Competitividade) and by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project STORMEx FCOMP-01-0124-FEDER- 019524 (PTDC/AAC-CLI/121339/2010).

Adaptive beam shaping for improving the power coupling of a two-Cassegrain-telescope

NASA Astrophysics Data System (ADS)

Ma, Haotong; Hu, Haojun; Xie, Wenke; Zhao, Haichuan; Xu, Xiaojun; Chen, Jinbao

2013-08-01

We demonstrate the adaptive beam shaping for improving the power coupling of a two-Cassegrain-telescope based on the stochastic parallel gradient descent (SPGD) algorithm and dual phase only liquid crystal spatial light modulators (LC-SLMs). Adaptive pre-compensation the wavefront of projected laser beam at the transmitter telescope is chosen to improve the power coupling efficiency. One phase only LC-SLM adaptively optimizes phase distribution of the projected laser beam and the other generates turbulence phase screen. The intensity distributions of the dark hollow beam after passing through the turbulent atmosphere with and without adaptive beam shaping are analyzed in detail. The influence of propagation distance and aperture size of the Cassegrain-telescope on coupling efficiency are investigated theoretically and experimentally. These studies show that the power coupling can be significantly improved by adaptive beam shaping. The technique can be used in optical communication, deep space optical communication and relay mirror.

An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change

PubMed Central

Casajus, Nicolas; Périé, Catherine; Logan, Travis; Lambert, Marie-Claude; de Blois, Sylvie; Berteaux, Dominique

2016-01-01

An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one. PMID:27015274

An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change.

PubMed

Casajus, Nicolas; Périé, Catherine; Logan, Travis; Lambert, Marie-Claude; de Blois, Sylvie; Berteaux, Dominique

2016-01-01

An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.

Spatial transferability of habitat suitability models of Nephrops norvegicus among fished areas in the Northeast Atlantic: sufficiently stable for marine resource conservation?

PubMed

Lauria, Valentina; Power, Anne Marie; Lordan, Colm; Weetman, Adrian; Johnson, Mark P

2015-01-01

Knowledge of the spatial distribution and habitat associations of species in relation to the environment is essential for their management and conservation. Habitat suitability models are useful in quantifying species-environment relationships and predicting species distribution patterns. Little is known, however, about the stability and performance of habitat suitability models when projected into new areas (spatial transferability) and how this can inform resource management. The aims of this study were to model habitat suitability of Norway lobster (Nephrops norvegicus) in five fished areas of the Northeast Atlantic (Aran ground, Irish Sea, Celtic Sea, Scotland Inshore and Fladen ground), and to test for spatial transferability of habitat models among multiple regions. Nephrops burrow density was modelled using generalised additive models (GAMs) with predictors selected from four environmental variables (depth, slope, sediment and rugosity). Models were evaluated and tested for spatial transferability among areas. The optimum models (lowest AICc) for different areas always included depth and sediment as predictors. Burrow densities were generally greater at depth and in finer sediments, but relationships for individual areas were sometimes more complex. Aside from an inclusion of depth and sediment, the optimum models differed between fished areas. When it came to tests of spatial transferability, however, most of the models were able to predict Nephrops density in other areas. Furthermore, transferability was not dependent on use of the optimum models since competing models were also able to achieve a similar level of transferability to new areas. A degree of decoupling between model 'fitting' performance and spatial transferability supports the use of simpler models when extrapolating habitat suitability maps to different areas. Differences in the form and performance of models from different areas may supply further information on the processes shaping species' distributions. Spatial transferability of habitat models can be used to support fishery management when the information is scarce but caution needs to be applied when making inference and a multi-area transferability analysis is preferable to bilateral comparisons between areas.

Climate change and natural disasters – integrating science and practice to protect health

PubMed Central

Sauerborn, Rainer; Ebi, Kristie

2012-01-01

Background Hydro-meteorological disasters are the focus of this paper. The authors examine, to which extent climate change increases their frequency and intensity. Methods Review of IPCC-projections of climate-change related extreme weather events and related literature on health effects. Results Projections show that climate change is likely to increase the frequency, intensity, duration, and spatial distribution of a range of extreme weather events over coming decades. Conclusions There is a need for strengthened collaboration between climate scientists, the health researchers and policy-makers as well as the disaster community to jointly develop adaptation strategies to protect human. PMID:23273248

Soil moisture optimal sampling strategy for Sentinel 1 validation super-sites in Poland

NASA Astrophysics Data System (ADS)

Usowicz, Boguslaw; Lukowski, Mateusz; Marczewski, Wojciech; Lipiec, Jerzy; Usowicz, Jerzy; Rojek, Edyta; Slominska, Ewa; Slominski, Jan

2014-05-01

Soil moisture (SM) exhibits a high temporal and spatial variability that is dependent not only on the rainfall distribution, but also on the topography of the area, physical properties of soil and vegetation characteristics. Large variability does not allow on certain estimation of SM in the surface layer based on ground point measurements, especially in large spatial scales. Remote sensing measurements allow estimating the spatial distribution of SM in the surface layer on the Earth, better than point measurements, however they require validation. This study attempts to characterize the SM distribution by determining its spatial variability in relation to the number and location of ground point measurements. The strategy takes into account the gravimetric and TDR measurements with different sampling steps, abundance and distribution of measuring points on scales of arable field, wetland and commune (areas: 0.01, 1 and 140 km2 respectively), taking into account the different status of SM. Mean values of SM were lowly sensitive on changes in the number and arrangement of sampling, however parameters describing the dispersion responded in a more significant manner. Spatial analysis showed autocorrelations of the SM, which lengths depended on the number and the distribution of points within the adopted grids. Directional analysis revealed a differentiated anisotropy of SM for different grids and numbers of measuring points. It can therefore be concluded that both the number of samples, as well as their layout on the experimental area, were reflected in the parameters characterizing the SM distribution. This suggests the need of using at least two variants of sampling, differing in the number and positioning of the measurement points, wherein the number of them must be at least 20. This is due to the value of the standard error and range of spatial variability, which show little change with the increase in the number of samples above this figure. Gravimetric method gives a more varied distribution of SM than those derived from TDR measurements. It should be noted that reducing the number of samples in the measuring grid leads to flattening the distribution of SM from both methods and increasing the estimation error at the same time. Grid of sensors for permanent measurement points should include points that have similar distributions of SM in the vicinity. Results of the analysis including number, the maximum correlation ranges and the acceptable estimation error should be taken into account when choosing of the measurement points. Adoption or possible adjustment of the distribution of the measurement points should be verified by performing additional measuring campaigns during the dry and wet periods. Presented approach seems to be appropriate for creation of regional-scale test (super) sites, to validate products of satellites equipped with SAR (Synthetic Aperture Radar), operating in C-band, with spatial resolution suited to single field scale, as for example: ERS-1, ERS-2, Radarsat and Sentinel-1, which is going to be launched in next few months. The work was partially funded by the Government of Poland through an ESA Contract under the PECS ELBARA_PD project No. 4000107897/13/NL/KML.

Accuracy and Spatial Variability in GPS Surveying for Landslide Mapping on Road Inventories at a Semi-Detailed Scale: the Case in Colombia

NASA Astrophysics Data System (ADS)

Murillo Feo, C. A.; Martnez Martinez, L. J.; Correa Muñoz, N. A.

2016-06-01

The accuracy of locating attributes on topographic surfaces when, using GPS in mountainous areas, is affected by obstacles to wave propagation. As part of this research on the semi-automatic detection of landslides, we evaluate the accuracy and spatial distribution of the horizontal error in GPS positioning in the tertiary road network of six municipalities located in mountainous areas in the department of Cauca, Colombia, using geo-referencing with GPS mapping equipment and static-fast and pseudo-kinematic methods. We obtained quality parameters for the GPS surveys with differential correction, using a post-processing method. The consolidated database underwent exploratory analyses to determine the statistical distribution, a multivariate analysis to establish relationships and partnerships between the variables, and an analysis of the spatial variability and calculus of accuracy, considering the effect of non-Gaussian distribution errors. The evaluation of the internal validity of the data provide metrics with a confidence level of 95% between 1.24 and 2.45 m in the static-fast mode and between 0.86 and 4.2 m in the pseudo-kinematic mode. The external validity had an absolute error of 4.69 m, indicating that this descriptor is more critical than precision. Based on the ASPRS standard, the scale obtained with the evaluated equipment was in the order of 1:20000, a level of detail expected in the landslide-mapping project. Modelling the spatial variability of the horizontal errors from the empirical semi-variogram analysis showed predictions errors close to the external validity of the devices.

Interannual evolutions of (sub)mesoscale dynamics in the Bay of Biscay and the English Channel

NASA Astrophysics Data System (ADS)

Charria, G.; Vandermeirsch, F.; Theetten, S.; Yelekçi, Ö.; Assassi, C.; Audiffren, N. J.

2016-02-01

In a context of global change, ocean regions as the Bay of the Biscay and the English Channel represent key domains to estimate the local impact on the coasts of interannual evolutions. Indeed, the coastal (considering in this project regions above the continental shelf) and regional (including the continental slope and the abyssal plain) environments are sensitive to the long-term fluctuations driven by the open ocean, the atmosphere and the watersheds. These evolutions can have impacts on the whole ecosystem. To understand and, by extension, forecast evolutions of these ecosystems, we need to go further in the description and the analysis of the past interannual variability over decadal to pluri-decadal periods. This variability can be described at different spatial scales from small (< 1 km) to basin scales (> 100 km). With a focus on smaller scales, the modelled dynamics, using a Coastal Circulation Model on national computing resources (GENCI/CINES), is discussed from interannual simulations (10 to 53 years) with different spatial (4 km to 1 km) and vertical (40 to 100 sigma levels) resolutions compared with available in situ observations. Exploring vorticity and kinetic energy based diagnostics; dynamical patterns are described including the vertical distribution of the mesoscale activity. Despite the lack of deep and spatially distributed observations, present numerical experiments draw a first picture of the 3D mesoscale distribution and its evolution at interannual time scales.

Eye-rotation-induced spatial reorganization of horizontal connections in field 17 of the cat cortex.

PubMed

Shkorbatova, P Yu; Alekseenko, S V

2006-06-01

Six cats with rotation of one or both eyes (strabismus) produced surgically in the early postnatal period demonstrated torsional deviation of the eyes by 10-20 degrees in addition to the rotation. The spatial distribution of retrograde labeled neurons in field 17 was studied by microiontophoretic administration of horseradish peroxidase into individual cortical columns in fields 17 and 18. These studies showed that rotation of the eyes increased the extent of horizontal neuronal connections in field 17 along the projection of the vertical meridian of the field of vision. It is suggested that this reorganization of neuronal connections may support functional changes compensating for eye rotation, as described in the literature.

Role of resolution in regional climate change projections over China

NASA Astrophysics Data System (ADS)

Shi, Ying; Wang, Guiling; Gao, Xuejie

2017-11-01

This paper investigates the sensitivity of projected future climate changes over China to the horizontal resolution of a regional climate model RegCM4.4 (RegCM), using RCP8.5 as an example. Model validation shows that RegCM performs better in reproducing the spatial distribution and magnitude of present-day temperature, precipitation and climate extremes than the driving global climate model HadGEM2-ES (HadGEM, at 1.875° × 1.25° degree resolution), but little difference is found between the simulations at 50 and 25 km resolutions. Comparison with observational data at different resolutions confirmed the added value of the RCM and finer model resolutions in better capturing the probability distribution of precipitation. However, HadGEM and RegCM at both resolutions project a similar pattern of significant future warming during both winter and summer, and a similar pattern of winter precipitation changes including dominant increase in most areas of northern China and little change or decrease in the southern part. Projected precipitation changes in summer diverge among the three models, especially over eastern China, with a general increase in HadGEM, little change in RegCM at 50 km, and a mix of increase and decrease in RegCM at 25 km resolution. Changes of temperature-related extremes (annual total number of daily maximum temperature > 25 °C, the maximum value of daily maximum temperature, the minimum value of daily minimum temperature in the three simulations especially in the two RegCM simulations are very similar to each other; so are the precipitation-related extremes (maximum consecutive dry days, maximum consecutive 5-day precipitation and extremely wet days' total amount). Overall, results from this study indicate a very low sensitivity of projected changes in this region to model resolution. While fine resolution is critical for capturing the spatial variability of the control climate, it may not be as important for capturing the climate response to homogeneous forcing (in this case greenhouse gas concentration changes).

Enhancing the relevance of new scenarios for climate change impacts, adaptation and vulnerability research

NASA Astrophysics Data System (ADS)

van Ruijven, B. J.

2013-12-01

Over the past three decades, scenario analyses have occupied a central role in assessments of the potential impacts of climate change on natural and human systems at different scales during the 21st century. Here, we discuss the role and relevance of new scenarios using shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs) for climate change impacts, adaptation, and vulnerability (IAV) research. It first provides an overview of uses of social-environmental scenarios in IAV studies and identifies the main shortcomings of earlier such scenarios. Second, the paper elaborates on two aspects of new scenarios needing to be improved in order to enhance their usefulness for IAV studies: the ability to work coherently across spatial scales and adding indicators of importance to projections of vulnerability and adaptive capacity in addition to standard indicators of population and gross domestic product. This paper presents a research agenda to add income distribution, spatial population, human health projections, and governance indicators to the new scenarios.

Projected impacts of climate change on farmers' extraction of groundwater from crystalline aquifers in South India

PubMed Central

Ferrant, Sylvain; Caballero, Yvan; Perrin, Jérome; Gascoin, Simon; Dewandel, Benoit; Aulong, Stéphanie; Dazin, Fabrice; Ahmed, Shakeel; Maréchal, Jean-Christophe

2014-01-01

Local groundwater levels in South India are falling alarmingly. In the semi-arid crystalline Deccan plateau area, agricultural production relies on groundwater resources. Downscaled Global Climate Model (GCM) data are used to force a spatially distributed agro-hydrological model in order to evaluate Climate Change (CC) effects on local groundwater extraction (GWE). The slight increase of precipitation may alleviate current groundwater depletion on average, despite the increased evaporation due to warming. Nevertheless, projected climatic extremes create worse GWE shortages than for present climate. Local conditions may lead to opposing impacts on GWE, from increases to decreases (+/−20 mm/year), for a given spatially homogeneous CC forcing. Areas vulnerable to CC in terms of irrigation apportionment are thus identified. Our results emphasize the importance of accounting for local characteristics (water harvesting systems and maximal aquifer capacity versus GWE) in developing measures to cope with CC impacts in the South Indian region. PMID:24424295

High resolution global gridded data for use in population studies

NASA Astrophysics Data System (ADS)

Lloyd, Christopher T.; Sorichetta, Alessandro; Tatem, Andrew J.

2017-01-01

Recent years have seen substantial growth in openly available satellite and other geospatial data layers, which represent a range of metrics relevant to global human population mapping at fine spatial scales. The specifications of such data differ widely and therefore the harmonisation of data layers is a prerequisite to constructing detailed and contemporary spatial datasets which accurately describe population distributions. Such datasets are vital to measure impacts of population growth, monitor change, and plan interventions. To this end the WorldPop Project has produced an open access archive of 3 and 30 arc-second resolution gridded data. Four tiled raster datasets form the basis of the archive: (i) Viewfinder Panoramas topography clipped to Global ADMinistrative area (GADM) coastlines; (ii) a matching ISO 3166 country identification grid; (iii) country area; (iv) and slope layer. Further layers include transport networks, landcover, nightlights, precipitation, travel time to major cities, and waterways. Datasets and production methodology are here described. The archive can be downloaded both from the WorldPop Dataverse Repository and the WorldPop Project website.

High resolution global gridded data for use in population studies.

PubMed

Lloyd, Christopher T; Sorichetta, Alessandro; Tatem, Andrew J

2017-01-31

Recent years have seen substantial growth in openly available satellite and other geospatial data layers, which represent a range of metrics relevant to global human population mapping at fine spatial scales. The specifications of such data differ widely and therefore the harmonisation of data layers is a prerequisite to constructing detailed and contemporary spatial datasets which accurately describe population distributions. Such datasets are vital to measure impacts of population growth, monitor change, and plan interventions. To this end the WorldPop Project has produced an open access archive of 3 and 30 arc-second resolution gridded data. Four tiled raster datasets form the basis of the archive: (i) Viewfinder Panoramas topography clipped to Global ADMinistrative area (GADM) coastlines; (ii) a matching ISO 3166 country identification grid; (iii) country area; (iv) and slope layer. Further layers include transport networks, landcover, nightlights, precipitation, travel time to major cities, and waterways. Datasets and production methodology are here described. The archive can be downloaded both from the WorldPop Dataverse Repository and the WorldPop Project website.

Choice of baseline climate data impacts projected species' responses to climate change.

PubMed

Baker, David J; Hartley, Andrew J; Butchart, Stuart H M; Willis, Stephen G

2016-07-01

Climate data created from historic climate observations are integral to most assessments of potential climate change impacts, and frequently comprise the baseline period used to infer species-climate relationships. They are often also central to downscaling coarse resolution climate simulations from General Circulation Models (GCMs) to project future climate scenarios at ecologically relevant spatial scales. Uncertainty in these baseline data can be large, particularly where weather observations are sparse and climate dynamics are complex (e.g. over mountainous or coastal regions). Yet, importantly, this uncertainty is almost universally overlooked when assessing potential responses of species to climate change. Here, we assessed the importance of historic baseline climate uncertainty for projections of species' responses to future climate change. We built species distribution models (SDMs) for 895 African bird species of conservation concern, using six different climate baselines. We projected these models to two future periods (2040-2069, 2070-2099), using downscaled climate projections, and calculated species turnover and changes in species-specific climate suitability. We found that the choice of baseline climate data constituted an important source of uncertainty in projections of both species turnover and species-specific climate suitability, often comparable with, or more important than, uncertainty arising from the choice of GCM. Importantly, the relative contribution of these factors to projection uncertainty varied spatially. Moreover, when projecting SDMs to sites of biodiversity importance (Important Bird and Biodiversity Areas), these uncertainties altered site-level impacts, which could affect conservation prioritization. Our results highlight that projections of species' responses to climate change are sensitive to uncertainty in the baseline climatology. We recommend that this should be considered routinely in such analyses. © 2016 John Wiley & Sons Ltd.

Impact of climate change on global malaria distribution.

PubMed

Caminade, Cyril; Kovats, Sari; Rocklov, Joacim; Tompkins, Adrian M; Morse, Andrew P; Colón-González, Felipe J; Stenlund, Hans; Martens, Pim; Lloyd, Simon J

2014-03-04

Malaria is an important disease that has a global distribution and significant health burden. The spatial limits of its distribution and seasonal activity are sensitive to climate factors, as well as the local capacity to control the disease. Malaria is also one of the few health outcomes that has been modeled by more than one research group and can therefore facilitate the first model intercomparison for health impacts under a future with climate change. We used bias-corrected temperature and rainfall simulations from the Coupled Model Intercomparison Project Phase 5 climate models to compare the metrics of five statistical and dynamical malaria impact models for three future time periods (2030s, 2050s, and 2080s). We evaluated three malaria outcome metrics at global and regional levels: climate suitability, additional population at risk and additional person-months at risk across the model outputs. The malaria projections were based on five different global climate models, each run under four emission scenarios (Representative Concentration Pathways, RCPs) and a single population projection. We also investigated the modeling uncertainty associated with future projections of populations at risk for malaria owing to climate change. Our findings show an overall global net increase in climate suitability and a net increase in the population at risk, but with large uncertainties. The model outputs indicate a net increase in the annual person-months at risk when comparing from RCP2.6 to RCP8.5 from the 2050s to the 2080s. The malaria outcome metrics were highly sensitive to the choice of malaria impact model, especially over the epidemic fringes of the malaria distribution.

Impact of climate change on global malaria distribution

PubMed Central

Caminade, Cyril; Kovats, Sari; Rocklov, Joacim; Tompkins, Adrian M.; Morse, Andrew P.; Colón-González, Felipe J.; Stenlund, Hans; Martens, Pim; Lloyd, Simon J.

2014-01-01

Malaria is an important disease that has a global distribution and significant health burden. The spatial limits of its distribution and seasonal activity are sensitive to climate factors, as well as the local capacity to control the disease. Malaria is also one of the few health outcomes that has been modeled by more than one research group and can therefore facilitate the first model intercomparison for health impacts under a future with climate change. We used bias-corrected temperature and rainfall simulations from the Coupled Model Intercomparison Project Phase 5 climate models to compare the metrics of five statistical and dynamical malaria impact models for three future time periods (2030s, 2050s, and 2080s). We evaluated three malaria outcome metrics at global and regional levels: climate suitability, additional population at risk and additional person-months at risk across the model outputs. The malaria projections were based on five different global climate models, each run under four emission scenarios (Representative Concentration Pathways, RCPs) and a single population projection. We also investigated the modeling uncertainty associated with future projections of populations at risk for malaria owing to climate change. Our findings show an overall global net increase in climate suitability and a net increase in the population at risk, but with large uncertainties. The model outputs indicate a net increase in the annual person-months at risk when comparing from RCP2.6 to RCP8.5 from the 2050s to the 2080s. The malaria outcome metrics were highly sensitive to the choice of malaria impact model, especially over the epidemic fringes of the malaria distribution. PMID:24596427

Legacies of Lead in Charm City’s Soil: Lessons from the Baltimore Ecosystem Study

PubMed Central

Schwarz, Kirsten; Pouyat, Richard V.; Yesilonis, Ian

2016-01-01

Understanding the spatial distribution of soil lead has been a focus of the Baltimore Ecosystem Study since its inception in 1997. Through multiple research projects that span spatial scales and use different methodologies, three overarching patterns have been identified: (1) soil lead concentrations often exceed state and federal regulatory limits; (2) the variability of soil lead concentrations is high; and (3) despite multiple sources and the highly heterogeneous and patchy nature of soil lead, discernable patterns do exist. Specifically, housing age, the distance to built structures, and the distance to a major roadway are strong predictors of soil lead concentrations. Understanding what drives the spatial distribution of soil lead can inform the transition of underutilized urban space into gardens and other desirable land uses while protecting human health. A framework for management is proposed that considers three factors: (1) the level of contamination; (2) the desired land use; and (3) the community’s preference in implementing the desired land use. The goal of the framework is to promote dialogue and resultant policy changes that support consistent and clear regulatory guidelines for soil lead, without which urban communities will continue to be subject to the potential for lead exposure. PMID:26861371

Spatio-temporal reconstruction of brain dynamics from EEG with a Markov prior.

PubMed

Hansen, Sofie Therese; Hansen, Lars Kai

2017-03-01

Electroencephalography (EEG) can capture brain dynamics in high temporal resolution. By projecting the scalp EEG signal back to its origin in the brain also high spatial resolution can be achieved. Source localized EEG therefore has potential to be a very powerful tool for understanding the functional dynamics of the brain. Solving the inverse problem of EEG is however highly ill-posed as there are many more potential locations of the EEG generators than EEG measurement points. Several well-known properties of brain dynamics can be exploited to alleviate this problem. More short ranging connections exist in the brain than long ranging, arguing for spatially focal sources. Additionally, recent work (Delorme et al., 2012) argues that EEG can be decomposed into components having sparse source distributions. On the temporal side both short and long term stationarity of brain activation are seen. We summarize these insights in an inverse solver, the so-called "Variational Garrote" (Kappen and Gómez, 2013). Using a Markov prior we can incorporate flexible degrees of temporal stationarity. Through spatial basis functions spatially smooth distributions are obtained. Sparsity of these are inherent to the Variational Garrote solver. We name our method the MarkoVG and demonstrate its ability to adapt to the temporal smoothness and spatial sparsity in simulated EEG data. Finally a benchmark EEG dataset is used to demonstrate MarkoVG's ability to recover non-stationary brain dynamics. Copyright © 2016 Elsevier Inc. All rights reserved.

Numerical study of radiometric forces via the direct solution of the Boltzmann kinetic equation

NASA Astrophysics Data System (ADS)

Anikin, Yu. A.

2011-07-01

The two-dimensional rarefied gas motion in a Crookes radiometer and the resulting radiometric forces are studied by numerically solving the Boltzmann kinetic equation. The collision integral is directly evaluated using a projection method, and second-order accurate TVD schemes are used to solve the advection equation. The radiometric forces are found as functions of the Knudsen number and the temperatures, and their spatial distribution is analyzed.

Longitudinal patterns of fish assemblages, aquatic habitat, and water temperature in the Lower Crooked River, Oregon

USGS Publications Warehouse

Torgersen, Christian E.; Hockman-Wert, David P.; Bateman, Douglas S.; Leer, David W.; Gresswell, Robert E.

2007-01-01

The goal of this project was to examine longitudinal patterns in fish assemblages, aquatic habitat, and water temperature in the Lower Crooked River during summer conditions. Specific objectives were to (1) characterize the spatial distribution of native and non-native fishes, (2) describe variation in channel morphology, substrate composition, and water temperature, and (3) evaluate the associations between fishes, aquatic habitat, and water temperature.

Spatial and temporal variations in toxicity in a marsh receiving urban runoff

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

Katznelson, R.; Jewell, W.T.; Anderson, S.L.

1993-06-01

This project is composed of two sections. The first section describes dry weather toxicity surveys to evaluate the distribution of toxicity in the waters of San Francisco Bay and adjacent wetland habitat, and the second is a series of wet weather toxicity studies with emphasis on a marsh receiving urban runoff. The dry weather studies are reported in the appendices, while the wet weather work comprises the main report.

Genetic and ecological insights into glacial refugia of walnut (Juglans regia L.)

PubMed Central

Aradhya, Mallikarjuna; Ibrahimov, Zakir; Toktoraliev, Biimyrza; Maghradze, David; Musayev, Mirza; Bobokashvili, Zviadi; Preece, John E.

2017-01-01

The distribution and survival of trees during the last glacial maximum (LGM) has been of interest to paleoecologists, biogeographers, and geneticists. Ecological niche models that associate species occurrence and abundance with climatic variables are widely used to gain ecological and evolutionary insights and to predict species distributions over space and time. The present study deals with the glacial history of walnut to address questions related to past distributions through genetic analysis and ecological modeling of the present, LGM and Last Interglacial (LIG) periods. A maximum entropy method was used to project the current walnut distribution model on to the LGM (21–18 kyr BP) and LIG (130–116 kyr BP) climatic conditions. Model tuning identified the walnut data set filtered at 10 km spatial resolution as the best for modeling the current distribution and to hindcast past (LGM and LIG) distributions of walnut. The current distribution model predicted southern Caucasus, parts of West and Central Asia extending into South Asia encompassing northern Afghanistan, Pakistan, northwestern Himalayan region, and southwestern Tibet, as the favorable climatic niche matching the modern distribution of walnut. The hindcast of distributions suggested the occurrence of walnut during LGM was somewhat limited to southern latitudes from southern Caucasus, Central and South Asian regions extending into southwestern Tibet, northeastern India, Himalayan region of Sikkim and Bhutan, and southeastern China. Both CCSM and MIROC projections overlapped, except that MIROC projected a significant presence of walnut in the Balkan Peninsula during the LGM. In contrast, genetic analysis of the current walnut distribution suggested a much narrower area in northern Pakistan and the surrounding areas of Afghanistan, northwestern India, and southern Tajikistan as a plausible hotspot of diversity where walnut may have survived glaciations. Overall, the findings suggest that walnut perhaps survived the last glaciations in several refugia across a wide geographic area between 30° and 45° North latitude. However, humans probably played a significant role in the recent history and modern distribution of walnut. PMID:29023476

Genetic and ecological insights into glacial refugia of walnut (Juglans regia L.).

PubMed

Aradhya, Mallikarjuna; Velasco, Dianne; Ibrahimov, Zakir; Toktoraliev, Biimyrza; Maghradze, David; Musayev, Mirza; Bobokashvili, Zviadi; Preece, John E

2017-01-01

The distribution and survival of trees during the last glacial maximum (LGM) has been of interest to paleoecologists, biogeographers, and geneticists. Ecological niche models that associate species occurrence and abundance with climatic variables are widely used to gain ecological and evolutionary insights and to predict species distributions over space and time. The present study deals with the glacial history of walnut to address questions related to past distributions through genetic analysis and ecological modeling of the present, LGM and Last Interglacial (LIG) periods. A maximum entropy method was used to project the current walnut distribution model on to the LGM (21-18 kyr BP) and LIG (130-116 kyr BP) climatic conditions. Model tuning identified the walnut data set filtered at 10 km spatial resolution as the best for modeling the current distribution and to hindcast past (LGM and LIG) distributions of walnut. The current distribution model predicted southern Caucasus, parts of West and Central Asia extending into South Asia encompassing northern Afghanistan, Pakistan, northwestern Himalayan region, and southwestern Tibet, as the favorable climatic niche matching the modern distribution of walnut. The hindcast of distributions suggested the occurrence of walnut during LGM was somewhat limited to southern latitudes from southern Caucasus, Central and South Asian regions extending into southwestern Tibet, northeastern India, Himalayan region of Sikkim and Bhutan, and southeastern China. Both CCSM and MIROC projections overlapped, except that MIROC projected a significant presence of walnut in the Balkan Peninsula during the LGM. In contrast, genetic analysis of the current walnut distribution suggested a much narrower area in northern Pakistan and the surrounding areas of Afghanistan, northwestern India, and southern Tajikistan as a plausible hotspot of diversity where walnut may have survived glaciations. Overall, the findings suggest that walnut perhaps survived the last glaciations in several refugia across a wide geographic area between 30° and 45° North latitude. However, humans probably played a significant role in the recent history and modern distribution of walnut.

Limitations to the Use of Species-Distribution Models for Environmental-Impact Assessments in the Amazon.

PubMed

Carneiro, Lorena Ribeiro de A; Lima, Albertina P; Machado, Ricardo B; Magnusson, William E

2016-01-01

Species-distribution models (SDM) are tools with potential to inform environmental-impact studies (EIA). However, they are not always appropriate and may result in improper and expensive mitigation and compensation if their limitations are not understood by decision makers. Here, we examine the use of SDM for frogs that were used in impact assessment using data obtained from the EIA of a hydroelectric project located in the Amazon Basin in Brazil. The results show that lack of knowledge of species distributions limits the appropriate use of SDM in the Amazon region for most target species. Because most of these targets are newly described and their distributions poorly known, data about their distributions are insufficient to be effectively used in SDM. Surveys that are mandatory for the EIA are often conducted only near the area under assessment, and so models must extrapolate well beyond the sampled area to inform decisions made at much larger spatial scales, such as defining areas to be used to offset the negative effects of the projects. Using distributions of better-known species in simulations, we show that geographical-extrapolations based on limited information of species ranges often lead to spurious results. We conclude that the use of SDM as evidence to support project-licensing decisions in the Amazon requires much greater area sampling for impact studies, or, alternatively, integrated and comparative survey strategies, to improve biodiversity sampling. When more detailed distribution information is unavailable, SDM will produce results that generate uncertain and untestable decisions regarding impact assessment. In many cases, SDM is unlikely to be better than the use of expert opinion.

Limitations to the Use of Species-Distribution Models for Environmental-Impact Assessments in the Amazon

PubMed Central

Carneiro, Lorena Ribeiro de A.; Lima, Albertina P.; Machado, Ricardo B.; Magnusson, William E.

2016-01-01

Species-distribution models (SDM) are tools with potential to inform environmental-impact studies (EIA). However, they are not always appropriate and may result in improper and expensive mitigation and compensation if their limitations are not understood by decision makers. Here, we examine the use of SDM for frogs that were used in impact assessment using data obtained from the EIA of a hydroelectric project located in the Amazon Basin in Brazil. The results show that lack of knowledge of species distributions limits the appropriate use of SDM in the Amazon region for most target species. Because most of these targets are newly described and their distributions poorly known, data about their distributions are insufficient to be effectively used in SDM. Surveys that are mandatory for the EIA are often conducted only near the area under assessment, and so models must extrapolate well beyond the sampled area to inform decisions made at much larger spatial scales, such as defining areas to be used to offset the negative effects of the projects. Using distributions of better-known species in simulations, we show that geographical-extrapolations based on limited information of species ranges often lead to spurious results. We conclude that the use of SDM as evidence to support project-licensing decisions in the Amazon requires much greater area sampling for impact studies, or, alternatively, integrated and comparative survey strategies, to improve biodiversity sampling. When more detailed distribution information is unavailable, SDM will produce results that generate uncertain and untestable decisions regarding impact assessment. In many cases, SDM is unlikely to be better than the use of expert opinion. PMID:26784891

Impact of asymmetry in the total ozone distribution in Antarctic region to the South Ocean ecosystem

NASA Astrophysics Data System (ADS)

Kovalenok, S.; Evtushevsky, A.; Grytsai, A.; Milinevsky, G.

2009-04-01

Impact of asymmetry in the total ozone distribution in Antarctic region to South Ocean ecosystem is studied. The existence of the considerable zonal asymmetry in total ozone distribution over Antarctica observed last decades based on the satellite TOMS measurements in 1979-2005 due to existence of quasi-stationary planetary waves in a polar stratosphere. As was shown by authors earlier in the latitudinal interval of 55-75°S in Antarctic spring months (Sep-Nov) the region of zonal total ozone minimum experienced the systematic spatial drift to the east. In the same period a minimum and maximum of quasi-stationary wave in TOC distribution are located: minimum over the Antarctic Peninsula and Weddell Sea area, and maximum in the Ross Sea area. We expect that zonal asymmetry in total ozone distribution and its long-term spatial changes should impact to South Ocean ecosystem food chain, especially in primary level. The systematic eastern shift of the quasi-stationary minimum in ozone distribution over north Weddell Sea area should cause the increased UV radiation on sea surface in comparison to Ross Sea area, where the lack of UVR should exist in spring month. To study this influence the available data of phytoplankton distribution in South Ocean in 1997-2007 were analyzed. The results of analysis in connections with Antarctic Peninsula regional climate warming are discussed. The research was partly supported by project 06BF051-12 of the National Taras Shevchenko University of Kyiv.

Geophysical monitoring of a field-scale biostimulation pilot project

USGS Publications Warehouse

Lane, J.W.; Day-Lewis, F. D.; Casey, C.C.

2006-01-01

The USGS conducted a geophysical investigation in support of a U.S. Naval Facilities Engineering Command, Southern Division field-scale biostimulation pilot project at Anoka County Riverfront Park (ACP), downgradient of the Naval Industrial Reserve Ordnance Plant, Fridley, Minnesota. The goal of the pilot project is to evaluate subsurface injection of vegetable oil emulsion (VOE) to stimulate microbial degradation of chlorinated hydrocarbons. To monitor the emplacement and movement of the VOE and changes in water chemistry resulting from VOE dissolution and/or enhanced biological activity, the USGS acquired cross-hole radar zero-offset profiles, traveltime tomograms, and borehole geophysical logs during five site visits over 1.5 years. Analysis of pre- and postinjection data sets using petrophysical models developed to estimate VOE saturation and changes in total dissolved solids provides insights into the spatial and temporal distribution of VOE and ground water with altered chemistry. Radar slowness-difference tomograms and zero-offset slowness profiles indicate that the VOE remained close to the injection wells, whereas radar attenuation profiles and electromagnetic induction logs indicate that bulk electrical conductivity increased downgradient of the injection zone, diagnostic of changing water chemistry. Geophysical logs indicate that some screened intervals were located above or below zones of elevated dissolved solids; hence, the geophysical data provide a broader context for interpretation of water samples and evaluation of the biostimulation effort. Our results include (1) demonstration of field and data analysis methods for geophysical monitoring of VOE biostimulation and (2) site-specific insights into the spatial and temporal distributions of VOE at the ACP. ?? 2006 National Ground Water Association.

Geophysical monitoring of a field-scale biostimulation pilot project.

PubMed

Lane, John W; Day-Lewis, Frederick D; Casey, Clifton C

2006-01-01

The USGS conducted a geophysical investigation in support of a U.S. Naval Facilities Engineering Command, Southern Division field-scale biostimulation pilot project at Anoka County Riverfront Park (ACP), down-gradient of the Naval Industrial Reserve Ordnance Plant, Fridley, Minnesota. The goal of the pilot project is to evaluate subsurface injection of vegetable oil emulsion (VOE) to stimulate microbial degradation of chlorinated hydrocarbons. To monitor the emplacement and movement of the VOE and changes in water chemistry resulting from VOE dissolution and/or enhanced biological activity, the USGS acquired cross-hole radar zero-offset profiles, travel-time tomograms, and borehole geophysical logs during five site visits over 1.5 years. Analysis of pre- and postinjection data sets using petrophysical models developed to estimate VOE saturation and changes in total dissolved solids provides insights into the spatial and temporal distribution of VOE and ground water with altered chemistry. Radar slowness-difference tomograms and zero-offset slowness profiles indicate that the VOE remained close to the injection wells, whereas radar attenuation profiles and electromagnetic induction logs indicate that bulk electrical conductivity increased down-gradient of the injection zone, diagnostic of changing water chemistry. Geophysical logs indicate that some screened intervals were located above or below zones of elevated dissolved solids; hence, the geophysical data provide a broader context for interpretation of water samples and evaluation of the biostimulation effort. Our results include (1) demonstration of field and data analysis methods for geophysical monitoring of VOE biostimulation and (2) site-specific insights into the spatial and temporal distributions of VOE at the ACP.

The future demographic niche of a declining grassland bird fails to shift poleward in response to climate change

USGS Publications Warehouse

McCauley, Lisa A.; Ribic, Christine; Pomara, Lars Y.; Zuckerberg, Benjamin

2017-01-01

ContextTemperate grasslands and their dependent species are exposed to high variability in weather and climate due to the lack of natural buffers such as forests. Grassland birds are particularly vulnerable to this variability, yet have failed to shift poleward in response to recent climate change like other bird species in North America. However, there have been few studies examining the effect of weather on grassland bird demography and consequent influence of climate change on population persistence and distributional shifts.ObjectivesThe goal of this study was to estimate the vulnerability of Henslow’s Sparrow (Ammodramus henslowii), an obligate grassland bird that has been declining throughout much of its range, to past and future climatic variability.MethodsWe conducted a demographic meta-analysis from published studies and quantified the relationship between nest success rates and variability in breeding season climate. We projected the climate-demography relationships spatially, throughout the breeding range, and temporally, from 1981 to 2050. These projections were used to evaluate population dynamics by implementing a spatially explicit population model.ResultsWe uncovered a climate-demography linkage for Henslow’s Sparrow with summer precipitation, and to a lesser degree, temperature positively affecting nest success. We found that future climatic conditions—primarily changes in precipitation—will likely contribute to reduced population persistence and a southwestward range contraction.ConclusionsFuture distributional shifts in response to climate change may not always be poleward and assessing projected changes in precipitation is critical for grassland bird conservation and climate change adaptation.

Climate change is projected to reduce carrying capacity and redistribute species richness in North Pacific pelagic marine ecosystems.

PubMed

Woodworth-Jefcoats, Phoebe A; Polovina, Jeffrey J; Drazen, Jeffrey C

2017-03-01

Climate change is expected to impact all aspects of marine ecosystems, including fisheries. Here, we use output from a suite of 11 earth system models to examine projected changes in two ecosystem-defining variables: temperature and food availability. In particular, we examine projected changes in epipelagic temperature and, as a proxy for food availability, zooplankton density. We find that under RCP8.5, a high business-as-usual greenhouse gas scenario, increasing temperatures may alter the spatial distribution of tuna and billfish species richness across the North Pacific basin. Furthermore, warmer waters and declining zooplankton densities may act together to lower carrying capacity for commercially valuable fish by 2-5% per decade over the 21st century. These changes have the potential to significantly impact the magnitude, composition, and distribution of commercial fish catch across the pelagic North Pacific. Such changes will in turn ultimately impact commercial fisheries' economic value. Fishery managers should anticipate these climate impacts to ensure sustainable fishery yields and livelihoods. © 2016 John Wiley & Sons Ltd.

A neural network approach for image reconstruction in electron magnetic resonance tomography.

PubMed

Durairaj, D Christopher; Krishna, Murali C; Murugesan, Ramachandran

2007-10-01

An object-oriented, artificial neural network (ANN) based, application system for reconstruction of two-dimensional spatial images in electron magnetic resonance (EMR) tomography is presented. The standard back propagation algorithm is utilized to train a three-layer sigmoidal feed-forward, supervised, ANN to perform the image reconstruction. The network learns the relationship between the 'ideal' images that are reconstructed using filtered back projection (FBP) technique and the corresponding projection data (sinograms). The input layer of the network is provided with a training set that contains projection data from various phantoms as well as in vivo objects, acquired from an EMR imager. Twenty five different network configurations are investigated to test the ability of the generalization of the network. The trained ANN then reconstructs two-dimensional temporal spatial images that present the distribution of free radicals in biological systems. Image reconstruction by the trained neural network shows better time complexity than the conventional iterative reconstruction algorithms such as multiplicative algebraic reconstruction technique (MART). The network is further explored for image reconstruction from 'noisy' EMR data and the results show better performance than the FBP method. The network is also tested for its ability to reconstruct from limited-angle EMR data set.

Advances in Significance Testing for Cluster Detection

NASA Astrophysics Data System (ADS)

Coleman, Deidra Andrea

Over the past two decades, much attention has been given to data driven project goals such as the Human Genome Project and the development of syndromic surveillance systems. A major component of these types of projects is analyzing the abundance of data. Detecting clusters within the data can be beneficial as it can lead to the identification of specified sequences of DNA nucleotides that are related to important biological functions or the locations of epidemics such as disease outbreaks or bioterrorism attacks. Cluster detection techniques require efficient and accurate hypothesis testing procedures. In this dissertation, we improve upon the hypothesis testing procedures for cluster detection by enhancing distributional theory and providing an alternative method for spatial cluster detection using syndromic surveillance data. In Chapter 2, we provide an efficient method to compute the exact distribution of the number and coverage of h-clumps of a collection of words. This method involves defining a Markov chain using a minimal deterministic automaton to reduce the number of states needed for computation. We allow words of the collection to contain other words of the collection making the method more general. We use our method to compute the distributions of the number and coverage of h-clumps in the Chi motif of H. influenza.. In Chapter 3, we provide an efficient algorithm to compute the exact distribution of multiple window discrete scan statistics for higher-order, multi-state Markovian sequences. This algorithm involves defining a Markov chain to efficiently keep track of probabilities needed to compute p-values of the statistic. We use our algorithm to identify cases where the available approximation does not perform well. We also use our algorithm to detect unusual clusters of made free throw shots by National Basketball Association players during the 2009-2010 regular season. In Chapter 4, we give a procedure to detect outbreaks using syndromic surveillance data while controlling the Bayesian False Discovery Rate (BFDR). The procedure entails choosing an appropriate Bayesian model that captures the spatial dependency inherent in epidemiological data and considers all days of interest, selecting a test statistic based on a chosen measure that provides the magnitude of the maximumal spatial cluster for each day, and identifying a cutoff value that controls the BFDR for rejecting the collective null hypothesis of no outbreak over a collection of days for a specified region.We use our procedure to analyze botulism-like syndrome data collected by the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT).

A parallel-processing approach to computing for the geographic sciences; applications and systems enhancements

USGS Publications Warehouse

Crane, Michael; Steinwand, Dan; Beckmann, Tim; Krpan, Greg; Liu, Shu-Guang; Nichols, Erin; Haga, Jim; Maddox, Brian; Bilderback, Chris; Feller, Mark; Homer, George

2001-01-01

The overarching goal of this project is to build a spatially distributed infrastructure for information science research by forming a team of information science researchers and providing them with similar hardware and software tools to perform collaborative research. Four geographically distributed Centers of the U.S. Geological Survey (USGS) are developing their own clusters of low-cost, personal computers into parallel computing environments that provide a costeffective way for the USGS to increase participation in the high-performance computing community. Referred to as Beowulf clusters, these hybrid systems provide the robust computing power required for conducting information science research into parallel computing systems and applications.

State-and-transition simulation models: a framework for forecasting landscape change

USGS Publications Warehouse

Daniel, Colin; Frid, Leonardo; Sleeter, Benjamin M.; Fortin, Marie-Josée

2016-01-01

SummaryA wide range of spatially explicit simulation models have been developed to forecast landscape dynamics, including models for projecting changes in both vegetation and land use. While these models have generally been developed as separate applications, each with a separate purpose and audience, they share many common features.We present a general framework, called a state-and-transition simulation model (STSM), which captures a number of these common features, accompanied by a software product, called ST-Sim, to build and run such models. The STSM method divides a landscape into a set of discrete spatial units and simulates the discrete state of each cell forward as a discrete-time-inhomogeneous stochastic process. The method differs from a spatially interacting Markov chain in several important ways, including the ability to add discrete counters such as age and time-since-transition as state variables, to specify one-step transition rates as either probabilities or target areas, and to represent multiple types of transitions between pairs of states.We demonstrate the STSM method using a model of land-use/land-cover (LULC) change for the state of Hawai'i, USA. Processes represented in this example include expansion/contraction of agricultural lands, urbanization, wildfire, shrub encroachment into grassland and harvest of tree plantations; the model also projects shifts in moisture zones due to climate change. Key model output includes projections of the future spatial and temporal distribution of LULC classes and moisture zones across the landscape over the next 50 years.State-and-transition simulation models can be applied to a wide range of landscapes, including questions of both land-use change and vegetation dynamics. Because the method is inherently stochastic, it is well suited for characterizing uncertainty in model projections. When combined with the ST-Sim software, STSMs offer a simple yet powerful means for developing a wide range of models of landscape dynamics.

Structural sensitivity of x-ray Bragg projection ptychography to domain patterns in epitaxial thin films

DOE PAGES

Hruszkewycz, S. O.; Zhang, Q.; Holt, M. V.; ...

2016-10-04

Bragg projection ptychography (BPP) is a coherent diffraction imaging technique capable of mapping the spatial distribution of the Bragg structure factor in nanostructured thin films. Here, we show that, because these images are projections, the structural sensitivity of the resulting images depends on the film thickness and the aspect ratio and orientation of the features of interest and that image interpretation depends on these factors. Lastly, we model changes in contrast in the BPP reconstructions of simulated PbTiO 3 ferroelectric thin films with meandering 180° stripe domains as a function of film thickness, discuss their origin, and comment on themore » implication of these factors on the design of BPP experiments of general nanostructured films.« less

Role of the repartition of wetland breeding sites on the spatial distribution of Anopheles and Culex, human disease vectors in southern France.

PubMed

Cailly, Priscilla; Balenghien, Thomas; Ezanno, Pauline; Fontenille, Didier; Toty, Céline; Tran, Annelise

2011-05-06

In this study, carried out in the Camargue region (France), we combined entomological data with geomatic and modelling tools to assess whether the location of breeding sites may explain the spatial distribution of adult mosquitoes. The species studied are important and competent disease vectors in Europe: Culex modestus Ficalbi and Cx. pipiens Linnaeus (West Nile virus), Anopheles atroparvus Van Thiel, a former Plasmodium vector, and An. melanoon Hackett, competent to transmit Plasmodium.Using a logistic regression model, we first evaluated which land cover variables determined the presence of Culex and Anopheles larva. The resulting probability map of larval presence then was used to project the average probability of finding adults in a buffer area. This was compared to the actual number of adults collected, providing a quantitative assessment of adult dispersal ability for each species. The distribution of Cx. modestus and An. melanoon is mainly driven by the repartition of irrigated farm fields and reed beds, their specific breeding habitats. The presence of breeding sites explained the distribution of adults of both species. The buffer size, reflecting the adult dispersal ability, was 700 m for Cx. modestus and 1000 m for An. melanoon. The comparatively stronger correlation observed for Cx. modestus suggested that other factors may affect the distribution of adult An. melanoon. We did not find any association between Cx. pipiens larval presence and the biotope due to the species' ubiquist character. By applying the same method to different species, we highlighted different strengths of association between land cover (irrigated farm fields and reed beds), larval presence and adult population distribution.This paper demonstrates the power of geomatic tools to quantify the spatial organization of mosquito populations, and allows a better understanding of links between landcover, breeding habitats, presence of immature mosquito populations and adult distributions for different species.

Role of the repartition of wetland breeding sites on the spatial distribution of Anopheles and Culex, human disease vectors in Southern France

PubMed Central

2011-01-01

Background In this study, carried out in the Camargue region (France), we combined entomological data with geomatic and modelling tools to assess whether the location of breeding sites may explain the spatial distribution of adult mosquitoes. The species studied are important and competent disease vectors in Europe: Culex modestus Ficalbi and Cx. pipiens Linnaeus (West Nile virus), Anopheles atroparvus Van Thiel, a former Plasmodium vector, and An. melanoon Hackett, competent to transmit Plasmodium. Using a logistic regression model, we first evaluated which land cover variables determined the presence of Culex and Anopheles larva. The resulting probability map of larval presence then was used to project the average probability of finding adults in a buffer area. This was compared to the actual number of adults collected, providing a quantitative assessment of adult dispersal ability for each species. Results The distribution of Cx. modestus and An. melanoon is mainly driven by the repartition of irrigated farm fields and reed beds, their specific breeding habitats. The presence of breeding sites explained the distribution of adults of both species. The buffer size, reflecting the adult dispersal ability, was 700 m for Cx. modestus and 1000 m for An. melanoon. The comparatively stronger correlation observed for Cx. modestus suggested that other factors may affect the distribution of adult An. melanoon. We did not find any association between Cx. pipiens larval presence and the biotope due to the species' ubiquist character. Conclusion By applying the same method to different species, we highlighted different strengths of association between land cover (irrigated farm fields and reed beds), larval presence and adult population distribution. This paper demonstrates the power of geomatic tools to quantify the spatial organization of mosquito populations, and allows a better understanding of links between landcover, breeding habitats, presence of immature mosquito populations and adult distributions for different species. PMID:21548912

Temperature drives abundance fluctuations, but spatial dynamics is constrained by landscape configuration: Implications for climate-driven range shift in a butterfly.

PubMed

Fourcade, Yoan; Ranius, Thomas; Öckinger, Erik

2017-10-01

Prediction of species distributions in an altered climate requires knowledge on how global- and local-scale factors interact to limit their current distributions. Such knowledge can be gained through studies of spatial population dynamics at climatic range margins. Here, using a butterfly (Pyrgus armoricanus) as model species, we first predicted based on species distribution modelling that its climatically suitable habitats currently extend north of its realized range. Projecting the model into scenarios of future climate, we showed that the distribution of climatically suitable habitats may shift northward by an additional 400 km in the future. Second, we used a 13-year monitoring dataset including the majority of all habitat patches at the species northern range margin to assess the synergetic impact of temperature fluctuations and spatial distribution of habitat, microclimatic conditions and habitat quality, on abundance and colonization-extinction dynamics. The fluctuation in abundance between years was almost entirely determined by the variation in temperature during the species larval development. In contrast, colonization and extinction dynamics were better explained by patch area, between-patch connectivity and host plant density. This suggests that the response of the species to future climate change may be limited by future land use and how its host plants respond to climate change. It is, thus, probable that dispersal limitation will prevent P. armoricanus from reaching its potential future distribution. We argue that models of range dynamics should consider the factors influencing metapopulation dynamics, especially at the range edges, and not only broad-scale climate. It includes factors acting at the scale of habitat patches such as habitat quality and microclimate and landscape-scale factors such as the spatial configuration of potentially suitable patches. Knowledge of population dynamics under various environmental conditions, and the incorporation of realistic scenarios of future land use, appears essential to provide predictions useful for actions mitigating the negative effects of climate change. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

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

Kerisit, Sebastien N.; Gao, Fei; Xie, YuLong

This Final Report presents work carried out at Pacific Northwest National Laboratory (PNNL) under the project entitled “Validated Models for Radiation Response and Signal Generation in Scintillators” (Project number: PL10-Scin-theor-PD2Jf) and led by Drs. Fei Gao and Sebastien N. Kerisit. This project was divided into four tasks: 1) Electronic response functions (ab initio data model) 2) Electron-hole yield, variance, and spatial distribution 3) Ab initio calculations of information carrier properties 4) Transport of electron-hole pairs and scintillation efficiency Detailed information on the results obtained in each of the four tasks is provided in this Final Report. Furthermore, published peer-reviewed articlesmore » based on the work carried under this project are included in Appendix. This work was supported by the National Nuclear Security Administration, Office of Nuclear Nonproliferation Research and Development (DNN R&D/NA-22), of the U.S. Department of Energy (DOE).« less

Effects of geometrical structure on spatial distribution of thermal energy in two-dimensional triangular lattices

NASA Astrophysics Data System (ADS)

Liu, Yong-Yang; Xu, Yu-Liang; Liu, Zhong-Qiang; Li, Jing; Wang, Chun-Yang; Kong, Xiang-Mu

2018-07-01

Employing the correlation matrix technique, the spatial distribution of thermal energy in two-dimensional triangular lattices in equilibrium, interacting with linear springs, is studied. It is found that the spatial distribution of thermal energy varies with the included angle of the springs. In addition, the average thermal energy of the longer springs is lower. Springs with different included angle and length will lead to an inhomogeneous spatial distribution of thermal energy. This suggests that the spatial distribution of thermal energy is affected by the geometrical structure of the system: the more asymmetric the geometrical structure of the system is, the more inhomogeneous is the spatial distribution of thermal energy.

Ultrasound phase contrast thermal imaging with reflex transmission imaging methods in tissue phantoms

PubMed Central

Farny, Caleb H.; Clement, Gregory T.

2009-01-01

Thermal imaging measurements using ultrasound phase contrast have been performed in tissue phantoms heated with a focused ultrasound source. Back projection and reflex transmission imaging principles were employed to detect sound speed-induced changes in the phase caused by an increase in the temperature. The temperature was determined from an empirical relationship for the temperature dependence on sound speed. The phase contrast was determined from changes in the sound field measured with a hydrophone scan conducted before and during applied heating. The lengthy scanning routine used to mimic a large two-dimensional array required a steady-state temperature distribution within the phantom. The temperature distribution in the phantom was validated with magnetic resonance (MR) thermal imaging measurements. The peak temperature was found to agree within 1°C with MR and good agreement was found between the temperature profiles. The spatial resolution was 0.3 × 0.3 × 0.3 mm, comparing favorably with the 0.625 × 0.625 × 1.5 mm MR spatial resolution. PMID:19683380

[Water resource quality as related to economic activity and health patterns in Sonora, Mexico].

PubMed

Manzanares Rivera, José Luis

2016-01-01

The aim of this work is to analyze the spatial distribution of potential pollution pathways of water resources given the economic activity in the Mexican border state of Sonora and propose a regional distribution in relation to cancer mortality rates across the state. The methodology is based in an exploratory and inferential data analysis using two sources of primary data: wastewater discharge concessions registered in the Public Registry on Water Rights [Registro Público de Derechos de Agua] (REPDA) and the records generated by the National Health Information System [Sistema Nacional de Información en Salud] (SINAIS) in the period 1998-2011 based on the International Classification of Disease (ICD-10). The spatial concentration analysis allows for the identification of specific cancer mortality causes at the regional level. Results indicate that the projected adjustments to the regulation NOM-250-SSA1-2014, which controls a subset of pollutants common in mining activity surroundings, is a matter of regional concern.

A New Approach to X-ray Analysis of SNRs

NASA Astrophysics Data System (ADS)

Frank, Kari A.; Burrows, David; Dwarkadas, Vikram

2016-06-01

We present preliminary results of applying a novel analysis method, Smoothed Particle Inference (SPI), to XMM-Newton observations of SNR RCW 103 and Tycho. SPI is a Bayesian modeling process that fits a population of gas blobs (”smoothed particles”) such that their superposed emission reproduces the observed spatial and spectral distribution of photons. Emission-weighted distributions of plasma properties, such as abundances and temperatures, are then extracted from the properties of the individual blobs. This technique has important advantages over analysis techniques which implicitly assume that remnants are two-dimensional objects in which each line of sight encompasses a single plasma. By contrast, SPI allows superposition of as many blobs of plasma as are needed to match the spectrum observed in each direction, without the need to bin the data spatially. The analyses of RCW 103 and Tycho are part of a pilot study for the larger SPIES (Smoothed Particle Inference Exploration of SNRs) project, in which SPI will be applied to a sample of 12 bright SNRs.

Smoothed Particle Inference Analysis of SNR RCW 103

NASA Astrophysics Data System (ADS)

Frank, Kari A.; Burrows, David N.; Dwarkadas, Vikram

2016-04-01

We present preliminary results of applying a novel analysis method, Smoothed Particle Inference (SPI), to an XMM-Newton observation of SNR RCW 103. SPI is a Bayesian modeling process that fits a population of gas blobs ("smoothed particles") such that their superposed emission reproduces the observed spatial and spectral distribution of photons. Emission-weighted distributions of plasma properties, such as abundances and temperatures, are then extracted from the properties of the individual blobs. This technique has important advantages over analysis techniques which implicitly assume that remnants are two-dimensional objects in which each line of sight encompasses a single plasma. By contrast, SPI allows superposition of as many blobs of plasma as are needed to match the spectrum observed in each direction, without the need to bin the data spatially. This RCW 103 analysis is part of a pilot study for the larger SPIES (Smoothed Particle Inference Exploration of SNRs) project, in which SPI will be applied to a sample of 12 bright SNRs.

SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses.

PubMed

Brown, Jason L; Bennett, Joseph R; French, Connor M

2017-01-01

SDMtoolbox 2.0 is a software package for spatial studies of ecology, evolution, and genetics. The release of SDMtoolbox 2.0 allows researchers to use the most current ArcGIS software and MaxEnt software, and reduces the amount of time that would be spent developing common solutions. The central aim of this software is to automate complicated and repetitive spatial analyses in an intuitive graphical user interface. One core tenant facilitates careful parameterization of species distribution models (SDMs) to maximize each model's discriminatory ability and minimize overfitting. This includes carefully processing of occurrence data, environmental data, and model parameterization. This program directly interfaces with MaxEnt, one of the most powerful and widely used species distribution modeling software programs, although SDMtoolbox 2.0 is not limited to species distribution modeling or restricted to modeling in MaxEnt. Many of the SDM pre- and post-processing tools have 'universal' analogs for use with any modeling software. The current version contains a total of 79 scripts that harness the power of ArcGIS for macroecology, landscape genetics, and evolutionary studies. For example, these tools allow for biodiversity quantification (such as species richness or corrected weighted endemism), generation of least-cost paths and corridors among shared haplotypes, assessment of the significance of spatial randomizations, and enforcement of dispersal limitations of SDMs projected into future climates-to only name a few functions contained in SDMtoolbox 2.0. Lastly, dozens of generalized tools exists for batch processing and conversion of GIS data types or formats, which are broadly useful to any ArcMap user.

Spatial distribution of lacunarity of voxelized airborne LiDAR point clouds in various forest assemblages

NASA Astrophysics Data System (ADS)

Székely, Balázs; Kania, Adam; Standovár, Tibor; Heilmeier, Hermann

2015-04-01

Forest ecosystems have characteristic structure of features defined by various structural elements of different scales and vertical positions: shrub layers, understory vegetation, tree trunks, and branches. Furthermore in most of the cases there are superimposed structures in distributions (mosaic or island patterns) due to topography, soil variability, or even anthropogenic factors like past/present forest management activity. This multifaceted spatial context of the forests is relevant for many ecological issues, especially for maintaining forest biodiversity. Our aim in this study is twofold: (1) to quantify this structural variability laterally and vertically using lacunarity, and (2) to relate these results to relevant ecological features, i.e quantitatively described forest properties. Airborne LiDAR data of various quality and point density have been used for our study including a number of forested sites in Central and East Europe (partly Natura 2000 sites). The point clouds have been converted to voxel format and then converted to horizontal layers as images. These images were processed further for the lacunarity calculation. Areas of interest (AOIs) have been selected based on evaluation of the forested areas and auxiliary field information. The calculation has been performed for the AOIs for all available vertical data slices. The lacunarity function referring to a certain point and given vicinity varies horizontally and vertically, depending on the vegetation structure. Furthermore, the topography may also influence this property as the growth of plants, especially spacing and size of trees are influenced by the local topography and relief (e.g., slope, aspect). The comparisons of the flatland and hilly settings show interesting differences and the spatial patterns also vary differently. Because of the large amount of data resulting from these calculations, sophisticated methods are required to analyse the results. The large data amount then has been structured according to AOIs and relevant AOI pairs or small groups have been formed for comparative purposes. Change detection techniques have been applied to reveal fine differences. The spatial variation can be related to ecologically relevant forest characteristics. Data used in this study have been acquired in the framework of ChangeHabitat2 project (an IAPP Marie Curie Actions project of the European Union), in Hungarian-Slovakian Transnational Cooperation Programme 2007-2013, "Management of World Heritage Aggtelek Karst/Slovakian Karst Caves" (HUSK/1101/221/0180, Aggtelek NP). These studies were partly carried out in the project 'Multipurpose assessment serving forest biodiversity conservation in the Carpathian region of Hungary', Swiss-Hungarian Cooperation Programme (SH/4/13 Project). BS contributed as an Alexander von Humboldt Research Fellow.

Assessment of online public opinions on large infrastructure projects: A case study of the Three Gorges Project in China

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

Jiang, Hanchen, E-mail: jhc13@mails.tsinghua.edu.cn; Qiang, Maoshan, E-mail: qiangms@tsinghua.edu.cn; Lin, Peng, E-mail: celinpe@mail.tsinghua.edu.cn

Public opinion becomes increasingly salient in the ex post evaluation stage of large infrastructure projects which have significant impacts to the environment and the society. However, traditional survey methods are inefficient in collection and assessment of the public opinion due to its large quantity and diversity. Recently, Social media platforms provide a rich data source for monitoring and assessing the public opinion on controversial infrastructure projects. This paper proposes an assessment framework to transform unstructured online public opinions on large infrastructure projects into sentimental and topical indicators for enhancing practices of ex post evaluation and public participation. The framework usesmore » web crawlers to collect online comments related to a large infrastructure project and employs two natural language processing technologies, including sentiment analysis and topic modeling, with spatio-temporal analysis, to transform these comments into indicators for assessing online public opinion on the project. Based on the framework, we investigate the online public opinion of the Three Gorges Project on China's largest microblogging site, namely, Weibo. Assessment results present spatial-temporal distributions of post intensity and sentiment polarity, reveals major topics with different sentiments and summarizes managerial implications, for ex post evaluation of the world's largest hydropower project. The proposed assessment framework is expected to be widely applied as a methodological strategy to assess public opinion in the ex post evaluation stage of large infrastructure projects. - Highlights: • We developed a framework to assess online public opinion on large infrastructure projects with environmental impacts. • Indicators were built to assess post intensity, sentiment polarity and major topics of the public opinion. • We took the Three Gorges Project (TGP) as an example to demonstrate the effectiveness proposed framework. • We revealed spatial-temporal patterns of post intensity and sentiment polarity on the TGP. • We drew implications for a more in-depth understanding of the public opinion on large infrastructure projects.« less

The Spatial Scaling of Global Rainfall Extremes

NASA Astrophysics Data System (ADS)

Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

2013-12-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

Toward an operational tool to simulate green roof hydrological impact at the basin scale: a new version of the distributed rainfall-runoff model Multi-Hydro.

PubMed

Versini, Pierre-Antoine; Gires, Auguste; Tchinguirinskaia, Ioulia; Schertzer, Daniel

2016-10-01

Currently widespread in new urban projects, green roofs have shown a positive impact on urban runoff at the building scale: decrease and slow-down of the peak discharge, and decrease of runoff volume. The present work aims to study their possible impact at the catchment scale, more compatible with stormwater management issues. For this purpose, a specific module dedicated to simulating the hydrological behaviour of a green roof has been developed in the distributed rainfall-runoff model (Multi-Hydro). It has been applied on a French urban catchment where most of the building roofs are flat and assumed to accept the implementation of a green roof. Catchment responses to several rainfall events covering a wide range of meteorological situations have been simulated. The simulation results show green roofs can significantly reduce runoff volume and the magnitude of peak discharge (up to 80%) depending on the rainfall event and initial saturation of the substrate. Additional tests have been made to assess the susceptibility of this response regarding both spatial distributions of green roofs and precipitation. It appears that the total area of greened roofs is more important than their locations. On the other hand, peak discharge reduction seems to be clearly dependent on spatial distribution of precipitation.

Three-dimensional hydrogeological modelling application to the Alverà mudslide (Cortina d'Ampezzo, Italy)

NASA Astrophysics Data System (ADS)

Bonomi, Tullia; Cavallin, Angelo

1999-10-01

Within the framework of Geographic Information System (GIS), the distributed three-dimensional groundwater model MODFLOW has been applied to evaluate the groundwater processes of the hydrogeological system in the Alverà mudslide (Cortina d'Ampezzo, Italy; test site in the TESLEC Project of the European Union). The application of this model has permitted an analysis of the spatial distribution of the structure (DTM and landslide bottom) and the mass transfer elements of the hydrogeological system. The field survey suggested zoning the area on the basis of the recharge, groundwater fluctuation and drainage system. For each zone, a hydraulic conductivity value to simulate the different recharge and the drainage responses has been assigned. The effect of rainfall infiltration into the ground and its effect on the groundwater table, with different intensity related to different time periods, have been simulated to reproduce the real condition of the area. The applied model can simulate the positive fluctuations of the water table on the whole landslide, with a different response of the hydrogeological system in each zone. The spatial simulated water level distribution is in accordance with the real one, with very small difference between them. The application of distributed three-dimensional models, within the framework of GIS, is an approach which permits data to be continually updated, standardised and integrated.

Distribution of electron traps in SiO2/HfO2 nMOSFET

NASA Astrophysics Data System (ADS)

Xiao-Hui, Hou; Xue-Feng, Zheng; Ao-Chen, Wang; Ying-Zhe, Wang; Hao-Yu, Wen; Zhi-Jing, Liu; Xiao-Wei, Li; Yin-He, Wu

2016-05-01

In this paper, the principle of discharge-based pulsed I-V technique is introduced. By using it, the energy and spatial distributions of electron traps within the 4-nm HfO2 layer have been extracted. Two peaks are observed, which are located at ΔE ˜ -1.0 eV and -1.43 eV, respectively. It is found that the former one is close to the SiO2/HfO2 interface and the latter one is close to the gate electrode. It is also observed that the maximum discharge time has little effect on the energy distribution. Finally, the impact of electrical stress on the HfO2 layer is also studied. During stress, no new electron traps and interface states are generated. Meanwhile, the electrical stress also has no impact on the energy and spatial distribution of as-grown traps. The results provide valuable information for theoretical modeling establishment, material assessment, and reliability improvement for advanced semiconductor devices. Project supported by the National Natural Science Foundation of China (Grant Nos. 61334002, 61106106, and 61474091), the New Experiment Development Funds for Xidian University, China (Grant No. SY1434), and the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry, China (Grant No. JY0600132501).

Recent and future rainfall erosivity on the territory of the Czech Republic

NASA Astrophysics Data System (ADS)

Krasa, Josef; Stredova, Hana; Stepanek, Petr; Hanel, Martin; Dostal, Tomas; Novotny, Ivan

2015-04-01

Water erosion is a main factor of degradation of soils used for agriculture in the Czech Republic. For landscape conservation purposes the soil erosion risk is defined here mostly by USLE (Wischmeier and Smith, 1978). Within USLE the precipitation impact on erosion is a function of rainfall kinetic energy and intensity represented by R-factor. In the Czech Republic historically and recently several research teams have analyzed rainfall data to assess R-factor. Till now not many European countries have performed detailed spatially distributed analyses of rain erosivities. Most studies use only simplified methods based on long-term rainfall averages or databases of only several station-datasets. The most recent study on rainfall erosivity spatial distribution over the Czech Republic was based on digital rain gauge data from automatic stations of the Czech Hydrometeorogical Institute. The erosive rains were derived from continuous 1 minute step 10-year rainfall data (2003-2012) from 245 stations. Based on the research recent annual R-factor values in the stations vary from 37 to 239 [N.h-1] (values over 100 are located in mountain regions with minimum of agricultural land). Average value is 69 [N.h-1.year-1]. For the Czech Republic the future prediction is based on 10km resolution ALADIN/CZ regional climate model. Within the EU FP6 project CECILIA it was coupled with GCM ARPEGE to provide a projection of future climate in two time slices, 2021-2050 and 2071-2100, according to the IPCC A1B emission scenario. Daily precipitation volumes and percentiles of maximal events allowed authors to develop R-factor maps of present and future scenarios. Based on the analyses we can conclude that average value for the whole territory of the Czech Republic will remain close to 70 [N.h-1.year-1] or even decrease for 2071-2100, but we can expect significant changes (30-40 % rise or decrease) for several large agricultural regions (eg. Southern Moravia). These changes will have impact on soil erosion dynamics of the specific areas. Details on the spatial distribution of recent and future rain erosivities over the Czech Republic and the consequences for the erosion risk will be presented. The paper was prepared within the projects NAZV QJ1230056 and BV VG 20122015092.

Combining dispersal, landscape connectivity and habitat suitability to assess climate-induced changes in the distribution of Cunningham’s skink, Egernia cunninghami

PubMed Central

Stow, Adam J.; Baumgartner, John B.; Beaumont, Linda J.

2017-01-01

The ability of species to track their climate niche is dependent on their dispersal potential and the connectivity of the landscape matrix linking current and future suitable habitat. However, studies modeling climate-driven range shifts rarely address the movement of species across landscapes realistically, often assuming “unlimited” or “no” dispersal. Here, we incorporate dispersal rate and landscape connectivity with a species distribution model (Maxent) to assess the extent to which the Cunningham’s skink (Egernia cunninghami) may be capable of tracking spatial shifts in suitable habitat as climate changes. Our model was projected onto four contrasting, but equally plausible, scenarios describing futures that are (relative to now) hot/wet, warm/dry, hot/with similar precipitation and warm/wet, at six time horizons with decadal intervals (2020–2070) and at two spatial resolutions: 1 km and 250 m. The size of suitable habitat was projected to decline 23–63% at 1 km and 26–64% at 250 m, by 2070. Combining Maxent output with the dispersal rate of the species and connectivity of the intervening landscape matrix showed that most current populations in regions projected to become unsuitable in the medium to long term, will be unable to shift the distance necessary to reach suitable habitat. In particular, numerous populations currently inhabiting the trailing edge of the species’ range are highly unlikely to be able to disperse fast enough to track climate change. Unless these populations are capable of adaptation they are likely to be extirpated. We note, however, that the core of the species distribution remains suitable across the broad spectrum of climate scenarios considered. Our findings highlight challenges faced by philopatric species and the importance of adaptation for the persistence of peripheral populations under climate change. PMID:28873398

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

Batiste, Merida; Bentz, Misty C.; Manne-Nicholas, Emily R.

We present new bulge stellar velocity dispersion measurements for 10 active galaxies with secure M {sub BH} determinations from reverberation mapping. These new velocity dispersion measurements are based on spatially resolved kinematics from integral-field (IFU) spectroscopy. In all but one case, the field of view of the IFU extends beyond the effective radius of the galaxy, and in the case of Mrk 79 it extends to almost one half the effective radius. This combination of spatial resolution and field of view allows for secure determinations of stellar velocity dispersion within the effective radius for all 10 target galaxies. Spatially resolvedmore » maps of the first ( V ) and second ( σ {sub ⋆}) moments of the line of sight velocity distribution indicate the presence of kinematic substructure in most cases. In future projects we plan to explore methods of correcting for the effects of kinematic substructure in the derived bulge stellar velocity dispersion measurements.« less

The BRAVE Program. I. Improved Bulge Stellar Velocity Dispersion Estimates for a Sample of Active Galaxies

NASA Astrophysics Data System (ADS)

Batiste, Merida; Bentz, Misty C.; Manne-Nicholas, Emily R.; Onken, Christopher A.; Bershady, Matthew A.

2017-02-01

We present new bulge stellar velocity dispersion measurements for 10 active galaxies with secure MBH determinations from reverberation mapping. These new velocity dispersion measurements are based on spatially resolved kinematics from integral-field (IFU) spectroscopy. In all but one case, the field of view of the IFU extends beyond the effective radius of the galaxy, and in the case of Mrk 79 it extends to almost one half the effective radius. This combination of spatial resolution and field of view allows for secure determinations of stellar velocity dispersion within the effective radius for all 10 target galaxies. Spatially resolved maps of the first (V) and second (σ⋆) moments of the line of sight velocity distribution indicate the presence of kinematic substructure in most cases. In future projects we plan to explore methods of correcting for the effects of kinematic substructure in the derived bulge stellar velocity dispersion measurements.

The Application of NASA Technology to Public Health

NASA Technical Reports Server (NTRS)

Rickman, Douglas L.; Watts, C.

2007-01-01

NASA scientists have a history of applying technologies created to handle satellite data to human health at various spatial scales. Scientists are now engaged in multiple public health application projects that integrate NASA satellite data with measures of public health. Such integration requires overcoming disparities between the environmental and the health data. Ground based sensors, satellite imagery, model outputs and other environmental sources have inconsistent spatial and temporal distributions. The MSFC team has recognized the approach used by environmental scientists to fill in the empty places can also be applied to outcomes, exposures and similar data. A revisit to the classic epidemiology study of 1854 using modern day surface modeling and GIS technology, demonstrates how spatial technology can enhance and change the future of environmental epidemiology. Thus, NASA brings to public health, not just a set of data, but an innovative way of thinking about the data.

Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750

Spatial distribution of traffic in a cellular mobile data network

NASA Astrophysics Data System (ADS)

Linnartz, J. P. M. G.

1987-02-01

The use of integral transforms of the probability density function for the received power to analyze the relation between the spatial distributions of offered and throughout packet traffic in a mobile radio network with Rayleigh fading channels and ALOHA multiple access was assessed. A method to obtain the spatial distribution of throughput traffic from a prescribed spatial distribution of offered traffic is presented. Incoherent and coherent addition of interference signals is considered. The channel behavior for heavy traffic loads is studied. In both the incoherent and coherent case, the spatial distribution of offered traffic required to ensure a prescribed spatially uniform throughput is synthesized numerically.

Tropical cyclone genesis potential index over the western North Pacific simulated by CMIP5 models

NASA Astrophysics Data System (ADS)

Song, Yajuan; Wang, Lei; Lei, Xiaoyan; Wang, Xidong

2015-11-01

Tropical cyclone (TC) genesis over the western North Pacific (WNP) is analyzed using 23 CMIP5 (Coupled Model Intercomparison Project Phase 5) models and reanalysis datasets. The models are evaluated according to TC genesis potential index (GPI). The spatial and temporal variations of the GPI are first calculated using three atmospheric reanalysis datasets (ERA-Interim, NCEP/NCAR Reanalysis-1, and NCEP/DOE Reanalysis-2). Spatial distributions of July-October-mean TC frequency based on the GPI from ERA-interim are more consistent with observed ones derived from IBTrACS global TC data. So, the ERA-interim reanalysis dataset is used to examine the CMIP5 models in terms of reproducing GPI during the period 1982-2005. Although most models possess deficiencies in reproducing the spatial distribution of the GPI, their multimodel ensemble (MME) mean shows a reasonable climatological GPI pattern characterized by a high GPI zone along 20°N in the WNP. There was an upward trend of TC genesis frequency during 1982 to 1998, followed by a downward trend. Both MME results and reanalysis data can represent a robust increasing trend during 1982-1998, but the models cannot simulate the downward trend after 2000. Analysis based on future projection experiments shows that the GPI exhibits no significant change in the first half of the 21st century, and then starts to decrease at the end of the 21st century under the representative concentration pathway (RCP) 2.6 scenario. Under the RCP8.5 scenario, the GPI shows an increasing trend in the vicinity of 20°N, indicating more TCs could possibly be expected over the WNP under future global warming.

Crop connectivity under climate change: future environmental and geographic risks of potato late blight in Scotland.

PubMed

Skelsey, Peter; Cooke, David E L; Lynott, James S; Lees, Alison K

2016-11-01

The impact of climate change on dispersal processes is largely ignored in risk assessments for crop diseases, as inoculum is generally assumed to be ubiquitous and nonlimiting. We suggest that consideration of the impact of climate change on the connectivity of crops for inoculum transmission may provide additional explanatory and predictive power in disease risk assessments, leading to improved recommendations for agricultural adaptation to climate change. In this study, a crop-growth model was combined with aerobiological models and a newly developed infection risk model to provide a framework for quantifying the impact of future climates on the risk of disease occurrence and spread. The integrated model uses standard meteorological variables and can be easily adapted to various crop pathosystems characterized by airborne inoculum. In a case study, the framework was used with data defining the spatial distribution of potato crops in Scotland and spatially coherent, probabilistic climate change data to project the future connectivity of crop distributions for Phytophthora infestans (causal agent of potato late blight) inoculum and the subsequent risk of infection. Projections and control recommendations are provided for multiple combinations of potato cultivar and CO 2 emissions scenario, and temporal and spatial averaging schemes. Overall, we found that relative to current climatic conditions, the risk of late blight will increase in Scotland during the first half of the potato growing season and decrease during the second half. To guide adaptation strategies, we also investigated the potential impact of climate change-driven shifts in the cropping season. Advancing the start of the potato growing season by 1 month proved to be an effective strategy from both an agronomic and late blight management perspective. © 2016 John Wiley & Sons Ltd.

Requirements for future development of small scale rainfall simulators

NASA Astrophysics Data System (ADS)

Iserloh, Thomas; Ries, Johannes B.; Seeger, Manuel

2013-04-01

Rainfall simulation with small scale simulators is a method used worldwide to assess the generation of overland flow, soil erosion, infiltration and interrelated processes such as soil sealing, crusting, splash and redistribution of solids and solutes. Following the outcomes of the project "Comparability of simulation results of different rainfall simulators as input data for soil erosion modelling (Deutsche Forschungsgemeinschaft - DFG, Project No. Ri 835/6-1)" and the "International Rainfall Simulator Workshop 2011" in Trier, the necessity for further technical improvements of simulators and strategies towards an adaption of designs and methods becomes obvious. Uniform measurements of artificially generated rainfall and comparative measurements on a prepared bare fallow with rainfall simulators used by European research groups showed limitations of the comparability of the results. The following requirements, essential for small portable rainfall simulators, were identified: (I) Low and efficient water consumption for use in areas with water shortage, (II) easy handling and control of test conditions, (III) homogeneous spatial rainfall distribution, (IV) best possible drop spectrum (physically), (V) reproducibility and knowledge of spatial distribution and drop spectrum, (VI) easy and fast training of operators to obtain reproducible experiments and (VII) good mobility and easy installation for use in remote areas and in regions where highly erosive rainfall events are rare or irregular. The presentation discusses possibilities for a common use of identical plot designs, rainfall intensities and nozzles.

The RINGS Survey. III. Medium-resolution Hα Fabry–Pérot Kinematic Data Set

NASA Astrophysics Data System (ADS)

Mitchell, Carl J.; Sellwood, J. A.; Williams, T. B.; Spekkens, Kristine; Kuzio de Naray, Rachel; Bixel, Alex

2018-03-01

The distributions of stars, gas, and dark matter in disk galaxies provide important constraints on galaxy formation models, particularly on small spatial scales (<1 kpc). We have designed the RSS Imaging spectroscopy Nearby Galaxy Survey (RINGS) to target a sample of 19 nearby spiral galaxies. For each of these galaxies, we obtain and model Hα and H I 21 cm spectroscopic data as well as multi-band photometric data. We intend to use these models to explore the underlying structure and evolution of these galaxies in a cosmological context, as well as whether the predictions of ΛCDM are consistent with the mass distributions of these galaxies. In this paper, we present spectroscopic imaging data for 14 of the RINGS galaxies observed with the medium spectral resolution Fabry–Pérot etalon on the Southern African Large Telescope. From these observations, we derive high spatial resolution line-of-sight velocity fields of the Hα line of excited hydrogen, as well as maps and azimuthally averaged profiles of the integrated Hα and [N II] emission and oxygen abundances. We then model these kinematic maps with axisymmetric models, from which we extract rotation curves and projection geometries for these galaxies. We show that our derived rotation curves agree well with other determinations, and the similarity of the projection angles with those derived from our photometric images argues against these galaxies having intrinsically oval disks.

Extreme Temperature Exceedances Change more Rapidly Under Future Warming in Regions of non-Gaussian Short Temperature Distribution Tails

NASA Astrophysics Data System (ADS)

Loikith, P. C.; Neelin, J. D.; Meyerson, J.

2017-12-01

Regions of shorter-than-Gaussian warm and cold side temperature distribution tails are shown to occur in spatially coherent patterns in the current climate. Under such conditions, warming may be manifested in more complex ways than if the underlying distribution were close to Gaussian. For example, under a uniform warm shift, the simplest prototype for future warming, a location with a short warm side tail would experience a greater increase in extreme warm exceedances compared to if the distribution were Gaussian. Similarly, for a location with a short cold side tail, a uniform warm shift would result in a rapid decrease in extreme cold exceedances. Both scenarios carry major societal and environmental implications including but not limited to negative impacts on human and ecosystem health, agriculture, and the economy. It is therefore important for climate models to be able to realistically reproduce short tails in simulations of historical climate in order to boost confidence in projections of future temperature extremes. Overall, climate models contributing to the fifth phase of the Coupled Model Intercomparison Project capture many of the principal observed regions of short tails. This suggests the underlying dynamics and physics occur on scales resolved by the models, and helps build confidence in model projections of extremes. Furthermore, most GCMs show more rapid changes in exceedances of extreme temperature thresholds in regions of short tails. Results therefore suggest that the shape of the tails of the underlying temperature distribution is an indicator of how rapidly a location will experience changes to extreme temperature occurrence under future warming.

Particle size distribution of the stratospheric aerosol from SCIAMACHY limb measurements

NASA Astrophysics Data System (ADS)

Rozanov, Alexei; Malinina, Elizaveta; Bovensmann, Heinrich; Burrows, John

2017-04-01

A crucial role of the stratospheric aerosols for the radiative budget of the Earth's atmosphere and the consequences for the climate change are widely recognized. A reliable knowledge on physical and optical properties of the stratospheric aerosols as well as on their vertical and spatial distributing is a key issue to assure a proper initialization and running conditions for climate models. On a global scale this information can only be gained from space borne measurements. While a series of past, present and future instruments provide extensive date sets of such aerosol characteristics as extinction coefficient or backscattering ratio, information on a size distribution of the stratospheric aerosols is sparse. One of the important sources on vertically and spatially resolved information on the particle size distribution of stratospheric aerosols is provided by space borne measurements of the scattered solar light in limb viewing geometry performed in visible, near-infrared and short-wave infrared spectral ranges. SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) instrument operated on the European satellite Envisat from 2002 to 2102 was capable of providing spectral information needed to retrieve parameters of aerosol particle size distributions. In this presentation we discuss the retrieval method, present first validation results with SAGE II data and analyze first data sets of stratospheric aerosol particle size distribution parameters obtained from SCIAMACHY limb measurements. The research work was performed in the framework of ROMIC (Role of the middle atmosphere in climate) project.

Comparative ecology of widely distributed pelagic fish species in the North Atlantic: Implications for modelling climate and fisheries impacts

NASA Astrophysics Data System (ADS)

Trenkel, V. M.; Huse, G.; MacKenzie, B. R.; Alvarez, P.; Arrizabalaga, H.; Castonguay, M.; Goñi, N.; Grégoire, F.; Hátún, H.; Jansen, T.; Jacobsen, J. A.; Lehodey, P.; Lutcavage, M.; Mariani, P.; Melvin, G. D.; Neilson, J. D.; Nøttestad, L.; Óskarsson, G. J.; Payne, M. R.; Richardson, D. E.; Senina, I.; Speirs, D. C.

2014-12-01

This paper reviews the current knowledge on the ecology of widely distributed pelagic fish stocks in the North Atlantic basin with emphasis on their role in the food web and the factors determining their relationship with the environment. We consider herring (Clupea harengus), mackerel (Scomber scombrus), capelin (Mallotus villosus), blue whiting (Micromesistius poutassou), and horse mackerel (Trachurus trachurus), which have distributions extending beyond the continental shelf and predominantly occur on both sides of the North Atlantic. We also include albacore (Thunnus alalunga), bluefin tuna (Thunnus thynnus), swordfish (Xiphias gladius), and blue marlin (Makaira nigricans), which, by contrast, show large-scale migrations at the basin scale. We focus on the links between life history processes and the environment, horizontal and vertical distribution, spatial structure and trophic role. Many of these species carry out extensive migrations from spawning grounds to nursery and feeding areas. Large oceanographic features such as the North Atlantic subpolar gyre play an important role in determining spatial distributions and driving variations in stock size. Given the large biomasses of especially the smaller species considered here, these stocks can exert significant top-down pressures on the food web and are important in supporting higher trophic levels. The review reveals commonalities and differences between the ecology of widely distributed pelagic fish in the NE and NW Atlantic basins, identifies knowledge gaps and modelling needs that the EURO-BASIN project attempts to address.

Spatial analysis techniques applied to uranium prospecting in Chihuahua State, Mexico

NASA Astrophysics Data System (ADS)

Hinojosa de la Garza, Octavio R.; Montero Cabrera, María Elena; Sanín, Luz H.; Reyes Cortés, Manuel; Martínez Meyer, Enrique

2014-07-01

To estimate the distribution of uranium minerals in Chihuahua, the advanced statistical model "Maximun Entropy Method" (MaxEnt) was applied. A distinguishing feature of this method is that it can fit more complex models in case of small datasets (x and y data), as is the location of uranium ores in the State of Chihuahua. For georeferencing uranium ores, a database from the United States Geological Survey and workgroup of experts in Mexico was used. The main contribution of this paper is the proposal of maximum entropy techniques to obtain the mineral's potential distribution. For this model were used 24 environmental layers like topography, gravimetry, climate (worldclim), soil properties and others that were useful to project the uranium's distribution across the study area. For the validation of the places predicted by the model, comparisons were done with other research of the Mexican Service of Geological Survey, with direct exploration of specific areas and by talks with former exploration workers of the enterprise "Uranio de Mexico". Results. New uranium areas predicted by the model were validated, finding some relationship between the model predictions and geological faults. Conclusions. Modeling by spatial analysis provides additional information to the energy and mineral resources sectors.

Distributed Visualization Project

NASA Technical Reports Server (NTRS)

Craig, Douglas; Conroy, Michael; Kickbusch, Tracey; Mazone, Rebecca

2016-01-01

Distributed Visualization allows anyone, anywhere to see any simulation at any time. Development focuses on algorithms, software, data formats, data systems and processes to enable sharing simulation-based information across temporal and spatial boundaries without requiring stakeholders to possess highly-specialized and very expensive display systems. It also introduces abstraction between the native and shared data, which allows teams to share results without giving away proprietary or sensitive data. The initial implementation of this capability is the Distributed Observer Network (DON) version 3.1. DON 3.1 is available for public release in the NASA Software Store (https://software.nasa.gov/software/KSC-13775) and works with version 3.0 of the Model Process Control specification (an XML Simulation Data Representation and Communication Language) to display complex graphical information and associated Meta-Data.

Design of two-DMD based zoom MW and LW dual-band IRSP using pixel fusion

NASA Astrophysics Data System (ADS)

Pan, Yue; Xu, Xiping; Qiao, Yang

2018-06-01

In order to test the anti-jamming ability of mid-wave infrared (MWIR) and long-wave infrared (LWIR) dual-band imaging system, a zoom mid-wave (MW) and long-wave (LW) dual-band infrared scene projector (IRSP) based on two-digital micro-mirror device (DMD) was designed by using a projection method of pixel fusion. Two illumination systems, which illuminate the two DMDs directly with Kohler telecentric beam respectively, were combined with projection system by a spatial layout way. The distances of projection entrance pupil and illumination exit pupil were also analyzed separately. MWIR and LWIR virtual scenes were generated respectively by two DMDs and fused by a dichroic beam combiner (DBC), resulting in two radiation distributions in projected image. The optical performance of each component was evaluated by ray tracing simulations. Apparent temperature and image contrast were demonstrated by imaging experiments. On the basis of test and simulation results, the aberrations of optical system were well corrected, and the quality of projected image meets test requirements.

Development of an emittance meter and off-line measurements for the SPES project

NASA Astrophysics Data System (ADS)

Montano, Jacobo; Vasquez, Jesus; Andrighetto, Aberto; Poggi, Marco; Bassato, Giorgio; Boscagli, Lucia; Prete, Gianfranco; Conforto, Nicola

2012-02-01

In the framework of the Selective Production of Exotic Species (SPES) project, an emittance meter has been designed and constructed to determine the ion sources operational characteristics. This instrument allows scanning the beam in two orthogonal planes establishing the distribution of the beam spatial density as well as the particles directions. The controls of the scanning sequence and the data collection during the measurements are performed by an appropriated electronic unit. The collected data is then analyzed and the twiss parameters are determined including the emittance for both planes under scrutiny. Finally a user friendly interface is developed that allows a general user to perform the mentioned tasks.

Malaria vectors in South America: current and future scenarios.

PubMed

Laporta, Gabriel Zorello; Linton, Yvonne-Marie; Wilkerson, Richard C; Bergo, Eduardo Sterlino; Nagaki, Sandra Sayuri; Sant'Ana, Denise Cristina; Sallum, Maria Anice Mureb

2015-08-19

Malaria remains a significant public health issue in South America. Future climate change may influence the distribution of the disease, which is dependent on the distribution of those Anopheles mosquitoes competent to transmit Plasmodium falciparum. Herein, predictive niche models of the habitat suitability for P. falciparum, the current primary vector Anopheles darlingi and nine other known and/or potential vector species of the Neotropical Albitarsis Complex, were used to document the current situation and project future scenarios under climate changes in South America in 2070. To build each ecological niche model, we employed topography, climate and biome, and the currently defined distribution of P. falciparum, An. darlingi and nine species comprising the Albitarsis Complex in South America. Current and future (i.e., 2070) distributions were forecast by projecting the fitted ecological niche model onto the current environmental situation and two scenarios of simulated climate change. Statistical analyses were performed between the parasite and each vector in both the present and future scenarios to address potential vector roles in the dynamics of malaria transmission. Current distributions of malaria vector species were associated with that of P. falciparum, confirming their role in transmission, especially An. darlingi, An. marajoara and An. deaneorum. Projected climate changes included higher temperatures, lower water availability and biome modifications. Regardless of future scenarios considered, the geographic distribution of P. falciparum was exacerbated in 2070 South America, with the distribution of the pathogen covering 35-46% of the continent. As the current primary vector An. darlingi showed low tolerance for drier environments, the projected climate change would significantly reduce suitable habitat, impacting both its distribution and abundance. Conversely, climate generalist members of the Albitarsis Complex showed significant spatial and temporal expansion potential in 2070, and we conclude these species will become more important in the dynamics of malaria transmission in South America. Our data suggest that climate and landscape effects will elevate the importance of members of the Albitarsis Complex in malaria transmission in South America in 2070, highlighting the need for further studies addressing the bionomics, ecology and behaviours of the species comprising the Albitarsis Complex.

Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images.

PubMed

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

2018-02-01

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

Spatial fuel data products of the LANDFIRE Project

Treesearch

Matt Reeves; Kevin C. Ryan; Matthew G. Rollins; Thomas G. Thompson

2009-01-01

The Landscape Fire and Resource Management Planning Tools (LANDFIRE) Project is mapping wildland fuels, vegetation, and fire regime characteristics across the United States. The LANDFIRE project is unique because of its national scope, creating an integrated product suite at 30-m spatial resolution and complete spatial coverage of all lands within the 50...

Geologic database for digital geology of California, Nevada, and Utah: an application of the North American Data Model

USGS Publications Warehouse

Bedford, David R.; Ludington, Steve; Nutt, Constance M.; Stone, Paul A.; Miller, David M.; Miller, Robert J.; Wagner, David L.; Saucedo, George J.

2003-01-01

The USGS is creating an integrated national database for digital state geologic maps that includes stratigraphic, age, and lithologic information. The majority of the conterminous 48 states have digital geologic base maps available, often at scales of 1:500,000. This product is a prototype, and is intended to demonstrate the types of derivative maps that will be possible with the national integrated database. This database permits the creation of a number of types of maps via simple or sophisticated queries, maps that may be useful in a number of areas, including mineral-resource assessment, environmental assessment, and regional tectonic evolution. This database is distributed with three main parts: a Microsoft Access 2000 database containing geologic map attribute data, an Arc/Info (Environmental Systems Research Institute, Redlands, California) Export format file containing points representing designation of stratigraphic regions for the Geologic Map of Utah, and an ArcView 3.2 (Environmental Systems Research Institute, Redlands, California) project containing scripts and dialogs for performing a series of generalization and mineral resource queries. IMPORTANT NOTE: Spatial data for the respective stage geologic maps is not distributed with this report. The digital state geologic maps for the states involved in this report are separate products, and two of them are produced by individual state agencies, which may be legally and/or financially responsible for this data. However, the spatial datasets for maps discussed in this report are available to the public. Questions regarding the distribution, sale, and use of individual state geologic maps should be sent to the respective state agency. We do provide suggestions for obtaining and formatting the spatial data to make it compatible with data in this report. See section ‘Obtaining and Formatting Spatial Data’ in the PDF version of the report.

Spatial patterns of distribution and abundance of Harrisia portoricensis, an endangered Caribbean cactus

Treesearch

J. Rojas-Sandoval; E. J. Melendez-Ackerman; NO-VALUE

2013-01-01

Aims The spatial distribution of biotic and abiotic factors may play a dominant role in determining the distribution and abundance of plants in arid and semiarid environments. In this study, we evaluated how spatial patterns of microhabitat variables and the degree of spatial dependence of these variables influence the distribution and abundance of the endangered...

[Spatial distribution pattern of Chilo suppressalis analyzed by classical method and geostatistics].

PubMed

Yuan, Zheming; Fu, Wei; Li, Fangyi

2004-04-01

Two original samples of Chilo suppressalis and their grid, random and sequence samples were analyzed by classical method and geostatistics to characterize the spatial distribution pattern of C. suppressalis. The limitations of spatial distribution analysis with classical method, especially influenced by the original position of grid, were summarized rather completely. On the contrary, geostatistics characterized well the spatial distribution pattern, congregation intensity and spatial heterogeneity of C. suppressalis. According to geostatistics, the population was up to Poisson distribution in low density. As for higher density population, its distribution was up to aggregative, and the aggregation intensity and dependence range were 0.1056 and 193 cm, respectively. Spatial heterogeneity was also found in the higher density population. Its spatial correlativity in line direction was more closely than that in row direction, and the dependence ranges in line and row direction were 115 and 264 cm, respectively.

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

USGS Publications Warehouse

Bahn, V.; O'Connor, R.J.; Krohn, W.B.

2006-01-01

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography.

Land Use Compounds Habitat Losses under Projected Climate Change in a Threatened California Ecosystem

PubMed Central

Riordan, Erin Coulter; Rundel, Philip W.

2014-01-01

Given the rapidly growing human population in mediterranean-climate systems, land use may pose a more immediate threat to biodiversity than climate change this century, yet few studies address the relative future impacts of both drivers. We assess spatial and temporal patterns of projected 21st century land use and climate change on California sage scrub (CSS), a plant association of considerable diversity and threatened status in the mediterranean-climate California Floristic Province. Using a species distribution modeling approach combined with spatially-explicit land use projections, we model habitat loss for 20 dominant shrub species under unlimited and no dispersal scenarios at two time intervals (early and late century) in two ecoregions in California (Central Coast and South Coast). Overall, projected climate change impacts were highly variable across CSS species and heavily dependent on dispersal assumptions. Projected anthropogenic land use drove greater relative habitat losses compared to projected climate change in many species. This pattern was only significant under assumptions of unlimited dispersal, however, where considerable climate-driven habitat gains offset some concurrent climate-driven habitat losses. Additionally, some of the habitat gained with projected climate change overlapped with projected land use. Most species showed potential northern habitat expansion and southern habitat contraction due to projected climate change, resulting in sharply contrasting patterns of impact between Central and South Coast Ecoregions. In the Central Coast, dispersal could play an important role moderating losses from both climate change and land use. In contrast, high geographic overlap in habitat losses driven by projected climate change and projected land use in the South Coast underscores the potential for compounding negative impacts of both drivers. Limiting habitat conversion may be a broadly beneficial strategy under climate change. We emphasize the importance of addressing both drivers in conservation and resource management planning. PMID:24466116

Past and ongoing shifts in Joshua tree distribution support future modeled range contraction

USGS Publications Warehouse

Cole, Kenneth L.; Ironside, Kirsten; Eischeid, Jon K.; Garfin, Gregg; Duffy, Phil; Toney, Chris

2011-01-01

The future distribution of the Joshua tree (Yucca brevifolia) is projected by combining a geostatistical analysis of 20th-century climates over its current range, future modeled climates, and paleoecological data showing its response to a past similar climate change. As climate rapidly warmed ;11 700 years ago, the range of Joshua tree contracted, leaving only the populations near what had been its northernmost limit. Its ability to spread northward into new suitable habitats after this time may have been inhibited by the somewhat earlier extinction of megafaunal dispersers, especially the Shasta ground sloth. We applied a model of climate suitability for Joshua tree, developed from its 20th-century range and climates, to future climates modeled through a set of six individual general circulation models (GCM) and one suite of 22 models for the late 21st century. All distribution data, observed climate data, and future GCM results were scaled to spatial grids of ;1 km and ;4 km in order to facilitate application within this topographically complex region. All of the models project the future elimination of Joshua tree throughout most of the southern portions of its current range. Although estimates of future monthly precipitation differ between the models, these changes are outweighed by large increases in temperature common to all the models. Only a few populations within the current range are predicted to be sustainable. Several models project significant potential future expansion into new areas beyond the current range, but the species' Historical and current rates of dispersal would seem to prevent natural expansion into these new areas. Several areas are predicted to be potential sites for relocation/ assisted migration. This project demonstrates how information from paleoecology and modern ecology can be integrated in order to understand ongoing processes and future distributions.

Modelling dynamic fronto-parietal behaviour during minimally invasive surgery--a Markovian trip distribution approach.

PubMed

Leff, Daniel Richard; Orihuela-Espina, Felipe; Leong, Julian; Darzi, Ara; Yang, Guang-Zhong

2008-01-01

Learning to perform Minimally Invasive Surgery (MIS) requires considerable attention, concentration and spatial ability. Theoretically, this leads to activation in executive control (prefrontal) and visuospatial (parietal) centres of the brain. A novel approach is presented in this paper for analysing the flow of fronto-parietal haemodynamic behaviour and the associated variability between subjects. Serially acquired functional Near Infrared Spectroscopy (fNIRS) data from fourteen laparoscopic novices at different stages of learning is projected into a low-dimensional 'geospace', where sequentially acquired data is mapped to different locations. A trip distribution matrix based on consecutive directed trips between locations in the geospace reveals confluent fronto-parietal haemodynamic changes and a gravity model is applied to populate this matrix. To model global convergence in haemodynamic behaviour, a Markov chain is constructed and by comparing sequential haemodynamic distributions to the Markov's stationary distribution, inter-subject variability in learning an MIS task can be identified.

International Satellite Cloud Climatology Project (ISCCP) Ice Snow Product in Native (NAT) Format (ISCCP_ICESNOW_NAT)

NASA Technical Reports Server (NTRS)

Rossow, William B. (Principal Investigator)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=112 Km; Longitude_Resolution=112 Km; Temporal_Resolution=5-day].

Simulated hydrologic response to projected changes in precipitation and temperature in the Congo River basin

NASA Astrophysics Data System (ADS)

Aloysius, Noel; Saiers, James

2017-08-01

Despite their global significance, the impacts of climate change on water resources and associated ecosystem services in the Congo River basin (CRB) have been understudied. Of particular need for decision makers is the availability of spatial and temporal variability of runoff projections. Here, with the aid of a spatially explicit hydrological model forced with precipitation and temperature projections from 25 global climate models (GCMs) under two greenhouse gas emission scenarios, we explore the variability in modeled runoff in the near future (2016-2035) and mid-century (2046-2065). We find that total runoff from the CRB is projected to increase by 5 % [-9 %; 20 %] (mean - min and max - across model ensembles) over the next two decades and by 7 % [-12 %; 24 %] by mid-century. Projected changes in runoff from subwatersheds distributed within the CRB vary in magnitude and sign. Over the equatorial region and in parts of northern and southwestern CRB, most models project an overall increase in precipitation and, subsequently, runoff. A simulated decrease in precipitation leads to a decline in runoff from headwater regions located in the northeastern and southeastern CRB. Climate model selection plays an important role in future projections for both magnitude and direction of change. The multimodel ensemble approach reveals that precipitation and runoff changes under business-as-usual and avoided greenhouse gas emission scenarios (RCP8.5 vs. RCP4.5) are relatively similar in the near term but deviate in the midterm, which underscores the need for rapid action on climate change adaptation. Our assessment demonstrates the need to include uncertainties in climate model and emission scenario selection during decision-making processes related to climate change mitigation and adaptation.

Mapping and simulating systematics due to spatially-varying observing conditions in DES science verification data

DOE PAGES

Leistedt, B.; Peiris, H. V.; Elsner, F.; ...

2016-10-17

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. Wemore » illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We then analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. However, they will need to be carefully characterised in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.« less

CNMM: a Catchment Environmental Model for Managing Water Quality and Greenhouse Gas Emissions

NASA Astrophysics Data System (ADS)

Li, Y.

2015-12-01

Mitigating agricultural diffuse pollution and greenhouse gas emissions is a complicated task due to tempo-spatial lags between the field practices and the watershed responses. Spatially-distributed modeling is essential to the implementation of cost-effective and best management practices (BMPs) to optimize land uses and nutrient applications as well as to project the impact of climate change on the watershed service functions. CNMM (the Catchment Nutrients Management Model) is a 3D spatially-distributed, grid-based and process-oriented biophysical model comprehensively developed to simulate energy balance, hydrology, plant/crop growth, biogeochemistry of life elements (e.g., C, N and P), waste treatment, waterway vegetation/purification, stream water quality and land management in agricultural watersheds as affected by land utilization strategies such as BMPs and by climate change. The CNMM is driven by a number of spatially-distributed data such as weather, topography (including DEM and shading), stream network, stream water, soil, vegetation and land management (including waste treatments), and runs at an hourly time step. It represents a catchment as a matrix of square uniformly-sized cells, where each cell is defined as a homogeneous hydrological response unit with all the hydrologically-significant parameters the same but varied at soil depths in fine intervals. Therefore, spatial variability is represented by allowing parameters to vary horizontally and vertically in space. A four-direction flux routing algorithm is applied to route water and nutrients across soils of cells governed by the gradients of either water head or elevation. A linear channel reservoir scheme is deployed to route water and nutrients in stream networks. The model is capable of computing CO2, CH4, NH3, NO, N2O and N2 emissions from soils and stream waters. The CNMM can serve as an idea modelling tool to investigate the overwhelming critical zone research at various catchment scales.

Relationship between gaseous N dynamics and the hydraulic state of hierarchically structured soils

NASA Astrophysics Data System (ADS)

Schlüter, Steffen; Dörsch, Peter; Vogel, Hans-Jörg

2017-04-01

The inherent spatial heterogeneity of soil generates spatially distributed micro-sites with different local N gas (NO, N2O, N2) production and release rates. Moreover, local micro-site conditions and the pathways between them depend on soil moisture which itself is highly dynamic close to the soil surface. These relationships need to be taken into account for a quantitative understanding of soil denitrification and associated N gas dynamics. Soil structure has been recognized as a key factor to understand the high spatial variability of N gas emissions. In particular gaseous N release from soils depends on: i) the total denitrification rate, which is related to the spatial extent and distribution of anaerobic sites and ii) the probability of N2O to escape from the soil without being further reduced to N2. This impact of soil structure is typically ignored in studies with soil slurries or repacked soil. In this project we run well-defined mesocosm experiments on N gas dynamics with hierarchically structured, artificial soils in which the spatial distribution of substrate and denitrifiers is known exactly. Sintered, porous glass pellets are inoculated with strains of Paracoccus denitrificans and/or Agrobacterium tumefaciens and amended with nutrient solution. These pellets are embedded in coarse-grained sand within gas-tight columns under O2/He atmosphere. The pellets are either places in layers or randomly to create different patterns of N gas production sites and diffusion pathways. Denitrification occurs in the anaerobic centers of the porous pellets, while the partially saturated sand matrix controls the diffusive transport of N gases towards the headspace, where all relevant gas concentrations are monitored with gas chromatography. Water saturations are adjusted such that the diffusive pathways are either fully continuous or partially discontinuous. Preliminary results indicate that the water content exert a major control on the magnitude of denitrification, whereas the onset and dynamics are mainly controlled by the position of the substrate and the denitrifiers.

Geostatistics as a tool to improve the natural background level definition: An application in groundwater.

PubMed

Dalla Libera, Nico; Fabbri, Paolo; Mason, Leonardo; Piccinini, Leonardo; Pola, Marco

2017-11-15

The Natural Background Level (NBL), suggested by UE BRIDGE project, is suited for spatially distributed datasets providing a regional value that could be higher than the Threshold Value (TV) set by every country. In hydro-geochemically dis-homogeneous areas, the use of a unique regional NBL, higher than TV, could arise problems to distinguish between natural occurrences and anthropogenic contaminant sources. Hence, the goal of this study is to improve the NBL definition employing a geostatistical approach, which reconstructs the contaminant spatial structure accounting geochemical and hydrogeological relationships. This integrated mapping is fundamental to evaluate the contaminant's distribution impact on the NBL, giving indications to improve it. We decided to test this method on the Drainage Basin of Venice Lagoon (DBVL, NE Italy), where the existing NBL is seven times higher than the TV. This area is notoriously affected by naturally occurring arsenic contamination. An available geochemical dataset collected by 50 piezometers was used to reconstruct the spatial distribution of arsenic in the densely populated area of the DBVL. A cokriging approach was applied exploiting the geochemical relationships among As, Fe and NH4+. The obtained spatial predictions of arsenic concentrations were divided into three different zones: i) areas with an As concentration lower than the TV, ii) areas with an As concentration between the TV and the median of the values higher than the TV, and iii) areas with an As concentration higher than the median. Following the BRIDGE suggestions, where enough samples were available, the 90th percentile for each zone was calculated to obtain a local NBL (LNBL). Differently from the original NBL, this local value gives more detailed water quality information accounting the hydrogeological and geochemical setting, and contaminant spatial variation. Hence, the LNBL could give more indications about the distinction between natural occurrence and anthropogenic contamination. Copyright © 2017 Elsevier B.V. All rights reserved.

MAPPING AND SIMULATING SYSTEMATICS DUE TO SPATIALLY VARYING OBSERVING CONDITIONS IN DES SCIENCE VERIFICATION DATA

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

Leistedt, B.; Peiris, H. V.; Elsner, F.

Spatially varying depth and the characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, particularly in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES-SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. Wemore » illustrate the complementary nature of these two approaches by comparing the SV data with BCC-UFig, a synthetic sky catalog generated by forward-modeling of the DES-SV images. We analyze the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and are well-captured by the maps of observing conditions. The combined use of the maps, the SV data, and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak-lensing analyses. However, they will need to be carefully characterized in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented here is relevant to all multi-epoch surveys and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky« less

Mapping and simulating systematics due to spatially-varying observing conditions in DES science verification data

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

Leistedt, B.; Peiris, H. V.; Elsner, F.

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. Wemore » illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We then analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. However, they will need to be carefully characterised in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.« less

Time Is Not Space: Core Computations and Domain-Specific Networks for Mental Travels.

PubMed

Gauthier, Baptiste; van Wassenhove, Virginie

2016-11-23

Humans can consciously project themselves in the future and imagine themselves at different places. Do mental time travel and mental space navigation abilities share common cognitive and neural mechanisms? To test this, we recorded fMRI while participants mentally projected themselves in time or in space (e.g., 9 years ago, in Paris) and ordered historical events from their mental perspective. Behavioral patterns were comparable for mental time and space and shaped by self-projection and by the distance of historical events to the mental position of the self, suggesting the existence of egocentric mapping in both dimensions. Nonetheless, self-projection in space engaged the medial and lateral parietal cortices, whereas self-projection in time engaged a widespread parietofrontal network. Moreover, while a large distributed network was found for spatial distances, temporal distances specifically engaged the right inferior parietal cortex and the anterior insula. Across these networks, a robust overlap was only found in a small region of the inferior parietal lobe, adding evidence for its role in domain-general egocentric mapping. Our findings suggest that mental travel in time or space capitalizes on egocentric remapping and on distance computation, which are implemented in distinct dimension-specific cortical networks converging in inferior parietal lobe. As humans, we can consciously imagine ourselves at a different time (mental time travel) or at a different place (mental space navigation). Are such abilities domain-general, or are the temporal and spatial dimensions of our conscious experience separable? Here, we tested the hypothesis that mental time travel and mental space navigation required the egocentric remapping of events, including the estimation of their distances to the self. We report that, although both remapping and distance computation are foundational for the processing of the temporal and spatial dimensions of our conscious experience, their neuroanatomical implementations were clearly dissociable and engaged distinct parietal and parietofrontal networks for mental space navigation and mental time travel, respectively. Copyright © 2016 the authors 0270-6474/16/3611891-13$15.00/0.

Variability of precipitation in Poland under climate change

NASA Astrophysics Data System (ADS)

Szwed, Małgorzata

2018-02-01

The surface warming has been widespread over the entire globe. Central Europe, including Poland, is not an exception. Global temperature increases are accompanied by changes in other climatic variables. Climate change in Poland manifests itself also as change in annual sums of precipitation. They have been slightly growing but, what is more important, seasonal and monthly distributions of precipitation have been also changing. The most visible increases have been observed during colder half-year, especially in March. A decreasing contribution of summer precipitation total (June-August) to the annual total is observed. Climate projections for Poland predict further warming and continuation of already observed changes in the quantity of precipitation as well as its spatial and seasonal distribution.

Electrical Conductivity Distributions in Discrete Fluid-Filled Fractures

NASA Astrophysics Data System (ADS)

James, S. C.; Ahmmed, B.; Knox, H. A.; Johnson, T.; Dunbar, J. A.

2017-12-01

It is commonly asserted that hydraulic fracturing enhances permeability by generating new fractures in the reservoir. Furthermore, it is assumed that in the fractured system predominant flow occurs in these newly formed and pre-existing fractures. Among the phenomenology that remains enigmatic are fluid distributions inside fractures. Therefore, determining fluid distribution and their associated temporal and spatial evolution in fractures is critical for safe and efficient hydraulic fracturing. Previous studies have used both forward modeling and inversion of electrical data to show that a geologic system consisting of fluid filled fractures has a conductivity distribution, where fractures act as electrically conductive bodies when the fluids are more conductive than the host material. We will use electrical inversion for estimating electrical conductivity distribution within multiple fractures from synthetic and measured data. Specifically, we will use data and well geometries from an experiment performed at Blue Canyon Dome in Socorro, NM, which was used as a study site for subsurface technology, engineering, and research (SubTER) funded by DOE. This project used a central borehole for energetically stimulating the system and four monitoring boreholes, emplaced in the cardinal directions. The electrical data taken during this project used 16 temporary electrodes deployed in the stimulation borehole and 64 permanent electrodes in the monitoring wells (16 each). We present results derived using E4D from scenarios with two discrete fractures, thereby discovering the electric potential response of both spatially and temporarily variant fluid distribution and the resolution of fluid and fracture boundaries. These two fractures have dimensions of 3m × 0.01m × 7m and are separated by 1m. These results can be used to develop stimulation and flow tests at the meso-scale that will be important for model validation. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Quantitative assessment of industrial VOC emissions in China: Historical trend, spatial distribution, uncertainties, and projection

NASA Astrophysics Data System (ADS)

Zheng, Chenghang; Shen, Jiali; Zhang, Yongxin; Huang, Weiwei; Zhu, Xinbo; Wu, Xuecheng; Chen, Linghong; Gao, Xiang; Cen, Kefa

2017-02-01

The temporal trends of industrial volatile organic compound (VOC) emissions was comprehensively summarized for the 2011 to 2013 period, and the projections for 2020 to 2050 for China were set. The results demonstrate that industrial VOC emissions in China increased from 15.3 Tg in 2011 to 29.4 Tg in 2013 at an annual average growth rate of 38.3%. Guangdong (3.45 Tg), Shandong (2.85 Tg), and Jiangsu (2.62 Tg) were the three largest contributors collectively accounting for 30.4% of the national total emissions in 2013. The top three average industrial VOC emissions per square kilometer were Shanghai (247.2 ton/km2), Tianjin (62.8 ton/km2), and Beijing (38.4 ton/km2), which were 12-80 times of the average level in China. The data from the inventory indicate that the use of VOC-containing products, as well as the production and use of VOCs as raw materials, as well as for storage and transportation contributed 75.4%, 10.3%, 9.1%, and 5.2% of the total emissions, respectively. ArcGIS was used to display the remarkable spatial distribution variation by allocating the emission into 1 km × 1 km grid cells with a population as surrogate indexes. Combined with future economic development and population change, as well as implementation of policy and upgrade of control technologies, three scenarios (scenarios A, B, and C) were set to project industrial VOC emissions for the years 2020, 2030, and 2050, which present the industrial VOC emissions in different scenarios and the potential of reducing emissions. Finally, the result shows that the collaborative control policies considerably influenced industrial VOC emissions.

Climatic water deficit, tree species ranges, and climate change in Yosemite National Park

USGS Publications Warehouse

Lutz, James A.; Van Wagtendonk, Jan W.; Franklin, Jerry F.

2010-01-01

Aim  (1) To calculate annual potential evapotranspiration (PET), actual evapotranspiration (AET) and climatic water deficit (Deficit) with high spatial resolution; (2) to describe distributions for 17 tree species over a 2300-m elevation gradient in a 3000-km2 landscape relative to AET and Deficit; (3) to examine changes in AET and Deficit between past (c. 1700), present (1971–2000) and future (2020–49) climatological means derived from proxies, observations and projections; and (4) to infer how the magnitude of changing Deficit may contribute to changes in forest structure and composition.Location  Yosemite National Park, California, USA.Methods  We calculated the water balance within Yosemite National Park using a modified Thornthwaite-type method and correlated AET and Deficit with tree species distribution. We used input data sets with different spatial resolutions parameterized for variation in latitude, precipitation, temperature, soil water-holding capacity, slope and aspect. We used climate proxies and climate projections to model AET and Deficit for past and future climate. We compared the modelled future water balance in Yosemite with current species water-balance ranges in North America.Results  We calculated species climatic envelopes over broad ranges of environmental gradients – a range of 310 mm for soil water-holding capacity, 48.3°C for mean monthly temperature (January minima to July maxima), and 918 mm yr−1 for annual precipitation. Tree species means were differentiated by AET and Deficit, and at higher levels of Deficit, species means were increasingly differentiated. Modelled Deficit for all species increased by a mean of 5% between past (c. 1700) and present (1971–2000). Projected increases in Deficit between present and future (2020–49) were 23% across all plots.Main conclusions  Modelled changes in Deficit between past, present and future climate scenarios suggest that recent past changes in forest structure and composition may accelerate in the future, with species responding individualistically to further declines in water availability. Declining water availability may disproportionately affect Pinus monticola and Tsuga mertensiana. Fine-scale heterogeneity in soil water-holding capacity, aspect and slope implies that plant water balance may vary considerably within the grid cells of kilometre-scale climate models. Sub-grid-cell soil and topographical data can partially compensate for the lack of spatial heterogeneity in gridded climate data, potentially improving vegetation-change projections in mountainous landscapes with heterogeneous topography.

Global Swath and Gridded Data Tiling

NASA Technical Reports Server (NTRS)

Thompson, Charles K.

2012-01-01

This software generates cylindrically projected tiles of swath-based or gridded satellite data for the purpose of dynamically generating high-resolution global images covering various time periods, scaling ranges, and colors called "tiles." It reconstructs a global image given a set of tiles covering a particular time range, scaling values, and a color table. The program is configurable in terms of tile size, spatial resolution, format of input data, location of input data (local or distributed), number of processes run in parallel, and data conditioning.

Metadata Creation, Management and Search System for your Scientific Data

NASA Astrophysics Data System (ADS)

Devarakonda, R.; Palanisamy, G.

2012-12-01

Mercury Search Systems is a set of tools for creating, searching, and retrieving of biogeochemical metadata. Mercury toolset provides orders of magnitude improvements in search speed, support for any metadata format, integration with Google Maps for spatial queries, multi-facetted type search, search suggestions, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. Mercury's metadata editor provides a easy way for creating metadata and Mercury's search interface provides a single portal to search for data and information contained in disparate data management systems, each of which may use any metadata format including FGDC, ISO-19115, Dublin-Core, Darwin-Core, DIF, ECHO, and EML. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury is being used more than 14 different projects across 4 federal agencies. It was originally developed for NASA, with continuing development funded by NASA, USGS, and DOE for a consortium of projects. Mercury search won the NASA's Earth Science Data Systems Software Reuse Award in 2008. References: R. Devarakonda, G. Palanisamy, B.E. Wilson, and J.M. Green, "Mercury: reusable metadata management data discovery and access system", Earth Science Informatics, vol. 3, no. 1, pp. 87-94, May 2010. R. Devarakonda, G. Palanisamy, J.M. Green, B.E. Wilson, "Data sharing and retrieval using OAI-PMH", Earth Science Informatics DOI: 10.1007/s12145-010-0073-0, (2010);

Climate change and stream temperature projections in the Columbia River basin: habitat implications of spatial variation in hydrologic drivers

NASA Astrophysics Data System (ADS)

Ficklin, D. L.; Barnhart, B. L.; Knouft, J. H.; Stewart, I. T.; Maurer, E. P.; Letsinger, S. L.; Whittaker, G. W.

2014-12-01

Water temperature is a primary physical factor regulating the persistence and distribution of aquatic taxa. Considering projected increases in air temperature and changes in precipitation in the coming century, accurate assessment of suitable thermal habitats in freshwater systems is critical for predicting aquatic species' responses to changes in climate and for guiding adaptation strategies. We use a hydrologic model coupled with a stream temperature model and downscaled general circulation model outputs to explore the spatially and temporally varying changes in stream temperature for the late 21st century at the subbasin and ecological province scale for the Columbia River basin (CRB). On average, stream temperatures are projected to increase 3.5 °C for the spring, 5.2 °C for the summer, 2.7 °C for the fall, and 1.6 °C for the winter. While results indicate changes in stream temperature are correlated with changes in air temperature, our results also capture the important, and often ignored, influence of hydrological processes on changes in stream temperature. Decreases in future snowcover will result in increased thermal sensitivity within regions that were previously buffered by the cooling effect of flow originating as snowmelt. Other hydrological components, such as precipitation, surface runoff, lateral soil water flow, and groundwater inflow, are negatively correlated to increases in stream temperature depending on the ecological province and season. At the ecological province scale, the largest increase in annual stream temperature was within the Mountain Snake ecological province, which is characterized by migratory coldwater fish species. Stream temperature changes varied seasonally with the largest projected stream temperature increases occurring during the spring and summer for all ecological provinces. Our results indicate that stream temperatures are driven by local processes and ultimately require a physically explicit modeling approach to accurately characterize the habitat regulating the distribution and diversity of aquatic taxa.

Climate change and stream temperature projections in the Columbia River Basin: biological implications of spatial variation in hydrologic drivers

NASA Astrophysics Data System (ADS)

Ficklin, D. L.; Barnhart, B. L.; Knouft, J. H.; Stewart, I. T.; Maurer, E. P.; Letsinger, S. L.; Whittaker, G. W.

2014-06-01

Water temperature is a primary physical factor regulating the persistence and distribution of aquatic taxa. Considering projected increases in temperature and changes in precipitation in the coming century, accurate assessment of suitable thermal habitat in freshwater systems is critical for predicting aquatic species responses to changes in climate and for guiding adaptation strategies. We use a hydrologic model coupled with a stream temperature model and downscaled General Circulation Model outputs to explore the spatially and temporally varying changes in stream temperature at the subbasin and ecological province scale for the Columbia River Basin. On average, stream temperatures are projected to increase 3.5 °C for the spring, 5.2 °C for the summer, 2.7 °C for the fall, and 1.6 °C for the winter. While results indicate changes in stream temperature are correlated with changes in air temperature, our results also capture the important, and often ignored, influence of hydrological processes on changes in stream temperature. Decreases in future snowcover will result in increased thermal sensitivity within regions that were previously buffered by the cooling effect of flow originating as snowmelt. Other hydrological components, such as precipitation, surface runoff, lateral soil flow, and groundwater, are negatively correlated to increases in stream temperature depending on the season and ecological province. At the ecological province scale, the largest increase in annual stream temperature was within the Mountain Snake ecological province, which is characterized by non-migratory coldwater fish species. Stream temperature changes varied seasonally with the largest projected stream temperature increases occurring during the spring and summer for all ecological provinces. Our results indicate that stream temperatures are driven by local processes and ultimately require a physically-explicit modeling approach to accurately characterize the habitat regulating the distribution and diversity of aquatic taxa.

Spatial analysis of cities using Renyi entropy and fractal parameters

NASA Astrophysics Data System (ADS)

Chen, Yanguang; Feng, Jian

2017-12-01

The spatial distributions of cities fall into two groups: one is the simple distribution with characteristic scale (e.g. exponential distribution), and the other is the complex distribution without characteristic scale (e.g. power-law distribution). The latter belongs to scale-free distributions, which can be modeled with fractal geometry. However, fractal dimension is not suitable for the former distribution. In contrast, spatial entropy can be used to measure any types of urban distributions. This paper is devoted to generalizing multifractal parameters by means of dual relation between Euclidean and fractal geometries. The main method is mathematical derivation and empirical analysis, and the theoretical foundation is the discovery that the normalized fractal dimension is equal to the normalized entropy. Based on this finding, a set of useful spatial indexes termed dummy multifractal parameters are defined for geographical analysis. These indexes can be employed to describe both the simple distributions and complex distributions. The dummy multifractal indexes are applied to the population density distribution of Hangzhou city, China. The calculation results reveal the feature of spatio-temporal evolution of Hangzhou's urban morphology. This study indicates that fractal dimension and spatial entropy can be combined to produce a new methodology for spatial analysis of city development.

Laser SRS tracker for reverse prototyping tasks

NASA Astrophysics Data System (ADS)

Kolmakov, Egor; Redka, Dmitriy; Grishkanich, Aleksandr; Tsvetkov, Konstantin

2017-10-01

According to the current great interest concerning Large-Scale Metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance, are assuming a more and more important role among system requirements. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of chip and microlasers as radiators on the linear-angular characteristics of existing measurement systems. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The system consists of a distributed network-based layout, whose modularity allows to fit differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load.

The Potential for Spatial Distribution Indices to Signal Thresholds in Marine Fish Biomass

PubMed Central

Reuchlin-Hugenholtz, Emilie

2015-01-01

The frequently observed positive relationship between fish population abundance and spatial distribution suggests that changes in distribution can be indicative of trends in abundance. If contractions in spatial distribution precede declines in spawning stock biomass (SSB), spatial distribution reference points could complement the SSB reference points that are commonly used in marine conservation biology and fisheries management. When relevant spatial distribution information is integrated into fisheries management and recovery plans, risks and uncertainties associated with a plan based solely on the SSB criterion would be reduced. To assess the added value of spatial distribution data, we examine the relationship between SSB and four metrics of spatial distribution intended to reflect changes in population range, concentration, and density for 10 demersal populations (9 species) inhabiting the Scotian Shelf, Northwest Atlantic. Our primary purpose is to assess their potential to serve as indices of SSB, using fisheries independent survey data. We find that metrics of density offer the best correlate of spawner biomass. A decline in the frequency of encountering high density areas is associated with, and in a few cases preceded by, rapid declines in SSB in 6 of 10 populations. Density-based indices have considerable potential to serve both as an indicator of SSB and as spatially based reference points in fisheries management. PMID:25789624

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

NASA Astrophysics Data System (ADS)

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

2003-03-01

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

Photoacoustic projection imaging using an all-optical detector array

NASA Astrophysics Data System (ADS)

Bauer-Marschallinger, J.; Felbermayer, K.; Berer, T.

2018-02-01

We present a prototype for all-optical photoacoustic projection imaging. By generating projection images, photoacoustic information of large volumes can be retrieved with less effort compared to common photoacoustic computed tomography where many detectors and/or multiple measurements are required. In our approach, an array of 60 integrating line detectors is used to acquire photoacoustic waves. The line detector array consists of fiber-optic MachZehnder interferometers, distributed on a cylindrical surface. From the measured variation of the optical path lengths of the interferometers, induced by photoacoustic waves, a photoacoustic projection image can be reconstructed. The resulting images represent the projection of the three-dimensional spatial light absorbance within the imaged object onto a two-dimensional plane, perpendicular to the line detector array. The fiber-optic detectors achieve a noise-equivalent pressure of 24 Pascal at a 10 MHz bandwidth. We present the operational principle, the structure of the array, and resulting images. The system can acquire high-resolution projection images of large volumes within a short period of time. Imaging large volumes at high frame rates facilitates monitoring of dynamic processes.

SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses

PubMed Central

Bennett, Joseph R.; French, Connor M.

2017-01-01

SDMtoolbox 2.0 is a software package for spatial studies of ecology, evolution, and genetics. The release of SDMtoolbox 2.0 allows researchers to use the most current ArcGIS software and MaxEnt software, and reduces the amount of time that would be spent developing common solutions. The central aim of this software is to automate complicated and repetitive spatial analyses in an intuitive graphical user interface. One core tenant facilitates careful parameterization of species distribution models (SDMs) to maximize each model’s discriminatory ability and minimize overfitting. This includes carefully processing of occurrence data, environmental data, and model parameterization. This program directly interfaces with MaxEnt, one of the most powerful and widely used species distribution modeling software programs, although SDMtoolbox 2.0 is not limited to species distribution modeling or restricted to modeling in MaxEnt. Many of the SDM pre- and post-processing tools have ‘universal’ analogs for use with any modeling software. The current version contains a total of 79 scripts that harness the power of ArcGIS for macroecology, landscape genetics, and evolutionary studies. For example, these tools allow for biodiversity quantification (such as species richness or corrected weighted endemism), generation of least-cost paths and corridors among shared haplotypes, assessment of the significance of spatial randomizations, and enforcement of dispersal limitations of SDMs projected into future climates—to only name a few functions contained in SDMtoolbox 2.0. Lastly, dozens of generalized tools exists for batch processing and conversion of GIS data types or formats, which are broadly useful to any ArcMap user. PMID:29230356

FRESHEM - Fresh-saline groundwater distribution in Zeeland (NL) derived from airborne EM

NASA Astrophysics Data System (ADS)

Siemon, Bernhard; van Baaren, Esther; Dabekaussen, Willem; Delsman, Joost; Gunnik, Jan; Karaoulis, Marios; de Louw, Perry; Oude Essink, Gualbert; Pauw, Pieter; Steuer, Annika; Meyer, Uwe

2017-04-01

In a setting of predominantly saline surface waters, the availability of fresh water for agricultural purposes is not obvious in Zeeland, The Netherlands. Canals and ditches are mainly brackish to saline due to saline seepage, which originates from old marine deposits and salt-water transgressions during historical times. The only available fresh groundwater is present in the form of freshwater lenses floating on top of the saline groundwater. This fresh groundwater is vital for agricultural, industrial, ecological, water conservation and drinking water functions. An essential first step for managing this fresh groundwater properly is to know the present spatial fresh-brackish-saline groundwater distribution. As traditional salinity monitoring is labour-intensive, airborne electromagnetics (AEM), which is fast and can cover large areas in short time, is an efficient alternative. A consortium of BGR, Deltares and TNO started FRESHEM Zeeland (FREsh Salt groundwater distribution by Helicopter ElectroMagnetic survey in the Province of Zeeland) in October 2014. Within 3x2 weeks of the first project year, the entire area of about 2000 km2 was surveyed using BGR's helicopter-borne geophysical system totalling to about 10,000 line-km. The HEM datasets of 17 subareas were carefully processed using advanced BGR in-house software and inverted to 2.5 Million resistivity-depth models. Ground truthing demonstrated that the large-scale HEM results fit very well with small-scale ground EM data (ECPT). Based on this spatial resistivity distribution, a 3D voxel model for Chloride concentration was derived for the entire province taking into account geological model data (GeoTOP) for the lithology correction and local in-situ groundwater measurements for the translation of water conductivity to Chloride concentration. The 3D voxel model enables stakeholders to implement spatial Chloride concentration in their groundwater models.

Managing and delivering of 3D geo data across institutions has a web based solution - intermediate results of the project GeoMol.

NASA Astrophysics Data System (ADS)

Gietzel, Jan; Schaeben, Helmut; Gabriel, Paul

2014-05-01

The increasing relevance of geological information for policy and economy at transnational level has recently been recognized by the European Commission, who has called for harmonized information related to reserves and resources in the EU Member States. GeoMol's transnational approach responds to that, providing consistent and seamless 3D geological information of the Alpine Foreland Basins based on harmonized data and agreed methodologies. However, until recently no adequate tool existed to ensure full interoperability among the involved GSOs and to distribute the multi-dimensional information of a transnational project facing diverse data policy, data base systems and software solutions. In recent years (open) standards describing 2D spatial data have been developed and implemented in different software systems including production environments for 2D spatial data (like regular 2D-GI-Systems). Easy yet secured access to the data is of upmost importance and thus priority for any spatial data infrastructure. To overcome limitations conditioned by highly sophisticated and platform dependent geo modeling software packages functionalities of a web portals can be utilized. Thus, combining a web portal with a "check-in-check-out" system allows distributed organized editing of data and models but requires standards for the exchange of 3D geological information to ensure interoperability. Another major concern is the management of large models and the ability of 3D tiling into spatially restricted models with refined resolution, especially when creating countrywide models . Using GST ("Geosciences in Space and Time") developed initially at TU Bergakademie Freiberg and continuously extended by the company GiGa infosystems, incorporating these key issues and based on an object-relational data model, it is possible to check out parts or whole models for edits and check in again after modification. GST is the core of GeoMol's web-based collaborative environment designed to serve the GSOs concerned and the scientific community. Recently common users spaces have been installed providing a central access point to manage locally stored data at each of the project partners' IT sites. This distributed-organized system allows to keep the data of the live system locally and to share just cleared portions of the data, thus adhering to national regulations on geo data access. GST also allows for a dynamic generation of virtual drilling profiles and cross sections of the stored models. As this enables to deduce classified borehole data, a role based log in giving full access to the live system only for legally mandated or licensed bodies. The beta version of GeoMol's GST based geo data infrastructure and dissemination tool for multi-dimensional information, implemented incrementally, will be installed on GeoMol's website (http://geomol.eu) by end of February. It will be available for testing to further improve the performance and applicability of GeoMol's 3D-Explorer for instant web based access to GeoMol's future outputs. The project GeoMol is co-funded by the Alpine Space Program as part of the European Territorial Cooperation 2007-2013. The project integrates partners from Austria, France, Germany, Italy, Slovenia and Switzerland and runs from September 2012 to June 2015. Further information on http://geomol.eu.

Morphology and mechanism of the very large dunes in the tidal reach of the Yangtze River, China

NASA Astrophysics Data System (ADS)

Shuwei, Zheng; Heqin, Cheng; Shuaihu, Wu; Shengyu, Shi; Wei, Xu; Quanping, Zhou; Yuehua, Jiang

2017-05-01

High-resolution multibeam data was used to interpret the surface morphology of very large dunes (VLDs) in the tidal reach of the Yangtze River, China. These VLDs can be divided into three categories according to their surface morphological characteristics. (1) VLDs-I: those with a smooth surface and cross-section; (2) VLDs-II: those accompanied by secondary dunes; (3) VLDs-III: those accompanied by secondary dunes and numerous elliptical pits. Parameters and spatial distribution of VLDs, and bed surface sediment were analyzed in the laboratory. Overall, channel morphology is an important factor affecting the development of VLDs, and channels with narrow and straight and certain water surface slope are facilitating the development of VLDs by constraining stream power. Meanwhile, distribution density of VLDs depicts a decreasing trend from Chizhou towards the estuary, are probably influenced by channel morphology and width. Associated pits in VLDs-III change the 3D dune morphology by distributing in secondary dunes as beads. The Three Gorges Dam project (TGP) leads to the bed surface sediment activity frequently and leads to the riverbed surface sediment coarsens, which promotes the further development of dunes. Moreover, other human activities, such as river regulation project, sand mining and Deep Water Channel Regulation Project have changed the regional river boundary conditions and hydrodynamic conditions are influential on the development of VLDs.

End-of-winter snow depth variability on glaciers in Alaska

NASA Astrophysics Data System (ADS)

McGrath, Daniel; Sass, Louis; O'Neel, Shad; Arendt, Anthony; Wolken, Gabriel; Gusmeroli, Alessio; Kienholz, Christian; McNeil, Christopher

2015-08-01

A quantitative understanding of snow thickness and snow water equivalent (SWE) on glaciers is essential to a wide range of scientific and resource management topics. However, robust SWE estimates are observationally challenging, in part because SWE can vary abruptly over short distances in complex terrain due to interactions between topography and meteorological processes. In spring 2013, we measured snow accumulation on several glaciers around the Gulf of Alaska using both ground- and helicopter-based ground-penetrating radar surveys, complemented by extensive ground truth observations. We found that SWE can be highly variable (40% difference) over short spatial scales (tens to hundreds of meters), especially in the ablation zone where the underlying ice surfaces are typically rough. Elevation provides the dominant basin-scale influence on SWE, with gradients ranging from 115 to 400 mm/100 m. Regionally, total accumulation and the accumulation gradient are strongly controlled by a glacier's distance from the coastal moisture source. Multiple linear regressions, used to calculate distributed SWE fields, show that robust results require adequate sampling of the true distribution of multiple terrain parameters. Final SWE estimates (comparable to winter balances) show reasonable agreement with both the Parameter-elevation Relationships on Independent Slopes Model climate data set (9-36% difference) and the U.S. Geological Survey Alaska Benchmark Glaciers (6-36% difference). All the glaciers in our study exhibit substantial sensitivity to changing snow-rain fractions, regardless of their location in a coastal or continental climate. While process-based SWE projections remain elusive, the collection of ground-penetrating radar (GPR)-derived data sets provides a greatly enhanced perspective on the spatial distribution of SWE and will pave the way for future work that may eventually allow such projections.

Measuring changes in ambient noise levels from the installation and operation of a surge wave energy converter in the coastal ocean

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

Haxel, Joe H; Henkel, Sarah K

Ecosystem impacts resulting from elevated underwater noise levels generated by anthropogenic activities in the coastal ocean are poorly understood and remain difficult to address as a result of a significant gap in knowledge for existing nearshore sound levels. Ambient noise is an important habitat component for marine mammals and fish that use sound for essential functions such as communication, navigation, and foraging. Questions surrounding the amplitudes, frequency distributions, and durations of noise emissions from renewable wave energy conversion (WEC) projects during their construction and operation present concerns for long-term consequences in marine habitats. Oregon’s dynamic nearshore environment presents significant challengesmore » for passive acoustic monitoring that include flow noise contamination from wave orbital motions, turbulence from breaking surf, equipment burial, and fishing pressure from sport and commercial crabbers. This project included 2 techniques for passive acoustic data collection: 1) campaign style deployments of fixed hydrophone lander stations to capture temporal variations in noise levels and 2) a drifting hydrophone system to record spatial variations within the project site. The hydrophone lander deployments were effective and economically feasible for enabling robust temporal measurements of ambient noise levels in a variety of sea state conditions. Limiting factors for the fixed stations included 1) a flow shield mitigation strategy failure in the first deployment resulting in significant wideband data contamination and 2) flow noise contamination of the unshielded sensors restricting valuable analysis to frequencies above 500 Hz for subsequent deployments. Drifting hydrophone measurements were also effective and economically feasible (although logistically challenging in the beginning of the project due to vessel time constraints) providing a spatial distribution of sound levels, comparisons of noise levels in varying levels of vessel traffic during similar sea states, and reducing the frequencies contaminated by flow noise to f < 50 Hz by an effective drifting hydrophone system design strategy. Results from this project can still assist regulatory agencies and WEC developers in permitting and licensing, reducing project costs overall and assisting the economic development of the WEC industry, thus furthering the MHK energy industry and easing the U.S. reliance on foreign oil for energy production. Additionally, results from this project can be used to help inform coastal resource managers and regulatory agencies on existing baseline noise level variability and ecosystem health.« less

Access to Emissions Distributions and Related Ancillary Data through the ECCAD database

NASA Astrophysics Data System (ADS)

Darras, Sabine; Granier, Claire; Liousse, Catherine; De Graaf, Erica; Enriquez, Edgar; Boulanger, Damien; Brissebrat, Guillaume

2017-04-01

The ECCAD database (Emissions of atmospheric Compounds and Compilation of Ancillary Data) provides a user-friendly access to global and regional surface emissions for a large set of chemical compounds and ancillary data (land use, active fires, burned areas, population,etc). The emissions inventories are time series gridded data at spatial resolution from 1x1 to 0.1x0.1 degrees. ECCAD is the emissions database of the GEIA (Global Emissions InitiAtive) project and a sub-project of the French Atmospheric Data Center AERIS (http://www.aeris-data.fr). ECCAD has currently more than 2200 users originating from more than 80 countries. The project benefits from this large international community of users to expand the number of emission datasets made available. ECCAD provides detailed metadata for each of the datasets and various tools for data visualization, for computing global and regional totals and for interactive spatial and temporal analysis. The data can be downloaded as interoperable NetCDF CF-compliant files, i.e. the data are compatible with many other client interfaces. The presentation will provide information on the datasets available within ECCAD, as well as examples of the analysis work that can be done online through the website: http://eccad.aeris-data.fr.

Access to Emissions Distributions and Related Ancillary Data through the ECCAD database

NASA Astrophysics Data System (ADS)

Darras, Sabine; Enriquez, Edgar; Granier, Claire; Liousse, Catherine; Boulanger, Damien; Fontaine, Alain

2016-04-01

The ECCAD database (Emissions of atmospheric Compounds and Compilation of Ancillary Data) provides a user-friendly access to global and regional surface emissions for a large set of chemical compounds and ancillary data (land use, active fires, burned areas, population,etc). The emissions inventories are time series gridded data at spatial resolution from 1x1 to 0.1x0.1 degrees. ECCAD is the emissions database of the GEIA (Global Emissions InitiAtive) project and a sub-project of the French Atmospheric Data Center AERIS (http://www.aeris-data.fr). ECCAD has currently more than 2200 users originating from more than 80 countries. The project benefits from this large international community of users to expand the number of emission datasets made available. ECCAD provides detailed metadata for each of the datasets and various tools for data visualization, for computing global and regional totals and for interactive spatial and temporal analysis. The data can be downloaded as interoperable NetCDF CF-compliant files, i.e. the data are compatible with many other client interfaces. The presentation will provide information on the datasets available within ECCAD, as well as examples of the analysis work that can be done online through the website: http://eccad.aeris-data.fr.

Projected range contractions of European protected oceanic montane plant communities: focus on climate change impacts is essential for their future conservation.

PubMed

Hodd, Rory L; Bourke, David; Skeffington, Micheline Sheehy

2014-01-01

Global climate is rapidly changing and while many studies have investigated the potential impacts of this on the distribution of montane plant species and communities, few have focused on those with oceanic montane affinities. In Europe, highly sensitive bryophyte species reach their optimum occurrence, highest diversity and abundance in the north-west hyperoceanic regions, while a number of montane vascular plant species occur here at the edge of their range. This study evaluates the potential impact of climate change on the distribution of these species and assesses the implications for EU Habitats Directive-protected oceanic montane plant communities. We applied an ensemble of species distribution modelling techniques, using atlas data of 30 vascular plant and bryophyte species, to calculate range changes under projected future climate change. The future effectiveness of the protected area network to conserve these species was evaluated using gap analysis. We found that the majority of these montane species are projected to lose suitable climate space, primarily at lower altitudes, or that areas of suitable climate will principally shift northwards. In particular, rare oceanic montane bryophytes have poor dispersal capacity and are likely to be especially vulnerable to contractions in their current climate space. Significantly different projected range change responses were found between 1) oceanic montane bryophytes and vascular plants; 2) species belonging to different montane plant communities; 3) species categorised according to different biomes and eastern limit classifications. The inclusion of topographical variables in addition to climate, significantly improved the statistical and spatial performance of models. The current protected area network is projected to become less effective, especially for specialised arctic-montane species, posing a challenge to conserving oceanic montane plant communities. Conservation management plans need significantly greater focus on potential climate change impacts, including models with higher-resolution species distribution and environmental data, to aid these communities' long-term survival.

Projected Range Contractions of European Protected Oceanic Montane Plant Communities: Focus on Climate Change Impacts Is Essential for Their Future Conservation

PubMed Central

Skeffington, Micheline Sheehy

2014-01-01

Global climate is rapidly changing and while many studies have investigated the potential impacts of this on the distribution of montane plant species and communities, few have focused on those with oceanic montane affinities. In Europe, highly sensitive bryophyte species reach their optimum occurrence, highest diversity and abundance in the north-west hyperoceanic regions, while a number of montane vascular plant species occur here at the edge of their range. This study evaluates the potential impact of climate change on the distribution of these species and assesses the implications for EU Habitats Directive-protected oceanic montane plant communities. We applied an ensemble of species distribution modelling techniques, using atlas data of 30 vascular plant and bryophyte species, to calculate range changes under projected future climate change. The future effectiveness of the protected area network to conserve these species was evaluated using gap analysis. We found that the majority of these montane species are projected to lose suitable climate space, primarily at lower altitudes, or that areas of suitable climate will principally shift northwards. In particular, rare oceanic montane bryophytes have poor dispersal capacity and are likely to be especially vulnerable to contractions in their current climate space. Significantly different projected range change responses were found between 1) oceanic montane bryophytes and vascular plants; 2) species belonging to different montane plant communities; 3) species categorised according to different biomes and eastern limit classifications. The inclusion of topographical variables in addition to climate, significantly improved the statistical and spatial performance of models. The current protected area network is projected to become less effective, especially for specialised arctic-montane species, posing a challenge to conserving oceanic montane plant communities. Conservation management plans need significantly greater focus on potential climate change impacts, including models with higher-resolution species distribution and environmental data, to aid these communities' long-term survival. PMID:24752011

Mercury: Reusable software application for Metadata Management, Data Discovery and Access

NASA Astrophysics Data System (ADS)

Devarakonda, Ranjeet; Palanisamy, Giri; Green, James; Wilson, Bruce E.

2009-12-01

Mercury is a federated metadata harvesting, data discovery and access tool based on both open source packages and custom developed software. It was originally developed for NASA, and the Mercury development consortium now includes funding from NASA, USGS, and DOE. Mercury is itself a reusable toolset for metadata, with current use in 12 different projects. Mercury also supports the reuse of metadata by enabling searching across a range of metadata specification and standards including XML, Z39.50, FGDC, Dublin-Core, Darwin-Core, EML, and ISO-19115. Mercury provides a single portal to information contained in distributed data management systems. It collects metadata and key data from contributing project servers distributed around the world and builds a centralized index. The Mercury search interfaces then allow the users to perform simple, fielded, spatial and temporal searches across these metadata sources. One of the major goals of the recent redesign of Mercury was to improve the software reusability across the projects which currently fund the continuing development of Mercury. These projects span a range of land, atmosphere, and ocean ecological communities and have a number of common needs for metadata searches, but they also have a number of needs specific to one or a few projects To balance these common and project-specific needs, Mercury’s architecture includes three major reusable components; a harvester engine, an indexing system and a user interface component. The harvester engine is responsible for harvesting metadata records from various distributed servers around the USA and around the world. The harvester software was packaged in such a way that all the Mercury projects will use the same harvester scripts but each project will be driven by a set of configuration files. The harvested files are then passed to the Indexing system, where each of the fields in these structured metadata records are indexed properly, so that the query engine can perform simple, keyword, spatial and temporal searches across these metadata sources. The search user interface software has two API categories; a common core API which is used by all the Mercury user interfaces for querying the index and a customized API for project specific user interfaces. For our work in producing a reusable, portable, robust, feature-rich application, Mercury received a 2008 NASA Earth Science Data Systems Software Reuse Working Group Peer-Recognition Software Reuse Award. The new Mercury system is based on a Service Oriented Architecture and effectively reuses components for various services such as Thesaurus Service, Gazetteer Web Service and UDDI Directory Services. The software also provides various search services including: RSS, Geo-RSS, OpenSearch, Web Services and Portlets, integrated shopping cart to order datasets from various data centers (ORNL DAAC, NSIDC) and integrated visualization tools. Other features include: Filtering and dynamic sorting of search results, book-markable search results, save, retrieve, and modify search criteria.

High resolution global gridded data for use in population studies

PubMed Central

Lloyd, Christopher T.; Sorichetta, Alessandro; Tatem, Andrew J.

2017-01-01

Recent years have seen substantial growth in openly available satellite and other geospatial data layers, which represent a range of metrics relevant to global human population mapping at fine spatial scales. The specifications of such data differ widely and therefore the harmonisation of data layers is a prerequisite to constructing detailed and contemporary spatial datasets which accurately describe population distributions. Such datasets are vital to measure impacts of population growth, monitor change, and plan interventions. To this end the WorldPop Project has produced an open access archive of 3 and 30 arc-second resolution gridded data. Four tiled raster datasets form the basis of the archive: (i) Viewfinder Panoramas topography clipped to Global ADMinistrative area (GADM) coastlines; (ii) a matching ISO 3166 country identification grid; (iii) country area; (iv) and slope layer. Further layers include transport networks, landcover, nightlights, precipitation, travel time to major cities, and waterways. Datasets and production methodology are here described. The archive can be downloaded both from the WorldPop Dataverse Repository and the WorldPop Project website. PMID:28140386

Cruise report for A1-98-SC southern California Earthquake Hazards Project

USGS Publications Warehouse

Normark, William R.; Bohannon, Robert G.; Sliter, Ray; Dunhill, Gita; Scholl, David W.; Laursen, Jane; Reid, Jane A.; Holton, David

1999-01-01

The focus of the Southern California Earthquake Hazards project, within the Western Region Coastal and Marine Geology team (WRCMG), is to identify the landslide and earthquake hazards and related ground-deformation processes that can potentially impact the social and economic well-being of the inhabitants of the Southern California coastal region, the most populated urban corridor along the U.S. Pacific margin. The primary objective is to help mitigate the earthquake hazards for the Southern California region by improving our understanding of how deformation is distributed (spatially and temporally) in the offshore with respect to the onshore region. To meet this overall objective, we are investigating the distribution, character, and relative intensity of active (i.e., primarily Holocene) deformation within the basins and along the shelf adjacent to the most highly populated areas (see Fig. 1). In addition, the project will examine the Pliocene-Pleistocene record of how this deformation has shifted in space and time. The results of this study should improve our knowledge of shifting deformation for both the long-term (105 to several 106 yr) and short-term (<50 ky) time frames and enable us to identify actively deforming structures that may constitute current significant seismic hazards.

The Arbo‑zoonet Information System.

PubMed

Di Lorenzo, Alessio; Di Sabatino, Daria; Blanda, Valeria; Cioci, Daniela; Conte, Annamaria; Bruno, Rossana; Sauro, Francesca; Calistri, Paolo; Savini, Lara

2016-06-30

The Arbo‑zoonet Information System has been developed as part of the 'International Network for Capacity Building for the Control of Emerging Viral Vector Borne Zoonotic Diseases (Arbo‑zoonet)' project. The project aims to create common knowledge, sharing data, expertise, experiences, and scientific information on West Nile Disease (WND), Crimean‑Congo haemorrhagic fever (CCHF), and Rift Valley fever (RVF). These arthropod‑borne diseases of domestic and wild animals can affect humans, posing great threat to public health. Since November 2011, when the Schmallenberg virus (SBV) has been discovered for the first time in Northern Europe, the Arbo‑zoonet Information System has been used in order to collect information on newly discovered disease and to manage the epidemic emergency. The system monitors the geographical distribution and epidemiological evolution of CCHF, RVF, and WND since 1946. More recently, it has also been deployed to monitor the SBV data. The Arbo‑zoonet Information System includes a web application for the management of the database in which data are stored and a WebGIS application to explore spatial disease distributions, facilitating the epidemiological analysis. The WebGIS application is an effective tool to show and share the information and to facilitate the exchange and dissemination of relevant data among project's participants.

Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Y Churmakov, D.; Meglinski, I. V.; Piletsky, S. A.; Greenhalgh, D. A.

2003-07-01

A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an `effective' depth.

Citizen observatory of water as a data engine supporting the people-hydrology nexus: experience of the WeSenseIt project

NASA Astrophysics Data System (ADS)

Ferri, Michele; Baruffi, Francesco; Norbiato, Daniele; Monego, Martina; Tomei, Giovanni; Solomatine, Dimitri; Alfonso, Leonardo; Mazzoleni, Maurizio; Chacon, Juan Carlos; Wehn, Uta; Ciravegna, Fabio

2016-04-01

Citizen observatories (COs) present an interesting case of strong multi-facet feedback between the physical (water) system and humans. CO is a form of crowdsourcing ensuring a data flow from citizens observing environment (e.g. water level in a river) to a central data processing unit which is typically part of a more complex social arrangement (e.g. water authorities responsible for flood forecasting). The EU-funded project WeSenseIt (www.wesenseit.eu) aims at developing technologies and tools supporting creation of such COs [1,2,3,4]. Citizens which form a CO play the role of "social sensors" which however are very specific. The data streams from such sensors have varying temporal and spatial coverage and information value (uncertainty). The crowdsourced data can be of course simply visualized and presented to public, but it is much more interesting to consider cases when such data are assimilated into the existing forecasting systems, e.g. flood early warning systems based on hydrological and hydraulic models. COs may also affect water management and governance [4], and in fact can be seen as data engines supporting the people-hydrology nexus. In the framework of WeSenseIt project several approaches were developed allowing for optimal assimilation of intermittent data streams with varying spatial coverage into distributed hydrological models [1, 2]. The mentioned specific features of CO data required updates of the existing data assimilation algorithms (Ensemble Kalman Filter was used as the basic algorithm). The developed algorithms have been implemented in the operational flood forecasting systems of the Alto Adriatico Water Authority (AAWA), Venice. In this paper we analyse various scenarios of employing citizens data (COs) for flood forecasting. This study is partly supported by the FP7 European Project WeSenseIt Citizen Water Observatory (www.http://wesenseit.eu/). References [1] Mazzoleni, M., Alfonso, L., Chacon-Hurtado, J., Solomatine, D. (2015). Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models. Advances in Water Res., 83, 323-339 (Online on September 1, 2015). [2] Mazzoleni M., Verlaan M., Alfonso L., Monego M., Norbiato D., Ferri M., and Solomatine D.P. (2015) Can assimilation of crowdsourced streamflow observations in hydrological modelling improve flood prediction?, Hydrology and Earth System Sciences, under review. [3] Mazzoleni M., Alfonso L. and Solomatine D.P. (2015) Effect of spatial distribution and quality of sensors on the assimilation of distributed streamflow observations in hydrological modeling, Hydrological Sciences Journal, under review. [4] Wehn, U., McCarty, S., Lanfranchi, V. and Tapsell, S. (2015) Citizen observatories as facilitators of change in water governance? Experiences from three European cases, Special Issue on ICTs and Water, Journal of Environmental Engineering and Management, 2073-2086.

Intensification and spatial homogenization of coastal upwelling under climate change.

PubMed

Wang, Daiwei; Gouhier, Tarik C; Menge, Bruce A; Ganguly, Auroop R

2015-02-19

The timing and strength of wind-driven coastal upwelling along the eastern margins of major ocean basins regulate the productivity of critical fisheries and marine ecosystems by bringing deep and nutrient-rich waters to the sunlit surface, where photosynthesis can occur. How coastal upwelling regimes might change in a warming climate is therefore a question of vital importance. Although enhanced land-ocean differential heating due to greenhouse warming has been proposed to intensify coastal upwelling by strengthening alongshore winds, analyses of observations and previous climate models have provided little consensus on historical and projected trends in coastal upwelling. Here we show that there are strong and consistent changes in the timing, intensity and spatial heterogeneity of coastal upwelling in response to future warming in most Eastern Boundary Upwelling Systems (EBUSs). An ensemble of climate models shows that by the end of the twenty-first century the upwelling season will start earlier, end later and become more intense at high but not low latitudes. This projected increase in upwelling intensity and duration at high latitudes will result in a substantial reduction of the existing latitudinal variation in coastal upwelling. These patterns are consistent across three of the four EBUSs (Canary, Benguela and Humboldt, but not California). The lack of upwelling intensification and greater uncertainty associated with the California EBUS may reflect regional controls associated with the atmospheric response to climate change. Given the strong linkages between upwelling and marine ecosystems, the projected changes in the intensity, timing and spatial structure of coastal upwelling may influence the geographical distribution of marine biodiversity.

Testing LMC Microlensing Scenarios: The Discrimination Power of the SuperMACHO Microlensing Survey

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

Rest, A; Stubbs, C; Becker, A C

Characterizing the nature and spatial distribution of the lensing objects that produce the observed microlensing optical depth toward the Large Magellanic Cloud (LMC) remains an open problem. They present an appraisal of the ability of the SuperMACHO Project, a next-generation microlensing survey pointed toward the LMC, to discriminate between various proposed lensing populations. they consider two scenarios: lensing by a uniform foreground screen of objects and self-lensing of LMC stars. The optical depth for ''screen-lensing'' is essentially constant across the face of the LMC; whereas, the optical depth for self-lensing shows a strong spatial dependence. they have carried out extensivemore » simulations, based upon actual data obtained during the first year of the project, to assess the SuperMACHO survey's ability to discriminate between these two scenarios. In the simulations they predict the expected number of observed microlensing events for each of their fields by adding artificial stars to the images and estimating the spatial and temporal efficiency of detecting microlensing events using Monte-Carlo methods. They find that the event rate itself shows significant sensitivity to the choice of the LMC luminosity function shape and other parameters, limiting the conclusions which can be drawn from the absolute rate. By instead determining the differential event rate across the LMC, they can decrease the impact of these systematic uncertainties rendering the conclusions more robust. With this approach the SuperMACHO Project should be able to distinguish between the two categories of lens populations and provide important constraints on the nature of the lensing objects.« less

The use of spatial empirical models to estimate soil erosion in arid ecosystems.

PubMed

Abdullah, Meshal; Feagin, Rusty; Musawi, Layla

2017-02-01

The central objective of this project was to utilize geographical information systems and remote sensing to compare soil erosion models, including Modified Pacific South-west Inter Agency Committee (MPSIAC), Erosion Potential Method (EPM), and Revised Universal Soil Loss Equation (RUSLE), and to determine their applicability for arid regions such as Kuwait. The northern portion of Umm Nigga, containing both coastal and desert ecosystems, falls within the boundaries of the de-militarized zone (DMZ) adjacent to Iraq and has been fenced off to restrict public access since 1994. Results showed that the MPSIAC and EPM models were similar in spatial distribution of erosion, though the MPSIAC had a more realistic spatial distribution of erosion and presented finer level details. The RUSLE presented unrealistic results. We then predicted the amount of soil loss between coastal and desert areas and fenced and unfenced sites for each model. In the MPSIAC and EPM models, soil loss was different between fenced and unfenced sites at the desert areas, which was higher at the unfenced due to the low vegetation cover. The overall results implied that vegetation cover played an important role in reducing soil erosion and that fencing is much more important in the desert ecosystems to protect against human activities such as overgrazing. We conclude that the MPSIAC model is best for predicting soil erosion for arid regions such as Kuwait. We also recommend the integration of field-based experiments with lab-based spatial analysis and modeling in future research.

Integrating satellite actual evapotranspiration patterns into distributed model parametrization and evaluation for a mesoscale catchment

NASA Astrophysics Data System (ADS)

Demirel, M. C.; Mai, J.; Stisen, S.; Mendiguren González, G.; Koch, J.; Samaniego, L. E.

2016-12-01

Distributed hydrologic models are traditionally calibrated and evaluated against observations of streamflow. Spatially distributed remote sensing observations offer a great opportunity to enhance spatial model calibration schemes. For that it is important to identify the model parameters that can change spatial patterns before the satellite based hydrologic model calibration. Our study is based on two main pillars: first we use spatial sensitivity analysis to identify the key parameters controlling the spatial distribution of actual evapotranspiration (AET). Second, we investigate the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale Hydrologic Model (mHM). This distributed model is selected as it allows for a change in the spatial distribution of key soil parameters through the calibration of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) directly as input. In addition the simulated AET can be estimated at the spatial resolution suitable for comparison to the spatial patterns observed using MODIS data. We introduce a new dynamic scaling function employing remotely sensed vegetation to downscale coarse reference evapotranspiration. In total, 17 parameters of 47 mHM parameters are identified using both sequential screening and Latin hypercube one-at-a-time sampling methods. The spatial patterns are found to be sensitive to the vegetation parameters whereas streamflow dynamics are sensitive to the PTF parameters. The results of multi-objective model calibration show that calibration of mHM against observed streamflow does not reduce the spatial errors in AET while they improve only the streamflow simulations. We will further examine the results of model calibration using only multi spatial objective functions measuring the association between observed AET and simulated AET maps and another case including spatial and streamflow metrics together.

Geographic and ecologic distributions of the Anopheles gambiae complex predicted using a genetic algorithm.

PubMed

Levine, Rebecca S; Peterson, A Townsend; Benedict, Mark Q

2004-02-01

The distribution of the Anopheles gambiae complex of malaria vectors in Africa is uncertain due to under-sampling of vast regions. We use ecologic niche modeling to predict the potential distribution of three members of the complex (A. gambiae, A. arabiensis, and A. quadriannulatus) and demonstrate the statistical significance of the models. Predictions correspond well to previous estimates, but provide detail regarding spatial discontinuities in the distribution of A. gambiae s.s. that are consistent with population genetic studies. Our predictions also identify large areas of Africa where the presence of A. arabiensis is predicted, but few specimens have been obtained, suggesting under-sampling of the species. Finally, we project models developed from African distribution data for the late 1900s into the past and to South America to determine retrospectively whether the deadly 1929 introduction of A. gambiae sensu lato into Brazil was more likely that of A. gambiae sensu stricto or A. arabiensis.

Mapping species distributions: a comparison of skilled naturalist and lay citizen science recording.

PubMed

van der Wal, René; Anderson, Helen; Robinson, Annie; Sharma, Nirwan; Mellish, Chris; Roberts, Stuart; Darvill, Ben; Siddharthan, Advaith

2015-11-01

To assess the ability of traditional biological recording schemes and lay citizen science approaches to gather data on species distributions and changes therein, we examined bumblebee records from the UK's national repository (National Biodiversity Network) and from BeeWatch. The two recording approaches revealed similar relative abundances of bumblebee species but different geographical distributions. For the widespread common carder (Bombus pascuorum), traditional recording scheme data were patchy, both spatially and temporally, reflecting active record centre rather than species distribution. Lay citizen science records displayed more extensive geographic coverage, reflecting human population density, thus offering better opportunities to account for recording effort. For the rapidly spreading tree bumblebee (Bombus hypnorum), both recording approaches revealed similar distributions due to a dedicated mapping project which overcame the patchy nature of naturalist records. We recommend, where possible, complementing skilled naturalist recording with lay citizen science programmes to obtain a nation-wide capability, and stress the need for timely uploading of data to the national repository.

Patterns of Spatial Variation of Assemblages Associated with Intertidal Rocky Shores: A Global Perspective

PubMed Central

Cruz-Motta, Juan José; Miloslavich, Patricia; Palomo, Gabriela; Iken, Katrin; Konar, Brenda; Pohle, Gerhard; Trott, Tom; Benedetti-Cecchi, Lisandro; Herrera, César; Hernández, Alejandra; Sardi, Adriana; Bueno, Andrea; Castillo, Julio; Klein, Eduardo; Guerra-Castro, Edlin; Gobin, Judith; Gómez, Diana Isabel; Riosmena-Rodríguez, Rafael; Mead, Angela; Bigatti, Gregorio; Knowlton, Ann; Shirayama, Yoshihisa

2010-01-01

Assemblages associated with intertidal rocky shores were examined for large scale distribution patterns with specific emphasis on identifying latitudinal trends of species richness and taxonomic distinctiveness. Seventy-two sites distributed around the globe were evaluated following the standardized sampling protocol of the Census of Marine Life NaGISA project (www.nagisa.coml.org). There were no clear patterns of standardized estimators of species richness along latitudinal gradients or among Large Marine Ecosystems (LMEs); however, a strong latitudinal gradient in taxonomic composition (i.e., proportion of different taxonomic groups in a given sample) was observed. Environmental variables related to natural influences were strongly related to the distribution patterns of the assemblages on the LME scale, particularly photoperiod, sea surface temperature (SST) and rainfall. In contrast, no environmental variables directly associated with human influences (with the exception of the inorganic pollution index) were related to assemblage patterns among LMEs. Correlations of the natural assemblages with either latitudinal gradients or environmental variables were equally strong suggesting that neither neutral models nor models based solely on environmental variables sufficiently explain spatial variation of these assemblages at a global scale. Despite the data shortcomings in this study (e.g., unbalanced sample distribution), we show the importance of generating biological global databases for the use in large-scale diversity comparisons of rocky intertidal assemblages to stimulate continued sampling and analyses. PMID:21179546

Medieval land use management and geochemistry - spatial analyses on scales from households properties to whole fields systems

NASA Astrophysics Data System (ADS)

Horák, Jan; Janovský, Martin; Klír, Tomáš; Šmejda, Ladislav; Legut-Pintal, Maria

2017-04-01

We present the final or preliminary results of our researches of five villages: Spindelbach (Ore Mountains, North-Western Bohemia), Hol (near Prague, Central Bohemia), Lovětín and Regenholz (near Třešť, Czech-Moravian Upland) and Goschwitz (near Wroclaw, Poland). Our research is methodically based on broad spatial sampling of soil samples and mapping of basic soil conditions. We use XRF spectrometry as a main tool for multi-elemental analyses and as a tool for first step screening of large areas. The crucial factor of our methods is also a design of sampling based on a respect to historical land and land use features like parts of village field system or possesions of the households. Also macroscopic visual method of getting data and knowledge of the site is crucial. It was revealed that generally used and acknowledged human indicator - Phosphorus - can be present at only very low levels of concentration, or undetectable, even in the nearness of households. The natural conditions cannot be the causing factor at all cases. This situation is caused also by last human activity intensity and by its spatial manifestation. In such cases, multi-elemental analysis is very useful. Zinc is usually correlated with Phosphorus, which is also connected to Lead. The past human activity indicators are spatially usually connected to modern pollution indicators. These two inputs can be sometimes distinguished by statistical analyses and by spatial visualisation of data. Working with just concentrations can be misleading. Past land use management and its strategies were important for spatial distribution of soil geochemical indicators. Therefore, we can use them not only as quantifiers of human impact on nature, but we can also detect different management or knowledge and experience. As it was revealed e. g. by analyses of households` possessions differences. For example, generally presumed decreasing gradient of management intensity (e.g. manuring) along the distance from village can be found on on the level of a whole field system, but it varies a lot between the possessions` parcels. Funding: this output was created within the project New insights on a functional structure of abandoned villages field systems and on relationship between human activities and environment by way of pedochemical methods funded by Charles University Grant Agency (project No. 307415) and within the project Kulturní techniky: materialita, medialita a imaginace, subproject Středověká ves a její přírodní prostředí. Mezioborový výzkum zaniklých vsí v zázemí Prahy solved at Charles University from the Specific university research in 2016 and within the project Landscape of Medieval Prague funded by Czech Science Foundation, project No. 16-20763S.

Shapes on a plane: Evaluating the impact of projection distortion on spatial binning

USGS Publications Warehouse

Battersby, Sarah E.; Strebe, Daniel “daan”; Finn, Michael P.

2017-01-01

One method for working with large, dense sets of spatial point data is to aggregate the measure of the data into polygonal containers, such as political boundaries, or into regular spatial bins such as triangles, squares, or hexagons. When mapping these aggregations, the map projection must inevitably distort relationships. This distortion can impact the reader’s ability to compare count and density measures across the map. Spatial binning, particularly via hexagons, is becoming a popular technique for displaying aggregate measures of point data sets. Increasingly, we see questionable use of the technique without attendant discussion of its hazards. In this work, we discuss when and why spatial binning works and how mapmakers can better understand the limitations caused by distortion from projecting to the plane. We introduce equations for evaluating distortion’s impact on one common projection (Web Mercator) and discuss how the methods used generalize to other projections. While we focus on hexagonal binning, these same considerations affect spatial bins of any shape, and more generally, any analysis of geographic data performed in planar space.

Applying transport-distance specific SOC distribution to calibrate soil erosion model WaTEM

NASA Astrophysics Data System (ADS)

Hu, Yaxian; Heckrath, Goswin J.; Kuhn, Nikolaus J.

2016-04-01

Slope-scale soil erosion, transport and deposition fundamentally decide the spatial redistribution of eroded sediments in terrestrial and aquatic systems, which further affect the burial and decomposition of eroded SOC. However, comparisons of SOC contents between upper eroding slope and lower depositional site cannot fully reflect the movement of eroded SOC in-transit along hillslopes. The actual transport distance of eroded SOC is decided by its settling velocity. So far, the settling velocity distribution of eroded SOC is mostly calculated from mineral particle specific SOC distribution. Yet, soil is mostly eroded in form of aggregates, and the movement of aggregates differs significantly from individual mineral particles. This urges a SOC erodibility parameter based on actual transport distance distribution of eroded fractions to better calibrate soil erosion models. Previous field investigation on a freshly seeded cropland in Denmark has shown immediate deposition of fast settling soil fractions and the associated SOC at footslopes, followed by a fining trend at the slope tail. To further quantify the long-term effects of topography on erosional redistribution of eroded SOC, the actual transport-distance specific SOC distribution observed on the field was applied to a soil erosion model WaTEM (based on USLE). After integrating with local DEM, our calibrated model succeeded in locating the hotspots of enrichment/depletion of eroded SOC on different topographic positions, much better corresponding to the real-world field observation. By extrapolating into repeated erosion events, our projected results on the spatial distribution of eroded SOC are also adequately consistent with the SOC properties in the consecutive sample profiles along the slope.

Scaling Effects of Cr(VI) Reduction Kinetics. The Role of Geochemical Heterogeneity

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

Wang, Li; Li, Li

2015-10-22

The natural subsurface is highly heterogeneous with minerals distributed in different spatial patterns. Fundamental understanding of how mineral spatial distribution patterns regulate sorption process is important for predicting the transport and fate of chemicals. Existing studies about the sorption was carried out in well-mixed batch reactors or uniformly packed columns, with few data available on the effects of spatial heterogeneities. As a result, there is a lack of data and understanding on how spatial heterogeneities control sorption processes. In this project, we aim to understand and develop modeling capabilities to predict the sorption of Cr(VI), an omnipresent contaminant in naturalmore » systems due to its natural occurrence and industrial utilization. We systematically examine the role of spatial patterns of illite, a common clay, in determining the extent of transport limitation and scaling effects associated with Cr(VI) sorption capacity and kinetics using column experiments and reactive transport modeling. Our results showed that the sorbed mass and rates can differ by an order of magnitude due to of the illite spatial heterogeneities and transport limitation. With constraints from data, we also developed the capabilities of modeling Cr(VI) in heterogeneous media. The developed model is then utilized to understand the general principles that govern the relationship between sorption and connectivity, a key measure of the spatial pattern characteristics. This correlation can be used to estimate Cr(VI) sorption characteristics in heterogeneous porous media. Insights gained here bridge gaps between laboratory and field application in hydrogeology and geochemical field, and advance predictive understanding of reactive transport processes in the natural heterogeneous subsurface. We believe that these findings will be of interest to a large number of environmental geochemists and engineers, hydrogeologists, and those interested in contaminant fate and transport, water quality and water composition, and natural attenuation processes in natural systems.« less

Emittance study of a 28 GHz electron cyclotron resonance ion source for the Rare Isotope Science Project superconducting linear accelerator.

PubMed

Park, Bum-Sik; Hong, In-Seok; Jang, Ji-Ho; Jin, Hyunchang; Choi, Sukjin; Kim, Yonghwan

2016-02-01

A 28 GHz electron cyclotron resonance (ECR) ion source is being developed for use as an injector for the superconducting linear accelerator of the Rare Isotope Science Project. Beam extraction from the ECR ion source has been simulated using the KOBRA3-INP software. The simulation software can calculate charged particle trajectories in three dimensional complex magnetic field structures, which in this case are formed by the arrangement of five superconducting magnets. In this study, the beam emittance is simulated to understand the effects of plasma potential, mass-to-charge ratio, and spatial distribution. The results of these simulations and their comparison to experimental results are presented in this paper.

Effects of spatial and temporal resolution on simulated feedbacks from polygonal tundra.

NASA Astrophysics Data System (ADS)

Coon, E.; Atchley, A. L.; Painter, S. L.; Karra, S.; Moulton, J. D.; Wilson, C. J.; Liljedahl, A.

2014-12-01

Earth system land models typically resolve permafrost regions at spatial resolutions grossly larger than the scales of topographic variation. This observation leads to two critical questions: How much error is introduced by this lack of resolution, and what is the effect of this approximation on other coupled components of the Earth system, notably the energy balance and carbon cycle? Here we use the Arctic Terrestrial Simulator (ATS) to run micro-topography resolving simulations of polygonal ground, driven by meteorological data from Barrow, AK, to address these questions. ATS couples surface and subsurface processes, including thermal hydrology, surface energy balance, and a snow model. Comparisons are made between one-dimensional "column model" simulations (similar to, for instance, CLM or other land models typically used in Earth System models) and higher-dimensional simulations which resolve micro-topography, allowing for distributed surface runoff, horizontal flow in the subsurface, and uneven snow distribution. Additionally, we drive models with meteorological data averaged over different time scales from daily to weekly moving windows. In each case, we compare fluxes important to the surface energy balance including albedo, latent and sensible heat fluxes, and land-to-atmosphere long-wave radiation. Results indicate that spatial topography variation and temporal variability are important in several ways. Snow distribution greatly affects the surface energy balance, fundamentally changing the partitioning of incoming solar radiation between the subsurface and the atmosphere. This has significant effects on soil moisture and temperature, with implications for vegetation and decomposition. Resolving temporal variability is especially important in spring, when early warm days can alter the onset of snowmelt by days to weeks. We show that high-resolution simulations are valuable in evaluating current land models, especially in areas of polygonal ground. This work was supported by LANL Laboratory Directed Research and Development Project LDRD201200068DR and by the The Next-Generation Ecosystem Experiments (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the DOE Office of Science. LA-UR-14-26227.

An estimation method of the direct benefit of a waterlogging control project applicable to the changing environment

NASA Astrophysics Data System (ADS)

Zengmei, L.; Guanghua, Q.; Zishen, C.

2015-05-01

The direct benefit of a waterlogging control project is reflected by the reduction or avoidance of waterlogging loss. Before and after the construction of a waterlogging control project, the disaster-inducing environment in the waterlogging-prone zone is generally different. In addition, the category, quantity and spatial distribution of the disaster-bearing bodies are also changed more or less. Therefore, under the changing environment, the direct benefit of a waterlogging control project should be the reduction of waterlogging losses compared to conditions with no control project. Moreover, the waterlogging losses with or without the project should be the mathematical expectations of the waterlogging losses when rainstorms of all frequencies meet various water levels in the drainage-accepting zone. So an estimation model of the direct benefit of waterlogging control is proposed. Firstly, on the basis of a Copula function, the joint distribution of the rainstorms and the water levels are established, so as to obtain their joint probability density function. Secondly, according to the two-dimensional joint probability density distribution, the dimensional domain of integration is determined, which is then divided into small domains so as to calculate the probability for each of the small domains and the difference between the average waterlogging loss with and without a waterlogging control project, called the regional benefit of waterlogging control project, under the condition that rainstorms in the waterlogging-prone zone meet the water level in the drainage-accepting zone. Finally, it calculates the weighted mean of the project benefit of all small domains, with probability as the weight, and gets the benefit of the waterlogging control project. Taking the estimation of benefit of a waterlogging control project in Yangshan County, Guangdong Province, as an example, the paper briefly explains the procedures in waterlogging control project benefit estimation. The results show that the waterlogging control benefit estimation model constructed is applicable to the changing conditions that occur in both the disaster-inducing environment of the waterlogging-prone zone and disaster-bearing bodies, considering all conditions when rainstorms of all frequencies meet different water levels in the drainage-accepting zone. Thus, the estimation method of waterlogging control benefit can reflect the actual situation more objectively, and offer a scientific basis for rational decision-making for waterlogging control projects.

Jordan Water Project: an interdisciplinary evaluation of freshwater vulnerability and security

NASA Astrophysics Data System (ADS)

Gorelick, S.; Yoon, J.; Rajsekhar, D.; Muller, M. F.; Zhang, H.; Gawel, E.; Klauer, B.; Klassert, C. J. A.; Sigel, K.; Thilmant, A.; Avisse, N.; Lachaut, T.; Harou, J. J.; Knox, S.; Selby, P. D.; Mustafa, D.; Talozi, S.; Haddad, Y.; Shamekh, M.

2016-12-01

The Jordan Water Project, part of the Belmont Forum projects, is an interdisciplinary, international research effort focused on evaluation of freshwater security in Jordan, one of the most water-vulnerable countries in the world. The team covers hydrology, water resources systems analysis, economics, policy evaluation, geography, risk and remote sensing analyses, and model platform development. The entire project team communally engaged in construction of an integrated hydroeconomic model for water supply policy evaluation. To represent water demand and allocation behavior at multiple levels of decision making,the model integrates biophysical modules that simulate natural and engineered hydrologic phenomena with human behavioral modules. Hydrologic modules include spatially-distributed groundwater and surface-water models for the major aquifers and watersheds throughout Jordan. For the human modules, we adopt a multi-agent modeling approach to represent decision-making processes. The integrated model was developed in Pynsim, a new open-source, object-oriented platform in Python for network-based water resource systems. We continue to explore the impacts of future scenarios and interventions.This project had tremendous encouragement and data support from Jordan's Ministry of Water and Irrigation. Modeling technology is being transferred through a companion NSF/USAID PEER project awarded toJordan University of Science and Technology. Individual teams have also conducted a range of studies aimed at evaluating Jordanian and transboundary surface water and groundwater systems. Surveys, interviews, and econometric analyses enabled us to better understandthe behavior of urban households, farmers, private water resellers, water use pattern of the commercial sector and irrigation water user associations. We analyzed nationwide spatial and temporal statistical trends in rainfall, developed urban and national comparative metrics to quantify water supply vulnerability, improved remote sensing methods to estimate crop-water use, and evaluated the impacts of climate change on future drought severity.

Enhanced Representation of Soil NO Emissions in the Community Multiscale Air Quality (CMAQ) Model Version 5.0.2

NASA Technical Reports Server (NTRS)

Rasool, Quazi Z.; Zhang, Rui; Lash, Benjamin; Cohan, Daniel S.; Cooter, Ellen J.; Bash, Jesse O.; Lamsal, Lok N.

2016-01-01

Modeling of soil nitric oxide (NO) emissions is highly uncertain and may misrepresent its spatial and temporal distribution. This study builds upon a recently introduced parameterization to improve the timing and spatial distribution of soil NO emission estimates in the Community Multiscale Air Quality (CMAQ) model. The parameterization considers soil parameters, meteorology, land use, and mineral nitrogen (N) availability to estimate NO emissions. We incorporate daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model to replace the annual generic data of the initial parameterization, and use a 12km resolution soil biome map over the continental USA. CMAQ modeling for July 2011 shows slight differences in model performance in simulating fine particulate matter and ozone from Interagency Monitoring of Protected Visual Environments (IMPROVE) and Clean Air Status and Trends Network (CASTNET) sites and NO2 columns from Ozone Monitoring Instrument (OMI) satellite retrievals. We also simulate how the change in soil NO emissions scheme affects the expected O3 response to projected emissions reductions.

Determination of the Changes of Drought Occurrence in Turkey Using Regional Climate Modeling

NASA Astrophysics Data System (ADS)

Sibel Saygili, Fatma; Tufan Turp, M.; Kurnaz, M. Levent

2017-04-01

As a consequence of the negative impacts of climate change, Turkey, being a country in the Mediterranean Basin, is under a serious risk of increased drought conditions. In this study, it is aimed to determine and compare the spatial distributions of climatological drought probabilities for Turkey. For this purpose, by making use of Regional Climate Model (RegCM4.4) of the Abdus Salam International Centre for Theoretical Physics (ICTP), the outputs of the MPI-ESM-MR global climate model of the Max Planck Institute for Meteorology are downscaled to 50km for Turkey. To make the future projection over Turkey for the period of 2071-2100 with respect to the reference period of 1986-2005, the worst case emission pathway RCP8.5 is used. The Palmer Drought Severity Index (PDSI) values are computed and classified in accordance with the seven classifications of National Oceanic and Atmospheric Administration (NOAA). Finally, the spatial distribution maps showing the changes in drought probabilities over Turkey are obtained in order to see the impact of climate change on Turkey's drought patterns.

Inter-comparison of multiple statistically downscaled climate datasets for the Pacific Northwest, USA

PubMed Central

Jiang, Yueyang; Kim, John B.; Still, Christopher J.; Kerns, Becky K.; Kline, Jeffrey D.; Cunningham, Patrick G.

2018-01-01

Statistically downscaled climate data have been widely used to explore possible impacts of climate change in various fields of study. Although many studies have focused on characterizing differences in the downscaling methods, few studies have evaluated actual downscaled datasets being distributed publicly. Spatially focusing on the Pacific Northwest, we compare five statistically downscaled climate datasets distributed publicly in the US: ClimateNA, NASA NEX-DCP30, MACAv2-METDATA, MACAv2-LIVNEH and WorldClim. We compare the downscaled projections of climate change, and the associated observational data used as training data for downscaling. We map and quantify the variability among the datasets and characterize the spatio-temporal patterns of agreement and disagreement among the datasets. Pair-wise comparisons of datasets identify the coast and high-elevation areas as areas of disagreement for temperature. For precipitation, high-elevation areas, rainshadows and the dry, eastern portion of the study area have high dissimilarity among the datasets. By spatially aggregating the variability measures into watersheds, we develop guidance for selecting datasets within the Pacific Northwest climate change impact studies. PMID:29461513

Inter-comparison of multiple statistically downscaled climate datasets for the Pacific Northwest, USA.

PubMed

Jiang, Yueyang; Kim, John B; Still, Christopher J; Kerns, Becky K; Kline, Jeffrey D; Cunningham, Patrick G

2018-02-20

Statistically downscaled climate data have been widely used to explore possible impacts of climate change in various fields of study. Although many studies have focused on characterizing differences in the downscaling methods, few studies have evaluated actual downscaled datasets being distributed publicly. Spatially focusing on the Pacific Northwest, we compare five statistically downscaled climate datasets distributed publicly in the US: ClimateNA, NASA NEX-DCP30, MACAv2-METDATA, MACAv2-LIVNEH and WorldClim. We compare the downscaled projections of climate change, and the associated observational data used as training data for downscaling. We map and quantify the variability among the datasets and characterize the spatio-temporal patterns of agreement and disagreement among the datasets. Pair-wise comparisons of datasets identify the coast and high-elevation areas as areas of disagreement for temperature. For precipitation, high-elevation areas, rainshadows and the dry, eastern portion of the study area have high dissimilarity among the datasets. By spatially aggregating the variability measures into watersheds, we develop guidance for selecting datasets within the Pacific Northwest climate change impact studies.

Unveiling Galaxy Bias via the Halo Model, KiDS and GAMA

NASA Astrophysics Data System (ADS)

Dvornik, Andrej; Hoekstra, Henk; Kuijken, Konrad; Schneider, Peter; Amon, Alexandra; Nakajima, Reiko; Viola, Massimo; Choi, Ami; Erben, Thomas; Farrow, Daniel J.; Heymans, Catherine; Hildebrandt, Hendrik; Sifón, Cristóbal; Wang, Lingyu

2018-06-01

We measure the projected galaxy clustering and galaxy-galaxy lensing signals using the Galaxy And Mass Assembly (GAMA) survey and Kilo-Degree Survey (KiDS) to study galaxy bias. We use the concept of non-linear and stochastic galaxy biasing in the framework of halo occupation statistics to constrain the parameters of the halo occupation statistics and to unveil the origin of galaxy biasing. The bias function Γgm(rp), where rp is the projected comoving separation, is evaluated using the analytical halo model from which the scale dependence of Γgm(rp), and the origin of the non-linearity and stochasticity in halo occupation models can be inferred. Our observations unveil the physical reason for the non-linearity and stochasticity, further explored using hydrodynamical simulations, with the stochasticity mostly originating from the non-Poissonian behaviour of satellite galaxies in the dark matter haloes and their spatial distribution, which does not follow the spatial distribution of dark matter in the halo. The observed non-linearity is mostly due to the presence of the central galaxies, as was noted from previous theoretical work on the same topic. We also see that overall, more massive galaxies reveal a stronger scale dependence, and out to a larger radius. Our results show that a wealth of information about galaxy bias is hidden in halo occupation models. These models should therefore be used to determine the influence of galaxy bias in cosmological studies.

The Boston Methane Project: Mapping Surface Emissions to Inform Atmospheric Estimation of Urban Methane Flux

NASA Astrophysics Data System (ADS)

Phillips, N.; Crosson, E.; Down, A.; Hutyra, L.; Jackson, R. B.; McKain, K.; Rella, C.; Raciti, S. M.; Wofsy, S. C.

2012-12-01

Lost and unaccounted natural gas can amount to over 6% of Massachusetts' total annual greenhouse gas inventory (expressed as equivalent CO2 tonnage). An unknown portion of this loss is due to natural gas leaks in pipeline distribution systems. The objective of the Boston Methane Project is to estimate the overall leak rate from natural gas systems in metropolitan Boston, and to compare this flux with fluxes from the other primary methane emissions sources. Companion talks at this meeting describe the atmospheric measurement and modeling framework, and chemical and isotopic tracers that can partition total atmospheric methane flux into natural gas and non-natural gas components. This talk focuses on estimation of surface emissions that inform the atmospheric modeling and partitioning. These surface emissions include over 3,300 pipeline natural gas leaks in Boston. For the state of Massachusetts as a whole, the amount of natural gas reported as lost and unaccounted for by utility companies was greater than estimated landfill emissions by an order of magnitude. Moreover, these landfill emissions were overwhelmingly located outside of metro Boston, while gas leaks are concentrated in exactly the opposite pattern, increasing from suburban Boston toward the urban core. Work is in progress to estimate spatial distribution of methane emissions from wetlands and sewer systems. We conclude with a description of how these spatial data sets will be combined and represented for application in atmospheric modeling.

Star Formation in Undergraduate ALFALFA Team Galaxy Groups and Clusters

NASA Astrophysics Data System (ADS)

Koopmann, Rebecca A.; Durbala, Adriana; Finn, Rose; Haynes, Martha P.; Coble, Kimberly A.; Craig, David W.; Hoffman, G. Lyle; Miller, Brendan P.; Crone-Odekon, Mary; O'Donoghue, Aileen A.; Troischt, Parker; Undergraduate ALFALFA Team; ALFALFA Team

2017-01-01

The Undergraduate ALFALFA Team (UAT) Groups project is a coordinated study of gas and star formation properties of galaxies in and around 36 nearby (z<0.03) groups and clusters of varied richness, morphological type mix, and X-ray luminosity. By studying a large range of environments and considering the spatial distributions of star formation, we probe mechanisms of gas depletion and morphological transformation. The project uses ALFALFA HI observations, optical observations, and digital databases like SDSS, and incorporates work undertaken by faculty and students at different institutions within the UAT. Here we present results from our wide area Hα and broadband R imaging project carried out with the WIYN 0.9m+MOSAIC/HDI at KPNO, including an analysis of radial star formation rates and extents of galaxies in the NGC 5846, Abell 779, NRGb331, and HCG 69 groups/clusters. This work has been supported by NSF grant AST-1211005 and AST-1637339.

Bigfoot Field Manual, Version 2.1

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

Campbell, J.L.; Burrows, S.; Gower, S.T.

1999-09-01

The BigFoot Project is funded by the Earth Science Enterprise to collect and organize data to be used in the National Aeronautics and Space Administration's Earth Observing System (EOS) Validation Program. The data collected by the BigFoot Project are unique in being ground-based observations coincident with satellite overpasses. In addition to collecting data, the BigFoot project will develop and test new algorithms for scaling point measurements to the same spatial scales as the EOS satellite products. This BigFoot Field Manual will be used to achieve completeness and consistency of data collected at four initial BigFoot sites and at future sitesmore » that may collect similar validation data. Therefore, validation datasets submitted to the Oak Ridge National Laboratory Distributed Active Archive Center that have been compiled in a manner consistent with the field manual will be especially valuable in the validation program.« less

The effects of climate downscaling technique and observational data set on modeled ecological responses.

PubMed

Pourmokhtarian, Afshin; Driscoll, Charles T; Campbell, John L; Hayhoe, Katharine; Stoner, Anne M K

2016-07-01

Assessments of future climate change impacts on ecosystems typically rely on multiple climate model projections, but often utilize only one downscaling approach trained on one set of observations. Here, we explore the extent to which modeled biogeochemical responses to changing climate are affected by the selection of the climate downscaling method and training observations used at the montane landscape of the Hubbard Brook Experimental Forest, New Hampshire, USA. We evaluated three downscaling methods: the delta method (or the change factor method), monthly quantile mapping (Bias Correction-Spatial Disaggregation, or BCSD), and daily quantile regression (Asynchronous Regional Regression Model, or ARRM). Additionally, we trained outputs from four atmosphere-ocean general circulation models (AOGCMs) (CCSM3, HadCM3, PCM, and GFDL-CM2.1) driven by higher (A1fi) and lower (B1) future emissions scenarios on two sets of observations (1/8º resolution grid vs. individual weather station) to generate the high-resolution climate input for the forest biogeochemical model PnET-BGC (eight ensembles of six runs).The choice of downscaling approach and spatial resolution of the observations used to train the downscaling model impacted modeled soil moisture and streamflow, which in turn affected forest growth, net N mineralization, net soil nitrification, and stream chemistry. All three downscaling methods were highly sensitive to the observations used, resulting in projections that were significantly different between station-based and grid-based observations. The choice of downscaling method also slightly affected the results, however not as much as the choice of observations. Using spatially smoothed gridded observations and/or methods that do not resolve sub-monthly shifts in the distribution of temperature and/or precipitation can produce biased results in model applications run at greater temporal and/or spatial resolutions. These results underscore the importance of carefully considering field observations used for training, as well as the downscaling method used to generate climate change projections, for smaller-scale modeling studies. Different sources of variability including selection of AOGCM, emissions scenario, downscaling technique, and data used for training downscaling models, result in a wide range of projected forest ecosystem responses to future climate change. © 2016 by the Ecological Society of America.

[Spatial distribution pattern of Pontania dolichura larvae and sampling technique].

PubMed

Zhang, Feng; Chen, Zhijie; Zhang, Shulian; Zhao, Huiyan

2006-03-01

In this paper, the spatial distribution pattern of Pontania dolichura larvae was analyzed with Taylor's power law, Iwao's distribution function, and six aggregation indexes. The results showed that the spatial distribution pattern of P. dolichura larvae was of aggregated, and the basic component of the distribution was individual colony, with the aggregation intensity increased with density. On branches, the aggregation was caused by the adult behavior of laying eggs and the spatial position of leaves, while on leaves, the aggregation was caused by the spatial position of news leaves in spring when m < 2.37, and by the spatial position of news leaves in spring and the behavior of eclosion and laying eggs when m > 2.37. By using the parameters alpha and beta in Iwao's m * -m regression equation, the optimal and sequential sampling numbers were determined.

Inner membrane fusion mediates spatial distribution of axonal mitochondria

PubMed Central

Yu, Yiyi; Lee, Hao-Chih; Chen, Kuan-Chieh; Suhan, Joseph; Qiu, Minhua; Ba, Qinle; Yang, Ge

2016-01-01

In eukaryotic cells, mitochondria form a dynamic interconnected network to respond to changing needs at different subcellular locations. A fundamental yet unanswered question regarding this network is whether, and if so how, local fusion and fission of individual mitochondria affect their global distribution. To address this question, we developed high-resolution computational image analysis techniques to examine the relations between mitochondrial fusion/fission and spatial distribution within the axon of Drosophila larval neurons. We found that stationary and moving mitochondria underwent fusion and fission regularly but followed different spatial distribution patterns and exhibited different morphology. Disruption of inner membrane fusion by knockdown of dOpa1, Drosophila Optic Atrophy 1, not only increased the spatial density of stationary and moving mitochondria but also changed their spatial distributions and morphology differentially. Knockdown of dOpa1 also impaired axonal transport of mitochondria. But the changed spatial distributions of mitochondria resulted primarily from disruption of inner membrane fusion because knockdown of Milton, a mitochondrial kinesin-1 adapter, caused similar transport velocity impairment but different spatial distributions. Together, our data reveals that stationary mitochondria within the axon interconnect with moving mitochondria through fusion and fission and that local inner membrane fusion between individual mitochondria mediates their global distribution. PMID:26742817

Development of a module for Cost-Benefit analysis of risk reduction measures for natural hazards for the CHANGES-SDSS platform

NASA Astrophysics Data System (ADS)

Berlin, Julian; Bogaard, Thom; Van Westen, Cees; Bakker, Wim; Mostert, Eric; Dopheide, Emile

2014-05-01

Cost benefit analysis (CBA) is a well know method used widely for the assessment of investments either in the private and public sector. In the context of risk mitigation and the evaluation of risk reduction alternatives for natural hazards its use is very important to evaluate the effectiveness of such efforts in terms of avoided monetary losses. However the current method has some disadvantages related to the spatial distribution of the costs and benefits, the geographical distribution of the avoided damage and losses, the variation in areas that are benefited in terms of invested money and avoided monetary risk. Decision-makers are often interested in how the costs and benefits are distributed among different administrative units of a large area or region, so they will be able to compare and analyse the cost and benefits per administrative unit as a result of the implementation of the risk reduction projects. In this work we first examined the Cost benefit procedure for natural hazards, how the costs are assessed for several structural and non-structural risk reduction alternatives, we also examined the current problems of the method such as the inclusion of cultural and social considerations that are complex to monetize , the problem of discounting future values using a defined interest rate and the spatial distribution of cost and benefits. We also examined the additional benefits and the indirect costs associated with the implementation of the risk reduction alternatives such as the cost of having a ugly landscape (also called negative benefits). In the last part we examined the current tools and software used in natural hazards assessment with support to conduct CBA and we propose design considerations for the implementation of the CBA module for the CHANGES-SDSS Platform an initiative of the ongoing 7th Framework Programme "CHANGES of the European commission. Keywords: Risk management, Economics of risk mitigation, EU Flood Directive, resilience, prevention, cost benefit analysis, spatial distribution of costs and benefits

Climate change impact on the establishment and seasonal abundance of Invasive Mosquito Species: current state and future risk maps over southeast Europe

NASA Astrophysics Data System (ADS)

Tagaris, Efthimios; -Eleni Sotiropoulou, Rafaella; Sotiropoulos, Andreas; Spanos, Ioannis; Milonas, Panayiotis; Michaelakis, Antonios

2017-04-01

Establishment and seasonal abundance of a region for Invasive Mosquito Species (IMS) are related to climatic parameters such as temperature and precipitation. In this work the current state is assessed using data from the European Climate Assessment and Dataset (ECA&D) project over Greece and Italy for the development of current spatial risk databases of IMS. Results are validated from the installation of a prototype IMS monitoring device that has been designed and developed in the framework of the LIFE CONOPS project at key points across the two countries. Since climate models suggest changes in future temperature and precipitation rates, the future potentiality of IMS establishment and spread over Greece and Italy is assessed using the climatic parameters in 2050's provided by the NASA GISS GCM ModelE under the IPCC-A1B emissions scenarios. The need for regional climate projections in a finer grid size is assessed using the Weather Research and Forecasting (WRF) model to dynamically downscale GCM simulations. The estimated changes in the future meteorological parameters are combined with the observation data in order to estimate the future levels of the climatic parameters of interest. The final product includes spatial distribution maps presenting the future suitability of a region for the establishment and seasonal abundance of the IMS over Greece and Italy. Acknowledgement: LIFE CONOPS project "Development & demonstration of management plans against - the climate change enhanced - invasive mosquitoes in S. Europe" (LIFE12 ENV/GR/000466).

Unbiased methods for removing systematics from galaxy clustering measurements

NASA Astrophysics Data System (ADS)

Elsner, Franz; Leistedt, Boris; Peiris, Hiranya V.

2016-02-01

Measuring the angular clustering of galaxies as a function of redshift is a powerful method for extracting information from the three-dimensional galaxy distribution. The precision of such measurements will dramatically increase with ongoing and future wide-field galaxy surveys. However, these are also increasingly sensitive to observational and astrophysical contaminants. Here, we study the statistical properties of three methods proposed for controlling such systematics - template subtraction, basic mode projection, and extended mode projection - all of which make use of externally supplied template maps, designed to characterize and capture the spatial variations of potential systematic effects. Based on a detailed mathematical analysis, and in agreement with simulations, we find that the template subtraction method in its original formulation returns biased estimates of the galaxy angular clustering. We derive closed-form expressions that should be used to correct results for this shortcoming. Turning to the basic mode projection algorithm, we prove it to be free of any bias, whereas we conclude that results computed with extended mode projection are biased. Within a simplified setup, we derive analytical expressions for the bias and discuss the options for correcting it in more realistic configurations. Common to all three methods is an increased estimator variance induced by the cleaning process, albeit at different levels. These results enable unbiased high-precision clustering measurements in the presence of spatially varying systematics, an essential step towards realizing the full potential of current and planned galaxy surveys.

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience.

PubMed

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R; Bock, Davi D; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R Clay; Smith, Stephen J; Szalay, Alexander S; Vogelstein, Joshua T; Vogelstein, R Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes - neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience

PubMed Central

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R.; Bock, Davi D.; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C.; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R. Clay; Smith, Stephen J.; Szalay, Alexander S.; Vogelstein, Joshua T.; Vogelstein, R. Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes— neural connectivity maps of the brain—using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems—reads to parallel disk arrays and writes to solid-state storage—to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization. PMID:24401992

Spatial and temporal variability of soil temperature, moisture and surface soil properties

NASA Technical Reports Server (NTRS)

Hajek, B. F.; Dane, J. H.

1993-01-01

The overall objectives of this research were to: (l) Relate in-situ measured soil-water content and temperature profiles to remotely sensed surface soil-water and temperature conditions; to model simultaneous heat and water movement for spatially and temporally changing soil conditions; (2) Determine the spatial and temporal variability of surface soil properties affecting emissivity, reflectance, and material and energy flux across the soil surface. This will include physical, chemical, and mineralogical characteristics of primary soil components and aggregate systems; and (3) Develop surface soil classes of naturally occurring and distributed soil property assemblages and group classes to be tested with respect to water content, emissivity and reflectivity. This document is a report of studies conducted during the period funded by NASA grants. The project was designed to be conducted over a five year period. Since funding was discontinued after three years, some of the research started was not completed. Additional publications are planned whenever funding can be obtained to finalize data analysis for both the arid and humid locations.

Change detection analysis of multi-temporal imagery to assess environmental development on AL Sammalyah Island, Abu-Dhabi

NASA Astrophysics Data System (ADS)

Essa, Salem M.; Loughland, R.; Khogali, Mohamed E.

2005-10-01

AL Sammalyah Island is considered an important protected area in Abu Dhabi Emirate. The island has witnessed high rates of change in land use in the past few years starting from the early 1990s. Change detection analysis is conducted to monitor rate and spatial distribution of change occurring on the island. A three-phase research project has been implemented, an integrated Geographic Information System (GIS) database for the Island is the focus; the current phase main objective was to assess rate and spatial distribution of the change on the island using multi-date large scale aerial photos. Results of the current study demonstrated that total vegetation cover extent has increased from 3.742 km2 in 1994 to 5.101 km2 in 2005, an increase of 36.3% between 1994 and 2005. The study also showed that this increase in vegetation extent is mostly attributed to the increase in mangrove planted areas with an increase from 2.256 km2 in 1994 to 3.568 km2 in 2005, an increase of 58.2% in ten years. Remote sensing and GIS have been successfully used to quantify change extent, distribution and trajectories of change. The next step will be to complete the GIS database for AL Sammalyah Island.

Remote rainfall sensing for landslide hazard analysis

USGS Publications Warehouse

Wieczorek, Gerald F.; McWreath, Harry; Davenport, Clay

2001-01-01

Methods of assessing landslide hazards and providing warnings are becoming more advanced as remote sensing of rainfall provides more detailed temporal and spatial data on rainfall distribution. Two recent landslide disasters are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. For the June 27, 1995, storm in Madison County, Virginia, USA, National Weather Service WSR-88D Doppler radar provided rainfall estimates based on a relation between cloud reflectivity and moisture content on a 1 sq. km. resolution every 6 minutes. Ground-based measurements of rainfall intensity and precipitation total, in addition to landslide timing and distribution, were compared with the radar-derived rainfall data. For the December 14-16, 1999, storm in Vargas State, Venezuela, infrared sensing from the GOES-8 satellite of cloud top temperatures provided the basis for NOAA/NESDIS rainfall estimates on a 16 sq. km. resolution every 30 minutes. These rainfall estimates were also compared with ground-based measurements of rainfall and landslide distribution. In both examples, the remotely sensed data either overestimated or underestimated ground-based values by up to a factor of 2. The factors that influenced the accuracy of rainfall data include spatial registration and map projection, as well as prevailing wind direction, cloud orientation, and topography.

Projected changes in the evolution of drought assessed with the SPEI over the Czech Republic

NASA Astrophysics Data System (ADS)

Potop, V.; Boroneana, C.; Stepanek, P.; Skalak, P.; Mozny, M.

2012-04-01

In previous studies the spatial and temporal evolution of drought events in the Czech Republic were extensively analyzed by comparing results from the most advanced drought indices (e.g. the SPI and SPEI), which take into account the role of antecedent conditions in quantifying drought severity. In the present study, the Standardized Precipitation Evapotranspiration Index (SPEI) was adopted to assess and project drought characteristics in the Czech Republic based on the regional climate model ALADIN-Climate/CZ simulated data. The simulations were conducted at high resolution (10km) for the current (1961-2000) and two future climates (2021-2050 and 2071-2100). First, the observed data of air temperature and precipitation totals was transferred into a regular grid of ALADIN-Climate/CZ model. The bias correction was applied on the scenario runs. The bias correction method is based on variable correction using individual percentiles whose relationship is derived from observations and control RCM simulation. The SPEI was calculated based on observed monthly data of mean temperature and precipitation totals for the period 1961-1990, as reference period, and for the periods 2021-2050 and 2071-2100, as future climates under A1B SRES scenario. The SPEI were calculated with various lags, 1, 3, 6, 12 and 24 months because the drought at these time scales is relevant for agricultural, hydrological and socio-economic impact, respectively. The study refers at the warm season of the year (April to September). As in the case of observational study, we have identified three climatically homogeneous regions, corresponding to the altitudes below 400 m, between 401 and 700 m and, above 700 m. For these three regions the frequency distribution of the SPEI values in 7 classes of drought category (%) were calculated based on grid point data falling in each region, both for the observed data and scenario runs. The paper presents the projected changes in frequency distribution of SPEI at various time scales, in intensity, duration and spatial distribution of drought over the territory of the Czech Republic under A1B scenario for the middle and the end of 21st century. We gratefully acknowledge the support of the Ministry of Education, Youth and Sports for projects OC10010.

Distributed Research Center for Analysis of Regional Climatic Changes and Their Impacts on Environment

NASA Astrophysics Data System (ADS)

Shiklomanov, A. I.; Okladnikov, I.; Gordov, E. P.; Proussevitch, A. A.; Titov, A. G.

2016-12-01

Presented is a collaborative project carrying out by joint team of researchers from the Institute of Monitoring of Climatic and Ecological Systems, Russia and Earth Systems Research Center, University of New Hampshire, USA. Its main objective is development of a hardware and software prototype of Distributed Research Center (DRC) for monitoring and projecting of regional climatic and and their impacts on the environment over the Northern extratropical areas. In the framework of the project new approaches to "cloud" processing and analysis of large geospatial datasets (big geospatial data) are being developed. It will be deployed on technical platforms of both institutions and applied in research of climate change and its consequences. Datasets available at NCEI and IMCES include multidimensional arrays of climatic, environmental, demographic, and socio-economic characteristics. The project is aimed at solving several major research and engineering tasks: 1) structure analysis of huge heterogeneous climate and environmental geospatial datasets used in the project, their preprocessing and unification; 2) development of a new distributed storage and processing model based on a "shared nothing" paradigm; 3) development of a dedicated database of metadata describing geospatial datasets used in the project; 4) development of a dedicated geoportal and a high-end graphical frontend providing intuitive user interface, internet-accessible online tools for analysis of geospatial data and web services for interoperability with other geoprocessing software packages. DRC will operate as a single access point to distributed archives of spatial data and online tools for their processing. Flexible modular computational engine running verified data processing routines will provide solid results of geospatial data analysis. "Cloud" data analysis and visualization approach will guarantee access to the DRC online tools and data from all over the world. Additionally, exporting of data processing results through WMS and WFS services will be used to provide their interoperability. Financial support of this activity by the RF Ministry of Education and Science under Agreement 14.613.21.0037 (RFMEFI61315X0037) and by the Iola Hubbard Climate Change Endowment is acknowledged.

GENESI-DR Portal: a scientific gateway to distributed repositories

NASA Astrophysics Data System (ADS)

Goncalves, Pedro; Brito, Fabrice; D'Andria, Fabio; Cossu, Roberto; Fusco, Luigi

2010-05-01

GENESI-DR (Ground European Network for Earth Science Interoperations - Digital Repositories) is a European Commission (EC)-funded project, kicked-off early 2008 lead by ESA; partners include Space Agencies (DLR, ASI, CNES), both space and no-space data providers such as ENEA (I), Infoterra (UK), K-SAT (N), NILU (N), JRC (EU) and industry as Elsag Datamat (I), CS (F) and TERRADUE (I). GENESI-DR intends to meet the challenge of facilitating "time to science" from different Earth Science disciplines in discovery, access and use (combining, integrating, processing, …) of historical and recent Earth-related data from space, airborne and in-situ sensors, which are archived in large distributed repositories. "Discovering" which data are available on a "geospatial web" is one of the main challenges ES scientists have to face today. Some well- known data sets are referred to in many places, available from many sources. For core information with a common purpose many copies are distributed, e.g., VMap0, Landsat, and SRTM. Other data sets in low or local demand may only be found in a few places and niche communities. Relevant services, results of analysis, applications and tools are accessible in a very scattered and uncoordinated way, often through individual initiatives from Earth Observation mission operators, scientific institutes dealing with ground measurements, service companies or data catalogues. In the discourse of Spatial Data Infrastructures, there are "catalogue services" - directories containing information on where spatial data and services can be found. For metadata "records" describing spatial data and services, there are "registries". The Geospatial industry coins specifications for search interfaces, where it might do better to reach out to other information retrieval and Internet communities. These considerations are the basis for the GENESI-DR scientific portal, which adopts a simple model allowing the geo-spatial classification and discovery of information as a loosely connected federation of nodes. This network had however to be resilient to node failures and able to scale with the growing addition of new information about data and services. The GENESI-DR scientific portal is still evolving as the project deploys the different components amongst the different partners, but the aim is to provide the connection to information, establish rights, access it and in some cases apply algorithms using the computer power available on the infrastructure with simple interfaces. As information is discovered in the network, it can be further exploited, filtered or enhanced according to the user goals. To implement this vision two specialized graphical interfaces were designed on the portal. The first, concentrates on the text-based search of information, while the second is a command and control of submission and order status on a distributed processing environment. The text search uses natural language features that extract the spatial temporal components from the user query. This is then propagated to the nodes by mapping them to OpenSearch extensions, and then returned to the user as an aggregated list of the resources. These can either be access points to dataset series or services that can be further analysed and processed. At this stage, the user is presented with dedicated interfaces that correspond to context of the action that is performing. Be it a bulk data download, data processing or data mining, the different services offer specialized interfaces that are integrated on the portal. In the overall, the GENESI-DR project identifies best practices and supporting context for the use of a minimal abstract model to loosely connect a federation of Digital Repositories. Surpassing the apparent lack of cost effectiveness of the Spatial Data Infrastructures effort in developing "catalogue services" is achieved by trimming the use cases to the most common and relevant. The GENESI-DR scientific portal is, as such, the visible front-end of a dedicated infrastructure providing transparent access to information and allowing Earth Science communities to easily and quickly derive objective information and share knowledge based on all environmentally sensitive domains.

Simulation of climate change in San Francisco Bay Basins, California: Case studies in the Russian River Valley and Santa Cruz Mountains

USGS Publications Warehouse

Flint, Lorraine E.; Flint, Alan L.

2012-01-01

As a result of ongoing changes in climate, hydrologic and ecologic effects are being seen across the western United States. A regional study of how climate change affects water resources and habitats in the San Francisco Bay area relied on historical climate data and future projections of climate, which were downscaled to fine spatial scales for application to a regional water-balance model. Changes in climate, potential evapotranspiration, recharge, runoff, and climatic water deficit were modeled for the Bay Area. In addition, detailed studies in the Russian River Valley and Santa Cruz Mountains, which are on the northern and southern extremes of the Bay Area, respectively, were carried out in collaboration with local water agencies. Resource managers depend on science-based projections to inform planning exercises that result in competent adaptation to ongoing and future changes in water supply and environmental conditions. Results indicated large spatial variability in climate change and the hydrologic response across the region; although there is warming under all projections, potential change in precipitation by the end of the 21st century differed according to model. Hydrologic models predicted reduced early and late wet season runoff for the end of the century for both wetter and drier future climate projections, which could result in an extended dry season. In fact, summers are projected to be longer and drier in the future than in the past regardless of precipitation trends. While water supply could be subject to increased variability (that is, reduced reliability) due to greater variability in precipitation, water demand is likely to steadily increase because of increased evapotranspiration rates and climatic water deficit during the extended summers. Extended dry season conditions and the potential for drought, combined with unprecedented increases in precipitation, could serve as additional stressors on water quality and habitat. By focusing on the relationship between soil moisture storage and evapotranspiration pressures, climatic water deficit integrates the effects of increasing temperature and varying precipitation on basin conditions. At the fine-scale used for these analyses, this variable is an effective indicator of the areas in the landscape that are the most resilient or vulnerable to projected changes. These analyses have shown that regardless of the direction of precipitation change, climatic water deficit is projected to increase, which implies greater water demand to maintain current agricultural resources or land cover. Fine-scale modeling provides a spatially distributed view of locations in the landscape that could prove to be resilient to climatic changes in contrast to locations where vegetation is currently living on the edge of its present-day bioclimatic distribution and, therefore, is more likely to perish or shift to other dominant species under future warming. This type of modeling and the associated analyses provide a useful means for greater understanding of water and land resources, which can lead to better resource management and planning.

Ordinary kriging vs inverse distance weighting: spatial interpolation of the sessile community of Madagascar reef, Gulf of Mexico.

PubMed

Zarco-Perello, Salvador; Simões, Nuno

2017-01-01

Information about the distribution and abundance of the habitat-forming sessile organisms in marine ecosystems is of great importance for conservation and natural resource managers. Spatial interpolation methodologies can be useful to generate this information from in situ sampling points, especially in circumstances where remote sensing methodologies cannot be applied due to small-scale spatial variability of the natural communities and low light penetration in the water column. Interpolation methods are widely used in environmental sciences; however, published studies using these methodologies in coral reef science are scarce. We compared the accuracy of the two most commonly used interpolation methods in all disciplines, inverse distance weighting (IDW) and ordinary kriging (OK), to predict the distribution and abundance of hard corals, octocorals, macroalgae, sponges and zoantharians and identify hotspots of these habitat-forming organisms using data sampled at three different spatial scales (5, 10 and 20 m) in Madagascar reef, Gulf of Mexico. The deeper sandy environments of the leeward and windward regions of Madagascar reef were dominated by macroalgae and seconded by octocorals. However, the shallow rocky environments of the reef crest had the highest richness of habitat-forming groups of organisms; here, we registered high abundances of octocorals and macroalgae, with sponges, Millepora alcicornis and zoantharians dominating in some patches, creating high levels of habitat heterogeneity. IDW and OK generated similar maps of distribution for all the taxa; however, cross-validation tests showed that IDW outperformed OK in the prediction of their abundances. When the sampling distance was at 20 m, both interpolation techniques performed poorly, but as the sampling was done at shorter distances prediction accuracies increased, especially for IDW. OK had higher mean prediction errors and failed to correctly interpolate the highest abundance values measured in situ , except for macroalgae, whereas IDW had lower mean prediction errors and high correlations between predicted and measured values in all cases when sampling was every 5 m. The accurate spatial interpolations created using IDW allowed us to see the spatial variability of each taxa at a biological and spatial resolution that remote sensing would not have been able to produce. Our study sets the basis for further research projects and conservation management in Madagascar reef and encourages similar studies in the region and other parts of the world where remote sensing technologies are not suitable for use.

Ordinary kriging vs inverse distance weighting: spatial interpolation of the sessile community of Madagascar reef, Gulf of Mexico

PubMed Central

Simões, Nuno

2017-01-01

Information about the distribution and abundance of the habitat-forming sessile organisms in marine ecosystems is of great importance for conservation and natural resource managers. Spatial interpolation methodologies can be useful to generate this information from in situ sampling points, especially in circumstances where remote sensing methodologies cannot be applied due to small-scale spatial variability of the natural communities and low light penetration in the water column. Interpolation methods are widely used in environmental sciences; however, published studies using these methodologies in coral reef science are scarce. We compared the accuracy of the two most commonly used interpolation methods in all disciplines, inverse distance weighting (IDW) and ordinary kriging (OK), to predict the distribution and abundance of hard corals, octocorals, macroalgae, sponges and zoantharians and identify hotspots of these habitat-forming organisms using data sampled at three different spatial scales (5, 10 and 20 m) in Madagascar reef, Gulf of Mexico. The deeper sandy environments of the leeward and windward regions of Madagascar reef were dominated by macroalgae and seconded by octocorals. However, the shallow rocky environments of the reef crest had the highest richness of habitat-forming groups of organisms; here, we registered high abundances of octocorals and macroalgae, with sponges, Millepora alcicornis and zoantharians dominating in some patches, creating high levels of habitat heterogeneity. IDW and OK generated similar maps of distribution for all the taxa; however, cross-validation tests showed that IDW outperformed OK in the prediction of their abundances. When the sampling distance was at 20 m, both interpolation techniques performed poorly, but as the sampling was done at shorter distances prediction accuracies increased, especially for IDW. OK had higher mean prediction errors and failed to correctly interpolate the highest abundance values measured in situ, except for macroalgae, whereas IDW had lower mean prediction errors and high correlations between predicted and measured values in all cases when sampling was every 5 m. The accurate spatial interpolations created using IDW allowed us to see the spatial variability of each taxa at a biological and spatial resolution that remote sensing would not have been able to produce. Our study sets the basis for further research projects and conservation management in Madagascar reef and encourages similar studies in the region and other parts of the world where remote sensing technologies are not suitable for use. PMID:29204321

Projective rectification of infrared images from air-cooled condenser temperature measurement by using projection profile features and cross-ratio invariability.

PubMed

Xu, Lijun; Chen, Lulu; Li, Xiaolu; He, Tao

2014-10-01

In this paper, we propose a projective rectification method for infrared images obtained from the measurement of temperature distribution on an air-cooled condenser (ACC) surface by using projection profile features and cross-ratio invariability. In the research, the infrared (IR) images acquired by the four IR cameras utilized are distorted to different degrees. To rectify the distorted IR images, the sizes of the acquired images are first enlarged by means of bicubic interpolation. Then, uniformly distributed control points are extracted in the enlarged images by constructing quadrangles with detected vertical lines and detected or constructed horizontal lines. The corresponding control points in the anticipated undistorted IR images are extracted by using projection profile features and cross-ratio invariability. Finally, a third-order polynomial rectification model is established and the coefficients of the model are computed with the mapping relationship between the control points in the distorted and anticipated undistorted images. Experimental results obtained from an industrial ACC unit show that the proposed method performs much better than any previous method we have adopted. Furthermore, all rectified images are stitched together to obtain a complete image of the whole ACC surface with a much higher spatial resolution than that obtained by using a single camera, which is not only useful but also necessary for more accurate and comprehensive analysis of ACC performance and more reliable optimization of ACC operations.

Distributions of ectomycorrhizal and foliar endophytic fungal communities associated with Pinus ponderosa along a spatially constrained elevation gradient.

PubMed

Bowman, Elizabeth A; Arnold, A Elizabeth

2018-04-01

Understanding distributions of plant-symbiotic fungi is important for projecting responses to environmental change. Many coniferous trees host ectomycorrhizal fungi (EM) in association with roots and foliar endophytic fungi (FE) in leaves. We examined how EM and FE associated with Pinus ponderosa each vary in abundance, diversity, and community structure over a spatially constrained elevation gradient that traverses four plant communities, 4°C in mean annual temperature, and 15 cm in mean annual precipitation. We sampled 63 individuals of Pinus ponderosa in 10 sites along a 635 m elevation gradient that encompassed a geographic distance of 9.8 km. We used standard methods to characterize each fungal group (amplified and sequenced EM from root tips; isolated and sequenced FE from leaves). Abundance and diversity of EM were similar across sites, but community composition and distributions of the most common EM differed with elevation (i.e., with climate, soil chemistry, and plant communities). Abundance and composition of FE did not differ with elevation, but diversity peaked in mid-to-high elevations. Our results suggest relatively tight linkages between EM and climate, soil chemistry, and plant communities. That FE appear less linked with these factors may speak to limitations of a culture-based approach, but more likely reflects the small spatial scale encompassed by our study. Future work should consider comparable methods for characterizing these functional groups, and additional transects to understand relationships of EM and FE to environmental factors that are likely to shift as a function of climate change. © 2018 Botanical Society of America.

Present and future assessment of growing degree days over selected Greek areas with different climate conditions

NASA Astrophysics Data System (ADS)

Paparrizos, Spyridon; Matzarakis, Andreas

2017-10-01

The determination of heat requirements in the first developing phases of plants has been expressed as Growing Degree Days (GDD). The current study focuses on three selected study areas in Greece that are characterised by different climatic conditions due to their location and aims to assess the future variation and spatial distribution of Growing Degree Days (GDD) and how these can affect the main cultivations in the study areas. Future temperature data were obtained and analysed by the ENSEMBLES project. The analysis was performed for the future periods 2021-2050 and 2071-2100 with the A1B and B1 scenarios. Spatial distribution was performed using a combination of dynamical and statistical downscaling technique through ArcGIS 10.2.1. The results indicated that for all the future periods and scenarios, the GDD are expected to increase. Furthermore, the increase in the Sperchios River basin will be the highest, followed by the Ardas and the Geropotamos River basins. Moreover, the cultivation period will be shifted from April-October to April-September which will have social, economical and environmental benefits. Additionally, the spatial distribution indicated that in the upcoming years the existing cultivations can find favourable conditions and can be expanded in mountainous areas as well. On the other hand, due to the rough topography that exists in the study areas, the wide expansion of the existing cultivations into higher altitudes is unaffordable. Nevertheless, new more profitable cultivations can be introduced which can find propitious conditions in terms of GDD.

A Modular GIS-Based Software Architecture for Model Parameter Estimation using the Method of Anchored Distributions (MAD)

NASA Astrophysics Data System (ADS)

Ames, D. P.; Osorio-Murillo, C.; Over, M. W.; Rubin, Y.

2012-12-01

The Method of Anchored Distributions (MAD) is an inverse modeling technique that is well-suited for estimation of spatially varying parameter fields using limited observations and Bayesian methods. This presentation will discuss the design, development, and testing of a free software implementation of the MAD technique using the open source DotSpatial geographic information system (GIS) framework, R statistical software, and the MODFLOW groundwater model. This new tool, dubbed MAD-GIS, is built using a modular architecture that supports the integration of external analytical tools and models for key computational processes including a forward model (e.g. MODFLOW, HYDRUS) and geostatistical analysis (e.g. R, GSLIB). The GIS-based graphical user interface provides a relatively simple way for new users of the technique to prepare the spatial domain, to identify observation and anchor points, to perform the MAD analysis using a selected forward model, and to view results. MAD-GIS uses the Managed Extensibility Framework (MEF) provided by the Microsoft .NET programming platform to support integration of different modeling and analytical tools at run-time through a custom "driver." Each driver establishes a connection with external programs through a programming interface, which provides the elements for communicating with core MAD software. This presentation gives an example of adapting the MODFLOW to serve as the external forward model in MAD-GIS for inferring the distribution functions of key MODFLOW parameters. Additional drivers for other models are being developed and it is expected that the open source nature of the project will engender the development of additional model drivers by 3rd party scientists.

Rainwater content estimated using polarimetric radar parameters in the Heihe River Basin

NASA Astrophysics Data System (ADS)

Zhao, Guo; Chu, Rongzhong; Zhang, Tong; Jia, Wei

2013-02-01

The rainwater content of cold and arid regions has strong spatial and temporal heterogeneity. Representing rainwater content at high resolution can help us understand the characteristics of inland river basin water cycles and improve the prediction accuracy of hydrological models. Data were used from the Watershed Allied Telemetry Experimental Research (WATER) project of the Heihe River Basin, which is the second largest inland river basin in the arid regions of northwest China. We used raindrop size distributions to improve the rain water content estimation of meteorological radar and to obtain accurate rain water content data in this area. Subsequently, four estimation methods applied in the polarimetric radar were tested. The results of a non-linear regression method show that M(KDP, ZH, ZDR) has the highest accuracy for measuring rain water content. Finally, the formula for measuring the spatial rain water content was applied to a polarimetric radar with an X-band (714XDP). The influence of raindrop size distribution (DSD) on the formula M(KDP, ZH, ZDR) is lowest sensitivity, and it can be explained as follows. On the one hand, the horizontal and vertical front reflection cross sections of the radar are different, so KDP is proportional to the 3rd power of the raindrop diameter. On the other hand, the rear cross section of the radar is proportional to the sixth power of the raindrop diameter. The rainfall's spatial water content M is proportional to the 3rd power of the raindrop diameter, so the influence of the drop size distribution (DSD) on KDP is much smaller than that of ZH.

A High Spatial Resolution Study of Far IR Emission of Galaxies

NASA Technical Reports Server (NTRS)

Caldwell, Barrie A.

2000-01-01

This grant funded observations, data reduction, professional publications and travel for scientific efforts on the Kuiper Airborne Observatory. The research project was successfully completed. New insights into the distribution of far infrared emission across star forming regions was obtained, and student training was achieved. The efforts contributed towards new observing strategies, such as calibration and intercomparison of data from different infrared astronomical observing platforms, that will impact future NASA missions, such as SOFIA. The results of the effort have been presented in several papers in the refereed literature, including: "The Structure of IR Luminous Galaxies at 100 Microns". " Far Infrared Thermal Emission from the Inner Cooling Flow Region of NGC1275". "Distribution of Light in the "Dusty Hand" Galaxy NGC2146".

Neutron Microtomography of MgB2 Superconducting Multifilament Wire

NASA Astrophysics Data System (ADS)

Trtik, Pavel; Scheuerlein, Christian; Alknes, Patrick; Meyer, Michael; Schmid, Florian; Lehmann, Eberhard

Neutron imaging of sub-10-micrometres spatial resolution has been recently achieved in 2D mode within the framework of the Neutron Microscope project at the Paul Scherrer Institut. Here we report on the development of the PSI Neutron Microscope instrument and the results of the first microtomographic imaging experiment of multifilament superconducting MgB2 wire. The sample of MgB2 superconducting 37 multifilaments embedded in copper-nickel matrix was investigated -in microtomographic mode- with the scientific interest regarding the distribution of boron within the individual superconducting filaments (about 40 μm in diameter). The resulting tomographic dataset revealed the distribution of boron within the entire 0.8 mm thick multifilamental wire with the isotropic voxel size of 2.6 micrometres.

Investigación observacional sobre el papel de las estrellas binarias en la ecología de cúmulos estelares

NASA Astrophysics Data System (ADS)

González, J. F.; Levato, H.; Grosso, M.

We present preliminary results of a long-term project devoted to the observational study of the binary star population in open clusters and its connection with the dynamical and evolutionary properties of the clusters. We report the discovery of 17 double-lined spectroscopic binaries, 30 radial velocity variables and about 30 suspected variables. In the 17 clusters of our sample the binary frequency ranges between 20 and 40 %, and reaches typically 60 % if all suspected binaries are included. We study the spatial distribution of the binary stars with respect to the cluster center and we discuss the statistical correlation of the mass-ratio distribution with the cluster age.

A soil sampling reference site: the challenge in defining reference material for sampling.

PubMed

de Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria; Fajgelj, Ales; Jacimovic, Radojko; Jeran, Zvonka; Sansone, Umberto; van der Perk, Marcel

2008-11-01

In the frame of the international SOILSAMP project, funded and coordinated by the Italian Environmental Protection Agency, an agricultural area was established as a reference site suitable for performing soil sampling inter-comparison exercises. The reference site was characterized for trace element content in soil, in terms of the spatial and temporal variability of their mass fraction. Considering that the behaviour of long-lived radionuclides in soil can be expected to be similar to that of some stable trace elements and that the distribution of these trace elements in soil can simulate the distribution of radionuclides, the reference site characterised in term of trace elements, can be also used to compare the soil sampling strategies developed for radionuclide investigations.

OGC and Grid Interoperability in enviroGRIDS Project

NASA Astrophysics Data System (ADS)

Gorgan, Dorian; Rodila, Denisa; Bacu, Victor; Giuliani, Gregory; Ray, Nicolas

2010-05-01

EnviroGRIDS (Black Sea Catchment Observation and Assessment System supporting Sustainable Development) [1] is a 4-years FP7 Project aiming to address the subjects of ecologically unsustainable development and inadequate resource management. The project develops a Spatial Data Infrastructure of the Black Sea Catchment region. The geospatial technologies offer very specialized functionality for Earth Science oriented applications as well as the Grid oriented technology that is able to support distributed and parallel processing. One challenge of the enviroGRIDS project is the interoperability between geospatial and Grid infrastructures by providing the basic and the extended features of the both technologies. The geospatial interoperability technology has been promoted as a way of dealing with large volumes of geospatial data in distributed environments through the development of interoperable Web service specifications proposed by the Open Geospatial Consortium (OGC), with applications spread across multiple fields but especially in Earth observation research. Due to the huge volumes of data available in the geospatial domain and the additional introduced issues (data management, secure data transfer, data distribution and data computation), the need for an infrastructure capable to manage all those problems becomes an important aspect. The Grid promotes and facilitates the secure interoperations of geospatial heterogeneous distributed data within a distributed environment, the creation and management of large distributed computational jobs and assures a security level for communication and transfer of messages based on certificates. This presentation analysis and discusses the most significant use cases for enabling the OGC Web services interoperability with the Grid environment and focuses on the description and implementation of the most promising one. In these use cases we give a special attention to issues such as: the relations between computational grid and the OGC Web service protocols, the advantages offered by the Grid technology - such as providing a secure interoperability between the distributed geospatial resource -and the issues introduced by the integration of distributed geospatial data in a secure environment: data and service discovery, management, access and computation. enviroGRIDS project proposes a new architecture which allows a flexible and scalable approach for integrating the geospatial domain represented by the OGC Web services with the Grid domain represented by the gLite middleware. The parallelism offered by the Grid technology is discussed and explored at the data level, management level and computation level. The analysis is carried out for OGC Web service interoperability in general but specific details are emphasized for Web Map Service (WMS), Web Feature Service (WFS), Web Coverage Service (WCS), Web Processing Service (WPS) and Catalog Service for Web (CSW). Issues regarding the mapping and the interoperability between the OGC and the Grid standards and protocols are analyzed as they are the base in solving the communication problems between the two environments: grid and geospatial. The presetation mainly highlights how the Grid environment and Grid applications capabilities can be extended and utilized in geospatial interoperability. Interoperability between geospatial and Grid infrastructures provides features such as the specific geospatial complex functionality and the high power computation and security of the Grid, high spatial model resolution and geographical area covering, flexible combination and interoperability of the geographical models. According with the Service Oriented Architecture concepts and requirements of interoperability between geospatial and Grid infrastructures each of the main functionality is visible from enviroGRIDS Portal and consequently, by the end user applications such as Decision Maker/Citizen oriented Applications. The enviroGRIDS portal is the single way of the user to get into the system and the portal faces a unique style of the graphical user interface. Main reference for further information: [1] enviroGRIDS Project, http://www.envirogrids.net/

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

USGS Publications Warehouse

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

2013-01-01

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

Spatially Complete Global Spectral Surface Albedos: Value-Added Datasets Derived from Terra MODIS Land Products

NASA Technical Reports Server (NTRS)

Moody, Eric G.; King, Michael D.; Platnick, Steven; Schaaf, Crystal B.; Gao, Feng

2004-01-01

Land surface albedo is an important parameter in describing the radiative properties of the earth s surface as it represents the amount of incoming solar radiation that is reflected from the surface. The amount and type of vegetation of the surface dramatically alters the amount of radiation that is reflected; for example, croplands that contain leafy vegetation will reflect radiation very differently than blacktop associated with urban areas. In addition, since vegetation goes through a growth, or phenological, cycle, the amount of radiation that is reflected changes over the course of a year. As a result, albedo is both temporally and spatially dependant upon global location as there is a distribution of vegetated surface types and growing conditions. Land surface albedo is critical for a wide variety of earth system research projects including but not restricted to remote sensing of atmospheric aerosol and cloud properties from space, ground-based analysis of aerosol optical properties from surface-based sun/sky radiometers, biophysically-based land surface modeling of the exchange of energy, water, momentum, and carbon for various land use categories, and surface energy balance studies. These projects require proper representation of the surface albedo s spatial, spectral, and temporal variations, however, these representations are often lacking in datasets prior to the latest generation of land surface albedo products.

Spatial heterogeneity of radiocesium in the soil of a broadleaved deciduous forest: the marked role of stemflow

NASA Astrophysics Data System (ADS)

Levia, Delphis; Imamura, Naohiro; Toriyama, Jumpei; Kobayashi, Masahiro; Nanko, Kazuki

2017-04-01

This project amplifies our understanding of the transport of Cs-137 via stemflow in a konara oak forest by examining the spatial distribution of Cs-137 in the soil in both proximal (near-trunk) and distal ( > 1 m form tree trunk) stem areas. We report the Cs-137 concentrations and stocks for twenty-four soil samples harvested from the proximal and distal stem areas around individual trees in a radioactively contaminated konara oak forest in east-central Honshu, Japan. Preferential flowpaths of stemflow on the tree trunk and its point of infiltration into the forest floor was observed by conducting a dye tracer experiment. Experimental results showed that Cs-137 concentrations and stocks were higher in the soils of the proximal stem area as compared to the distal stem area when they corresponded with the preferential flowpaths of stemflow. Moreover, there was a significant relationship between the canopy projection area of individual trees and average soil Cs-137 concentrations and stocks, despite some canopy overlap among even trees. Our findings demonstrate that the spatial patterning of Cs-137 concentrations and stocks in the soil of the proximal stem area are governed (at least partially) by the preferential flowpaths of stemflow along the tree trunk. [Note: This presentation is currently under peer-review for journal publication.

Metabolic Flexibility as a Major Predictor of Spatial Distribution in Microbial Communities

PubMed Central

Carbonero, Franck; Oakley, Brian B.; Purdy, Kevin J.

2014-01-01

A better understand the ecology of microbes and their role in the global ecosystem could be achieved if traditional ecological theories can be applied to microbes. In ecology organisms are defined as specialists or generalists according to the breadth of their niche. Spatial distribution is often used as a proxy measure of niche breadth; generalists have broad niches and a wide spatial distribution and specialists a narrow niche and spatial distribution. Previous studies suggest that microbial distribution patterns are contrary to this idea; a microbial generalist genus (Desulfobulbus) has a limited spatial distribution while a specialist genus (Methanosaeta) has a cosmopolitan distribution. Therefore, we hypothesise that this counter-intuitive distribution within generalist and specialist microbial genera is a common microbial characteristic. Using molecular fingerprinting the distribution of four microbial genera, two generalists, Desulfobulbus and the methanogenic archaea Methanosarcina, and two specialists, Methanosaeta and the sulfate-reducing bacteria Desulfobacter were analysed in sediment samples from along a UK estuary. Detected genotypes of both generalist genera showed a distinct spatial distribution, significantly correlated with geographic distance between sites. Genotypes of both specialist genera showed no significant differential spatial distribution. These data support the hypothesis that the spatial distribution of specialist and generalist microbes does not match that seen with specialist and generalist large organisms. It may be that generalist microbes, while having a wider potential niche, are constrained, possibly by intrageneric competition, to exploit only a small part of that potential niche while specialists, with far fewer constraints to their niche, are more capable of filling their potential niche more effectively, perhaps by avoiding intrageneric competition. We suggest that these counter-intuitive distribution patterns may be a common feature of microbes in general and represent a distinct microbial principle in ecology, which is a real challenge if we are to develop a truly inclusive ecology. PMID:24465487

Stepwise magnetic-geochemical approach for efficient assessment of heavy metal polluted sites

NASA Astrophysics Data System (ADS)

Appel, E.; Rösler, W.; Ojha, G.

2012-04-01

Previous studies have shown that magnetometry can outline the distribution of fly ash deposition in the surroundings of coal-burning power plants and steel industries. Especially the easy-to-measure magnetic susceptibility (MS) is capable to act as a proxy for heavy metal (HM) pollution caused by such kind of point source pollution. Here we present a demonstration project around the coal-burning power plant complex "Schwarze Pumpe" in eastern Germany. Before reunification of West and East Germany huge amounts of HM pollutants were emitted from the "Schwarze Pumpe" into the environment by both fly ash emission and dumped clinker. The project has been conducted as part of the TASK Centre of Competence which aims at bringing new innovative techniques closer to the market. Our project combines in situ and laboratory MS measurements and HM analyses in order to demonstrate the efficiency of a stepwise approach for site assessment of HM pollution around point sources of fly-ash emission and deposition into soil. The following scenario is played through: We assume that the "true" spatial distribution of HM pollution (given by the pollution load index PLI comprising Fe, Zn, Pb, and Cu) is represented by our entire set of 85 measured samples (XRF analyses) from forest sites around the "Schwarze Pumpe". Surface MS data (collected with a Bartington MS2D) and in situ vertical MS sections (logged by an SM400 instrument) are used to determine a qualitative overview of potentially higher and lower polluted areas. A suite of spatial HM distribution maps obtained by random selections of 30 out of the 85 analysed sites is compared to the HM map obtained from a targeted 30-sites-selection based on pre-information from the MS results. The PLI distribution map obtained from the targeted 30-sites-selection shows all essential details of the "true" pollution map, while the different random 30-sites-selections miss important features. This comparison shows that, for the same cost investment, a stepwise combined magnetic-geochemical site assessment leads to a clearly more significant characterization of soil pollution than by a common approach with exclusively random sampling for geochemical analysis, or alternatively to an equal quality result for lower costs.

The spatial distribution of cropland carbon transfer in Jilin province during 2014

NASA Astrophysics Data System (ADS)

Cai, Xintong; Meng, Jian; Li, Qiuhui; Gao, Shuang; Zhu, Xianjin

2018-01-01

Cropland carbon transfer (CCT, gC yr-1) is an important component in the carbon budget of terrestrial ecosystems. Analyzing the value of CCT and its spatial variation would provide a data basis for assessing the regional carbon balance. Based on the data from Jilin statistical yearbook 2015, we investigated the spatial variation of CCT in Jilin province during 2014. Results suggest that the CCT of Jilin province was 30.83 TgC, which exhibited a decreasing trend from the centre to the border but the west side was higher than the east. The magnitude of carbon transfer per area (MCT), which showed a similar spatial distribution with CCT, was the dominating component of CCT spatial distribution. The spatial distribution of MCT was jointly affected by that of the ratio of planting area to regional area (RPR) and carbon transfer per planting area (CTP), where RPR and CTP contributed 65.55% and 34.5% of MCT spatial distribution, respectively. Therefore, CCT in Jilin province spatially varied, which made it highly needed to consider the difference in CCT among regions when we assessing the regional carbon budget.

Benchmarking of vertically-integrated CO2 flow simulations at the Sleipner Field, North Sea

NASA Astrophysics Data System (ADS)

Cowton, L. R.; Neufeld, J. A.; White, N. J.; Bickle, M. J.; Williams, G. A.; White, J. C.; Chadwick, R. A.

2018-06-01

Numerical modeling plays an essential role in both identifying and assessing sub-surface reservoirs that might be suitable for future carbon capture and storage projects. Accuracy of flow simulations is tested by benchmarking against historic observations from on-going CO2 injection sites. At the Sleipner project located in the North Sea, a suite of time-lapse seismic reflection surveys enables the three-dimensional distribution of CO2 at the top of the reservoir to be determined as a function of time. Previous attempts have used Darcy flow simulators to model CO2 migration throughout this layer, given the volume of injection with time and the location of the injection point. Due primarily to computational limitations preventing adequate exploration of model parameter space, these simulations usually fail to match the observed distribution of CO2 as a function of space and time. To circumvent these limitations, we develop a vertically-integrated fluid flow simulator that is based upon the theory of topographically controlled, porous gravity currents. This computationally efficient scheme can be used to invert for the spatial distribution of reservoir permeability required to minimize differences between the observed and calculated CO2 distributions. When a uniform reservoir permeability is assumed, inverse modeling is unable to adequately match the migration of CO2 at the top of the reservoir. If, however, the width and permeability of a mapped channel deposit are allowed to independently vary, a satisfactory match between the observed and calculated CO2 distributions is obtained. Finally, the ability of this algorithm to forecast the flow of CO2 at the top of the reservoir is assessed. By dividing the complete set of seismic reflection surveys into training and validation subsets, we find that the spatial pattern of permeability required to match the training subset can successfully predict CO2 migration for the validation subset. This ability suggests that it might be feasible to forecast migration patterns into the future with a degree of confidence. Nevertheless, our analysis highlights the difficulty in estimating reservoir parameters away from the region swept by CO2 without additional observational constraints.

Spatial Harmonic Decomposition as a tool for unsteady flow phenomena analysis

NASA Astrophysics Data System (ADS)

Duparchy, A.; Guillozet, J.; De Colombel, T.; Bornard, L.

2014-03-01

Hydropower is already the largest single renewable electricity source today but its further development will face new deployment constraints such as large-scale projects in emerging economies and the growth of intermittent renewable energy technologies. The potential role of hydropower as a grid stabilizer leads to operating hydro power plants in "off-design" zones. As a result, new methods of analyzing associated unsteady phenomena are needed to improve the design of hydraulic turbines. The key idea of the development is to compute a spatial description of a phenomenon by using a combination from several sensor signals. The spatial harmonic decomposition (SHD) extends the concept of so-called synchronous and asynchronous pulsations by projecting sensor signals on a linearly independent set of a modal scheme. This mathematical approach is very generic as it can be applied on any linear distribution of a scalar quantity defined on a closed curve. After a mathematical description of SHD, this paper will discuss the impact of instrumentation and provide tools to understand SHD signals. Then, as an example of a practical application, SHD is applied on a model test measurement in order to capture and describe dynamic pressure fields. Particularly, the spatial description of the phenomena provides new tools to separate the part of pressure fluctuations that contribute to output power instability or mechanical stresses. The study of the machine stability in partial load operating range in turbine mode or the comparison between the gap pressure field and radial thrust behavior during turbine brake operation are both relevant illustrations of SHD contribution.

Relations between Spatial Distribution, Social Affiliations and Dominance Hierarchy in a Semi-Free Mandrill Population

PubMed Central

Naud, Alexandre; Chailleux, Eloise; Kestens, Yan; Bret, Céline; Desjardins, Dominic; Petit, Odile; Ngoubangoye, Barthélémy; Sueur, Cédric

2016-01-01

Although there exist advantages to group-living in comparison to a solitary lifestyle, costs and gains of group-living may be unequally distributed among group members. Predation risk, vigilance levels and food intake may be unevenly distributed across group spatial geometry and certain within-group spatial positions may be more or less advantageous depending on the spatial distribution of these factors. In species characterized with dominance hierarchy, high-ranking individuals are commonly observed in advantageous spatial position. However, in complex social systems, individuals can develop affiliative relationships that may balance the effect of dominance relationships in individual's spatial distribution. The objective of the present study is to investigate how the group spatial distribution of a semi-free ranging colony of Mandrills relates to its social organization. Using spatial observations in an area surrounding the feeding zone, we tested the three following hypothesis: (1) does dominance hierarchy explain being observed in proximity or far from a food patch? (2) Do affiliative associations also explain being observed in proximity or far from a food patch? (3) Do the differences in rank in the group hierarchy explain being co-observed in proximity of a food patch? Our results showed that high-ranking individuals were more observed in proximity of the feeding zone while low-ranking individuals were more observed at the boundaries of the observation area. Furthermore, we observed that affiliative relationships were also associated with individual spatial distributions and explain more of the total variance of the spatial distribution in comparison with dominance hierarchy. Finally, we found that individuals observed at a same moment in proximity of the feeding zone were more likely to be distant in the hierarchy while controlling for maternal kinship, age and sex similarity. This study brings some elements about how affiliative networks and dominance hierarchy are related to spatial positions in primates. PMID:27199845

Relations between Spatial Distribution, Social Affiliations and Dominance Hierarchy in a Semi-Free Mandrill Population.

PubMed

Naud, Alexandre; Chailleux, Eloise; Kestens, Yan; Bret, Céline; Desjardins, Dominic; Petit, Odile; Ngoubangoye, Barthélémy; Sueur, Cédric

2016-01-01

Although there exist advantages to group-living in comparison to a solitary lifestyle, costs and gains of group-living may be unequally distributed among group members. Predation risk, vigilance levels and food intake may be unevenly distributed across group spatial geometry and certain within-group spatial positions may be more or less advantageous depending on the spatial distribution of these factors. In species characterized with dominance hierarchy, high-ranking individuals are commonly observed in advantageous spatial position. However, in complex social systems, individuals can develop affiliative relationships that may balance the effect of dominance relationships in individual's spatial distribution. The objective of the present study is to investigate how the group spatial distribution of a semi-free ranging colony of Mandrills relates to its social organization. Using spatial observations in an area surrounding the feeding zone, we tested the three following hypothesis: (1) does dominance hierarchy explain being observed in proximity or far from a food patch? (2) Do affiliative associations also explain being observed in proximity or far from a food patch? (3) Do the differences in rank in the group hierarchy explain being co-observed in proximity of a food patch? Our results showed that high-ranking individuals were more observed in proximity of the feeding zone while low-ranking individuals were more observed at the boundaries of the observation area. Furthermore, we observed that affiliative relationships were also associated with individual spatial distributions and explain more of the total variance of the spatial distribution in comparison with dominance hierarchy. Finally, we found that individuals observed at a same moment in proximity of the feeding zone were more likely to be distant in the hierarchy while controlling for maternal kinship, age and sex similarity. This study brings some elements about how affiliative networks and dominance hierarchy are related to spatial positions in primates.

Rapid Estimates of Rupture Extent for Large Earthquakes Using Aftershocks

NASA Astrophysics Data System (ADS)

Polet, J.; Thio, H. K.; Kremer, M.

2009-12-01

The spatial distribution of aftershocks is closely linked to the rupture extent of the mainshock that preceded them and a rapid analysis of aftershock patterns therefore has potential for use in near real-time estimates of earthquake impact. The correlation between aftershocks and slip distribution has frequently been used to estimate the fault dimensions of large historic earthquakes for which no, or insufficient, waveform data is available. With the advent of earthquake inversions that use seismic waveforms and geodetic data to constrain the slip distribution, the study of aftershocks has recently been largely focused on enhancing our understanding of the underlying mechanisms in a broader earthquake mechanics/dynamics framework. However, in a near real-time earthquake monitoring environment, in which aftershocks of large earthquakes are routinely detected and located, these data may also be effective in determining a fast estimate of the mainshock rupture area, which would aid in the rapid assessment of the impact of the earthquake. We have analyzed a considerable number of large recent earthquakes and their aftershock sequences and have developed an effective algorithm that determines the rupture extent of a mainshock from its aftershock distribution, in a fully automatic manner. The algorithm automatically removes outliers by spatial binning, and subsequently determines the best fitting “strike” of the rupture and its length by projecting the aftershock epicenters onto a set of lines that cross the mainshock epicenter with incremental azimuths. For strike-slip or large dip-slip events, for which the surface projection of the rupture is recti-linear, the calculated strike correlates well with the strike of the fault and the corresponding length, determined from the distribution of aftershocks projected onto the line, agrees well with the rupture length. In the case of a smaller dip-slip rupture with an aspect ratio closer to 1, the procedure gives a measure of the rupture extent and dimensions, but not necessarily the strike. We found that using standard earthquake catalogs, such as the National Earthquake Information Center catalog, we can constrain the rupture extent, rupture direction, and in many cases the type of faulting, of the mainshock with the aftershocks that occur within the first hour after the mainshock. However, this data may not be currently available in near real-time. Since our results show that these early aftershock locations may be used to estimate first order rupture parameters for large global earthquakes, the near real-time availability of these data would be useful for fast earthquake damage assessment.

Considering the Spatial Layout Information of Bag of Features (BoF) Framework for Image Classification.

PubMed

Mu, Guangyu; Liu, Ying; Wang, Limin

2015-01-01

The spatial pooling method such as spatial pyramid matching (SPM) is very crucial in the bag of features model used in image classification. SPM partitions the image into a set of regular grids and assumes that the spatial layout of all visual words obey the uniform distribution over these regular grids. However, in practice, we consider that different visual words should obey different spatial layout distributions. To improve SPM, we develop a novel spatial pooling method, namely spatial distribution pooling (SDP). The proposed SDP method uses an extension model of Gauss mixture model to estimate the spatial layout distributions of the visual vocabulary. For each visual word type, SDP can generate a set of flexible grids rather than the regular grids from the traditional SPM. Furthermore, we can compute the grid weights for visual word tokens according to their spatial coordinates. The experimental results demonstrate that SDP outperforms the traditional spatial pooling methods, and is competitive with the state-of-the-art classification accuracy on several challenging image datasets.

Spatial coding-based approach for partitioning big spatial data in Hadoop

NASA Astrophysics Data System (ADS)

Yao, Xiaochuang; Mokbel, Mohamed F.; Alarabi, Louai; Eldawy, Ahmed; Yang, Jianyu; Yun, Wenju; Li, Lin; Ye, Sijing; Zhu, Dehai

2017-09-01

Spatial data partitioning (SDP) plays a powerful role in distributed storage and parallel computing for spatial data. However, due to skew distribution of spatial data and varying volume of spatial vector objects, it leads to a significant challenge to ensure both optimal performance of spatial operation and data balance in the cluster. To tackle this problem, we proposed a spatial coding-based approach for partitioning big spatial data in Hadoop. This approach, firstly, compressed the whole big spatial data based on spatial coding matrix to create a sensing information set (SIS), including spatial code, size, count and other information. SIS was then employed to build spatial partitioning matrix, which was used to spilt all spatial objects into different partitions in the cluster finally. Based on our approach, the neighbouring spatial objects can be partitioned into the same block. At the same time, it also can minimize the data skew in Hadoop distributed file system (HDFS). The presented approach with a case study in this paper is compared against random sampling based partitioning, with three measurement standards, namely, the spatial index quality, data skew in HDFS, and range query performance. The experimental results show that our method based on spatial coding technique can improve the query performance of big spatial data, as well as the data balance in HDFS. We implemented and deployed this approach in Hadoop, and it is also able to support efficiently any other distributed big spatial data systems.

Wave actions and topography determine the small-scale spatial distribution of newly settled Asari clams Ruditapes philippinarum on a tidal flat

NASA Astrophysics Data System (ADS)

Nambu, Ryogen; Saito, Hajime; Tanaka, Yoshio; Higano, Junya; Kuwahara, Hisami

2012-03-01

There are many studies on spatial distributions of Asari clam Ruditapes philippinarum adults on tidal flats but few have dealt with spatial distributions of newly settled Asari clam (<0.3 mm shell length, indicative of settlement patterns) in relation to physical/topographical conditions on tidal flats. We examined small-scale spatial distributions of newly settled individuals on the Matsunase tidal flat, central Japan, during the low spring tides on two days 29th-30th June 2007, together with the shear stress from waves and currents on the flat. The characteristics of spatial distribution of newly settled Asari clam markedly varied depending on both of hydrodynamic and topographical conditions on the tidal flat. Using generalized linear models (GLMs), factors responsible for affecting newly settled Asari clam density and its spatial distribution were distinguished between sampling days, with "crest" sites always having a negative influence each on the density and the distribution on both sampling days. The continuously recorded data for the wave-current flows at the "crest" site on the tidal flat showed that newly settled Asari clam, as well as bottom sediment particles, at the "crest" site to be easily displaced. Small-scale spatial distributions of newly settled Asari clam changed with more advanced benthic stages in relation to the wave shear stress.

Spatial distributions of dose enhancement around a gold nanoparticle at several depths of proton Bragg peak

NASA Astrophysics Data System (ADS)

Kwon, Jihun; Sutherland, Kenneth; Hashimoto, Takayuki; Shirato, Hiroki; Date, Hiroyuki

2016-10-01

Gold nanoparticles (GNPs) have been recognized as a promising candidate for a radiation sensitizer. A proton beam incident on a GNP can produce secondary electrons, resulting in an enhancement of the dose around the GNP. However, little is known about the spatial distribution of dose enhancement around the GNP, especially in the direction along the incident proton. The purpose of this study is to determine the spatial distribution of dose enhancement by taking the incident direction into account. Two steps of calculation were conducted using the Geant4 Monte Carlo simulation toolkit. First, the energy spectra of 100 and 195 MeV protons colliding with a GNP were calculated at the Bragg peak and three other depths around the peak in liquid water. Second, the GNP was bombarded by protons with the obtained energy spectra. Radial dose distributions were computed along the incident beam direction. The spatial distributions of the dose enhancement factor (DEF) and subtracted dose (Dsub) were then evaluated. The spatial DEF distributions showed hot spots in the distal radial region from the proton beam axis. The spatial Dsub distribution isotropically spread out around the GNP. Low energy protons caused higher and wider dose enhancement. The macroscopic dose enhancement in clinical applications was also evaluated. The results suggest that the consideration of the spatial distribution of GNPs in treatment planning will maximize the potential of GNPs.

Spatial Distribution of Surface Soil Moisture in a Small Forested Catchment

EPA Science Inventory

Predicting the spatial distribution of soil moisture is an important hydrological question. We measured the spatial distribution of surface soil moisture (upper 6 cm) using an Amplitude Domain Reflectometry sensor at the plot scale (2 × 2 m) and small catchment scale (0.84 ha) in...

Texas Urban Triangle : pilot study to implement a spatial decision support system (SDSS) for sustainable mobility.

DOT National Transportation Integrated Search

2011-03-01

This project addressed sustainable transportation in the Texas Urban Triangle (TUT) by conducting a pilot : project at the county scale. The project tested and developed the multi-attribute Spatial Decision Support : System (SDSS) developed in 2009 u...

[Analysis of influence on spatial distribution of fishing ground for Antarctic krill fishery in the northern South Shetland Islands based on GWR model].

PubMed

Chen, Lyu Feng; Zhu, Guo Ping

2018-03-01

Based on Antarctic krill fishery and marine environmental data collected by scientific observers, using geographically weighted regression (GWR) model, we analyzed the effects of the factors with spatial attributes, i.e., depth of krill swarm (DKS) and distance from fishing position to shore (DTS), and sea surface temperature (SST), on the spatial distribution of fishing ground in the northern South Shetland Islands. The results showed that there was no significant aggregation in spatial distribution of catch per unit fishing effort (CPUE). Spatial autocorrelations (positive) among three factors were observed in 2010 and 2013, but were not in 2012 and 2016. Results from GWR model showed that the extent for the impacts on spatial distribution of CPUEs varied among those three factors, following the order DKS>SST>DTS. Compared to the DKS and DTS, the impact of SST on the spatial distribution of CPUEs presented adverse trend in the eastern and western parts of the South Shetland Islands. Negative correlations occurred for the spatial effects of DKS and DTS on distribution of CPUEs, though with inter-annual and regional variation. Our results provide metho-dological reference for researches on the underlying mechanism for fishing ground formation for Antarctic krill fishery.

Real-time distribution of pelagic fish: combining hydroacoustics, GIS and spatial modelling at a fine spatial scale.

PubMed

Muška, Milan; Tušer, Michal; Frouzová, Jaroslava; Mrkvička, Tomáš; Ricard, Daniel; Seďa, Jaromír; Morelli, Federico; Kubečka, Jan

2018-03-29

Understanding spatial distribution of organisms in heterogeneous environment remains one of the chief issues in ecology. Spatial organization of freshwater fish was investigated predominantly on large-scale, neglecting important local conditions and ecological processes. However, small-scale processes are of an essential importance for individual habitat preferences and hence structuring trophic cascades and species coexistence. In this work, we analysed the real-time spatial distribution of pelagic freshwater fish in the Římov Reservoir (Czechia) observed by hydroacoustics in relation to important environmental predictors during 48 hours at 3-h interval. Effect of diurnal cycle was revealed of highest significance in all spatial models with inverse trends between fish distribution and predictors in day and night in general. Our findings highlighted daytime pelagic fish distribution as highly aggregated, with general fish preferences for central, deep and highly illuminated areas, whereas nighttime distribution was more disperse and fish preferred nearshore steep sloped areas with higher depth. This turnover suggests prominent movements of significant part of fish assemblage between pelagic and nearshore areas on a diel basis. In conclusion, hydroacoustics, GIS and spatial modelling proved as valuable tool for predicting local fish distribution and elucidate its drivers, which has far reaching implications for understanding freshwater ecosystem functioning.

Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics with Level Set Transformation.

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

Hammond, Glenn Edward; Song, Xuehang; Ye, Ming

A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. Themore » spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.« less

Methodology to study the three-dimensional spatial distribution of prostate cancer and their dependence on clinical parameters

PubMed Central

Rojas, Kristians Diaz; Montero, Maria L.; Yao, Jorge; Messing, Edward; Fazili, Anees; Joseph, Jean; Ou, Yangming; Rubens, Deborah J.; Parker, Kevin J.; Davatzikos, Christos; Castaneda, Benjamin

2015-01-01

Abstract. A methodology to study the relationship between clinical variables [e.g., prostate specific antigen (PSA) or Gleason score] and cancer spatial distribution is described. Three-dimensional (3-D) models of 216 glands are reconstructed from digital images of whole mount histopathological slices. The models are deformed into one prostate model selected as an atlas using a combination of rigid, affine, and B-spline deformable registration techniques. Spatial cancer distribution is assessed by counting the number of tumor occurrences among all glands in a given position of the 3-D registered atlas. Finally, a difference between proportions is used to compare different spatial distributions. As a proof of concept, we compare spatial distributions from patients with PSA greater and less than 5  ng/ml and from patients older and younger than 60 years. Results suggest that prostate cancer has a significant difference in the right zone of the prostate between populations with PSA greater and less than 5  ng/ml. Age does not have any impact in the spatial distribution of the disease. The proposed methodology can help to comprehend prostate cancer by understanding its spatial distribution and how it changes according to clinical parameters. Finally, this methodology can be easily adapted to other organs and pathologies. PMID:26236756

Anisotropic conductivity imaging with MREIT using equipotential projection algorithm.

PubMed

Değirmenci, Evren; Eyüboğlu, B Murat

2007-12-21

Magnetic resonance electrical impedance tomography (MREIT) combines magnetic flux or current density measurements obtained by magnetic resonance imaging (MRI) and surface potential measurements to reconstruct images of true conductivity with high spatial resolution. Most of the biological tissues have anisotropic conductivity; therefore, anisotropy should be taken into account in conductivity image reconstruction. Almost all of the MREIT reconstruction algorithms proposed to date assume isotropic conductivity distribution. In this study, a novel MREIT image reconstruction algorithm is proposed to image anisotropic conductivity. Relative anisotropic conductivity values are reconstructed iteratively, using only current density measurements without any potential measurement. In order to obtain true conductivity values, only either one potential or conductivity measurement is sufficient to determine a scaling factor. The proposed technique is evaluated on simulated data for isotropic and anisotropic conductivity distributions, with and without measurement noise. Simulation results show that the images of both anisotropic and isotropic conductivity distributions can be reconstructed successfully.

Overview of Sea-Ice Properties, Distribution and Temporal Variations, for Application to Ice-Atmosphere Chemical Processes.

NASA Astrophysics Data System (ADS)

Moritz, R. E.

2005-12-01

The properties, distribution and temporal variation of sea-ice are reviewed for application to problems of ice-atmosphere chemical processes. Typical vertical structure of sea-ice is presented for different ice types, including young ice, first-year ice and multi-year ice, emphasizing factors relevant to surface chemistry and gas exchange. Time average annual cycles of large scale variables are presented, including ice concentration, ice extent, ice thickness and ice age. Spatial and temporal variability of these large scale quantities is considered on time scales of 1-50 years, emphasizing recent and projected changes in the Arctic pack ice. The amount and time evolution of open water and thin ice are important factors that influence ocean-ice-atmosphere chemical processes. Observations and modeling of the sea-ice thickness distribution function are presented to characterize the range of variability in open water and thin ice.

Packaging and distributing ecological data from multisite studies

NASA Technical Reports Server (NTRS)

Olson, R. J.; Voorhees, L. D.; Field, J. M.; Gentry, M. J.

1996-01-01

Studies of global change and other regional issues depend on ecological data collected at multiple study areas or sites. An information system model is proposed for compiling diverse data from dispersed sources so that the data are consistent, complete, and readily available. The model includes investigators who collect and analyze field measurements, science teams that synthesize data, a project information system that collates data, a data archive center that distributes data to secondary users, and a master data directory that provides broader searching opportunities. Special attention to format consistency is required, such as units of measure, spatial coordinates, dates, and notation for missing values. Often data may need to be enhanced by estimating missing values, aggregating to common temporal units, or adding other related data such as climatic and soils data. Full documentation, an efficient data distribution mechanism, and an equitable way to acknowledge the original source of data are also required.

i-LOVE: ISS-JEM lidar for observation of vegetation environment

NASA Astrophysics Data System (ADS)

Asai, Kazuhiro; Sawada, Haruo; Sugimoto, Nobuo; Mizutani, Kohei; Ishii, Shoken; Nishizawa, Tomoaki; Shimoda, Haruhisa; Honda, Yoshiaki; Kajiwara, Koji; Takao, Gen; Hirata, Yasumasa; Saigusa, Nobuko; Hayashi, Masatomo; Oguma, Hiroyuki; Saito, Hideki; Awaya, Yoshio; Endo, Takahiro; Imai, Tadashi; Murooka, Jumpei; Kobatashi, Takashi; Suzuki, Keiko; Sato, Ryota

2012-11-01

It is very important to watch the spatial distribution of vegetation biomass and changes in biomass over time, representing invaluable information to improve present assessments and future projections of the terrestrial carbon cycle. A space lidar is well known as a powerful remote sensing technology for measuring the canopy height accurately. This paper describes the ISS(International Space Station)-JEM(Japanese Experimental Module)-EF(Exposed Facility) borne vegetation lidar using a two dimensional array detector in order to reduce the root mean square error (RMSE) of tree height due to sloped surface.

Integrating continuous stocks and flows into state-and-transition simulation models of landscape change

USGS Publications Warehouse

Daniel, Colin J.; Sleeter, Benjamin M.; Frid, Leonardo; Fortin, Marie-Josée

2018-01-01

State-and-transition simulation models (STSMs) provide a general framework for forecasting landscape dynamics, including projections of both vegetation and land-use/land-cover (LULC) change. The STSM method divides a landscape into spatially-referenced cells and then simulates the state of each cell forward in time, as a discrete-time stochastic process using a Monte Carlo approach, in response to any number of possible transitions. A current limitation of the STSM method, however, is that all of the state variables must be discrete.Here we present a new approach for extending a STSM, in order to account for continuous state variables, called a state-and-transition simulation model with stocks and flows (STSM-SF). The STSM-SF method allows for any number of continuous stocks to be defined for every spatial cell in the STSM, along with a suite of continuous flows specifying the rates at which stock levels change over time. The change in the level of each stock is then simulated forward in time, for each spatial cell, as a discrete-time stochastic process. The method differs from the traditional systems dynamics approach to stock-flow modelling in that the stocks and flows can be spatially-explicit, and the flows can be expressed as a function of the STSM states and transitions.We demonstrate the STSM-SF method by integrating a spatially-explicit carbon (C) budget model with a STSM of LULC change for the state of Hawai'i, USA. In this example, continuous stocks are pools of terrestrial C, while the flows are the possible fluxes of C between these pools. Importantly, several of these C fluxes are triggered by corresponding LULC transitions in the STSM. Model outputs include changes in the spatial and temporal distribution of C pools and fluxes across the landscape in response to projected future changes in LULC over the next 50 years.The new STSM-SF method allows both discrete and continuous state variables to be integrated into a STSM, including interactions between them. With the addition of stocks and flows, STSMs provide a conceptually simple yet powerful approach for characterizing uncertainties in projections of a wide range of questions regarding landscape change.

Spatio-temporal patterns of key exploited marine species in the Northwestern Mediterranean Sea.

PubMed

Morfin, Marie; Fromentin, Jean-Marc; Jadaud, Angélique; Bez, Nicolas

2012-01-01

This study analyzes the temporal variability/stability of the spatial distributions of key exploited species in the Gulf of Lions (Northwestern Mediterranean Sea). To do so, we analyzed data from the MEDITS bottom-trawl scientific surveys from 1994 to 2010 at 66 fixed stations and selected 12 key exploited species. We proposed a geostatistical approach to handle zero-inflated and non-stationary distributions and to test for the temporal stability of the spatial structures. Empirical Orthogonal Functions and other descriptors were then applied to investigate the temporal persistence and the characteristics of the spatial patterns. The spatial structure of the distribution (i.e. the pattern of spatial autocorrelation) of the 12 key species studied remained highly stable over the time period sampled. The spatial distributions of all species obtained through kriging also appeared to be stable over time, while each species displayed a specific spatial distribution. Furthermore, adults were generally more densely concentrated than juveniles and occupied areas included in the distribution of juveniles. Despite the strong persistence of spatial distributions, we also observed that the area occupied by each species was correlated to its abundance: the more abundant the species, the larger the occupation area. Such a result tends to support MacCall's basin theory, according to which density-dependence responses would drive the expansion of those 12 key species in the Gulf of Lions. Further analyses showed that these species never saturated their habitats, suggesting that they are below their carrying capacity; an assumption in agreement with the overexploitation of several of these species. Finally, the stability of their spatial distributions over time and their potential ability to diffuse outside their main habitats give support to Marine Protected Areas as a potential pertinent management tool.

The contribution of glacial isostatic adjustment to projections of sea-level change along the Atlantic and Gulf coasts of North America

NASA Astrophysics Data System (ADS)

Love, R.; Milne, G. A.; Tarasov, L.; Engelhart, S. E.; Hijma, M.; Latychev, K.; Horton, B.; Tornqvist, T. E.

2017-12-01

Using recently compiled and quality-assessed databases of past RSL, including new databases for the United States Gulf Coast and Atlantic Canada, we infer glacial isostatic adjustment (GIA) model parameters to aid in future projections of sea level change. Utilizing the aforementioned RSL databases, we determine those model parameters for 3 different regions which minimizes the misfit of our 1D spherically symmetric model of GIA. From our ensemble of of 363 different viscosity models and 35 different land ice histories we provide uncertainty estimates for future RSL at 13 cities along this coastline. Furthermore, we examine the role of lateral viscosity structure using a 3D finite volume Earth model and find that the influence of lateral structure on RSL is significant, particularly in the early to mid-Holocene. At 13 cities along this coastline, we estimate the GIA contribution to range from a few centimeters (e.g., 3 [-1 to 9] cm Miami) to a few decimeters (e.g., 18 [12-22] cm, Halifax) for the period 2085-2100 relative to 2006-2015 [1σ]. Contributions from ocean steric and dynamic changes as well as those from changes in land ice are also estimated to provide context for the GIA projections at the regional scale. When summing the contributions from all evaluated processes at the 13 cities considered along this coastline, using median or best-estimate values, the GIA signal comprises 5-38% of the total depending on the adopted climate forcing and location. Examining the spatial distribution of other contributors to RSL, we find an approximate net cancellation in their spatial variability. In our results, GIA dominates the net RSL spatial variability north of 35°N, emphasizing the importance of regional scale GIA studies in future sea level projections.

Internal variability of a dynamically downscaled climate over North America

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

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 km and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemblemore » during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late 21st century. However, the IV is larger than the projected changes in precipitation for the mid- and late 21st century.« less

Internal variability of a dynamically downscaled climate over North America

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

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble duringmore » the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.« less

Callosal connections of dorso-lateral premotor cortex.

PubMed

Marconi, B; Genovesio, A; Giannetti, S; Molinari, M; Caminiti, R

2003-08-01

This study investigated the organization of the callosal connections of the two subdivisions of the monkey dorsal premotor cortex (PMd), dorso-rostral (F7) and dorso-caudal (F2). In one animal, Fast blue and Diamidino yellow were injected in F7 and F2, respectively; in a second animal, the pattern of injections was reversed. F7 and F2 receive a major callosal input from their homotopic counterpart. The heterotopic connections of F7 originate mainly from F2, with smaller contingent from pre-supplementary motor area (pre-SMA, F6), area 8 (frontal eye fields), and prefrontal cortex (area 46), while those of F2 originate from F7, with smaller contributions from ventral premotor areas (F5, F4), SMA-proper (F3), and primary motor cortex (M1). Callosal cells projecting homotopically are mostly located in layers II-III, those projecting heterotopically occupy layers II-III and V-VI. A spectral analysis was used to characterize the spatial fluctuations of the distribution of callosal neurons, in both F7 and F2, as well as in adjacent cortical areas. The results revealed two main periodic components. The first, in the domain of the low spatial frequencies, corresponds to periodicities of cell density with peak-to-peak distances of approximately 10 mm, and suggests an arrangement of callosal cells in the form of 5-mm wide bands. The second corresponds to periodicities of approximately 2 mm, and probably reflects a 1-mm columnar-like arrangement. Coherency and phase analyses showed that, although similar in their spatial arrangements, callosal cells projecting to dorsal premotor areas are segregated in the tangential cortical domain.

Evaluation of representativeness of near-surface winds in station measurements, global and regional reanalysis for Germany

NASA Astrophysics Data System (ADS)

Kaspar, Frank; Kaiser-Weiss, Andrea K.; Heene, Vera; Borsche, Michael; Keller, Jan

2015-04-01

Within the preparation activities for a European COPERNICUS Climate Change Service (C3S) several ongoing research projects analyse the potential of global and regional model-based climate reanalyses for applications. A user survey in the FP7-project CORE-CLIMAX revealed that surface wind (10 m) is among the most frequently used parameters of global reanalysis products. The FP7 project UERRA (Uncertainties in Ensembles of Regional Re-Analysis) has the focus on regional European reanalysis and the associated uncertainties, also from a user perspective. Especially in the field of renewable energy planning and production there is a need for climatological information across all spatial scales, i.e., from climatology at a certain site to the spatial scale of national or continental renewable energy production. Here, we focus on a comparison of wind measurements of the Germany's meteorological service (Deutscher Wetterdienst, DWD) with global reanalyses of ECWMF and a regional reanalysis for Europe based on DWD's NWP-model COSMO (performed by the Hans-Ertel-Center for Weather Research, University of Bonn). Reanalyses can provide valuable additional information on larger scale variability, e.g. multi-annual variation over Germany. However, changes in the observing system, model errors and biases have to be carefully considered. On the other hand, the ground-based observation networks partly suffer from change of the station distribution, changes in instrumentation, measurements procedures and quality control as well as local changes which might modify their spatial representativeness. All these effects might often been unknown or hard to characterize, although plenty of the meta-data information has been recorded for the German stations. One focus of the presentation will be the added-value of the regional reanalysis.

Potential Impacts of Future Warming and Land Use Changes on Intra-Urban Heat Exposure in Houston, Texas

PubMed Central

Conlon, Kathryn; Monaghan, Andrew; Hayden, Mary; Wilhelmi, Olga

2016-01-01

Extreme heat events in the United States are projected to become more frequent and intense as a result of climate change. We investigated the individual and combined effects of land use and warming on the spatial and temporal distribution of daily minimum temperature (Tmin) and daily maximum heat index (HImax) during summer in Houston, Texas. Present-day (2010) and near-future (2040) parcel-level land use scenarios were embedded within 1-km resolution land surface model (LSM) simulations. For each land use scenario, LSM simulations were conducted for climatic scenarios representative of both the present-day and near-future periods. LSM simulations assuming present-day climate but 2040 land use patterns led to spatially heterogeneous temperature changes characterized by warmer conditions over most areas, with summer average increases of up to 1.5°C (Tmin) and 7.3°C (HImax) in some newly developed suburban areas compared to simulations using 2010 land use patterns. LSM simulations assuming present-day land use but a 1°C temperature increase above the urban canopy (consistent with warming projections for 2040) yielded more spatially homogeneous metropolitan-wide average increases of about 1°C (Tmin) and 2.5°C (HImax), respectively. LSM simulations assuming both land use and warming for 2040 led to summer average increases of up to 2.5°C (Tmin) and 8.3°C (HImax), with the largest increases in areas projected to be converted to residential, industrial and mixed-use types. Our results suggest that urbanization and climate change may significantly increase the average number of summer days that exceed current threshold temperatures for initiating a heat advisory for metropolitan Houston, potentially increasing population exposure to extreme heat. PMID:26863298

Internal variability of a dynamically downscaled climate over North America

NASA Astrophysics Data System (ADS)

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

2018-06-01

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

Internal variability of a dynamically downscaled climate over North America

NASA Astrophysics Data System (ADS)

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

2017-09-01

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

Distributed acoustic fibre optic sensors for condition monitoring of pipelines

NASA Astrophysics Data System (ADS)

Hussels, Maria-Teresa; Chruscicki, Sebastian; Habib, Abdelkarim; Krebber, Katerina

2016-05-01

Industrial piping systems are particularly relevant to public safety and the continuous availability of infrastructure. However, condition monitoring systems based on many discrete sensors are generally not well-suited for widespread piping systems due to considerable installation effort, while use of distributed fibre-optic sensors would reduce this effort to a minimum. Specifically distributed acoustic sensing (DAS) is employed for detection of third-party threats and leaks in oil and gas pipelines in recent years and can in principle also be applied to industrial plants. Further possible detection routes amenable by DAS that could identify damage prior to emission of medium are subject of a current project at BAM, which aims at qualifying distributed fibre optic methods such as DAS as a means for spatially continuous monitoring of industrial piping systems. Here, first tests on a short pipe are presented, where optical fibres were applied directly to the surface. An artificial signal was used to define suitable parameters of the measurement system and compare different ways of applying the sensor.

Climate change stimulates the growth of the intertidal macroalgae Ascophyllum nodosum near the northern distribution limit.

PubMed

Marbà, Núria; Krause-Jensen, Dorte; Olesen, Birgit; Christensen, Peter B; Merzouk, Anissa; Rodrigues, Joao; Wegeberg, Susse; Wilce, Robert T

2017-02-01

Ascophyllum nodosum is a foundation macroalgae of the intertidal zone that distributes across latitude 41.3-69.7°N. We tested the hypothesis that growth of A. nodosum near the northern distribution edge increases with warming. We retrospectively quantified the growth of eight A. nodosum populations at West Greenland and North Norway (from 64°N to 69°N). For seven populations, we measured growth rates since 1997-2002 and for one of them we extended the time series back to 1956 using published estimates. Individuals at northern populations elongated between 2.0 and 9.1 cm year -1 and this variability correlated with temperature and annual ice-free days. A spatial comparison of A. nodosum growth across the species distribution range showed that Northern (and coldest) populations grew at the slowest rates. Our results demonstrate that arctic climate change enhances the growth of A. nodosum populations and suggest that their productivity may increase in response to projected global warming.

[Suitability of spatial pattern of camping sites in Langxiang Natural Reserve, Northeast Chi- na, based on GIS technology].

PubMed

Yuan, Wei; Zhang, Jie; Tan Ji-qiang; Zhou, Bo; Kang, Rui-cun; Wang, Ai-hong; Liu, Wei; Zhang, Lu

2015-09-01

It is an effective way for natural reserves to enhance self-supportive ability and realize sustainable development by developing ecotourism. Taking the experimental zone of Langxiang Natural Reserve in Heilongjiang Province as research object, the forest sub-compartment as research unit, and spatial pattern of environmental suitability of camping sites as research content, an evaluation index system taking natural environment, geographical security, infrastructure and traffic as project levels was built. Delphi and AHP methods were used to determine index weights. A spatial distribution map of camping environmental suitability in Langxiang Natural Reserve was drawn using the GIS spatial information processing technology based on "3S" measurement and the survey data. The results showed that the highest score for quantification of environmental suitability was 90, while the lowest score was 78, and the average value was 83.66 in the 1067 forest sub-compartments for test. The area of forest sub-compartments which were suitable for camping was 1094.44 hm2, being 12.2% of the experimental zone. The forest sub-compartments which had high environmental suitability in the research area were distributed uniformly and centralized with low degree of fragmentation. It was suggested that the contiguous forest sub-compartments with high scores of environmental suitability could be integrated for camping tourism. Due to the high level of environmental suitability for camping, the experimental zone of Langxiang Natural Reserve is suitable for developing camping tourism. Based on "3S" technology, the land use conditions of ecotourism environment of a natural reserve could be evaluated quickly and quantitatively by mathematical model.

Data Sparsity Considerations in Climate Impact Analysis for the Water Sector (Invited)

NASA Astrophysics Data System (ADS)

Asante, K. O.; Khimsara, P.; Chan, A.

2013-12-01

Scientists and planners are helping governments and communities around the world to prepare for climate change by performing local impact studies and developing adaptation plans. Most studies begin by analyzing global climate models outputs to estimate the magnitude of projected change, assessing vulnerabilities and proposing adaptation measures. In these studies, climate projections from the Intergovernmental Panel on Climate Change (IPCC) Data Distribution Centre (DDC) are either used directly or downscaled using regional models. Since climate projections cover the entire global, climate change analysis can be performed for any location. However, selection of climate projections for use in historically data sparse regions presents special challenges. Key questions arise about the impact of historical data sparsity on quality of climate projections, spatial consistency of results and suitability for applications such as water resource planning. In this paper, a water-sector climate study conducted in a data-rich setting in California is compared to a similar study conducted a data-sparse setting in Mozambique. The challenges of selecting projections, performing analysis and interpreting the results for climate adaption planning are compared to illustrate the decision process and challenges encountered in these two very different settings.

A parametric approach for simultaneous bias correction and high-resolution downscaling of climate model rainfall

NASA Astrophysics Data System (ADS)

Mamalakis, Antonios; Langousis, Andreas; Deidda, Roberto; Marrocu, Marino

2017-03-01

Distribution mapping has been identified as the most efficient approach to bias-correct climate model rainfall, while reproducing its statistics at spatial and temporal resolutions suitable to run hydrologic models. Yet its implementation based on empirical distributions derived from control samples (referred to as nonparametric distribution mapping) makes the method's performance sensitive to sample length variations, the presence of outliers, the spatial resolution of climate model results, and may lead to biases, especially in extreme rainfall estimation. To address these shortcomings, we propose a methodology for simultaneous bias correction and high-resolution downscaling of climate model rainfall products that uses: (a) a two-component theoretical distribution model (i.e., a generalized Pareto (GP) model for rainfall intensities above a specified threshold u*, and an exponential model for lower rainrates), and (b) proper interpolation of the corresponding distribution parameters on a user-defined high-resolution grid, using kriging for uncertain data. We assess the performance of the suggested parametric approach relative to the nonparametric one, using daily raingauge measurements from a dense network in the island of Sardinia (Italy), and rainfall data from four GCM/RCM model chains of the ENSEMBLES project. The obtained results shed light on the competitive advantages of the parametric approach, which is proved more accurate and considerably less sensitive to the characteristics of the calibration period, independent of the GCM/RCM combination used. This is especially the case for extreme rainfall estimation, where the GP assumption allows for more accurate and robust estimates, also beyond the range of the available data.

Combined X-ray CT and mass spectrometry for biomedical imaging applications

NASA Astrophysics Data System (ADS)

Schioppa, E., Jr.; Ellis, S.; Bruinen, A. L.; Visser, J.; Heeren, R. M. A.; Uher, J.; Koffeman, E.

2014-04-01

Imaging technologies play a key role in many branches of science, especially in biology and medicine. They provide an invaluable insight into both internal structure and processes within a broad range of samples. There are many techniques that allow one to obtain images of an object. Different techniques are based on the analysis of a particular sample property by means of a dedicated imaging system, and as such, each imaging modality provides the researcher with different information. The use of multimodal imaging (imaging with several different techniques) can provide additional and complementary information that is not possible when employing a single imaging technique alone. In this study, we present for the first time a multi-modal imaging technique where X-ray computerized tomography (CT) is combined with mass spectrometry imaging (MSI). While X-ray CT provides 3-dimensional information regarding the internal structure of the sample based on X-ray absorption coefficients, MSI of thin sections acquired from the same sample allows the spatial distribution of many elements/molecules, each distinguished by its unique mass-to-charge ratio (m/z), to be determined within a single measurement and with a spatial resolution as low as 1 μm or even less. The aim of the work is to demonstrate how molecular information from MSI can be spatially correlated with 3D structural information acquired from X-ray CT. In these experiments, frozen samples are imaged in an X-ray CT setup using Medipix based detectors equipped with a CO2 cooled sample holder. Single projections are pre-processed before tomographic reconstruction using a signal-to-thickness calibration. In the second step, the object is sliced into thin sections (circa 20 μm) that are then imaged using both matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and secondary ion (SIMS) mass spectrometry, where the spatial distribution of specific molecules within the sample is determined. The combination of two vastly different imaging approaches provides complementary information (i.e., anatomical and molecular distributions) that allows the correlation of distinct structural features with specific molecules distributions leading to unique insights in disease development.

Evolutionary hotspots in the Mojave Desert

USGS Publications Warehouse

Vandergast, Amy G.; Inman, Richard D.; Barr, Kelly R.; Nussear, Kenneth E.; Esque, Todd C.; Hathaway, Stacie A.; Wood, Dustin A.; Medica, Philip A.; Breinholt, Jesse W.; Stephen, Catherine L.; Gottscho, Andrew D.; Marks, Sharyn B.; Jennings, W. Bryan; Fisher, Robert N.

2013-01-01

Genetic diversity within species provides the raw material for adaptation and evolution. Just as regions of high species diversity are conservation targets, identifying regions containing high genetic diversity and divergence within and among populations may be important to protect future evolutionary potential. When multiple co-distributed species show spatial overlap in high genetic diversity and divergence, these regions can be considered evolutionary hotspots. We mapped spatial population genetic structure for 17 animal species across the Mojave Desert, USA. We analyzed these in concurrence and located 10 regions of high genetic diversity, divergence or both among species. These were mainly concentrated along the western and southern boundaries where ecotones between mountain, grassland and desert habitat are prevalent, and along the Colorado River. We evaluated the extent to which these hotspots overlapped protected lands and utility-scale renewable energy development projects of the Bureau of Land Management. While 30–40% of the total hotspot area was categorized as protected, between 3–7% overlapped with proposed renewable energy project footprints, and up to 17% overlapped with project footprints combined with transmission corridors. Overlap of evolutionary hotspots with renewable energy development mainly occurred in 6 of the 10 identified hotspots. Resulting GIS-based maps can be incorporated into ongoing landscape planning efforts and highlight specific regions where further investigation of impacts to population persistence and genetic connectivity may be warranted.

ICLUS v1.3 Population Projections

EPA Pesticide Factsheets

Climate and land-use change are major components of global environmental change with feedbacks between these components. The consequences of these interactions show that land use may exacerbate or alleviate climate change effects. Based on these findings it is important to use land-use scenarios that are consistent with the specific assumptions underlying climate-change scenarios. The Integrated Climate and Land-Use Scenarios (ICLUS) project developed land-use outputs that are based on a downscaled version of the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines. ICLUS outputs are derived from a pair of models. A demographic model generates county-level population estimates that are distributed by a spatial allocation model (SERGoM v3) as housing density across the landscape. Land-use outputs were developed for the four main SRES storylines and a baseline (base case). The model is run for the conterminous USA and output is available for each scenario by decade to 2100. In addition to housing density at a 1 hectare spatial resolution, this project also generated estimates of impervious surface at a resolution of 1 square kilometer. This shapefile holds population data for all counties of the conterminous USA for all decades (2010-2100) and SRES population growth scenarios (A1, A2, B1, B2), as well as a 'base case' (BC) scenario, for use in the Integrated Climate and Land Use

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

Natural habitats matter: Determinants of spatial pattern in the composition of animal assemblages of the Czech Republic

NASA Astrophysics Data System (ADS)

Divíšek, Jan; Zelený, David; Culek, Martin; Št'astný, Karel

2014-08-01

Studies that explore species-environment relationships at a broad scale are usually limited by the availability of sufficient habitat description, which is often too coarse to differentiate natural habitat patches. Therefore, it is not well understood how the distribution of natural habitats affects broad-scale patterns in the distribution of animal species. In this study, we evaluate the role of field-mapped natural habitats, land-cover types derived from remote sensing and climate on the composition of assemblages of five distinct animal groups, namely non-volant mammals, birds, reptiles, amphibians and butterflies native to the Czech Republic. First, we used variation partitioning based on redundancy analysis to evaluate the extent to which the environmental variables and their spatial structure might underlie the observed spatial patterns in the composition of animal assemblages. Second, we partitioned variations explained by climate, natural habitats and land-cover to compare their relative importance. Finally, we tested the independent effects of each variable in order to evaluate the significance of their contributions to the environmental model. Our results showed that spatial patterns in the composition of assemblages of almost all the considered animal groups may be ascribed mostly to variations in the environment. Although the shared effects of climatic variables, natural habitats and land-cover types explained the largest proportion of variation in each animal group, the variation explained purely by natural habitats was always higher than the variation explained purely by climate or land-cover. We conclude that most spatial variation in the composition of assemblages of almost all animal groups probably arises from biological processes operating within a spatially structured environment and suggest that natural habitats are important to explain observed patterns because they often perform better than habitat descriptions based on remote sensing. This underlines the value of using appropriate habitat data, for which high-resolution and large-area field-mapping projects are necessary.

Multi-sensor Oceanographic Correlations for Pacific Hake Acoustic Survey Improvement

NASA Astrophysics Data System (ADS)

Brozen, M.; Hillyer, N.; Holt, B.; Armstrong, E. M.

2010-12-01

North Pacific hake (Merluccius productus), the most abundant groundfish along the Pacific coast of northwestern America, are an essential source of income for the coastal region from southern California to British Columbia, Canada. However, hake abundance and distribution are highly variable among years, exhibiting variance in both the north-south and east-west distribution as seen in the results from biannual acoustic surveys. This project is part of a larger undertaking, ultimately focused on the prediction of hake distribution to improve the distribution of survey effort and precision of stock assessments in the future. Four remotely sensed oceanographic variables are examined as a first step in improving our understanding the relationship between the intensity of coastal upwelling and other ocean dynamics, and the north-south summer hake distribution. Sea surface height, wind vectors, chlorophyll - a concentrations, and sea surface temperature were acquired from several satellites, including AVHRR, SeaWifs, TOPEX/Poseidon, Jason-1, Jason-2, SSM/I, ASMR-E, and QuikScat. Data were aligned to the same spatial and temporal resolution, and these re-gridded data were then analyzed using empirical orthogonal functions (EOFs). EOFs were used as a spatio-temporally compact representation of the data and to reduce the co-variability of the multiple time series in the dataset. The EOF results were plotted and acoustic survey results were overlaid to understand differences between regions. Although this pilot project used data from only a single year (2007), it demonstrated a methodology for reducing dimensionality of linearly related satellite variables that can used in future applications, and provided insight into multi-dimensional ocean characteristics important for hake distribution.

Development of Semi-distributed ecohydrological model in the Rio Grande De Manati River Basin, Puerto Rico

NASA Astrophysics Data System (ADS)

Setegn, S. G.; Ortiz, J.; Melendez, J.; Barreto, M.; Torres-Perez, J. L.; Guild, L. S.

2015-12-01

There are limited studies in Puerto Rico that shows the water resources availability and variability with respect to changing climates and land use. The main goal of the HICE-PR (Human Impacts to Coastal Ecosystems in Puerto Rico (HICE-PR): the Río Loco Watershed (southwest coast PR) project which was funded by NASA is to evaluate the impacts of land use/land cover changes on the quality and extent of coastal and marine ecosystems (CMEs) in two priority watersheds in Puerto Rico (Manatí and Guánica).The main objective of this study is to set up a physically based spatially distributed hydrological model, Soil and Water Assessment Tool (SWAT) for the analysis of hydrological processes in the Rio Grande de Manati river basin. SWAT (soil and water assessment tool) is a spatially distributed watershed model developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds. For efficient use of distributed models for hydrological and scenario analysis, it is important that these models pass through a careful calibration and uncertainty analysis. The model was calibrated and validated using Sequential Uncertainty Fitting (SUFI-2) calibration and uncertainty analysis algorithms. The model evaluation statistics for streamflows prediction shows that there is a good agreement between the measured and simulated flows that was verified by coefficients of determination and Nash Sutcliffe efficiency greater than 0.5. Keywords: Hydrological Modeling; SWAT; SUFI-2; Rio Grande De Manati; Puerto Rico

Spatial and temporal distribution of trunk-injected imidacloprid in apple tree canopies.

PubMed

Aćimović, Srđan G; VanWoerkom, Anthony H; Reeb, Pablo D; Vandervoort, Christine; Garavaglia, Thomas; Cregg, Bert M; Wise, John C

2014-11-01

Pesticide use in orchards creates drift-driven pesticide losses which contaminate the environment. Trunk injection of pesticides as a target-precise delivery system could greatly reduce pesticide losses. However, pesticide efficiency after trunk injection is associated with the underinvestigated spatial and temporal distribution of the pesticide within the tree crown. This study quantified the spatial and temporal distribution of trunk-injected imidacloprid within apple crowns after trunk injection using one, two, four or eight injection ports per tree. The spatial uniformity of imidacloprid distribution in apple crowns significantly increased with more injection ports. Four ports allowed uniform spatial distribution of imidacloprid in the crown. Uniform and non-uniform spatial distributions were established early and lasted throughout the experiment. The temporal distribution of imidacloprid was significantly non-uniform. Upper and lower crown positions did not significantly differ in compound concentration. Crown concentration patterns indicated that imidacloprid transport in the trunk occurred through radial diffusion and vertical uptake with a spiral pattern. By showing where and when a trunk-injected compound is distributed in the apple tree canopy, this study addresses a key knowledge gap in terms of explaining the efficiency of the compound in the crown. These findings allow the improvement of target-precise pesticide delivery for more sustainable tree-based agriculture. © 2014 Society of Chemical Industry.

Integrated monitoring and information systems for managing aquatic invasive species in a changing climate.

PubMed

Lee, Henry; Reusser, Deborah A; Olden, Julian D; Smith, Scott S; Graham, Jim; Burkett, Virginia; Dukes, Jeffrey S; Piorkowski, Robert J; McPhedran, John

2008-06-01

Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change.

Integrated monitoring and information systems for managing aquatic invasive species in a changing climate

USGS Publications Warehouse

Lee, Henry; Reusser, Deborah A.; Olden, Julian D.; Smith, Scott S.; Graham, Jim; Burkett, Virginia; Dukes, Jeffrey S.; Piorkowski, Robert J.; Mcphedran, John

2008-01-01

Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change

Modeling evolution of spatially distributed bacterial communities: a simulation with the haploid evolutionary constructor

PubMed Central

2015-01-01

Background Multiscale approaches for integrating submodels of various levels of biological organization into a single model became the major tool of systems biology. In this paper, we have constructed and simulated a set of multiscale models of spatially distributed microbial communities and study an influence of unevenly distributed environmental factors on the genetic diversity and evolution of the community members. Results Haploid Evolutionary Constructor software http://evol-constructor.bionet.nsc.ru/ was expanded by adding the tool for the spatial modeling of a microbial community (1D, 2D and 3D versions). A set of the models of spatially distributed communities was built to demonstrate that the spatial distribution of cells affects both intensity of selection and evolution rate. Conclusion In spatially heterogeneous communities, the change in the direction of the environmental flow might be reflected in local irregular population dynamics, while the genetic structure of populations (frequencies of the alleles) remains stable. Furthermore, in spatially heterogeneous communities, the chemotaxis might dramatically affect the evolution of community members. PMID:25708911

Research on the optimization of air quality monitoring station layout based on spatial grid statistical analysis method.

PubMed

Li, Tianxin; Zhou, Xing Chen; Ikhumhen, Harrison Odion; Difei, An

2018-05-01

In recent years, with the significant increase in urban development, it has become necessary to optimize the current air monitoring stations to reflect the quality of air in the environment. Highlighting the spatial representation of some air monitoring stations using Beijing's regional air monitoring station data from 2012 to 2014, the monthly mean particulate matter concentration (PM10) in the region was calculated and through the IDW interpolation method and spatial grid statistical method using GIS, the spatial distribution of PM10 concentration in the whole region was deduced. The spatial distribution variation of districts in Beijing using the gridding model was performed, and through the 3-year spatial analysis, PM10 concentration data including the variation and spatial overlay (1.5 km × 1.5 km cell resolution grid), the spatial distribution result obtained showed that the total PM10 concentration frequency variation exceeded the standard. It is very important to optimize the layout of the existing air monitoring stations by combining the concentration distribution of air pollutants with the spatial region using GIS.

Setting local rank constraints by orthogonal projections for image resolution analysis: application to the determination of a low dose pharmaceutical compound.

PubMed

Boiret, Mathieu; de Juan, Anna; Gorretta, Nathalie; Ginot, Yves-Michel; Roger, Jean-Michel

2015-09-10

Raman chemical imaging provides chemical and spatial information about pharmaceutical drug product. By using resolution methods on acquired spectra, the objective is to calculate pure spectra and distribution maps of image compounds. With multivariate curve resolution-alternating least squares, constraints are used to improve the performance of the resolution and to decrease the ambiguity linked to the final solution. Non negativity and spatial local rank constraints have been identified as the most powerful constraints to be used. In this work, an alternative method to set local rank constraints is proposed. The method is based on orthogonal projections pretreatment. For each drug product compound, raw Raman spectra are orthogonally projected to a basis including all the variability from the formulation compounds other than the product of interest. Presence or absence of the compound of interest is obtained by observing the correlations between the orthogonal projected spectra and a pure spectrum orthogonally projected to the same basis. By selecting an appropriate threshold, maps of presence/absence of compounds can be set up for all the product compounds. This method appears as a powerful approach to identify a low dose compound within a pharmaceutical drug product. The maps of presence/absence of compounds can be used as local rank constraints in resolution methods, such as multivariate curve resolution-alternating least squares process in order to improve the resolution of the system. The method proposed is particularly suited for pharmaceutical systems, where the identity of all compounds in the formulations is known and, therefore, the space of interferences can be well defined. Copyright © 2015 Elsevier B.V. All rights reserved.

Speed scanning system based on solid-state microchip laser for architectural planning

NASA Astrophysics Data System (ADS)

Redka, Dmitriy; Grishkanich, Alexsandr S.; Kolmakov, Egor; Tsvetkov, Konstantin

2017-10-01

According to the current great interest concerning Large-Scale Metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance, are assuming a more and more important role among system requirements. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The system consists of a distributed network-based layout, whose modularity allows to fit differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load.

Coordinate measuring system based on microchip lasers for reverse prototyping

NASA Astrophysics Data System (ADS)

Iakovlev, Alexey; Grishkanich, Alexsandr S.; Redka, Dmitriy; Tsvetkov, Konstantin

2017-02-01

According to the current great interest concerning Large-Scale Metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance, are assuming a more and more important role among system requirements. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of chip and microlasers as radiators on the linear-angular characteristics of existing measurement systems. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The system consists of a distributed network-based layout, whose modularity allows to fit differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load.

The interplay of climate and land use change affects the distribution of EU bumblebees.

PubMed

Marshall, Leon; Biesmeijer, Jacobus C; Rasmont, Pierre; Vereecken, Nicolas J; Dvorak, Libor; Fitzpatrick, Una; Francis, Frédéric; Neumayer, Johann; Ødegaard, Frode; Paukkunen, Juho P T; Pawlikowski, Tadeusz; Reemer, Menno; Roberts, Stuart P M; Straka, Jakub; Vray, Sarah; Dendoncker, Nicolas

2018-01-01

Bumblebees in Europe have been in steady decline since the 1900s. This decline is expected to continue with climate change as the main driver. However, at the local scale, land use and land cover (LULC) change strongly affects the occurrence of bumblebees. At present, LULC change is rarely included in models of future distributions of species. This study's objective is to compare the roles of dynamic LULC change and climate change on the projected distribution patterns of 48 European bumblebee species for three change scenarios until 2100 at the scales of Europe, and Belgium, Netherlands and Luxembourg (BENELUX). We compared three types of models: (1) only climate covariates, (2) climate and static LULC covariates and (3) climate and dynamic LULC covariates. The climate and LULC change scenarios used in the models include, extreme growth applied strategy (GRAS), business as might be usual and sustainable European development goals. We analysed model performance, range gain/loss and the shift in range limits for all bumblebees. Overall, model performance improved with the introduction of LULC covariates. Dynamic models projected less range loss and gain than climate-only projections, and greater range loss and gain than static models. Overall, there is considerable variation in species responses and effects were most pronounced at the BENELUX scale. The majority of species were predicted to lose considerable range, particularly under the extreme growth scenario (GRAS; overall mean: 64% ± 34). Model simulations project a number of local extinctions and considerable range loss at the BENELUX scale (overall mean: 56% ± 39). Therefore, we recommend species-specific modelling to understand how LULC and climate interact in future modelling. The efficacy of dynamic LULC change should improve with higher thematic and spatial resolution. Nevertheless, current broad scale representations of change in major land use classes impact modelled future distribution patterns. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Climate Risk and Vulnerability in the Caribbean and Gulf of Mexico Region: Interactions with Spatial Population and Land Cover Change

NASA Astrophysics Data System (ADS)

Chen, R. S.; Levy, M.; Baptista, S.; Adamo, S.

2010-12-01

Vulnerability to climate variability and change will depend on dynamic interactions between different aspects of climate, land-use change, and socioeconomic trends. Measurements and projections of these changes are difficult at the local scale but necessary for effective planning. New data sources and methods make it possible to assess land-use and socioeconomic changes that may affect future patterns of climate vulnerability. In this paper we report on new time series data sets that reveal trends in the spatial patterns of climate vulnerability in the Caribbean/Gulf of Mexico Region. Specifically, we examine spatial time series data for human population over the period 1990-2000, time series data on land use and land cover over 2000-2009, and infant mortality rates as a proxy for poverty for 2000-2008. We compare the spatial trends for these measures to the distribution of climate-related natural disaster risk hotspots (cyclones, floods, landslides, and droughts) in terms of frequency, mortality, and economic losses. We use these data to identify areas where climate vulnerability appears to be increasing and where it may be decreasing. Regions where trends and patterns are especially worrisome include coastal areas of Guatemala and Honduras.

Multidimensionally encoded magnetic resonance imaging.

PubMed

Lin, Fa-Hsuan

2013-07-01

Magnetic resonance imaging (MRI) typically achieves spatial encoding by measuring the projection of a q-dimensional object over q-dimensional spatial bases created by linear spatial encoding magnetic fields (SEMs). Recently, imaging strategies using nonlinear SEMs have demonstrated potential advantages for reconstructing images with higher spatiotemporal resolution and reducing peripheral nerve stimulation. In practice, nonlinear SEMs and linear SEMs can be used jointly to further improve the image reconstruction performance. Here, we propose the multidimensionally encoded (MDE) MRI to map a q-dimensional object onto a p-dimensional encoding space where p > q. MDE MRI is a theoretical framework linking imaging strategies using linear and nonlinear SEMs. Using a system of eight surface SEM coils with an eight-channel radiofrequency coil array, we demonstrate the five-dimensional MDE MRI for a two-dimensional object as a further generalization of PatLoc imaging and O-space imaging. We also present a method of optimizing spatial bases in MDE MRI. Results show that MDE MRI with a higher dimensional encoding space can reconstruct images more efficiently and with a smaller reconstruction error when the k-space sampling distribution and the number of samples are controlled. Copyright © 2012 Wiley Periodicals, Inc.

Continuous Variable Cluster State Generation over the Optical Spatial Mode Comb

DOE PAGES

Pooser, Raphael C.; Jing, Jietai

2014-10-20

One way quantum computing uses single qubit projective measurements performed on a cluster state (a highly entangled state of multiple qubits) in order to enact quantum gates. The model is promising due to its potential scalability; the cluster state may be produced at the beginning of the computation and operated on over time. Continuous variables (CV) offer another potential benefit in the form of deterministic entanglement generation. This determinism can lead to robust cluster states and scalable quantum computation. Recent demonstrations of CV cluster states have made great strides on the path to scalability utilizing either time or frequency multiplexingmore » in optical parametric oscillators (OPO) both above and below threshold. The techniques relied on a combination of entangling operators and beam splitter transformations. Here we show that an analogous transformation exists for amplifiers with Gaussian inputs states operating on multiple spatial modes. By judicious selection of local oscillators (LOs), the spatial mode distribution is analogous to the optical frequency comb consisting of axial modes in an OPO cavity. We outline an experimental system that generates cluster states across the spatial frequency comb which can also scale the amount of quantum noise reduction to potentially larger than in other systems.« less

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

NASA Technical Reports Server (NTRS)

Dorfman, Erik; Cromp, Robert F.

1992-01-01

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

Spectral refractive index assessment of turbid samples by combining spatial frequency near-infrared spectroscopy with Kramers-Kronig analysis

NASA Astrophysics Data System (ADS)

Meitav, Omri; Shaul, Oren; Abookasis, David

2018-03-01

A practical algorithm for estimating the wavelength-dependent refractive index (RI) of a turbid sample in the spatial frequency domain with the aid of Kramers-Kronig (KK) relations is presented. In it, phase-shifted sinusoidal patterns (structured illumination) are serially projected at a high spatial frequency onto the sample surface (mouse scalp) at different near-infrared wavelengths while a camera mounted normally to the sample surface captures the reflected diffuse light. In the offline analysis pipeline, recorded images at each wavelength are converted to spatial absorption maps by logarithmic function, and once the absorption coefficient information is obtained, the imaginary part (k) of the complex RI (CRI), based on Maxell's equations, can be calculated. Using the data represented by k, the real part of the CRI (n) is then resolved by KK analysis. The wavelength dependence of n ( λ ) is then fitted separately using four standard dispersion models: Cornu, Cauchy, Conrady, and Sellmeier. In addition, three-dimensional surface-profile distribution of n is provided based on phase profilometry principles and a phase-unwrapping-based phase-derivative-variance algorithm. Experimental results demonstrate the capability of the proposed idea for sample's determination of a biological sample's RI value.

Nightlights along the Eastern Alpine river network in Austria and Italy as a proxy of human presence

NASA Astrophysics Data System (ADS)

Ceola, Serena; Montanari, Alberto; Parajka, Juraj; Viglione, Alberto; Bloeschl, Guenter

2016-04-01

Understanding the spatial and temporal distribution of human settlements and economic activities in relation to the geographical location of streams and rivers is of fundamental concern for several hydrologic issues such as flood risk and drought management, water pollution and exploitation, as well as stream ecological purposes. Indeed, the human presence close to streams and rivers is known to have consistently increased worldwide, therefore introducing dramatic anthropogenic and environmental changes. This research study analyses the spatial and temporal evolution of human settlements and associated economic activity, derived from nighttime lights, in the Eastern Alpine region. Nightlights, available at a 1 km spatial resolution and for a 22-year period, constitute an excellent data base, which allows to explore in details human signatures. In this experiment, nightlights are associated to five distinct distance-from-river classes, by using the CCM river network data base. From the temporal perspective, nightlights in correspondence of each distance-from-river class within each study region show an overall increasing trend, whereas the spatial trends differs among the study regions. More information about the analysis and project are available at: http://www.water-switch-on.eu/.

Characterization of spatial distribution of Tetranychus urticae in peppermint in California and implication for improving sampling plan.

PubMed

Rijal, Jhalendra P; Wilson, Rob; Godfrey, Larry D

2016-02-01

Twospotted spider mite, Tetranychus urticae Koch, is an important pest of peppermint in California, USA. Spider mite feeding on peppermint leaves causes physiological changes in the plant, which coupling with the favorable environmental condition can lead to increased mite infestations. Significant yield loss can occur in absence of pest monitoring and timely management. Understating the within-field spatial distribution of T. urticae is critical for the development of reliable sampling plan. The study reported here aims to characterize the spatial distribution of mite infestation in four commercial peppermint fields in northern California using spatial techniques, variogram and Spatial Analysis by Distance IndicEs (SADIE). Variogram analysis revealed that there was a strong evidence for spatially dependent (aggregated) mite population in 13 of 17 sampling dates and the physical distance of the aggregation reached maximum to 7 m in peppermint fields. Using SADIE, 11 of 17 sampling dates showed aggregated distribution pattern of mite infestation. Combining results from variogram and SADIE analysis, the spatial aggregation of T. urticae was evident in all four fields for all 17 sampling dates evaluated. Comparing spatial association using SADIE, ca. 62% of the total sampling pairs showed a positive association of mite spatial distribution patterns between two consecutive sampling dates, which indicates a strong spatial and temporal stability of mite infestation in peppermint fields. These results are discussed in relation to behavior of spider mite distribution within field, and its implications for improving sampling guidelines that are essential for effective pest monitoring and management.

Extreme heat event projections for a coastal megacity

NASA Astrophysics Data System (ADS)

Ortiz, L. E.; Gonzalez, J.

2017-12-01

As summers become warmer, extreme heat events are expected to increase in intensity, frequency, and duration. Large urban centers may affect these projections by introducing feedbacks between the atmosphere and the built environment through processes involving anthropogenic heat, wind modification, radiation blocking, and others. General circulation models are often run with spatial resolutions in the order of 100 km, limiting their skill at resolving local scale processes and highly spatially varying features such as cities' heterogeneous landscape and mountain topography. This study employs climate simulations using the Weather Research and Forecast (WRF) model coupled with a modified multi-layer urban canopy and building energy model to downscale CESM1 at 1 km horizontal resolution across three time slices (2006-2010, 2075-2079, and 2095-2099) and two projections (RCP 4.5 and 8.5). New York City Metropolitan area, with a population of over 20 million and a complex urban canopy, is used as a case study. The urban canopy model of WRF was modified to include a drag coefficient as a function of the building plant area fraction and the introduction of evaporative cooling systems at building roofs to reject the anthropogenic heat from the buildings, with urban canopy parameters computed from the New York City Property Land-Use Tax-lot Output (PLUTO). Model performance is evaluated against the input model and historical records from airport stations, showing improvement in the statistical characteristics in the downscaled model output. Projection results are presented as spatially distributed anomalies in heat wave frequency, duration, and maximum intensity from the 2006-2010 benchmark period. Results show that local sea-breeze circulations mitigate heat wave impacts, following a positive gradient with increasing distance from the coastline. However, end of century RCP 8.5 projections show the possibility of reversal of this pattern, sea surface temperatures increase and reduce the sea-land temperature gradient, thus reducing the sea-breeze magnitude. Impacts to human health and buildings energy demand are explored for future climate scenarios as key examples of anticipated societal consequences.

Thematic and spatial resolutions affect model-based predictions of tree species distribution.

PubMed

Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei

2013-01-01

Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

Thematic and Spatial Resolutions Affect Model-Based Predictions of Tree Species Distribution

PubMed Central

Liang, Yu; He, Hong S.; Fraser, Jacob S.; Wu, ZhiWei

2013-01-01

Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution. PMID:23861828

Integration of DAS (distributed acoustic sensing) vertical seismic profile and geostatistically modeled lithology data to characterize an enhanced geothermal system.

NASA Astrophysics Data System (ADS)

Cronin, S. P.; Trainor Guitton, W.; Team, P.; Pare, A.; Jreij, S.; Powers, H.

2017-12-01

In March 2016, a 4-week field data acquisition took place at Brady's Natural Lab (BNL), an enhanced geothermal system (EGS) in Fallan, NV. During these 4 weeks, a vibe truck executed 6,633 sweeps, recorded by nodal seismometers, horizontal distributed acoustic sensing (DAS) cable, and 400 meters of vertical DAS cable. DAS provides lower signal to noise ratio than traditional geophones but better spatial resolution. The analysis of DAS VSP included Fourier transform, and filtering to remove all up-going energy. Thus, allowing for accurate first arrival picking. We present an example of the Gradual Deformation Method (GDM) using DAS VSP and lithological data to produce a distribution of valid velocity models of BNL. GDM generates continuous perturbations of prior model realizations seeking the best match to the data (i.e. minimize the misfit). Prior model realizations honoring the lithological data were created using sequential Gaussian simulation, a commonly used noniterative geostatistical method. Unlike least-squares-based methods of inversion, GDM readily incorporates a priori information, such as a variogram calculated from well-based lithology information. Additionally, by producing a distribution of models, as opposed to one optimal model, GDM allows for uncertainty quantification. This project aims at assessing the integrated technologies ability to monitor changes in the water table (possibly to one meter resolution) by exploiting the dependence of seismic wave velocities on water saturation of the subsurface. This project, which was funded in part by the National Science Foundation, is a part of the PoroTomo project, funded by a grant from the U.S. Department of Energy.

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

NASA Astrophysics Data System (ADS)

Boldina, Inna; Beninger, Peter G.

2014-04-01

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

Assessment of simulated and projected climate change in Pakistan using IPCC AR4-based AOGCMs

NASA Astrophysics Data System (ADS)

Saeed, F.; Athar, H.

2017-11-01

A detailed spatio-temporal assessment of two basic climatic parameters (temperature and precipitation) is carried out using 22 Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4)-based atmospheric oceanic general circulation models (AOGCMs) over data-sparse and climatically vulnerable region of Pakistan (20°-37° N and 60°-78° E), for the first time, for the baseline period (1975-1999), as well as for the three projected periods during the twenty-first century centered at 2025-2049, 2050-2074, and 2075-2099, respectively, both on seasonal and on annual bases, under three Special Report on Emission Scenarios (SRES): A2, A1B, and B1. An ensemble-based approach consisting of the IPCC AR4-based AOGCMs indicates that during the winter season (from December to March), 66% of the models display robust projected increase of winter precipitation by about 10% relative to the baseline period, irrespective of emission scenario and projection period, in the upper northern subregion of Pakistan (latitude > 35° N). The projected robust changes in the temperature by the end of twenty-first century are in the range of 3 to 4 ° C during the winter season and on an annual basis, in the central and western regions of Punjab province, especially in A2 and A1B emission scenarios. In particular, the IPCC AR4 models project a progressive increase in temperature throughout Pakistan, in contrast to spatial distribution of precipitation, where spatially less uniform and robust results for projected periods are obtained on sign of change. In general, changes in both precipitation and temperature are larger in the summer season (JAS) as compared to the winter season in the coming decades, relative to the baseline period. This may require comprehensive long-term strategic policies to adapt and mitigate climate change in Pakistan, in comparison to what is currently envisaged.

Future Freshwater Stress on Small Islands: Population, Aridity and Global Warming Targets

NASA Astrophysics Data System (ADS)

Karnauskas, K. B.; Schleussner, C. F.; Donnelly, J. P.; Anchukaitis, K. J.

2017-12-01

Small island developing states (SIDS) face multiple threats from anthropogenic climate change, including potential changes in freshwater resource availability. Future freshwater stress, including geographic and seasonal variability, has important implications for climate change adaptation scenarios for vulnerable human populations living on islands across the world ocean. Due to a mismatch in spatial scale between SIDS landforms and the horizontal resolution of global climate models (GCMs), SIDS are mostly unaccounted for in GCMs that are used to make future projections of global climate change and its regional impacts. Specific approaches are required to address this gap between broad-scale model projections and regional, policy-relevant outcomes. Here we apply a recently developed methodology to project future changes in aridity in combination with population projections associated with different shared socioeconomic pathways (SSPs) to evaluate overall changes in freshwater stress in SIDS at warming levels of 1.5°C and 2°C above pre-industrial levels. By accounting for evaporative demand a posteriori, we reveal a robust yet spatially variable tendency towards increasing aridity for 16 million people living on islands by mid-century. Although about half of the islands are projected to experience increased rainfall—predominantly in the deep tropics—projected changes in evaporation are more uniform, shifting the global distribution of changes in island freshwater balance towards greater aridity. In many cases, the magnitude of projected drying is comparable to the amplitude of the estimated observed interannual variability, with important consequences for extreme events. While we find that future population growth will dominate changes in projected freshwater stress especially towards the end of the century, projected changes in aridity are found to compound freshwater stress for the vast majority of SIDS. Particularly across the Caribbean region, a substantial fraction ( 25%) of the large overall freshwater stress projected under 2°C at 2030 can be avoided by limiting global warming to 1.5°C. Our findings add to a growing body of literature on the difference in climate impacts between 1.5°C and 2°C and underscore the need for regionally specific analysis.

Interactions of satellite-speed helium atoms with satellite surfaces. 3: Drag coefficients from spatial and energy distributions of reflected helium atoms

NASA Technical Reports Server (NTRS)

Sharma, P. K.; Knuth, E. L.

1977-01-01

Spatial and energy distributions of helium atoms scattered from an anodized 1235-0 aluminum surface as well as the tangential and normal momentum accommodation coefficients calculated from these distributions are reported. A procedure for calculating drag coefficients from measured values of spatial and energy distributions is given. The drag coefficient calculated for a 6061 T-6 aluminum sphere is included.

[The ecology of ticks, tick-borne diseases and biological tick control in Baden-Württemberg].

PubMed

Sebastian, P; Mackenstedt, U; Wassermann, M; Wurst, E; Hartelt, K; Petney, T; Pfäffle, M; Littwin, N; Steidle, J L M; Selzer, P; Norra, S; Böhnke, D; Gebhardt, R; Kahl, O; Dautel, H; Oehme, R

2014-05-01

Ticks and tick-borne diseases are of great significance for the health of humans and animals. However, the factors influencing their distribution and dynamics are inadequately known. In a project financed by the Baden-Württemberg Ministry of the Environment, Climate and Energy Industry, as part of the program BWPLUS, interdisciplinary specialists work together to determine the influence of weather, (micro)climate, habitat, land use, human activities, and the population dynamics of host animals on the distribution and abundance of ticks and the diseases that they transmit in Baden-Württemberg. The project comprises four modules: the large-scale distribution of ticks in Baden-Württemberg (module 1), detailed studies of host-tick-pathogen interaction in relation to the microclimate (module 2), and the spatial occurrence of important tick-borne pathogens (module 3). The fourth module involves the comprehensive analysis and synthesis of all data in order to determine the relative importance of the factors studied and to develop a risk model. Recently, intensive investigations into tick control have been undertaken using various entomopathogenic fungi and nematodes as well as a parasitoid wasp. Our aim was to determine whether these natural enemies could be used to effectively reduce the number of free-living ticks.

Predicting probability of occurrence and factors affecting distribution and abundance of three Ozark endemic crayfish species at multiple spatial scales

USGS Publications Warehouse

Nolen, Matthew S.; Magoulick, Daniel D.; DiStefano, Robert J.; Imhoff, Emily M.; Wagner, Brian K.

2014-01-01

We found that a range of environmental variables were important in predicting crayfish distribution and abundance at multiple spatial scales and their importance was species-, response variable- and scale dependent. We would encourage others to examine the influence of spatial scale on species distribution and abundance patterns.

Data set: 31 years of spatially distributed air temperature, humidity, precipitation amount and precipitation phase from a mountain catchment in the rain-snow transition zone

USDA-ARS?s Scientific Manuscript database

Thirty one years of spatially distributed air temperature, relative humidity, dew point temperature, precipitation amount, and precipitation phase data are presented for the Reynolds Creek Experimental Watershed. The data are spatially distributed over a 10m Lidar-derived digital elevation model at ...

The global impact distribution of Near-Earth objects

NASA Astrophysics Data System (ADS)

Rumpf, Clemens; Lewis, Hugh G.; Atkinson, Peter M.

2016-02-01

Asteroids that could collide with the Earth are listed on the publicly available Near-Earth object (NEO) hazard web sites maintained by the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA). The impact probability distribution of 69 potentially threatening NEOs from these lists that produce 261 dynamically distinct impact instances, or Virtual Impactors (VIs), were calculated using the Asteroid Risk Mitigation and Optimization Research (ARMOR) tool in conjunction with OrbFit. ARMOR projected the impact probability of each VI onto the surface of the Earth as a spatial probability distribution. The projection considers orbit solution accuracy and the global impact probability. The method of ARMOR is introduced and the tool is validated against two asteroid-Earth collision cases with objects 2008 TC3 and 2014 AA. In the analysis, the natural distribution of impact corridors is contrasted against the impact probability distribution to evaluate the distributions' conformity with the uniform impact distribution assumption. The distribution of impact corridors is based on the NEO population and orbital mechanics. The analysis shows that the distribution of impact corridors matches the common assumption of uniform impact distribution and the result extends the evidence base for the uniform assumption from qualitative analysis of historic impact events into the future in a quantitative way. This finding is confirmed in a parallel analysis of impact points belonging to a synthetic population of 10,006 VIs. Taking into account the impact probabilities introduced significant variation into the results and the impact probability distribution, consequently, deviates markedly from uniformity. The concept of impact probabilities is a product of the asteroid observation and orbit determination technique and, thus, represents a man-made component that is largely disconnected from natural processes. It is important to consider impact probabilities because such information represents the best estimate of where an impact might occur.

Evidence for an Accretion Origin for the Outer Halo Globular Cluster System of M31

NASA Astrophysics Data System (ADS)

Mackey, A. D.; Huxor, A. P.; Ferguson, A. M. N.; Irwin, M. J.; Tanvir, N. R.; McConnachie, A. W.; Ibata, R. A.; Chapman, S. C.; Lewis, G. F.

2010-07-01

We use a sample of newly discovered globular clusters from the Pan-Andromeda Archaeological Survey (PAndAS) in combination with previously cataloged objects to map the spatial distribution of globular clusters in the M31 halo. At projected radii beyond ≈30 kpc, where large coherent stellar streams are readily distinguished in the field, there is a striking correlation between these features and the positions of the globular clusters. Adopting a simple Monte Carlo approach, we test the significance of this association by computing the probability that it could be due to the chance alignment of globular clusters smoothly distributed in the M31 halo. We find that the likelihood of this possibility is low, below 1%, and conclude that the observed spatial coincidence between globular clusters and multiple tidal debris streams in the outer halo of M31 reflects a genuine physical association. Our results imply that the majority of the remote globular cluster system of M31 has been assembled as a consequence of the accretion of cluster-bearing satellite galaxies. This constitutes the most direct evidence to date that the outer halo globular cluster populations in some galaxies are largely accreted. Based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Science de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii.

Planetary Spatial Analyst

NASA Technical Reports Server (NTRS)

Keely, Leslie

2008-01-01

This is a status report for the project entitled Planetary Spatial Analyst (PSA). This report covers activities from the project inception on October 1, 2007 to June 1, 2008. Originally a three year proposal, PSA was awarded funding for one year and required a revised work statement and budget. At the time of this writing the project is well on track both for completion of work as well as budget. The revised project focused on two objectives: build a solid connection with the target community and implement a prototype software application that provides 3D visualization and spatial analysis technologies for that community. Progress has been made for both of these objectives.

Spatial distribution of soil organic carbon stock in Moso bamboo forests in subtropical China.

PubMed

Tang, Xiaolu; Xia, Mingpeng; Pérez-Cruzado, César; Guan, Fengying; Fan, Shaohui

2017-02-14

Moso bamboo (Phyllostachys heterocycla (Carr.) Mitford cv. Pubescens) is an important timber substitute in China. Site specific stand management requires an accurate estimate of soil organic carbon (SOC) stock for maintaining stand productivity and understanding global carbon cycling. This study compared ordinary kriging (OK) and inverse distance weighting (IDW) approaches to study the spatial distribution of SOC stock within 0-60 cm using 111 soil samples in Moso bamboo forests in subtropical China. Similar spatial patterns but different spatial distribution ranges of SOC stock from OK and IDW highlighted the necessity to apply different approaches to obtain accurate and consistent results of SOC stock distribution. Different spatial patterns of SOC stock suggested the use of different fertilization treatments in Moso bamboo forests across the study area. SOC pool within 0-60 cm was 6.46 and 6.22 Tg for OK and IDW; results which were lower than that of conventional approach (CA, 7.41 Tg). CA is not recommended unless coordinates of the sampling locations are missing and the spatial patterns of SOC stock are not required. OK is recommended for the uneven distribution of sampling locations. Our results can improve methodology selection for investigating spatial distribution of SOC stock in Moso bamboo forests.

Spatial distribution of soil organic carbon stock in Moso bamboo forests in subtropical China

PubMed Central

Tang, Xiaolu; Xia, Mingpeng; Pérez-Cruzado, César; Guan, Fengying; Fan, Shaohui

2017-01-01

Moso bamboo (Phyllostachys heterocycla (Carr.) Mitford cv. Pubescens) is an important timber substitute in China. Site specific stand management requires an accurate estimate of soil organic carbon (SOC) stock for maintaining stand productivity and understanding global carbon cycling. This study compared ordinary kriging (OK) and inverse distance weighting (IDW) approaches to study the spatial distribution of SOC stock within 0–60 cm using 111 soil samples in Moso bamboo forests in subtropical China. Similar spatial patterns but different spatial distribution ranges of SOC stock from OK and IDW highlighted the necessity to apply different approaches to obtain accurate and consistent results of SOC stock distribution. Different spatial patterns of SOC stock suggested the use of different fertilization treatments in Moso bamboo forests across the study area. SOC pool within 0–60 cm was 6.46 and 6.22 Tg for OK and IDW; results which were lower than that of conventional approach (CA, 7.41 Tg). CA is not recommended unless coordinates of the sampling locations are missing and the spatial patterns of SOC stock are not required. OK is recommended for the uneven distribution of sampling locations. Our results can improve methodology selection for investigating spatial distribution of SOC stock in Moso bamboo forests. PMID:28195207

The Emergence of Regional Immigrant Concentrations in USA and Australia: A Spatial Relatedness Approach

PubMed Central

Novotny, Josef; Hasman, Jiri

2015-01-01

This paper examines the patterns of the US and Australian immigration geography and the process of regional population diversification and the emergence of new immigrant concentrations at the regional level. It presents a new approach in the context of human migration studies, focusing on spatial relatedness between individual foreign-born groups as revealed from the analysis of their joint spatial concentrations. The approach employs a simple assumption that the more frequently the members of two population groups concentrate in the same locations the higher is the probability that these two groups can be related. Based on detailed data on the spatial distribution of foreign-born groups in US counties (2000–2010) and Australian postal areas (2006–2011) we firstly quantify the spatial relatedness between all pairs of foreign-born groups and model the aggregate patterns of US and Australian immigration systems conceptualized as the undirected networks of foreign-born groups linked by their spatial relatedness. Secondly, adopting a more dynamic perspective, we assume that immigrant groups with higher spatial relatedness to those groups already concentrated in a region are also more likely to settle in this region in future. As the ultimate goal of the paper, we examine the power of spatial relatedness measures in projecting the emergence of new immigrant concentrations in the US and Australian regions. The results corroborate that the spatial relatedness measures can serve as useful instruments in the analysis of the patterns of population structure and prediction of regional population change. More generally, this paper demonstrates that information contained in spatial patterns (relatedness in space) of population composition has yet to be fully utilized in population forecasting. PMID:25966371

Salinity tolerances and use of saline environments by freshwater turtles: implications of sea level rise.

PubMed

Agha, Mickey; Ennen, Joshua R; Bower, Deborah S; Nowakowski, A Justin; Sweat, Sarah C; Todd, Brian D

2018-03-25

The projected rise in global mean sea levels places many freshwater turtle species at risk of saltwater intrusion into freshwater habitats. Freshwater turtles are disproportionately more threatened than other taxa; thus, understanding the role of salinity in determining their contemporary distribution and evolution should be a research priority. Freshwater turtles are a slowly evolving lineage; however, they can adapt physiologically or behaviourally to various levels of salinity and, therefore, temporarily occur in marine or brackish environments. Here, we provide the first comprehensive global review on freshwater turtle use and tolerance of brackish water ecosystems. We link together current knowledge of geographic occurrence, salinity tolerance, phylogenetic relationships, and physiological and behavioural mechanisms to generate a baseline understanding of the response of freshwater turtles to changing saline environments. We also review the potential origins of salinity tolerance in freshwater turtles. Finally, we integrate 2100 sea level rise (SLR) projections, species distribution maps, literature gathered on brackish water use, and a phylogeny to predict the exposure of freshwater turtles to projected SLR globally. From our synthesis of published literature and available data, we build a framework for spatial and phylogenetic conservation prioritization of coastal freshwater turtles. Based on our literature review, 70 species (∼30% of coastal freshwater turtle species) from 10 of the 11 freshwater turtle families have been reported in brackish water ecosystems. Most anecdotal records, observations, and descriptions do not imply long-term salinity tolerance among freshwater turtles. Rather, experiments show that some species exhibit potential for adaptation and plasticity in physiological, behavioural, and life-history traits that enable them to endure varying periods (e.g. days or months) and levels of saltwater exposure. Species that specialize on brackish water habitats are likely to be vulnerable to SLR because of their exclusive coastal distributions and adaptations to a narrow range of salinities. Most species, however, have not been documented in brackish water habitats but may also be highly vulnerable to projected SLR. Our analysis suggests that approximately 90% of coastal freshwater turtle species assessed in our study will be affected by a 1-m increase in global mean SLR by 2100. Most at risk are freshwater turtles found in New Guinea, Southeast Asia, Australia, and North and South America that may lose more than 10% of their present geographic range. In addition, turtle species in the families Chelidae, Emydidae, and Trionychidae may experience the greatest exposure to projected SLR in their present geographic ranges. Better understanding of survival, growth, reproductive and population-level responses to SLR will improve region-specific population viability predictions of freshwater turtles that are increasingly exposed to SLR. Integrating phylogenetic, physiological, and spatial frameworks to assess the effects of projected SLR may improve identification of vulnerable species, guilds, and geographic regions in need of conservation prioritization. We conclude that the use of brackish and marine environments by freshwater turtles provides clues about the evolutionary processes that have prolonged their existence, shaped their unique coastal distributions, and may prove useful in predicting their response to a changing world. © 2018 Cambridge Philosophical Society.

Imaging of the Li spatial distribution within V 2O 5 cathode in a coin cell by neutron computed tomography

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

Zhang, Yuxuan; Chandran, K. S. Ravi; Bilheux, Hassina Z.

An understanding of Lithium (Li) spatial distribution within the electrodes of a Li-ion cell, during charge and discharge cycles, is essential to optimize the electrode parameters for increased performance under cycling. In this work, it is demonstrated that the spatial distribution of Li within Vanadium Pentoxide (V 2O 5) electrodes of a small coin cell can be imaged by neutron computed tomography. The neutron attenuation data has been used to construct the three-dimensional Li spatial images. Specifically, it is shown that there is sufficient neutron imaging contrast between lithiated and delithiated regions of V 2O 5 electrode making it possiblemore » to map Li distributions even in small electrodes with thicknesses <1 mm. The images reveal that the Li spatial distribution is inhomogeneous and a relatively higher C-rate leads to more non-uniform Li distribution after Li insertion. The non-uniform distribution suggests the limitation of Li diffusion within the electrode during the lithiation process under the relatively high cycling rates.« less

Imaging of the Li spatial distribution within V2O5 cathode in a coin cell by neutron computed tomography

NASA Astrophysics Data System (ADS)

Zhang, Yuxuan; Chandran, K. S. Ravi; Bilheux, Hassina Z.

2018-02-01

An understanding of Lithium (Li) spatial distribution within the electrodes of a Li-ion cell, during charge and discharge cycles, is essential to optimize the electrode parameters for increased performance under cycling. In this work, it is demonstrated that the spatial distribution of Li within Vanadium Pentoxide (V2O5) electrodes of a small coin cell can be imaged by neutron computed tomography. The neutron attenuation data has been used to construct the three-dimensional Li spatial images. Specifically, it is shown that there is sufficient neutron imaging contrast between lithiated and delithiated regions of V2O5 electrode making it possible to map Li distributions even in small electrodes with thicknesses <1 mm. The images reveal that the Li spatial distribution is inhomogeneous and a relatively higher C-rate leads to more non-uniform Li distribution after Li insertion. The non-uniform distribution suggests the limitation of Li diffusion within the electrode during the lithiation process under the relatively high cycling rates.

Imaging of the Li spatial distribution within V 2O 5 cathode in a coin cell by neutron computed tomography

DOE PAGES

Zhang, Yuxuan; Chandran, K. S. Ravi; Bilheux, Hassina Z.

2017-11-30

An understanding of Lithium (Li) spatial distribution within the electrodes of a Li-ion cell, during charge and discharge cycles, is essential to optimize the electrode parameters for increased performance under cycling. In this work, it is demonstrated that the spatial distribution of Li within Vanadium Pentoxide (V 2O 5) electrodes of a small coin cell can be imaged by neutron computed tomography. The neutron attenuation data has been used to construct the three-dimensional Li spatial images. Specifically, it is shown that there is sufficient neutron imaging contrast between lithiated and delithiated regions of V 2O 5 electrode making it possiblemore » to map Li distributions even in small electrodes with thicknesses <1 mm. The images reveal that the Li spatial distribution is inhomogeneous and a relatively higher C-rate leads to more non-uniform Li distribution after Li insertion. The non-uniform distribution suggests the limitation of Li diffusion within the electrode during the lithiation process under the relatively high cycling rates.« less

Spatial ecological processes and local factors predict the distribution and abundance of spawning by steelhead (Oncorhynchus mykiss) across a complex riverscape

USGS Publications Warehouse

Falke, Jeffrey A.; Dunham, Jason B.; Jordan, Christopher E.; McNyset, Kris M.; Reeves, Gordon H.

2013-01-01

Processes that influence habitat selection in landscapes involve the interaction of habitat composition and configuration and are particularly important for species with complex life cycles. We assessed the relative influence of landscape spatial processes and local habitat characteristics on patterns in the distribution and abundance of spawning steelhead (Oncorhynchus mykiss), a threatened salmonid fish, across ~15,000 stream km in the John Day River basin, Oregon, USA. We used hurdle regression and a multi-model information theoretic approach to identify the relative importance of covariates representing key aspects of the steelhead life cycle (e.g., site access, spawning habitat quality, juvenile survival) at two spatial scales: within 2-km long survey reaches (local sites) and ecological neighborhoods (5 km) surrounding the local sites. Based on Akaike’s Information Criterion, models that included covariates describing ecological neighborhoods provided the best description of the distribution and abundance of steelhead spawning given the data. Among these covariates, our representation of offspring survival (growing-season-degree-days, °C) had the strongest effect size (7x) relative to other predictors. Predictive performances of model-averaged composite and neighborhood-only models were better than a site-only model based on both occurrence (percentage of sites correctly classified = 0.80±0.03 SD, 0.78±0.02 vs. 0.62±0.05, respectively) and counts (root mean square error = 3.37, 3.93 vs. 5.57, respectively). The importance of both temperature and stream flow for steelhead spawning suggest this species may be highly sensitive to impacts of land and water uses, and to projected climate impacts in the region and that landscape context, complementation, and connectivity will drive how this species responds to future environments.

Spatial Distribution of Seismic Anisotropy in the Crust in the Northeast Front Zone of Tibetan Plateau

NASA Astrophysics Data System (ADS)

Gao, Y.; Wang, Q.; SHI, Y.

2017-12-01

There are orogenic belts and strong deformation in northeastern zone of Tibetan Plateau. The media in crust and in the upper mantle are seismic anisotropic there. This study uses seismic records by permanent seismic stations and portable seismic arrays, and adopts analysis techniques on body waves to obtain spatial anisotropic distribution in northeastern front zone of Tibetan Plateau. With seismic records of small local earthquakes, we study shear-wave splitting in the upper crust. The polarization of fast shear wave (PFS) can be obtained, and PFS is considered parallel to the strike of the cracks, as well as the direction of maximum horizontal compressive stress. However, the result shows the strong influence from tectonics, such as faults. It suggests multiple-influence including stress and fault. Spatial distribution of seismic anisotropy in study zone presents the effect in short range. PFS at the station on the strike-slip fault is quite different to PFS at station just hundreds of meters away from the fault. With seismic records of teleseismic waveforms, we obtained seismic anisotropy in the whole crust by receiver functions. The PFS directions from Pms receiver functions show consistency, generally in WNW. The time-delay of slow S phases is significant. With seismic records of SKS, PKS and SKKS phases, we can detect seismic anisotropy in the upper mantle by splitting analysis. The fast directions of these phases also show consistency, generally in WNW, similar to those of receiver functions, but larger time-delays. It suggests significant seismic anisotropy in the crust and crustal deformation is coherent to that in the upper mantle.Seismic anisotropy in the upper crust, in the whole crust and in the upper mantle are discussed both in difference and tectonic implications [Grateful to the support by NSFC Project 41474032].

Indicators for Assessing Climate Change Resilience Resulting from Emplacement of Green Infrastructure Projects Across an Urban Landscape

NASA Astrophysics Data System (ADS)

Parish, E. S.; Omitaomu, O.; Sylvester, L.; Nugent, P.

2015-12-01

Many U.S. cities are exploring the potential of using green infrastructure (e.g., porous pavements, green roofs, street planters) to reduce urban storm water runoff, which can be both be a nuisance and costly to treat. While tools exist to measure local runoff changes resulting from individual green infrastructure (GI) projects, most municipalities currently have no method of analyzing the collective impact of GI projects on urban stormwater systems under future rainfall scenarios and impervious surface distribution patterns. Using the mid-sized city of Knoxville, Tennessee as a case study, we propose a set of indicators that can be used to monitor and analyze the collective effects of GI emplacement on urban storm water runoff volumes as well as to quantify potential co-benefits of GI projects (e.g., urban heat island reduction, reduced stream scouring) under different climate projection ensembles and population growth scenarios. These indicators are intended to help the city prioritize GI projects as opportunities arise, as well as to track the effectiveness of GI implementation over time. We explore the aggregation of these indicators across different spatial scales (e.g., plot, neighborhood, watershed, city) in order to assess potential changes in climate change resilience resulting from the collective implementation of GI projects across an urban landscape.

Tactical Approaches for Making a Successful Satellite Passive Microwave ESDR

NASA Astrophysics Data System (ADS)

Hardman, M.; Brodzik, M. J.; Gotberg, J.; Long, D. G.; Paget, A. C.

2014-12-01

Our NASA MEaSUREs project is producing a new, enhanced resolution gridded Earth System Data Record for the entire satellite passive microwave (SMMR, SSM/I-SSMIS and AMSR-E) time series. Our project goals are twofold: to produce a well-documented, consistently processed, high-quality historical record at higher spatial resolutions than have previously been available, and to transition the production software to the NSIDC DAAC for ongoing processing after our project completion. In support of these goals, our distributed team at BYU and NSIDC faces project coordination challenges to produce a high-quality data set that our user community will accept as a replacement for the currently available historical versions of these data. We work closely with our DAAC liaison on format specifications, data and metadata plans, and project progress. In order for the user community to understand and support our project, we have solicited a team of Early Adopters who are reviewing and evaluating a prototype version of the data. Early Adopter feedback will be critical input to our final data content and format decisions. For algorithm transparency and accountability, we have released an Algorithm Theoretical Basis Document (ATBD) and detailed supporting technical documentation, with rationale for all algorithm implementation decisions. For distributed team management, we are using collaborative tools for software revision control and issue tracking. For reliably transitioning a research-quality image reconstruction software system to production-quality software suitable for use at the DAAC, we have adopted continuous integration methods for running automated regression testing. Our presentation will summarize bothadvantages and challenges of each of these tactics in ensuring production of a successful ESDR and an enduring production software system.

A Permutation-Randomization Approach to Test the Spatial Distribution of Plant Diseases.

PubMed

Lione, G; Gonthier, P

2016-01-01

The analysis of the spatial distribution of plant diseases requires the availability of trustworthy geostatistical methods. The mean distance tests (MDT) are here proposed as a series of permutation and randomization tests to assess the spatial distribution of plant diseases when the variable of phytopathological interest is categorical. A user-friendly software to perform the tests is provided. Estimates of power and type I error, obtained with Monte Carlo simulations, showed the reliability of the MDT (power > 0.80; type I error < 0.05). A biological validation on the spatial distribution of spores of two fungal pathogens causing root rot on conifers was successfully performed by verifying the consistency between the MDT responses and previously published data. An application of the MDT was carried out to analyze the relation between the plantation density and the distribution of the infection of Gnomoniopsis castanea, an emerging fungal pathogen causing nut rot on sweet chestnut. Trees carrying nuts infected by the pathogen were randomly distributed in areas with different plantation densities, suggesting that the distribution of G. castanea was not related to the plantation density. The MDT could be used to analyze the spatial distribution of plant diseases both in agricultural and natural ecosystems.

Snow water equivalent mapping in Norway

NASA Astrophysics Data System (ADS)

Tveito, O. E.; Udnæs, H.-C.; Engeset, R.; Førland, E. J.; Isaksen, K.; Mengistu, Z.

2003-04-01

In high latitude area snow covers the ground large parts of the year. Information about the water volume as snow is of major importance in many respects. Flood forecasters at NVE need it in order to assess possible flood risks. Hydropower producers need it to plan the most efficient production of the water in their reservoirs, traders to estimate the potential energy available for the market. Meteorologists on their side use the information as boundary conditions in weather forecasting models. The Norwegian meteorological institute has provided snow accumulation maps for Norway for more than 50 years. These maps are now produced twice a month in the winter season. They show the accumulated precipitation in the winter season from the day the permanent snow cover is established. They do however not take melting into account, and do therefore not give a good description of the actual snow amounts during and after periods with snowmelt. Due to an increased need for a direct measure of water volumes as snow cover, met.no and NVE initialized a joint project in order to establish maps of the actual snow cover expressed in water equivalents. The project utilizes recent developments in the use of GIS in spatial modeling. Daily precipitation and temperature are distributed in space by using objective spatial interpolation methods. The interpolation considers topographical and other geographical parameters as well as weather type information. A degree-day model is used at each modeling point to calculate snow-accumulation and snowmelt. The maps represent a spatial scale of 1x1 km2. The modeled snow reservoir is validated by snow pillow values as well traditional snow depth observations. Preliminary results show that the new snow modeling approach reproduces the snow water equivalent well. The spatial approach also opens for a wide use in the terms of areal analysis.