R. Bruce Anderson; R. Bruce Anderson
1991-01-01
To assess the impact of grocery pallet production on future hardwood resources, better information is needed on the current use of reusable pallets by the grocery and related products industry. A spatial model of pallet use in the grocery distribution system that identifies the locational aspects of grocery pallet production and distribution, determines how these...
Spatial analysis and characteristics of pig farming in Thailand.
Thanapongtharm, Weerapong; Linard, Catherine; Chinson, Pornpiroon; Kasemsuwan, Suwicha; Visser, Marjolein; Gaughan, Andrea E; Epprech, Michael; Robinson, Timothy P; Gilbert, Marius
2016-10-06
In Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Strategies toward more sustainable future developments are currently investigated, and these could be informed by a detailed assessment of the main trends in the pig sector, and on how different production systems are geographically distributed. This study had two main objectives. First, we aimed to describe the main trends and geographic patterns of pig production systems in Thailand in terms of pig type (native, breeding, and fattening pigs), farm scales (smallholder and large-scale farming systems) and type of farming systems (farrow-to-finish, nursery, and finishing systems) based on a very detailed 2010 census. Second, we aimed to study the statistical spatial association between these different types of pig farming distribution and a set of spatial variables describing access to feed and markets. Over the last decades, pig population gradually increased, with a continuously increasing number of pigs per holder, suggesting a continuing intensification of the sector. The different pig-production systems showed very contrasted geographical distributions. The spatial distribution of large-scale pig farms corresponds with that of commercial pig breeds, and spatial analysis conducted using Random Forest distribution models indicated that these were concentrated in lowland urban or peri-urban areas, close to means of transportation, facilitating supply to major markets such as provincial capitals and the Bangkok Metropolitan region. Conversely the smallholders were distributed throughout the country, with higher densities located in highland, remote, and rural areas, where they supply local rural markets. A limitation of the study was that pig farming systems were defined from the number of animals per farm, resulting in their possible misclassification, but this should have a limited impact on the main patterns revealed by the analysis. The very contrasted distribution of different pig production systems present opportunities for future regionalization of pig production. More specifically, the detailed geographical analysis of the different production systems will be used to spatially-inform planning decisions for pig farming accounting for the specific health, environment and economical implications of the different pig production systems.
Spatial pattern characteristics of water footprint for maize production in Northeast China.
Duan, Peili; Qin, Lijie; Wang, Yeqiao; He, Hongshi
2016-01-30
Water footprint (WF) methodology is essential for quantifying total water consumption of crop production and making efficient water management policies. This study calculated the green, blue, grey and total WFs of maize production in Northeast China from 1998 to 2012 and compared the values of the provinces. This study also analyzed the spatial variation and structure characteristics of the WFs at the prefecture level. The annual average WF of maize production was 1029 m(3) per ton, which was 51% green, 21% blue and 28% grey. The WF of maize production was highest in Liaoning Province, moderate in Heilongjiang Province and lowest in Jilin Province. The spatial differences of the WFs calculated for the 36 major maize production prefectures were significant in Northeast China. There was a moderate positive spatial autocorrelation among prefectures that had similar WFs. Local indicator of spatial autocorrelation index (LISA) analysis identified prefectures with higher WFs in the southeast region of Liaoning Province and the southwest region of Heilongjiang Province and prefectures with lower WFs in the middle of Jilin Province. Spatial differences in the WF of maize production were caused mainly by variations in climate conditions, soil quality, irrigation facilities and maize yield. The spatial distribution of WFs can help provide a scientific basis for optimizing maize production distribution and then formulate strategies to reduce the WF of maize production. © 2015 Society of Chemical Industry.
Spatial characteristics of net methylmercury production hot spots in peatlands
Carl P.J. Mitchell; Brian A. Branfireun; Randall K. Kolka
2008-01-01
Many wetlands are sources of methylmercury (MeHg) to surface waters, yet little information exists about the distribution of MeHg within wetlands. Total mercury (THg) and MeHg in peat pore waters were studied in four peatlands in spring, summer, and fall 2005. Marked spatial variability in the distribution of MeHg, and %MeHg as a proxy for net MeHg production, was...
2012-06-01
the diffusion length L and the mobility-lifetime product from the luminescence distribution using the 2D model for transport imaging in bulk...C. Scandrett, and N. M. Haegel, “Three-dimensional transport imaging for the spatially resolved determination of carrier diffusion length in bulk...that allows measurements of the diffusion length and extraction of the product in luminescent materials without the need for device processing
Le Boucher, Clémentine; Gagnaire, Valérie; Briard-Bion, Valérie; Jardin, Julien; Maillard, Marie-Bernadette; Dervilly-Pinel, Gaud; Le Bizec, Bruno; Lortal, Sylvie; Jeanson, Sophie; Thierry, Anne
2016-01-01
In cheese, lactic acid bacteria are immobilized at the coagulation step and grow as colonies. The spatial distribution of bacterial colonies is characterized by the size and number of colonies for a given bacterial population within cheese. Our objective was to demonstrate that different spatial distributions, which lead to differences in the exchange surface between the colonies and the cheese matrix, can influence the ripening process. The strategy was to generate cheeses with the same growth and acidification of a Lactococcus lactis strain with two different spatial distributions, big and small colonies, to monitor the production of the major ripening metabolites, including sugars, organic acids, peptides, free amino acids, and volatile metabolites, over 1 month of ripening. The monitored metabolites were qualitatively the same for both cheeses, but many of them were more abundant in the small-colony cheeses than in the big-colony cheeses over 1 month of ripening. Therefore, the results obtained showed that two different spatial distributions of L. lactis modulated the ripening time course by generating moderate but significant differences in the rates of production or consumption for many of the metabolites commonly monitored throughout ripening. The present work further explores the immobilization of bacteria as colonies within cheese and highlights the consequences of this immobilization on cheese ripening. Copyright © 2015, American Society for Microbiology. All Rights Reserved.
An Innovative Metric to Evaluate Satellite Precipitation's Spatial Distribution
NASA Astrophysics Data System (ADS)
Liu, H.; Chu, W.; Gao, X.; Sorooshian, S.
2011-12-01
Thanks to its capability to cover the mountains, where ground measurement instruments cannot reach, satellites provide a good means of estimating precipitation over mountainous regions. In regions with complex terrains, accurate information on high-resolution spatial distribution of precipitation is critical for many important issues, such as flood/landslide warning, reservoir operation, water system planning, etc. Therefore, in order to be useful in many practical applications, satellite precipitation products should possess high quality in characterizing spatial distribution. However, most existing validation metrics, which are based on point/grid comparison using simple statistics, cannot effectively measure satellite's skill of capturing the spatial patterns of precipitation fields. This deficiency results from the fact that point/grid-wised comparison does not take into account of the spatial coherence of precipitation fields. Furth more, another weakness of many metrics is that they can barely provide information on why satellite products perform well or poor. Motivated by our recent findings of the consistent spatial patterns of the precipitation field over the western U.S., we developed a new metric utilizing EOF analysis and Shannon entropy. The metric can be derived through two steps: 1) capture the dominant spatial patterns of precipitation fields from both satellite products and reference data through EOF analysis, and 2) compute the similarities between the corresponding dominant patterns using mutual information measurement defined with Shannon entropy. Instead of individual point/grid, the new metric treat the entire precipitation field simultaneously, naturally taking advantage of spatial dependence. Since the dominant spatial patterns are shaped by physical processes, the new metric can shed light on why satellite product can or cannot capture the spatial patterns. For demonstration, a experiment was carried out to evaluate a satellite precipitation product, CMORPH, against the U.S. daily precipitation analysis of Climate Prediction Center (CPC) at a daily and .25o scale over the Western U.S.
SPATIAL DISTRIBUTION OF PAIR PRODUCTION OVER THE PULSAR POLAR CAP
DOE Office of Scientific and Technical Information (OSTI.GOV)
Belyaev, Mikhail A.; Parfrey, Kyle, E-mail: mbelyaev@berkeley.edu
2016-10-20
Using an analytic, axisymmetric approach that includes general relativity, coupled to a condition for pair production deduced from simulations, we derive general results about the spatial distribution of pair-producing field lines over the pulsar polar cap. In particular, we show that pair production on magnetic field lines operates over only a fraction of the polar cap for an aligned rotator for general magnetic field configurations, assuming the magnetic field varies spatially on a scale that is larger than the size of the polar cap. We compare our result to force-free simulations of a pulsar with a dipole surface field andmore » find excellent agreement. Our work has implications for first-principles simulations of pulsar magnetospheres and for explaining observations of pulsed radio and high-energy emission.« less
David K. Weaver; Christian Nansen; Justin B. Runyon; Sharlene E. Sing; Wendell L. Morrill
2005-01-01
Bracon cephi and Bracon lissogaster are native parasitoids of the wheat stem sawfly, Cephus cinctus, an important pest of dryland wheat production. This spatial distribution study, using survey data from seven dryland wheat fields at four locations in north-central Montana over two years, examined: (1) the...
Modeling and Spatially Distributing Forest Net Primary Production at the Regional Scale
R.A. Mickler; T.S. Earnhardt; J.A. Moore
2002-01-01
Abstract - Forest, agricultural, rangeland, wetland, and urban landscapes have different rates of carbon sequestration and total carbon sequestration potential under alternative management options. Changes in the proportion and spatial distribution of land use could enhance or degrade that areaâs ability to sequester carbon in terrestrial ecosystems...
Farias, Paulo R S; Barbosa, José C; Busoli, Antonio C; Overal, William L; Miranda, Vicente S; Ribeiro, Susane M
2008-01-01
The fall armyworm, Spodoptera frugiperda (J.E. Smith), is one of the chief pests of maize in the Americas. The study of its spatial distribution is fundamental for designing correct control strategies, improving sampling methods, determining actual and potential crop losses, and adopting precise agricultural techniques. In São Paulo state, Brazil, a maize field was sampled at weekly intervals, from germination through harvest, for caterpillar densities, using quadrates. In each of 200 quadrates, 10 plants were sampled per week. Harvest weights were obtained in the field for each quadrate, and ear diameters and lengths were also sampled (15 ears per quadrate) and used to estimate potential productivity of the quadrate. Geostatistical analyses of caterpillar densities showed greatest ranges for small caterpillars when semivariograms were adjusted for a spherical model that showed greatest fit. As the caterpillars developed in the field, their spatial distribution became increasingly random, as shown by a model adjusted to a straight line, indicating a lack of spatial dependence among samples. Harvest weight and ear length followed the spherical model, indicating the existence of spatial variability of the production parameters in the maize field. Geostatistics shows promise for the application of precise methods in the integrated control of pests.
High resolution population distribution maps for Southeast Asia in 2010 and 2015.
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
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
Wilson, Jono R; Kay, Matthew C; Colgate, John; Qi, Roy; Lenihan, Hunter S
2012-01-01
A major challenge for small-scale fisheries management is high spatial variability in the demography and life history characteristics of target species. Implementation of local management actions that can reduce overfishing and maximize yields requires quantifying ecological heterogeneity at small spatial scales and is therefore limited by available resources and data. Collaborative fisheries research (CFR) is an effective means to collect essential fishery information at local scales, and to develop the social, technical, and logistical framework for fisheries management innovation. We used a CFR approach with fishing partners to collect and analyze geographically precise demographic information for grass rockfish (Sebastes rastrelliger), a sedentary, nearshore species harvested in the live fish fishery on the West Coast of the USA. Data were used to estimate geographically distinct growth rates, ages, mortality, and length frequency distributions in two environmental subregions of the Santa Barbara Channel, CA, USA. Results indicated the existence of two subpopulations; one located in the relatively cold, high productivity western Channel, and another in the relatively warm, low productivity eastern Channel. We parameterized yield per recruit models, the results of which suggested nearly twice as much yield per recruit in the high productivity subregion relative to the low productivity subregion. The spatial distribution of fishing in the two environmental subregions demonstrated a similar pattern to the yield per recruit outputs with greater landings, effort, and catch per unit effort in the high productivity subregion relative to the low productivity subregion. Understanding how spatial variability in stock dynamics translates to variability in fishery yield and distribution of effort is important to developing management plans that maximize fishing opportunities and conservation benefits at local scales.
Spatial surplus production modeling of Atlantic tunas and billfish.
Carruthers, Thomas R; McAllister, Murdoch K; Taylor, Nathan G
2011-10-01
We formulate and simulation-test a spatial surplus production model that provides a basis with which to undertake multispecies, multi-area, stock assessment. Movement between areas is parameterized using a simple gravity model that includes a "residency" parameter that determines the degree of stock mixing among areas. The model is deliberately simple in order to (1) accommodate nontarget species that typically have fewer available data and (2) minimize computational demand to enable simulation evaluation of spatial management strategies. Using this model, we demonstrate that careful consideration of spatial catch and effort data can provide the basis for simple yet reliable spatial stock assessments. If simple spatial dynamics can be assumed, tagging data are not required to reliably estimate spatial distribution and movement. When applied to eight stocks of Atlantic tuna and billfish, the model tracks regional catch data relatively well by approximating local depletions and exchange among high-abundance areas. We use these results to investigate and discuss the implications of using spatially aggregated stock assessment for fisheries in which the distribution of both the population and fishing vary over time.
The Biogeography of Putative Microbial Antibiotic Production
Bryant, Jessica A.; Charkoudian, Louise K.; Docherty, Kathryn M.; Jones, Evan; Kembel, Steven W.; Green, Jessica L.; Bohannan, Brendan J. M.
2015-01-01
Understanding patterns in the distribution and abundance of functional traits across a landscape is of fundamental importance to ecology. Mapping these distributions is particularly challenging for species-rich groups with sparse trait measurement coverage, such as flowering plants, insects, and microorganisms. Here, we use likelihood-based character reconstruction to infer and analyze the spatial distribution of unmeasured traits. We apply this framework to a microbial dataset comprised of 11,732 ketosynthase alpha gene sequences extracted from 144 soil samples from three continents to document the spatial distribution of putative microbial polyketide antibiotic production. Antibiotic production is a key competitive strategy for soil microbial survival and performance. Additionally, novel antibiotic discovery is highly relevant to human health, making natural antibiotic production by soil microorganisms a major target for bioprospecting. Our comparison of trait-based biogeographical patterns to patterns based on taxonomy and phylogeny is relevant to our basic understanding of microbial biogeography as well as the pressing need for new antibiotics. PMID:26102275
RiceAtlas, a spatial database of global rice calendars and production.
Laborte, Alice G; Gutierrez, Mary Anne; Balanza, Jane Girly; Saito, Kazuki; Zwart, Sander J; Boschetti, Mirco; Murty, M V R; Villano, Lorena; Aunario, Jorrel Khalil; Reinke, Russell; Koo, Jawoo; Hijmans, Robert J; Nelson, Andrew
2017-05-30
Knowing where, when, and how much rice is planted and harvested is crucial information for understanding the effects of policy, trade, and global and technological change on food security. We developed RiceAtlas, a spatial database on the seasonal distribution of the world's rice production. It consists of data on rice planting and harvesting dates by growing season and estimates of monthly production for all rice-producing countries. Sources used for planting and harvesting dates include global and regional databases, national publications, online reports, and expert knowledge. Monthly production data were estimated based on annual or seasonal production statistics, and planting and harvesting dates. RiceAtlas has 2,725 spatial units. Compared with available global crop calendars, RiceAtlas is nearly ten times more spatially detailed and has nearly seven times more spatial units, with at least two seasons of calendar data, making RiceAtlas the most comprehensive and detailed spatial database on rice calendar and production.
The accuracy of thematic map products is not spatially homogenous, but instead variable across most landscapes. Properly analyzing and representing the spatial distribution (pattern) of thematic map accuracy would provide valuable user information for assessing appropriate applic...
[Evaluation of ecosystem provisioning service and its economic value].
Wu, Nan; Gao, Ji-Xi; Sudebilige; Ricketts, Taylor H; Olwero, Nasser; Luo, Zun-Lan
2010-02-01
Aiming at the fact that the current approaches of evaluating the efficacy of ecosystem provisioning service were lack of spatial information and did not take the accessibility of products into account, this paper established an evaluation model to simulate the spatial distribution of ecosystem provisioning service and its economic value, based on ArcGIS 9. 2 and taking the supply and demand factors of ecosystem products into account. The provision of timber product in Laojunshan in 2000 was analyzed with the model. In 2000, the total physical quantity of the timber' s provisioning service in Laojunshan was 11.12 x 10(4) m3 x a(-1), occupying 3.2% of the total increment of timber stock volume. The total provisioning service value of timber was 6669.27 x 10(4) yuan, among which, coniferous forest contributed most (90.41%). Due to the denser distribution of populations and roads in the eastern area of Laojunshan, some parts of the area being located outside of conservancy district, and forests being in scattered distribution, the spatial distribution pattern of the physical quantity of timber's provisioning service was higher in the eastern than in the western area.
Artacho, Pamela; Bonomelli, Claudia
2016-05-01
Factors regulating fine-root growth are poorly understood, particularly in fruit tree species. In this context, the effects of N addition on the temporal and spatial distribution of fine-root growth and on the fine-root turnover were assessed in irrigated sweet cherry trees. The influence of other exogenous and endogenous factors was also examined. The rhizotron technique was used to measure the length-based fine-root growth in trees fertilized at two N rates (0 and 60 kg ha(-1)), and the above-ground growth, leaf net assimilation, and air and soil variables were simultaneously monitored. N fertilization exerted a basal effect throughout the season, changing the magnitude, temporal patterns and spatial distribution of fine-root production and mortality. Specifically, N addition enhanced the total fine-root production by increasing rates and extending the production period. On average, N-fertilized trees had a length-based production that was 110-180% higher than in control trees, depending on growing season. Mortality was proportional to production, but turnover rates were inconsistently affected. Root production and mortality was homogeneously distributed in the soil profile of N-fertilized trees while control trees had 70-80% of the total fine-root production and mortality concentrated below 50 cm depth. Root mortality rates were associated with soil temperature and water content. In contrast, root production rates were primarily under endogenous control, specifically through source-sink relationships, which in turn were affected by N supply through changes in leaf photosynthetic level. Therefore, exogenous and endogenous factors interacted to control the fine-root dynamics of irrigated sweet cherry trees. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Artacho, Pamela; Bonomelli, Claudia
2016-01-01
Factors regulating fine-root growth are poorly understood, particularly in fruit tree species. In this context, the effects of N addition on the temporal and spatial distribution of fine-root growth and on the fine-root turnover were assessed in irrigated sweet cherry trees. The influence of other exogenous and endogenous factors was also examined. The rhizotron technique was used to measure the length-based fine-root growth in trees fertilized at two N rates (0 and 60 kg ha−1), and the above-ground growth, leaf net assimilation, and air and soil variables were simultaneously monitored. N fertilization exerted a basal effect throughout the season, changing the magnitude, temporal patterns and spatial distribution of fine-root production and mortality. Specifically, N addition enhanced the total fine-root production by increasing rates and extending the production period. On average, N-fertilized trees had a length-based production that was 110–180% higher than in control trees, depending on growing season. Mortality was proportional to production, but turnover rates were inconsistently affected. Root production and mortality was homogeneously distributed in the soil profile of N-fertilized trees while control trees had 70–80% of the total fine-root production and mortality concentrated below 50 cm depth. Root mortality rates were associated with soil temperature and water content. In contrast, root production rates were primarily under endogenous control, specifically through source–sink relationships, which in turn were affected by N supply through changes in leaf photosynthetic level. Therefore, exogenous and endogenous factors interacted to control the fine-root dynamics of irrigated sweet cherry trees. PMID:26888890
NASA Technical Reports Server (NTRS)
Parse, Joseph B.; Wert, J. A.
1991-01-01
Inhomogeneities in the spatial distribution of second phase particles in engineering materials are known to affect certain mechanical properties. Progress in this area has been hampered by the lack of a convenient method for quantitative description of the spatial distribution of the second phase. This study intends to develop a broadly applicable method for the quantitative analysis and description of the spatial distribution of second phase particles. The method was designed to operate on a desktop computer. The Dirichlet tessellation technique (geometrical method for dividing an area containing an array of points into a set of polygons uniquely associated with the individual particles) was selected as the basis of an analysis technique implemented on a PC. This technique is being applied to the production of Al sheet by PM processing methods; vacuum hot pressing, forging, and rolling. The effect of varying hot working parameters on the spatial distribution of aluminum oxide particles in consolidated sheet is being studied. Changes in distributions of properties such as through-thickness near-neighbor distance correlate with hot-working reduction.
Spatio-temporal distribution of stored-product inects around food processing and storage facilities
USDA-ARS?s Scientific Manuscript database
Grain storage and processing facilities consist of a landscape of indoor and outdoor habitats that can potentially support stored-product insect pests, and understanding patterns of species diversity and spatial distribution in the landscape surrounding structures can provide insight into how the ou...
Spatial distribution of soil organic carbon stock in Moso bamboo forests in subtropical China.
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
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
Derivation of spatial patterns of soil hydraulic properties based on pedotransfer functions
USDA-ARS?s Scientific Manuscript database
Spatial patterns in soil hydrology are the product of the spatial distribution of soil hydraulic properties. These properties are notorious for the difficulties and high labor costs involved in measuring them. Often, there is a need to resort to estimating these parameters from other, more readily a...
Rigamonti, Ivo E; Brambilla, Carla; Colleoni, Emanuele; Jermini, Mauro; Trivellone, Valeria; Baumgärtner, Johann
2016-04-01
The paper deals with the study of the spatial distribution and the design of sampling plans for estimating nymph densities of the grape leafhopper Scaphoideus titanus Ball in vine plant canopies. In a reference vineyard sampled for model parameterization, leaf samples were repeatedly taken according to a multistage, stratified, random sampling procedure, and data were subjected to an ANOVA. There were no significant differences in density neither among the strata within the vineyard nor between the two strata with basal and apical leaves. The significant differences between densities on trunk and productive shoots led to the adoption of two-stage (leaves and plants) and three-stage (leaves, shoots, and plants) sampling plans for trunk shoots- and productive shoots-inhabiting individuals, respectively. The mean crowding to mean relationship used to analyze the nymphs spatial distribution revealed aggregated distributions. In both the enumerative and the sequential enumerative sampling plans, the number of leaves of trunk shoots, and of leaves and shoots of productive shoots, was kept constant while the number of plants varied. In additional vineyards data were collected and used to test the applicability of the distribution model and the sampling plans. The tests confirmed the applicability 1) of the mean crowding to mean regression model on the plant and leaf stages for representing trunk shoot-inhabiting distributions, and on the plant, shoot, and leaf stages for productive shoot-inhabiting nymphs, 2) of the enumerative sampling plan, and 3) of the sequential enumerative sampling plan. In general, sequential enumerative sampling was more cost efficient than enumerative sampling.
Spatial decision support system for tobacco enterprise based on spatial data mining
NASA Astrophysics Data System (ADS)
Mei, Xin; Liu, Junyi; Zhang, Xuexia; Cui, Weihong
2007-11-01
Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique and spatial data mining (SDM) to construct spatial decision support system (SDSS) of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision based on SDM is given. This paper describes how to use spatial analysis and data mining to realize the spatial decision processing such as monitoring tobacco planted acreage, analyzing and planning the cigarette sale network and so on.
Lumped versus distributed thermoregulatory control: results from a three-dimensional dynamic model.
Werner, J; Buse, M; Foegen, A
1989-01-01
In this study we use a three-dimensional model of the human thermal system, the spatial grid of which is 0.5 ... 1.0 cm. The model is based on well-known physical heat-transfer equations, and all parameters of the passive system have definite physical values. According to the number of substantially different areas and organs, 54 spatially different values are attributed to each physical parameter. Compatibility of simulation and experiment was achieved solely on the basis of physical considerations and physiological basic data. The equations were solved using a modification of the alternating direction implicit method. On the basis of this complex description of the passive system close to reality, various lumped and distributed parameter control equations were tested for control of metabolic heat production, blood flow and sweat production. The simplest control equations delivering results on closed-loop control compatible with experimental evidence were determined. It was concluded that it is essential to take into account the spatial distribution of heat production, blood flow and sweat production, and that at least for control of shivering, distributed controller gains different from the pattern of distribution of muscle tissue are required. For sweat production this is not so obvious, so that for simulation of sweating control after homogeneous heat load a lumped parameter control may be justified. Based on these conclusions three-dimensional temperature profiles for cold and heat load and the dynamics for changes of the environmental conditions were computed. In view of the exact simulation of the passive system and the compatibility with experimentally attainable variables there is good evidence that those values extrapolated by the simulation are adequately determined. The model may be used both for further analysis of the real thermoregulatory mechanisms and for special applications in environmental and clinical health care.
A New Global LAI Product and Its Use for Terrestrial Carbon Cycle Estimation
NASA Astrophysics Data System (ADS)
Chen, J. M.; Liu, R.; Ju, W.; Liu, Y.
2014-12-01
For improving the estimation of the spatio-temporal dynamics of the terrestrial carbon cycle, a new time series of the leaf area index (LAI) is generated for the global land surface at 8 km resolution from 1981 to 2012 by combining AVHRR and MODIS satellite data. This product differs from existing LAI products in the following two aspects: (1) the non-random spatial distribution of leaves with the canopy is considered, and (2) the seasonal variation of the vegetation background is included. The non-randomness of the leaf spatial distribution in the canopy is considered using the second vegetation structural parameter named clumping index (CI), which quantifies the deviation of the leaf spatial distribution from the random case. Using the MODIS Bidirectional Reflectance Distribution Function product, a global map of CI is produced at 500 m resolution. In our LAI algorithm, CI is used to convert the effective LAI obtained from mono-angle remote sensing into the true LAI, otherwise LAI would be considerably underestimated. The vegetation background is soil in crop, grass and shrub but includes soil, grass, moss, and litter in forests. Through processing a large volume of MISR data from 2000 to 2010, monthly red and near-infrared reflectances of the vegetation background is mapped globally at 1 km resolution. This new LAI product has been validated extensively using ground-based LAI measurements distributed globally. In carbon cycle modeling, the use of CI in addition to LAI allows for accurate separation of sunlit and shaded leaves as an important step in terrestrial photosynthesis and respiration modeling. Carbon flux measurements over 100 sites over the globe are used to validate an ecosystem model named Boreal Ecosystem Productivity Simulator (BEPS). The validated model is run globally at 8 km resolution for the period from 1981 to 2012 using the LAI product and other spatial datasets. The modeled results suggest that changes in vegetation structure as quantified by LAI do not contribute significantly to the increasing trend in carbon sink over the last 32 years. The increases in atmospheric CO2 concentration and nitrogen deposition are found to be the major causes for the increases in plant productivity and carbon sink over the last 32 years.
Research on tobacco enterprise spatial decision support system based on GIS
NASA Astrophysics Data System (ADS)
Mei, Xin; Cui, Weihong
2006-10-01
Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique taking GIS as representation to construct spatial decision support system of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision is given. At last the example of tobacco enterprise spatial CRM (client relation management) system is set up.
Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37831-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37831-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy, and Economics Appalachian State University Boone, NC 28608-2131 USA
2010-01-01
The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2013.html), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signature (del 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996) for years prior to 1990 and a variable population distribution for later years (Andres et al. 2016). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production). The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pankov, A. A., E-mail: pankov@ictp.it; Serenkova, I. A., E-mail: inna.serenkova@cern.ch; Tsytrinov, A. V., E-mail: tsytrin@gstu.by
2015-06-15
Prospects of discovering and identifying effects of extra spatial dimensions in dilepton and diphoton production at the Large Hadron Collider (LHC) are studied. Such effects may be revealed by the characteristic behavior of the invariant-mass distributions of dileptons and diphotons, and their identification can be performed on the basis of an analysis of their angular distributions. The discovery and identification reaches are estimated for the scale parameter M{sub S} of the Kaluza-Klein gravitational towers, which can be determined in experiments devoted to measuring the dilepton and diphoton channels at the LHC.
Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands
Baldwin, Robert F.; Leonard, Paul B.
2015-01-01
Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection. PMID:26465155
Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands.
Baldwin, Robert F; Leonard, Paul B
2015-01-01
Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection.
Production and Distribution of Global Products From MODIS
NASA Technical Reports Server (NTRS)
Masuoka, Edward; Smith, David E. (Technical Monitor)
2000-01-01
The Moderate Resolution Imaging Spectroradiometer was launched on the EOS Terra spacecraft in December 1999 and will also fly on EOS Aqua in December 2000. With 36 spectral bands from the visible through thermal infrared and spatial resolution of 250m to 1 kilometer, each MODIS instrument will image the entire Earth surface in 2 days. This paper traces the flow of MODIS data products from the receipt of Level 0 data at the EDOS facility, through the production and quality assurance process to the Distributed Active Archive Centers (DAACs), which ship products to the user community. It describes where to obtain products and plans for reprocessing MODIS products. As most components of the ground system are severely limited in their capacity to distribute MODIS products, it also describes the key characteristics of MODIS products and their metadata that allow a user to optimize their selection of products given anticipate bottlenecks in distribution.
Gidoin, Cynthia; Avelino, Jacques; Deheuvels, Olivier; Cilas, Christian; Bieng, Marie Ange Ngo
2014-03-01
Vegetation composition and plant spatial structure affect disease intensity through resource and microclimatic variation effects. The aim of this study was to evaluate the independent effect and relative importance of host composition and plant spatial structure variables in explaining disease intensity at the plot scale. For that purpose, frosty pod rot intensity, a disease caused by Moniliophthora roreri on cacao pods, was monitored in 36 cacao agroforests in Costa Rica in order to assess the vegetation composition and spatial structure variables conducive to the disease. Hierarchical partitioning was used to identify the most causal factors. Firstly, pod production, cacao tree density and shade tree spatial structure had significant independent effects on disease intensity. In our case study, the amount of susceptible tissue was the most relevant host composition variable for explaining disease intensity by resource dilution. Indeed, cacao tree density probably affected disease intensity more by the creation of self-shading rather than by host dilution. Lastly, only regularly distributed forest trees, and not aggregated or randomly distributed forest trees, reduced disease intensity in comparison to plots with a low forest tree density. A regular spatial structure is probably crucial to the creation of moderate and uniform shade as recommended for frosty pod rot management. As pod production is an important service expected from these agroforests, shade tree spatial structure may be a lever for integrated management of frosty pod rot in cacao agroforests.
NASA Technical Reports Server (NTRS)
Russo, N. Dello; Vervack, R. J., Jr.; Kawakita, H.; Cochran, A.; McKay, A. J.; Harris, W. M.; Weaver, H.A.; Lisse, C. M.; DiSanti, M. A.; Kobayashi, H.
2015-01-01
Volatile production rates, relative abundances, rotational temperatures, and spatial distributions in the coma were measured in C/2012 S1 (ISON) using long-slit high-dispersion (lambda/delta lambda approximately 2.5 times 10 (sup 4)) infrared spectroscopy as part of a worldwide observing campaign. Spectra were obtained on Universal Time 2013 October 26 and 28 with NIRSPEC (Near Infrared Spectrometer) at the W.M. Keck Observatory, and Universal Time 2013 November 19 and 20 with CSHELL (Cryogenic Echelle Spectrograph) at the NASA IRTF (Infrared Telescope Facility). H2O was detected on all dates, with production rates increasing markedly from (8.7 plus or minus 1.5) times 10 (sup 27) molecules per second on October 26 (Heliocentric Distance = 1.12 Astronomical Units) to (3.7 plus or minus 0.4) times 10 (sup 29) molecules per second on November 20 (Heliocentric Distance = 0.43 Astronomical Units). Short-term variability of H2O production is also seen as observations on November 19 show an increase in H2O production rate of nearly a factor of two over a period of about 6 hours. C2H6, CH3OH and CH4 abundances in ISON (International Scientific Optical Network) are slightly depleted relative to H2O when compared to mean values for comets measured at infrared wavelengths. On the November dates, C2H2, HCN and OCS abundances relative to H2O appear to be within the range of mean values, whereas H2CO and NH3 were significantly enhanced. There is evidence that the abundances with respect to H2O increased for some species but not others between October 28 (Heliocentric Distance = 1.07 Astronomical Units) and November 19 (Heliocentric Distance = 0.46 Astronomical Units). The high mixing ratios of H2CO to CH3OH and C2H2 to C2H6 on November 19, and changes in the mixing ratios of some species with respect to H2O between October 28 to November 19, indicates compositional changes that may be the result of a transition from sampling radiation-processed outer layers in this dynamically new comet to sampling more pristine natal material as the outer processed layer was increasingly eroded and the thermal wave propagated into the nucleus as the comet approached perihelion for the first time. On November 19 and 20, the spatial distribution for dust appears asymmetric and enhanced in the antisolar direction, whereas spatial distributions for volatiles (excepting CN) appear symmetric with their peaks slightly offset in the sunward direction compared to the dust. Spatial distributions for H2O, HCN, C2H6, C2H2, and H2CO on November 19 show no definitive evidence for significant contributions from extended sources; however, broader spatial distributions for NH3 and OCS may be consistent with extended sources for these species. Abundances of HCN and C2H2 on November 19 and 20 are insufficient to account for reported abundances of CN and C2 in ISON near this time. Differences in HCN and CN spatial distributions are also consistent with HCN as only a minor source of CN in ISON on November 19 as the spatial distribution of CN in the coma suggests a dominant distributed source that is correlated with dust and not volatile release. The spatial distributions for NH3 and NH2 are similar, suggesting that NH3 is the primary source of NH2 with no evidence of a significant dust source of NH2; however, the higher production rates derived for NH3 compared to NH2 on November 19 and 20 remain unexplained. This suggests a more complete analysis that treats NH2 as a distributed source and accounts for its emission mechanism is needed for future work.
NASA Astrophysics Data System (ADS)
Moulds, S.; Djordjevic, S.; Savic, D.
2017-12-01
The Global Change Assessment Model (GCAM), an integrated assessment model, provides insight into the interactions and feedbacks between physical and human systems. The land system component of GCAM, which simulates land use activities and the production of major crops, produces output at the subregional level which must be spatially downscaled in order to use with gridded impact assessment models. However, existing downscaling routines typically consider cropland as a homogeneous class and do not provide information about land use intensity or specific management practices such as irrigation and multiple cropping. This paper presents a spatial allocation procedure to downscale crop production data from GCAM to a spatial grid, producing a time series of maps which show the spatial distribution of specific crops (e.g. rice, wheat, maize) at four input levels (subsistence, low input rainfed, high input rainfed and high input irrigated). The model algorithm is constrained by available cropland at each time point and therefore implicitly balances extensification and intensification processes in order to meet global food demand. It utilises a stochastic approach such that an increase in production of a particular crop is more likely to occur in grid cells with a high biophysical suitability and neighbourhood influence, while a fall in production will occur more often in cells with lower suitability. User-supplied rules define the order in which specific crops are downscaled as well as allowable transitions. A regional case study demonstrates the ability of the model to reproduce historical trends in India by comparing the model output with district-level agricultural inventory data. Lastly, the model is used to predict the spatial distribution of crops globally under various GCAM scenarios.
Huang, Yi; Yang, Lei
2013-01-01
This study attempts to discuss the relationship between land use spatial distribution structure and energy-related carbon emission intensity in Guangdong during 1996–2008. We quantized the spatial distribution structure of five land use types including agricultural land, industrial land, residential and commercial land, traffic land, and other land through applying spatial Lorenz curve and Gini coefficient. Then the corresponding energy-related carbon emissions in each type of land were calculated in the study period. Through building the reasonable regression models, we found that the concentration degree of industrial land is negatively correlated with carbon emission intensity in the long term, whereas the concentration degree is positively correlated with carbon emission intensity in agricultural land, residential and commercial land, traffic land, and other land. The results also indicate that land use spatial distribution structure affects carbon emission intensity more intensively than energy efficiency and production efficiency do. These conclusions provide valuable reference to develop comprehensive policies for energy conservation and carbon emission reduction in a new perspective. PMID:23476128
Huang, Yi; Xia, Bin; Yang, Lei
2013-01-01
This study attempts to discuss the relationship between land use spatial distribution structure and energy-related carbon emission intensity in Guangdong during 1996-2008. We quantized the spatial distribution structure of five land use types including agricultural land, industrial land, residential and commercial land, traffic land, and other land through applying spatial Lorenz curve and Gini coefficient. Then the corresponding energy-related carbon emissions in each type of land were calculated in the study period. Through building the reasonable regression models, we found that the concentration degree of industrial land is negatively correlated with carbon emission intensity in the long term, whereas the concentration degree is positively correlated with carbon emission intensity in agricultural land, residential and commercial land, traffic land, and other land. The results also indicate that land use spatial distribution structure affects carbon emission intensity more intensively than energy efficiency and production efficiency do. These conclusions provide valuable reference to develop comprehensive policies for energy conservation and carbon emission reduction in a new perspective.
Analysis of shifts in the spatial distribution of vegetation due to climate change
NASA Astrophysics Data System (ADS)
del Jesus, Manuel; Díez-Sierra, Javier; Rinaldo, Andrea; Rodríguez-Iturbe, Ignacio
2017-04-01
Climate change will modify the statistical regime of most climatological variables, inducing changes on average values and in the natural variability of environmental variables. These environmental variables may be used to explain the spatial distribution of functional types of vegetation in arid and semiarid watersheds through the use of plant optimization theories. Therefore, plant optimization theories may be used to approximate the response of the spatial distribution of vegetation to a changing climate. Predicting changes in these spatial distributions is important to understand how climate change may affect vegetated ecosystems, but it is also important for hydrological engineering applications where climate change effects on water availability are assessed. In this work, Maximum Entropy Production (MEP) is used as the plant optimization theory that describes the spatial distribution of functional types of vegetation. Current climatological conditions are obtained from direct observations from meteorological stations. Climate change effects are evaluated for different temporal horizons and different climate change scenarios using numerical model outputs from the CMIP5. Rainfall estimates are downscaled by means of a stochastic point process used to model rainfall. The study is carried out for the Rio Salado watershed, located within the Sevilleta LTER site, in New Mexico (USA). Results show the expected changes in the spatial distribution of vegetation and allow to evaluate the expected variability of the changes. The updated spatial distributions allow to evaluate the vegetated ecosystem health and its updated resilience. These results can then be used to inform the hydrological modeling part of climate change assessments analyzing water availability in arid and semiarid watersheds.
Kumar, S.; Spaulding, S.A.; Stohlgren, T.J.; Hermann, K.A.; Schmidt, T.S.; Bahls, L.L.
2009-01-01
The diatom Didymosphenia geminata is a single-celled alga found in lakes, streams, and rivers. Nuisance blooms of D geminata affect the diversity, abundance, and productivity of other aquatic organisms. Because D geminata can be transported by humans on waders and other gear, accurate spatial prediction of habitat suitability is urgently needed for early detection and rapid response, as well as for evaluation of monitoring and control programs. We compared four modeling methods to predict D geminata's habitat distribution; two methods use presence-absence data (logistic regression and classification and regression tree [CART]), and two involve presence data (maximum entropy model [Maxent] and genetic algorithm for rule-set production [GARP]). Using these methods, we evaluated spatially explicit, bioclimatic and environmental variables as predictors of diatom distribution. The Maxent model provided the most accurate predictions, followed by logistic regression, CART, and GARP. The most suitable habitats were predicted to occur in the western US, in relatively cool sites, and at high elevations with a high base-flow index. The results provide insights into the factors that affect the distribution of D geminata and a spatial basis for the prediction of nuisance blooms. ?? The Ecological Society of America.
USDA-ARS?s Scientific Manuscript database
Non-destructive subsurface detection of encapsulated, coated, or seal-packaged foods and pharmaceuticals can help prevent distribution and consumption of counterfeit or hazardous products. This study used a Spatially Offset Raman Spectroscopy (SORS) method to detect and identify urea, ibuprofen, and...
Hinckley, A; Bachand, A; Nuckols, J; Reif, J
2005-01-01
Background and Aims: Epidemiological studies of disinfection by-products (DBPs) and reproductive outcomes have been hampered by misclassification of exposure. In most epidemiological studies conducted to date, all persons living within the boundaries of a water distribution system have been assigned a common exposure value based on facility-wide averages of trihalomethane (THM) concentrations. Since THMs do not develop uniformly throughout a distribution system, assignment of facility-wide averages may be inappropriate. One approach to mitigate this potential for misclassification is to select communities for epidemiological investigations that are served by distribution systems with consistently low spatial variability of THMs. Methods and Results: A feasibility study was conducted to develop methods for community selection using the Information Collection Rule (ICR) database, assembled by the US Environmental Protection Agency. The ICR database contains quarterly DBP concentrations collected between 1997 and 1998 from the distribution systems of 198 public water facilities with minimum service populations of 100 000 persons. Facilities with low spatial variation of THMs were identified using two methods; 33 facilities were found with low spatial variability based on one or both methods. Because brominated THMs may be important predictors of risk for adverse reproductive outcomes, sites were categorised into three exposure profiles according to proportion of brominated THM species and average TTHM concentration. The correlation between THMs and haloacetic acids (HAAs) in these facilities was evaluated to see whether selection by total trihalomethanes (TTHMs) corresponds to low spatial variability for HAAs. TTHMs were only moderately correlated with HAAs (r = 0.623). Conclusions: Results provide a simple method for a priori selection of sites with low spatial variability from state or national public water facility datasets as a means to reduce exposure misclassification in epidemiological studies of DBPs. PMID:15961627
Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas
2016-01-01
Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.
ERIC Educational Resources Information Center
Li, Jianyi; Nie, Lanying; Li, Zeyu; Lin, Lijun; Tang, Lei; Ouyang, Jun
2012-01-01
Anatomical corrosion casts of human specimens are useful teaching aids. However, their use is limited due to ethical dilemmas associated with their production, their lack of perfect reproducibility, and their consumption of original specimens in the process of casting. In this study, new approaches with modern distribution of complex anatomical…
PATTERNS OF ROOT GROWTH, TURNOVER, AND DISTRIBUTION IN DIFFERENT AGED PONDEROSA PINE STANDS
The objectives of this study are to examine the spatial distribution of roots in relation to canopy size and tree distribution, and to determine if rates of fine root production and turnover are similar in the different aged stands. During the fall of 1998, 54 clear plexiglass t...
Climatological Downscaling and Evaluation of AGRMET Precipitation Analyses Over the Continental U.S.
NASA Astrophysics Data System (ADS)
Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Tian, Y.; Zeng, J.
2007-05-01
The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002). It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for military and civilian customer applications.
Lasmar, O; Zanetti, R; dos Santos, A; Fernandes, B V
2012-08-01
One of the fundamental steps in pest sampling is the assessment of the population distribution in the field. Several studies have investigated the distribution and appropriate sampling methods for leaf-cutting ants; however, more reliable methods are still required, such as those that use geostatistics. The objective of this study was to determine the spatial distribution and infestation rate of leaf-cutting ant nests in eucalyptus plantations by using geostatistics. The study was carried out in 2008 in two eucalyptus stands in Paraopeba, Minas Gerais, Brazil. All of the nests in the studied area were located and used for the generation of GIS maps, and the spatial pattern of distribution was determined considering the number and size of nests. Each analysis and map was made using the R statistics program and the geoR package. The nest spatial distribution in a savanna area of Minas Gerais was clustered to a certain extent. The models generated allowed the production of kriging maps of areas infested with leaf-cutting ants, where chemical intervention would be necessary, reducing the control costs, impact on humans, and the environment.
Statistical analysis of the MODIS atmosphere products for the Tomsk region
NASA Astrophysics Data System (ADS)
Afonin, Sergey V.; Belov, Vladimir V.; Engel, Marina V.
2005-10-01
The paper presents the results of using the MODIS Atmosphere Products satellite information to study the atmospheric characteristics (the aerosol and water vapor) in the Tomsk Region (56-61°N, 75-90°E) in 2001-2004. The satellite data were received from the NASA Goddard Distributed Active Archive Center (DAAC) through the INTERNET.To use satellite data for a solution of scientific and applied problems, it is very important to know their accuracy. Despite the results of validation of the MODIS data have already been available in the literature, we decided to carry out additional investigations for the Tomsk Region. The paper presents the results of validation of the aerosol optical thickness (AOT) and total column precipitable water (TCPW), which are in good agreement with the test data. The statistical analysis revealed some interesting facts. Thus, for example, analyzing the data on the spatial distribution of the average seasonal values of AOT or TCPW for 2001-2003 in the Tomsk Region, we established that instead of the expected spatial homogeneity of these distributions, they have similar spatial structures.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, J. M.; Fung, J. W.; Mo, G.
2015-01-01
In order to improve quantification of the spatial distribution of carbon sinks and sources in the conterminous USA, we conduct a nested global atmospheric inversion with consideration of the spatial information of crop production and consumption. Spatially distributed 5 county-level cropland net primary productivity, harvested biomass, soil carbon change, and human and livestock consumption data over the conterminous USA are used for this purpose. Time-dependent Bayesian synthesis inversions are conducted based on CO₂ observations at 210 stations to infer CO₂ fluxes globally at monthly time steps with a nested focus on 30 regions in North America. Prior land surface carbonmore » 10 fluxes are first generated using a biospheric model, and the inversions are constrained using prior fluxes with and without adjustments for crop production and consumption over the 2002–2007 period. After these adjustments, the inverted regional carbon sink in the US Midwest increases from 0.25 ± 0.03 Pg C yr⁻¹ to 0.42 ± 0.13 Pg C yr⁻¹, whereas the large sink in the US Southeast forest region is weakened from 0.41±0.12 Pg C yr⁻¹ 15 to 0.29 ±0.12 Pg C yr⁻¹. These adjustments also reduce the inverted sink in the West region from 0.066 ± 0.04 Pg C yr⁻¹ to 0.040 ± 0.02 Pg C yr⁻1 because of high crop consumption and respiration by humans and livestock. The general pattern of sink increase in crop production areas and sink decreases (or source increases) in crop consumption areas highlights the importance of considering the lateral carbon transfer in crop 20 products in atmospheric inverse modeling, which provides an atmospheric perspective of the overall carbon balance of a region.« less
Spatial dynamics of a nutrient-phytoplankton system with toxic effect on phytoplankton.
Chakraborty, Subhendu; Tiwari, P K; Misra, A K; Chattopadhyay, J
2015-06-01
The production of toxins by some species of phytoplankton is known to have several economic, ecological, and human health impacts. However, the role of toxins on the spatial distribution of phytoplankton is not well understood. In the present study, the spatial dynamics of a nutrient-phytoplankton system with toxic effect on phytoplankton is investigated. We analyze the linear stability of the system and obtain the condition for Turing instability. In the presence of toxic effect, we find that the distribution of nutrient and phytoplankton becomes inhomogeneous in space and results in different patterns, like stripes, spots, and the mixture of them depending on the toxicity level. We also observe that the distribution of nutrient and phytoplankton shows spatiotemporal oscillation for certain toxicity level. Copyright © 2015 Elsevier Inc. All rights reserved.
Statistical Considerations of Data Processing in Giovanni Online Tool
NASA Technical Reports Server (NTRS)
Suhung, Shen; Leptoukh, G.; Acker, J.; Berrick, S.
2005-01-01
The GES DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni) is a web-based interface for the rapid visualization and analysis of gridded data from a number of remote sensing instruments. The GES DISC currently employs several Giovanni instances to analyze various products, such as Ocean-Giovanni for ocean products from SeaWiFS and MODIS-Aqua; TOMS & OM1 Giovanni for atmospheric chemical trace gases from TOMS and OMI, and MOVAS for aerosols from MODIS, etc. (http://giovanni.gsfc.nasa.gov) Foremost among the Giovanni statistical functions is data averaging. Two aspects of this function are addressed here. The first deals with the accuracy of averaging gridded mapped products vs. averaging from the ungridded Level 2 data. Some mapped products contain mean values only; others contain additional statistics, such as number of pixels (NP) for each grid, standard deviation, etc. Since NP varies spatially and temporally, averaging with or without weighting by NP will be different. In this paper, we address differences of various weighting algorithms for some datasets utilized in Giovanni. The second aspect is related to different averaging methods affecting data quality and interpretation for data with non-normal distribution. The present study demonstrates results of different spatial averaging methods using gridded SeaWiFS Level 3 mapped monthly chlorophyll a data. Spatial averages were calculated using three different methods: arithmetic mean (AVG), geometric mean (GEO), and maximum likelihood estimator (MLE). Biogeochemical data, such as chlorophyll a, are usually considered to have a log-normal distribution. The study determined that differences between methods tend to increase with increasing size of a selected coastal area, with no significant differences in most open oceans. The GEO method consistently produces values lower than AVG and MLE. The AVG method produces values larger than MLE in some cases, but smaller in other cases. Further studies indicated that significant differences between AVG and MLE methods occurred in coastal areas where data have large spatial variations and a log-bimodal distribution instead of log-normal distribution.
Colunga-Garcia, Manuel; Haack, Robert A; Adelaja, Adesoji O
2009-02-01
Freight transportation is an important pathway for the introduction and dissemination of exotic forest insects (EFI). Identifying the final destination of imports is critical in determining the likelihood of EFI establishment. We analyzed the use of regional freight transport information to characterize risk of urban and periurban areas to EFI introductions. Specific objectives were to 1) approximate the final distribution of selected imports among urban areas of the United States, 2) characterize the final distribution of imports in terms of their spatial aggregation and dominant world region of origin, and 3) assess the effect of the final distribution of imports on the level of risk to urban and periurban forests from EFI. Freight pattern analyses were conducted for three categories of imports whose products or packaging materials are associated with EFI: wood products, nonmetallic mineral products, and machinery. The final distribution of wood products was the most evenly distributed of the three selected imports, whereas machinery was most spatially concentrated. We found that the type of import and the world region of origin greatly influence the final distribution of imported products. Risk assessment models were built based on the amount of forestland and imports for each urban area The model indicated that 84-88% of the imported tonnage went to only 4-6% of the urban areas in the contiguous United States. We concluded that freight movement information is critical for proper risk assessment of EFI. Implications of our findings and future research needs are discussed.
Body size distributions signal a regime shift in a lake ecosystem
Communities of organisms, from mammals to microorganisms, have discontinuous distributions of body size. This pattern of size structuring is a conservative trait of community organization and is a product of processes that occur at multiple spatial and temporal scales. In this st...
Andres, R.J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Boden, T.A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Marland, G. [Appalachian State University, Boone, NC (United States)
2016-01-01
The monthly, fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Andres, R.J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Boden, T.A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Marland, J. [Appalachian State University, Boone, NC (United States)
2015-01-01
The monthly, fossil-fuel CO2 emissions estimates from 1950-2011 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2015), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.
2010-01-01
The monthly, fossil-fuel CO2 emissions estimates from 1950-2010 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2013), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Andres, R. J. [.; Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory Oak Ridge, TN (USA).; Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory Oak Ridge, TN (USA).; Marland, Greg [Appalachian State University, Boone, North Carolina (USA)
2009-01-01
The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2006.html), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA_; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.
2011-01-01
The monthly, fossil-fuel CO2 emissions estimates from 1950-2010 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2013), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Appalachian State University, Boone, North Caroline (USA)
2012-01-01
The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2009.html), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html Q10 for a description why emission totals based upon consumption differ from those based upon production).
Andres, R. J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Boden, T.A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Marland, G. [Appalachain State University, Boone, NC (United States)
1996-01-01
The monthly, fossil-fuel CO2 emissions estimates from 1950-2010 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2013), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Xiong, Zong-Wei; Gu, Sheng-Hao; Mao, Li-Li; Wang, Xue-Jiao; Zhang, Li-Zhen; Zhou, Zhi-Guo
2012-12-01
By using geographical information system (GIS), the cotton fiber quality data from 2005 to 2011 and the daily meteorological data from 1981 to 2010 at 82 sites (counties and cities) in China major cotton production regions were collected and treated with spatial interpolation. The spatial information system of cotton fiber quality in China major cotton production regions was established based on GIS, and the spatial distribution characteristics of the cotton fiber quality and their relationships with the local climatic factors were analyzed. In the northwest region (especially Xinjiang) of China, due to the abundant sunlight, low precipitation, and low relative humidity, the cotton fiber length, micronaire, and grade ranked the first. In the Yangtze River region and Yellow River region, the specific strength of cotton fiber was higher, and in the Yangtze River region, the cotton fiber length and specific strength were higher, while the micronaire and grade were lower than those in the Yellow River region. The cotton fiber quality was closely related to the climate factors such as temperature, sunlight, rainfall, and humidity.
NASA Astrophysics Data System (ADS)
Garcia-Eidell, Cynthia; Comiso, Josefino C.; Dinnat, Emmanuel; Brucker, Ludovic
2017-09-01
Global surface ocean salinity measurements have been available since the launch of SMOS in 2009 and coverage was further enhanced with the launch of Aquarius in 2011. In the polar regions where spatial and temporal changes in sea surface salinity (SSS) are deemed important, the data have not been as robustly validated because of the paucity of in situ measurements. This study presents a comparison of four SSS products in the ice-free Arctic region, three using Aquarius data and one using SMOS data. The accuracy of each product is assessed through comparative analysis with ship and other in situ measurements. Results indicate RMS errors ranging between 0.33 and 0.89 psu. Overall, the four products show generally good consistency in spatial distribution with the Atlantic side being more saline than the Pacific side. A good agreement between the ship and satellite measurements was also observed in the low salinity regions in the Arctic Ocean, where SSS in situ measurements are usually sparse, at the end of summer melt seasons. Some discrepancies including biases of about 1 psu between the products in spatial and temporal distribution are observed. These are due in part to differences in retrieval techniques, geophysical filtering, and sea ice and land masks. The monthly SSS retrievals in the Arctic from 2011 to 2015 showed variations (within ˜1 psu) consistent with effects of sea ice seasonal cycles. This study indicates that spaceborne observations capture the seasonality and interannual variability of SSS in the Arctic with reasonably good accuracy.
NASA Astrophysics Data System (ADS)
Pennino, Maria Grazia; Mérigot, Bastien; Fonseca, Vinícius Prado; Monni, Virginia; Rotta, Andrea
2017-07-01
Effective management and conservation of wild populations requires knowledge of their habitats, especially by mean of quantitative analyses of their spatial distributions. The Pelagos Sanctuary is a dedicated marine protected area for Mediterranean marine mammals covering an area of 90,000 km2 in the north-western Mediterranean Sea between Italy, France and the Principate of Monaco. In the south of the Sanctuary, i.e. along the Sardinian coast, a range of diverse human activities (cities, industry, fishery, tourism) exerts several current ad potential threats to cetacean populations. In addition, marine mammals are recognized by the EU Marine Strategy Framework Directive as essential components of sustainable ecosystems. Yet, knowledge on the spatial distribution and ecology of cetaceans in this area is quite scarce. Here we modeled occurrence of the three most abundant species known in the Sanctuary, i.e. the striped dolphin (Stenella coeruleoalba), the bottlenose dolphin (Tursiops truncatus) and the fin whales (Balaenoptera physalus), using sighting data from scientific surveys collected from 2012 to 2014 during summer time. Bayesian site-occupancy models were used to model their spatial distribution in relation to habitat taking into account oceanographic (sea surface temperature, primary production, photosynthetically active radiation, chlorophyll-a concentration) and topographic (depth, slope, distance of the land) variables. Cetaceans responded differently to the habitat features, with higher occurrence predicted in the more productive areas on submarine canyons. These results provide ecological information useful to enhance management plans and establish baseline for future population trend studies.
Chen, Qing; Xu, Pengfei; Liu, Wenzhong
2016-01-01
Computer vision as a fast, low-cost, noncontact, and online monitoring technology has been an important tool to inspect product quality, particularly on a large-scale assembly production line. However, the current industrial vision system is far from satisfactory in the intelligent perception of complex grain images, comprising a large number of local homogeneous fragmentations or patches without distinct foreground and background. We attempt to solve this problem based on the statistical modeling of spatial structures of grain images. We present a physical explanation in advance to indicate that the spatial structures of the complex grain images are subject to a representative Weibull distribution according to the theory of sequential fragmentation, which is well known in the continued comminution of ore grinding. To delineate the spatial structure of the grain image, we present a method of multiscale and omnidirectional Gaussian derivative filtering. Then, a product quality classifier based on sparse multikernel–least squares support vector machine is proposed to solve the low-confidence classification problem of imbalanced data distribution. The proposed method is applied on the assembly line of a food-processing enterprise to classify (or identify) automatically the production quality of rice. The experiments on the real application case, compared with the commonly used methods, illustrate the validity of our method. PMID:26986726
NASA Technical Reports Server (NTRS)
Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.
1998-01-01
The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.
Ozone production process in pulsed positive dielectric barrier discharge
NASA Astrophysics Data System (ADS)
Ono, Ryo; Oda, Tetsuji
2007-01-01
The ozone production process in a pulsed positive dielectric barrier discharge (DBD) is studied by measuring the spatial distribution of ozone density using a two-dimensional laser absorption method. DBD occurs in a 6 mm point-to-plane gap with a 1 mm-thick glass plate placed on the plane electrode. First, the propagation of DBD is observed using a short-gated ICCD camera. It is shown that DBD develops in three phases: primary streamer, secondary streamer and surface discharge phases. Next, the spatial distribution of ozone density is measured. It is shown that ozone is mostly produced in the secondary streamer and surface discharge, while only a small amount of ozone is produced in the primary streamer. The rate coefficient of the ozone production reaction, O + O2 + M → O3 + M, is estimated to be 2.5 × 10-34 cm6 s-1.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Serdar, Marijana; Meral, Cagla; Kunz, Martin
2015-05-15
The mineralogy and spatial distribution of nano-crystalline corrosion products that form in the steel/concrete interface were characterized using synchrotron X-ray micro-diffraction (μ-XRD). Two types of low-nickel high-chromium reinforcing steels embedded into mortar and exposed to NaCl solution were investigated. Corrosion in the samples was confirmed by electrochemical impedance spectroscopy (EIS). μ-XRD revealed that goethite (α-FeOOH) and akaganeite (β-FeOOH) are the main iron oxide–hydroxides formed during the chloride-induced corrosion of stainless steel in concrete. Goethite is formed closer to the surface of the steel due to the presence of chromium in the steel, while akaganeite is formed further away from themore » surface due to the presence of chloride ions. Detailed microstructural analysis is shown and discussed on one sample of each type of steel. - Highlights: • Synchrotron micro-diffraction used to map the distribution of crystalline phases. • Goethite and akaganeite are the main corrosion products during chloride induced corrosion in mortar. • Layers of goethite and akaganeite are negatively correlated. • EDS showed Cr present in corrosion products identified by SEM.« less
'Fracking', Induced Seismicity and the Critical Earth
NASA Astrophysics Data System (ADS)
Leary, P.; Malin, P. E.
2012-12-01
Issues of 'fracking' and induced seismicity are reverse-analogous to the equally complex issues of well productivity in hydrocarbon, geothermal and ore reservoirs. In low hazard reservoir economics, poorly producing wells and low grade ore bodies are many while highly producing wells and high grade ores are rare but high pay. With induced seismicity factored in, however, the same distribution physics reverses the high/low pay economics: large fracture-connectivity systems are hazardous hence low pay, while high probability small fracture-connectivity systems are non-hazardous hence high pay. Put differently, an economic risk abatement tactic for well productivity and ore body pay is to encounter large-scale fracture systems, while an economic risk abatement tactic for 'fracking'-induced seismicity is to avoid large-scale fracture systems. Well productivity and ore body grade distributions arise from three empirical rules for fluid flow in crustal rock: (i) power-law scaling of grain-scale fracture density fluctuations; (ii) spatial correlation between spatial fluctuations in well-core porosity and the logarithm of well-core permeability; (iii) frequency distributions of permeability governed by a lognormality skewness parameter. The physical origin of rules (i)-(iii) is the universal existence of a critical-state-percolation grain-scale fracture-density threshold for crustal rock. Crustal fractures are effectively long-range spatially-correlated distributions of grain-scale defects permitting fluid percolation on mm to km scales. The rule is, the larger the fracture system the more intense the percolation throughput. As percolation pathways are spatially erratic and unpredictable on all scales, they are difficult to model with sparsely sampled well data. Phenomena such as well productivity, induced seismicity, and ore body fossil fracture distributions are collectively extremely difficult to predict. Risk associated with unpredictable reservoir well productivity and ore body distributions can be managed by operating in a context which affords many small failures for a few large successes. In reverse view, 'fracking' and induced seismicity could be rationally managed in a context in which many small successes can afford a few large failures. However, just as there is every incentive to acquire information leading to higher rates of productive well drilling and ore body exploration, there are equal incentives for acquiring information leading to lower rates of 'fracking'-induced seismicity. Current industry practice of using an effective medium approach to reservoir rock creates an uncritical sense that property distributions in rock are essentially uniform. Well-log data show that the reverse is true: the larger the length scale the greater the deviation from uniformity. Applying the effective medium approach to large-scale rock formations thus appears to be unnecessarily hazardous. It promotes the notion that large scale fluid pressurization acts against weakly cohesive but essentially uniform rock to produce large-scale quasi-uniform tensile discontinuities. Indiscriminate hydrofacturing appears to be vastly more problematic in reality than as pictured by the effective medium hypothesis. The spatial complexity of rock, especially at large scales, provides ample reason to find more controlled pressurization strategies for enhancing in situ flow.
Jia, Xiaoxu; Xie, Baoni; Shao, Ming’an; Zhao, Chunlei
2015-01-01
Clarifying spatial variations in aboveground net primary productivity (ANPP) and precipitation-use efficiency (PUE) of grasslands is critical for effective prediction of the response of terrestrial ecosystem carbon and water cycle to future climate change. Though the combination use of remote sensing products and in situ ANPP measurements, we quantified the effects of climatic [mean annual precipitation (MAP) and precipitation seasonal distribution (PSD)], biotic [leaf area index (LAI)] and abiotic [slope gradient, aspect, soil water storage (SWS) and other soil physical properties] factors on the spatial variations in ANPP and PUE across different grassland types (i.e., meadow steppe, typical steppe and desert steppe) in the Loess Plateau. Based on the study, ANPP increased exponentially with MAP for the entire temperate grassland; suggesting that PUE increased with increasing MAP. Also PSD had a significant effect on ANPP and PUE; where more even PSD favored higher ANPP and PUE. Then MAP, more than PSD, explained spatial variations in typical steppe and desert steppe. However, PSD was the dominant driving factor of spatial variations in ANPP of meadow steppe. This suggested that in terms of spatial variations in ANPP of meadow steppe, change in PSD due to climate change was more important than that in total annual precipitation. LAI explained 78% of spatial PUE in the entire Loess Plateau temperate grassland. As such, LAI was the primary driving factor of spatial variations in PUE. Although the effect of SWS on ANPP and PUE was significant, it was nonetheless less than that of precipitation and vegetation. We therefore concluded that changes in vegetation structure and consequently in LAI and/or altered pattern of seasonal distribution of rainfall due to global climate change could significantly influence ecosystem carbon and water cycle in temperate grasslands. PMID:26295954
Jia, Xiaoxu; Xie, Baoni; Shao, Ming'an; Zhao, Chunlei
2015-01-01
Clarifying spatial variations in aboveground net primary productivity (ANPP) and precipitation-use efficiency (PUE) of grasslands is critical for effective prediction of the response of terrestrial ecosystem carbon and water cycle to future climate change. Though the combination use of remote sensing products and in situ ANPP measurements, we quantified the effects of climatic [mean annual precipitation (MAP) and precipitation seasonal distribution (PSD)], biotic [leaf area index (LAI)] and abiotic [slope gradient, aspect, soil water storage (SWS) and other soil physical properties] factors on the spatial variations in ANPP and PUE across different grassland types (i.e., meadow steppe, typical steppe and desert steppe) in the Loess Plateau. Based on the study, ANPP increased exponentially with MAP for the entire temperate grassland; suggesting that PUE increased with increasing MAP. Also PSD had a significant effect on ANPP and PUE; where more even PSD favored higher ANPP and PUE. Then MAP, more than PSD, explained spatial variations in typical steppe and desert steppe. However, PSD was the dominant driving factor of spatial variations in ANPP of meadow steppe. This suggested that in terms of spatial variations in ANPP of meadow steppe, change in PSD due to climate change was more important than that in total annual precipitation. LAI explained 78% of spatial PUE in the entire Loess Plateau temperate grassland. As such, LAI was the primary driving factor of spatial variations in PUE. Although the effect of SWS on ANPP and PUE was significant, it was nonetheless less than that of precipitation and vegetation. We therefore concluded that changes in vegetation structure and consequently in LAI and/or altered pattern of seasonal distribution of rainfall due to global climate change could significantly influence ecosystem carbon and water cycle in temperate grasslands.
Development of Lattice Trapped Paramagnetic Polar Molecules for Quantum Simulation
2015-06-23
2015 DISTRIBUTION A: Distribution approved for public release. AF Office Of Scientific Research (AFOSR)/ RTB Arlington, Virginia 22203 Air Force...Arlington, VA 22203 10. SPONSOR/MONITOR’S ACRONYM(S) AFRL/AFOSR RTB 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION /AVAILABILITY STATEMENT A... DISTRIBUTION UNLIMITED: PB Public Release 13. SUPPLEMENTARY NOTES 14. ABSTRACT We have demonstrated optimized production and spatial manipulation of Li
Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas
2017-01-01
Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments. PMID:28190948
Bennema, S C; Ducheyne, E; Vercruysse, J; Claerebout, E; Hendrickx, G; Charlier, J
2011-02-01
Fasciola hepatica, a trematode parasite with a worldwide distribution, is the cause of important production losses in the dairy industry. Diagnosis is hampered by the fact that the infection is mostly subclinical. To increase awareness and develop regionally adapted control methods, knowledge on the spatial distribution of economically important infection levels is needed. Previous studies modelling the spatial distribution of F. hepatica are mostly based on single cross-sectional samplings and have focussed on climatic and environmental factors, often ignoring management factors. This study investigated the associations between management, climatic and environmental factors affecting the spatial distribution of infection with F. hepatica in dairy herds in a temperate climate zone (Flanders, Belgium) over three consecutive years. A bulk-tank milk antibody ELISA was used to measure F. hepatica infection levels in a random sample of 1762 dairy herds in the autumns of 2006, 2007 and 2008. The infection levels were included in a Geographic Information System together with meteorological, environmental and management parameters. Logistic regression models were used to determine associations between possible risk factors and infection levels. The prevalence and spatial distribution of F. hepatica was relatively stable, with small interannual differences in prevalence and location of clusters. The logistic regression model based on both management and climatic/environmental factors included the factors: annual rainfall, mowing of pastures, proportion of grazed grass in the diet and length of grazing season as significant predictors and described the spatial distribution of F. hepatica better than the model based on climatic/environmental factors only (annual rainfall, elevation and slope, soil type), with an Area Under the Curve of the Receiver Operating Characteristic of 0.68 compared with 0.62. The results indicate that in temperate climate zones without large climatic and environmental variation, management factors affect the spatial distribution of F. hepatica, and should be included in future spatial distribution models. Copyright © 2010 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.
Modeling the magnitude and distribution of estuarine sediment contamination by pollutants of historic (e.g. PCB) and emerging concern (e.g., personal care products, PCP) is often limited by incomplete site knowledge and inadequate sediment contamination sampling. We tested a mode...
NASA Astrophysics Data System (ADS)
Liu, Q.; Chiu, L. S.; Hao, X.
2017-10-01
The abundance or lack of rainfall affects peoples' life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007), accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG). However, the models' resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling) procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA) at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days) and monthly resolutions. The probability distributions (PDF) and cumulative distribution functions(CDF) of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS) test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.
Spatial Patterns of Snow Cover in North Carolina: Surface and Satellite Perspectives
NASA Technical Reports Server (NTRS)
Fuhrmann, Christopher M.; Hall, Dorothy K.; Perry, L. Baker; Riggs, George A.
2010-01-01
Snow mapping is a common practice in regions that receive large amounts of snowfall annually, have seasonally-continuous snow cover, and where snowmelt contributes significantly to the hydrologic cycle. Although higher elevations in the southern Appalachian Mountains average upwards of 100 inches of snow annually, much of the remainder of the Southeast U.S. receives comparatively little snowfall (< 10 inches). Recent snowy winters in the region have provided an opportunity to assess the fine-grained spatial distribution of snow cover and the physical processes that act to limit or improve its detection across the Southeast. In the present work, both in situ and remote sensing data are utilized to assess the spatial distribution of snow cover for a sample of recent snowfall events in North Carolina. Specifically, this work seeks to determine how well ground measurements characterize the fine-grained patterns of snow cover in relation to Moderate- Resolution Imaging Spectroradiometer (MODIS) snow cover products (in this case, the MODIS Fractional Snow Cover product).
NASA Technical Reports Server (NTRS)
Fox, Robert; Prins, Elaine Mae; Feltz, Joleen M.
2001-01-01
In recent years, modeling and analysis efforts have suggested that the direct and indirect radiative effects of both anthropogenic and natural aerosols play a major role in the radiative balance of the earth and are an important factor in climate change calculations. The direct effects of aerosols on radiation and indirect effects on cloud properties are not well understood at this time. In order to improve the characterization of aerosols within climate models it is important to accurately parameterize aerosol forcing mechanisms at the local, regional, and global scales. This includes gaining information on the spatial and temporal distribution of aerosols, transport regimes and mechanisms, aerosol optical thickness, and size distributions. Although there is an expanding global network of ground measurements of aerosol optical thickness and size distribution at specific locations, satellite data must be utilized to characterize the spatial and temporal extent of aerosols and transport regimes on regional and global scales. This study was part of a collaborative effort to characterize aerosol radiative forcing over the Atlantic basin associated with the following three major aerosol components in this region: urban/sulfate, Saharan dust, and biomass burning. In-situ ground measurements obtained by a network of sun photometers during the Smoke Clouds and Radiation Experiment in Brazil (SCAR-B) and the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX) were utilized to develop, calibrate, and validate a Geostationary Operational Environmental Satellite (GOES)-8 aerosol optical thickness (AOT) product. Regional implementation of the GOES-8 AOT product was used to augment point source measurements to gain a better understanding of the spatial and temporal distributions of Atlantic basin aerosols during SCAR-B and TARFOX.
Quantitative evaluation of legacy phosphorus and its spatial distribution.
Lou, Hezhen; Zhao, Changsen; Yang, Shengtian; Shi, Liuhua; Wang, Yue; Ren, Xiaoyu; Bai, Juan
2018-04-01
A phosphorus resource crisis threatens the security of global crop production, especially in developing countries like China and Brazil. Legacy phosphorus (legacy-P), which is left behind in agricultural soil by over-fertilization, can help address this issue as a new resource in the soil phosphorus pool. However, issues involved with calculating and defining the spatial distribution of legacy-P hinder its future utilization. To resolve these issues, this study applied remote sensing and ecohydrological modeling to precisely quantify legacy-P and define its spatial distribution in China's Sanjiang Plain from 2000 to 2014. The total legacy-P in the study area was calculated as 579,090 t with an annual average of 38,600 t; this comprises 51.83% of the phosphorus fertilizer applied annually. From 2000 to 2014, the annual amount of legacy-P increased by more than 3.42-fold, equivalent to a 2460-ton increase each year. The spatial distribution of legacy-P showed heterogeneity and agglomeration in this area, with peaks in cultivated land experiencing long-term agricultural development. This study supplies a new approach to finding legacy-P in soil as a precondition for future utilization. Once its spatial distribution is known, legacy-P can be better utilized in agriculture to help alleviate the phosphorus resource crisis. Copyright © 2018 Elsevier Ltd. All rights reserved.
Puerta, Patricia; Hunsicker, Mary E.; Quetglas, Antoni; Álvarez-Berastegui, Diego; Esteban, Antonio; González, María; Hidalgo, Manuel
2015-01-01
Populations of the same species can experience different responses to the environment throughout their distributional range as a result of spatial and temporal heterogeneity in habitat conditions. This highlights the importance of understanding the processes governing species distribution at local scales. However, research on species distribution often averages environmental covariates across large geographic areas, missing variability in population-environment interactions within geographically distinct regions. We used spatially explicit models to identify interactions between species and environmental, including chlorophyll a (Chla) and sea surface temperature (SST), and trophic (prey density) conditions, along with processes governing the distribution of two cephalopods with contrasting life-histories (octopus and squid) across the western Mediterranean Sea. This approach is relevant for cephalopods, since their population dynamics are especially sensitive to variations in habitat conditions and rarely stable in abundance and location. The regional distributions of the two cephalopod species matched two different trophic pathways present in the western Mediterranean Sea, associated with the Gulf of Lion upwelling and the Ebro river discharges respectively. The effects of the studied environmental and trophic conditions were spatially variant in both species, with usually stronger effects along their distributional boundaries. We identify areas where prey availability limited the abundance of cephalopod populations as well as contrasting effects of temperature in the warmest regions. Despite distributional patterns matching productive areas, a general negative effect of Chla on cephalopod densities suggests that competition pressure is common in the study area. Additionally, results highlight the importance of trophic interactions, beyond other common environmental factors, in shaping the distribution of cephalopod populations. Our study presents a valuable approach for understanding the spatially variant ecology of cephalopod populations, which is important for fisheries and ecosystem management. PMID:26201075
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.
A spatial emergy model for Alachua County, Florida
NASA Astrophysics Data System (ADS)
Lambert, James David
A spatial model of the distribution of energy flows and storages in Alachua County, Florida, was created and used to analyze spatial patterns of energy transformation hierarchy in relation to spatial patterns of human settlement. Emergy, the available energy of one kind previously required directly or indirectly to make a product or service, was used as a measure of the quality of the different forms of energy flows and storages. Emergy provides a common unit of measure for comparing the productive contributions of natural processes with those of economic and social processes---it is an alternative to using money for measuring value. A geographic information system was used to create a spatial model and make maps that show the distribution and magnitude of different types of energy and emergy flows and storages occurring in one-hectare land units. Energy transformities were used to convert individual energy flows and storages into emergy units. Maps of transformities were created that reveal a clear spatial pattern of energy transformation hierarchy. The maps display patterns of widely-dispersed areas with lower transformity energy flows and storages, and smaller, centrally-located areas with higher transformities. Energy signature graphs and spatial unit transformities were used to characterize and compare the types and amounts of energy being consumed and stored according to land use classification, planning unit, and neighborhood categories. Emergy ratio maps and spatial unit ratios were created by dividing the values for specific emergy flows or storages by the values for other emergy flows or storages. Spatial context analysis was used to analyze the spatial distribution patterns of mean and maximum values for emergy flows and storages. The modeling method developed for this study is general and applicable to all types of landscapes and could be applied at any scale. An advantage of this general approach is that the results of other studies using this method will be directly comparable with the results of this study. The results and conclusions of this study reinforce the hypothesis that an urban landscape will develop a predictable spatial pattern that can be described in terms of a universal energy transformation hierarchy.
Forecasting Impacts of Climate Change on Indicators of British Columbia's Biodiversity
NASA Astrophysics Data System (ADS)
Holmes, Keith Richard
Understanding the relationships between biodiversity and climate is essential for predicting the impact of climate change on broad-scale landscape processes. Utilizing indirect indicators of biodiversity derived from remotely sensed imagery, we present an approach to forecast shifts in the spatial distribution of biodiversity. Indirect indicators, such as remotely sensed plant productivity metrics, representing landscape seasonality, minimum growth, and total greenness have been linked to species richness over broad spatial scales, providing unique capacity for biodiversity modeling. Our goal is to map future spatial distributions of plant productivity metrics based on expected climate change and to quantify anticipated change to park habitat in British Columbia. Using an archival dataset sourced from the Advanced Very High Resolution Radiometer (AVHRR) satellite from the years 1987 to 2007 at 1km spatial resolution, corresponding historical climate data, and regression tree modeling, we developed regional models of the relationships between climate and annual productivity growth. Historical interconnections between climate and annual productivity were coupled with three climate change scenarios modeled by the Canadian Centre for Climate Modeling and Analysis (CCCma) to predict and map productivity components to the year 2065. Results indicate we can expect a warmer and wetter environment, which may lead to increased productivity in the north and higher elevations. Overall, seasonality is expected to decrease and greenness productivity metrics are expected to increase. The Coastal Mountains and high elevation edge habitats across British Columbia are forecasted to experience the greatest amount of change. In the future, protected areas may have potential higher greenness and lower seasonality as represented by indirect biodiversity indicators. The predictive model highlights potential gaps in protection along the central interior and Rocky Mountains. Protected areas are expected to experience the greatest change with indirect indicators located along mountainous elevations of British Columbia. Our indirect indicator approach to predict change in biodiversity provides resource managers with information to mitigate and adapt to future habitat dynamics. Spatially specific recommendations from our dataset provide information necessary for management. For instance, knowing there is a projected depletion of habitat representation in the East Rocky Mountains, sensitive species in the threatened Mountain Hemlock ecozone, or preservation of rare habitats in the decreasing greenness of the southern interior region is essential information for managers tasked with long term biodiversity conservation. Forecasting productivity levels, linked to the distribution of species richness, presents a novel approach for understanding the future implications of climate change on broad scale biodiversity.
Electron temperature profiles in axial field 2.45 GHz ECR ion source with a ceramic chamber
NASA Astrophysics Data System (ADS)
Abe, K.; Tamura, R.; Kasuya, T.; Wada, M.
2017-08-01
An array of electrostatic probes was arranged on the plasma electrode of a 2.45 GHz microwave driven axial magnetic filter field type negative hydrogen (H-) ion source to clarify the spatial plasma distribution near the electrode. The measured spatial distribution of electron temperature indicated the lower temperature near the extraction hole of the plasma electrode corresponding to the effectiveness of the axial magnetic filter field geometry. When the ratio of electron saturation current to the ion saturation current was plotted as a function of position, the obtained distribution showed a higher ratio near the hydrogen gas inlet through which ground state hydrogen molecules are injected into the source. Though the efficiency in producing H- ions is smaller for a 2.45 GHz source than a source operated at 14 GHz, it gives more volume to measure spatial distributions of various plasma parameters to understand fundamental processes that are influential on H- production in this type of ion sources.
Walsh, Harvey J; Richardson, David E; Marancik, Katrin E; Hare, Jonathan A
2015-01-01
Many studies have documented long-term changes in adult marine fish distributions and linked these changes to climate change and multi-decadal climate variability. Most marine fish, however, have complex life histories with morphologically distinct stages, which use different habitats. Shifts in distribution of one stage may affect the connectivity between life stages and thereby impact population processes including spawning and recruitment. Specifically, many marine fish species have a planktonic larval stage, which lasts from weeks to months. We compared the spatial distribution and seasonal occurrence of larval fish in the Northeast U.S. Shelf Ecosystem to test whether spatial and temporal distributions changed between two decades. Two large-scale ichthyoplankton programs sampled using similar methods and spatial domain each decade. Adult distributions from a long-term bottom trawl survey over the same time period and spatial area were also analyzed using the same analytical framework to compare changes in larval and adult distributions between the two decades. Changes in spatial distribution of larvae occurred for 43% of taxa, with shifts predominately northward (i.e., along-shelf). Timing of larval occurrence shifted for 49% of the larval taxa, with shifts evenly split between occurring earlier and later in the season. Where both larvae and adults of the same species were analyzed, 48% exhibited different shifts between larval and adult stages. Overall, these results demonstrate that larval fish distributions are changing in the ecosystem. The spatial changes are largely consistent with expectations from a changing climate. The temporal changes are more complex, indicating we need a better understanding of reproductive timing of fishes in the ecosystem. These changes may impact population productivity through changes in life history connectivity and recruitment, and add to the accumulating evidence for changes in the Northeast U.S. Shelf Ecosystem with potential to impact fisheries and other ecosystem services.
2015-01-01
Many studies have documented long-term changes in adult marine fish distributions and linked these changes to climate change and multi-decadal climate variability. Most marine fish, however, have complex life histories with morphologically distinct stages, which use different habitats. Shifts in distribution of one stage may affect the connectivity between life stages and thereby impact population processes including spawning and recruitment. Specifically, many marine fish species have a planktonic larval stage, which lasts from weeks to months. We compared the spatial distribution and seasonal occurrence of larval fish in the Northeast U.S. Shelf Ecosystem to test whether spatial and temporal distributions changed between two decades. Two large-scale ichthyoplankton programs sampled using similar methods and spatial domain each decade. Adult distributions from a long-term bottom trawl survey over the same time period and spatial area were also analyzed using the same analytical framework to compare changes in larval and adult distributions between the two decades. Changes in spatial distribution of larvae occurred for 43% of taxa, with shifts predominately northward (i.e., along-shelf). Timing of larval occurrence shifted for 49% of the larval taxa, with shifts evenly split between occurring earlier and later in the season. Where both larvae and adults of the same species were analyzed, 48% exhibited different shifts between larval and adult stages. Overall, these results demonstrate that larval fish distributions are changing in the ecosystem. The spatial changes are largely consistent with expectations from a changing climate. The temporal changes are more complex, indicating we need a better understanding of reproductive timing of fishes in the ecosystem. These changes may impact population productivity through changes in life history connectivity and recruitment, and add to the accumulating evidence for changes in the Northeast U.S. Shelf Ecosystem with potential to impact fisheries and other ecosystem services. PMID:26398900
Casalegno, Stefano; Bennie, Jonathan J; Inger, Richard; Gaston, Kevin J
2014-01-01
Although the importance of addressing ecosystem service benefits in regional land use planning and decision-making is evident, substantial practical challenges remain. In particular, methods to identify priority areas for the provision of key ecosystem services and other environmental services (benefits from the environment not directly linked to the function of ecosystems) need to be developed. Priority areas are locations which provide disproportionally high benefits from one or more service. Here we map a set of ecosystem and environmental services and delineate priority areas according to different scenarios. Each scenario is produced by a set of weightings allocated to different services and corresponds to different landscape management strategies which decision makers could undertake. Using the county of Cornwall, U.K., as a case study, we processed gridded maps of key ecosystem services and environmental services, including renewable energy production and urban development. We explored their spatial distribution patterns and their spatial covariance and spatial stationarity within the region. Finally we applied a complementarity-based priority ranking algorithm (zonation) using different weighting schemes. Our conclusions are that (i) there are two main patterns of service distribution in this region, clustered services (including agriculture, carbon stocks, urban development and plant production) and dispersed services (including cultural services, energy production and floods mitigation); (ii) more than half of the services are spatially correlated and there is high non-stationarity in the spatial covariance between services; and (iii) it is important to consider both ecosystem services and other environmental services in identifying priority areas. Different weighting schemes provoke drastic changes in the delineation of priority areas and therefore decision making processes need to carefully consider the relative values attributed to different services.
Casalegno, Stefano; Bennie, Jonathan J.; Inger, Richard; Gaston, Kevin J.
2014-01-01
Although the importance of addressing ecosystem service benefits in regional land use planning and decision-making is evident, substantial practical challenges remain. In particular, methods to identify priority areas for the provision of key ecosystem services and other environmental services (benefits from the environment not directly linked to the function of ecosystems) need to be developed. Priority areas are locations which provide disproportionally high benefits from one or more service. Here we map a set of ecosystem and environmental services and delineate priority areas according to different scenarios. Each scenario is produced by a set of weightings allocated to different services and corresponds to different landscape management strategies which decision makers could undertake. Using the county of Cornwall, U.K., as a case study, we processed gridded maps of key ecosystem services and environmental services, including renewable energy production and urban development. We explored their spatial distribution patterns and their spatial covariance and spatial stationarity within the region. Finally we applied a complementarity-based priority ranking algorithm (zonation) using different weighting schemes. Our conclusions are that (i) there are two main patterns of service distribution in this region, clustered services (including agriculture, carbon stocks, urban development and plant production) and dispersed services (including cultural services, energy production and floods mitigation); (ii) more than half of the services are spatially correlated and there is high non-stationarity in the spatial covariance between services; and (iii) it is important to consider both ecosystem services and other environmental services in identifying priority areas. Different weighting schemes provoke drastic changes in the delineation of priority areas and therefore decision making processes need to carefully consider the relative values attributed to different services. PMID:25250775
NASA Astrophysics Data System (ADS)
Tableau, A.; Brind'Amour, A.; Woillez, M.; Le Bris, H.
2016-05-01
Soft sediments in coastal shallow waters constitute nursery habitats for juveniles of several flatfishes. The quality of a nursery is defined by its capacity to optimize the growth and the survival of juvenile fish. The influence of biotic factors, such as food availability, is poorly studied at the scale of a nursery ground. Whether food availability limits juvenile survival is still uncertain. A spatial approach is used to understand the influence of food availability on the distribution of juvenile fish of various benthic and demersal species in the Bay of Vilaine (France), a productive nursery ground. We quantified the spatial overlap between benthic macro-invertebrates and their predators (juvenile fish) to assess if the latter were spatially covering the most productive areas of the Bay. Three scenarios describing the shapes of the predator-prey spatial relationship were tested to quantify the strength of the relationship and consequently the importance of food availability in determining fish distribution. Our results underline that both food availability and fish densities vary greatly over the nursery ground. When considering small organisational levels (e.g., a single fish species), the predator-prey spatial relationship was not clear, likely because of additional environmental effects not identified here; but at larger organisational level (the whole juvenile fish community), a strong overlap between the fish predators and their prey was identified. The evidence that fish concentrate in sectors with high food availability suggests that either food is the limiting factor in that nursery or/and fish display behavioural responses by optimising their energetic expenditures associated with foraging. Further investigations are needed to test the two hypotheses and to assess the impact of benthic and demersal juvenile fish in the food web of coastal nurseries.
Ghosal, Sutapa; Wagner, Jeff
2013-07-07
We present correlated application of two micro-analytical techniques: scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDS) and Raman micro-spectroscopy (RMS) for the non-invasive characterization and molecular identification of flame retardants (FRs) in environmental dusts and consumer products. The SEM/EDS-RMS technique offers correlated, morphological, molecular, spatial distribution and semi-quantitative elemental concentration information at the individual particle level with micrometer spatial resolution and minimal sample preparation. The presented methodology uses SEM/EDS analyses for rapid detection of particles containing FR specific elements as potential indicators of FR presence in a sample followed by correlated RMS analyses of the same particles for characterization of the FR sub-regions and surrounding matrices. The spatially resolved characterization enabled by this approach provides insights into the distributional heterogeneity as well as potential transfer and exposure mechanisms for FRs in the environment that is typically not available through traditional FR analysis. We have used this methodology to reveal a heterogeneous distribution of highly concentrated deca-BDE particles in environmental dust, sometimes in association with identifiable consumer materials. The observed coexistence of deca-BDE with consumer material in dust is strongly indicative of its release into the environment via weathering/abrasion of consumer products. Ingestion of such enriched FR particles in dust represents a potential for instantaneous exposure to high FR concentrations. Therefore, correlated SEM/RMS analysis offers a novel investigative tool for addressing an area of important environmental concern.
Habitat-based frameworks have been proposed for developing Ecological Production Functions (EPFs) to describe the spatial distribution of ecosystem services. As proof of concept, we generated EPFs that compared bird use patterns among intertidal benthic habitats for Yaquina estu...
NASA Astrophysics Data System (ADS)
de Lavenne, Alban; Thirel, Guillaume; Andréassian, Vazken; Perrin, Charles; Ramos, Maria-Helena
2016-04-01
Semi-distributed hydrological models aim to provide useful information to understand and manage the spatial distribution of water resources. However, their evaluation is often limited to independent and single evaluations at each sub-catchment within larger catchments. This enables to qualify model performance at different points, but does not provide a coherent assessment of the overall spatial consistency of the model. To cope with these methodological deficiencies, we propose a two-step strategy. First, we apply a sequential spatial calibration procedure to define spatially consistent model parameters. Secondly, we evaluate the hydrological simulations using variables that involve some dependency between sub-catchments to evaluate the overall coherence of model outputs. In this study, we particularly choose to look at the simulated Intercatchment Groundwater Flows (IGF). The idea is that the water that is lost in one place should be recovered somewhere else within the catchment to guarantee a spatially coherent water balance in time. The model used is a recently developed daily semi-distributed model, which is based on a spatial distribution of the lumped GR5J model. The model has five parameters for each sub-catchments and a streamflow velocity parameter for flow routing between them. It implements two reservoirs, one for production and one for routing, and estimates IGF according to the level of the second in a way that catchment can release water to IGF during high flows and receive water through IGF during low flows. The calibration of the model is performed from upstream to downstream, making an efficient use of spatially distributed streamflow measurements. To take model uncertainty into account, we implemented three variants of the original model structure, each one computing in a different way the IGF in each sub-catchment. The study is applied on over 1000 catchments in France. By exploring a wide area and a variability of hydrometeorological conditions, we aim to detect IGF even between catchments which can be quite distant from one another.
NASA Astrophysics Data System (ADS)
Schmitt, R. J. P.; Bizzi, S.; Kondolf, G. M.; Rubin, Z.; Castelletti, A.
2016-12-01
Field and laboratory evidence indicates that the spatial distribution of transport in both alluvial and bedrock rivers is an adaptation to sediment supply. Sediment supply, in turn, depends on spatial distribution and properties (e.g., grain sizes and supply rates) of individual sediment sources. Analyzing the distribution of transport capacity in a river network could hence clarify the spatial distribution and properties of sediment sources. Yet, challenges include a) identifying magnitude and spatial distribution of transport capacity for each of multiple grain sizes being simultaneously transported, and b) estimating source grain sizes and supply rates, both at network scales. Herein, we approach the problem of identifying the spatial distribution of sediment sources and the resulting network sediment fluxes in a major, poorly monitored tributary (80,000 km2) of the Mekong. Therefore, we apply the CASCADE modeling framework (Schmitt et al. (2016)). CASCADE calculates transport capacities and sediment fluxes for multiple grainsizes on the network scale based on remotely-sensed morphology and modelled hydrology. CASCADE is run in an inverse Monte Carlo approach for 7500 random initializations of source grain sizes. In all runs, supply of each source is inferred from the minimum downstream transport capacity for the source grain size. Results for each realization are compared to sparse available sedimentary records. Only 1 % of initializations reproduced the sedimentary record. Results for these realizations revealed a spatial pattern in source supply rates, grain sizes, and network sediment fluxes that correlated well with map-derived patterns in lithology and river-morphology. Hence, we propose that observable river hydro-morphology contains information on upstream source properties that can be back-calculated using an inverse modeling approach. Such an approach could be coupled to more detailed models of hillslope processes in future to derive integrated models of hillslope production and fluvial transport processes, which is particularly useful to identify sediment provenance in poorly monitored river basins.
Snow Cover Distribution and Variation using MODIS in the Himalayas of India
NASA Astrophysics Data System (ADS)
Mondal, A.; Lakshmi, V.; Jain, S. K.; Kansara, P. H.
2017-12-01
Snow cover variation plays a big role in river discharge, permafrost distribution and mass balance of glaciers in mountainous watersheds. Spatial distribution and temporal variation of snow cover varies with elevation and climate. We study the spatial distribution and temporal change of snow cover that has been observed using Terra Moderate Resolution Imaging Spectrometer (MODIS) product (MOD10A2 version 5) from 2001 to 2016. This MODIS product is based on normalized-difference snow index (NDSI) using band 4 (0.545-0.565 μm) and band 6 (1.628-1.652 μm). The spatial resolution of MOD10A2 is 500 m and composited over 8 days. The study area is the Indian Himalayas, major snow covered part of which is located in the states of Jammu and Kashmir, Himachal Pradesh, Uttarakhand, West Bengal, Sikkim, Assam and Arunachal Pradesh. Distribution and variation in snow cover is examined on monthly and annual time scales in this study. The temporal changes in snow cover has been compared with terrain attributes (elevation, slope and aspect). The snow cover depletion and accumulation have been observed during April-August and September-March. The snow cover is highest in the March and lowest in the August in the Himachal region. This study will be helpful to identify the amount of water stored in the glaciers of the Indian Himalaya and also important for water resources management of river basins, which are located in this area. Key words: Snow cover, MODIS, NDSI, terrain attribute
Niu, Shan Dong; Lyu, Xiao; Shi, Yang Yang
2018-02-01
Under the theoretical framework of sustainable intensification of agricultural land-use (SIALU), We used material flow analysis (MFA) method to establish evaluation index system for SIALU by utilizing data in 2000, 2005, 2010 and 2015 to quantify the level of SIALU of 17 cities in Shandong Province, and analyzed the variation in input-output of resources factors of agricultural land, spatial distribution of resource productivity and environmental economic efficiency, in order to reveal spatial-temporal differentiation of SIALU. Results showed that the direct material input to agricultural lands decreased, whereas hidden flow, stock and pollutant emissions increased gradually from 2000 to 2015. The material productivity of all cities in the province showed that the coastal areas in the peninsula were relatively lower than the southern region, and the level of material productivity in the northwest region was relatively higher. Environmental economic efficiency was gradually enhanced, and the western region was relatively higher than coastal area of the peninsula. During the period examined here, the spatial pattern of SIALU of various cities showed clustered distribution change, with the western region tending to gradually increase and the eastern region tending to gradually reduce. The dynamics of SIALU among different regions were divided into six grades: Northwestern Shandong > Northern Shandong > Southwestern Shandong > Southern Shandong > Central Shandong > Coastal areas of Shandong Peninsula.
SEASONAL PATTERNS OF FINE ROOT PRODUCTION AND TURNOVER IN PONDEROSA PINE STANDS OF DIFFERENT AGES
Root minirhizotron tubes were installed in two ponderosa pine (Pinus ponderosa Laws.) stands around three different tree age classes (16, 45, and > 250 yr old) to examine root spatial distribution in relation to canopy size and tree distribution, and to determine if rates of fine...
NASA Astrophysics Data System (ADS)
Asrar, G.; Wolf, J.; Rafique, R.; West, T. O.; Ogle, S. M.
2016-12-01
Rangelands play an important role in providing ecosystem services such as food, forage, and fuels in many parts of the world. The net primary productivity (NPP), a difference between CO2 fixed by plants and CO2 lost to autotrophic respiration, is a good indicator of the productivity of rangeland ecosystems, and their contribution to the cycling of carbon in the Earth system. In this study, we estimated the NPP of global rangelands, the consumption thereof by grazing livestock, and associated uncertainties, to better understand and quantify the contribution of rangelands to land-based carbon storage. We estimated rangeland NPP using mean annual precipitation data from Climate Research Unit (CRU), and a regression model based on global observations (Del Grosso et al., 2008). Spatial distributions of annual livestock consumption of rangeland NPP (Wolf et al., 2015) were combined with gridded annual rangeland NPP for the years 2000 - 2011. The uncertainty analysis of these estimates was conducted using a Monte Carlo approach. The rangeland NPP estimates with associated uncertainties were also compared with the total modeled GPP estimates obtained from vegetation dynamic model simulations. Our results showed that mean above-ground NPP of rangelands is 1017.5 MgC/km2, while mean below-ground NPP is 847.6 MgC/km2. The total rangeland NPP represents a significant portion of the total NPP of the terrestrial ecosystem. The livestock area requirements used to geographically distribute livestock spatially are based on optimal pasturage and are low relative to area requirements on less productive land. Even so, ca. 90% of annual livestock consumption of rangeland NPP were met with no adjustment of livestock distributions. Moreover, the results of this study allowed us to explicitly quantify the temporal and spatial variations of rangeland NPP under different climatic conditions. Uncertainty analysis was helpful in identifying the strength and weakness of the methods used to estimate rangeland NPP. Overall, the results from this study are useful in quantifying the contribution of rangelands to the carbon cycle and for providing geospatially distributed carbon fluxes associated with the production and consumption of rangeland biomass.
Estimating the spatial distribution of artificial groundwater recharge using multiple tracers.
Moeck, Christian; Radny, Dirk; Auckenthaler, Adrian; Berg, Michael; Hollender, Juliane; Schirmer, Mario
2017-10-01
Stable isotopes of water, organic micropollutants and hydrochemistry data are powerful tools for identifying different water types in areas where knowledge of the spatial distribution of different groundwater is critical for water resource management. An important question is how the assessments change if only one or a subset of these tracers is used. In this study, we estimate spatial artificial infiltration along an infiltration system with stage-discharge relationships and classify different water types based on the mentioned hydrochemistry data for a drinking water production area in Switzerland. Managed aquifer recharge via surface water that feeds into the aquifer creates a hydraulic barrier between contaminated groundwater and drinking water wells. We systematically compare the information from the aforementioned tracers and illustrate differences in distribution and mixing ratios. Despite uncertainties in the mixing ratios, we found that the overall spatial distribution of artificial infiltration is very similar for all the tracers. The highest infiltration occurred in the eastern part of the infiltration system, whereas infiltration in the western part was the lowest. More balanced infiltration within the infiltration system could cause the elevated groundwater mound to be distributed more evenly, preventing the natural inflow of contaminated groundwater. Dedicated to Professor Peter Fritz on the occasion of his 80th birthday.
NASA Astrophysics Data System (ADS)
Lee, Dasom; An, Yong Rock; Park, Kyum Joon; Kim, Hyun Woo; Lee, Dabin; Joo, Hui Tae; Oh, Young Geun; Kim, Su Min; Kang, Chang Keun; Lee, Sang Heon
2017-09-01
The minke whale (Balaenoptera acutorostrata) is the most common baleen whale among several marine mammal species observed in Korea. Since a high concentrated condition of prey to whales can be obtained by physical structures, the foraging whale distribution can be an indicator of biological hotspot. Our main objective is verifying the coastal upwelling-southwestern East Sea as a productive biological hotspot based on the geographical distribution of minke whales. Among the cetacean research surveys of the National Institute of Fisheries Science since 1999, 9 years data for the minke whales available in the East Sea were used for this study. The regional primary productivity derived from Moderate-Resolution Imaging Spectroradiometer (MODIS) was used for a proxy of biological productivity. Minke whales observed during the sighting surveys were mostly concentrated in May and found mostly (approximately 70%) in the southwestern coastal areas (< 300 m) where high chlorophyll concentrations and primary productivity were generally detected. Based on MODIS-derived primary productivity algorithm, the annual primary production (320 g C m-2 y-1) estimated in the southwestern coastal region of the East Sea belongs to the highly productive coastal upwelling regions in the world. A change in the main spatial distribution of minke whales was found in recent years, which indicate that the major habitats of mink whales have been shifted into the north of the common coastal upwelling regions. This is consistent with the recently reported unprecedented coastal upwelling in the mid-eastern coast of Korea. Based on high phytoplankton productivity and high distribution of minke whales, the southwestern coastal regions can be considered as one of biological hotspots in the East Sea. These regions are important for ecosystem dynamics and the population biology of top marine predators, especially migratory whales and needed to be carefully managed from a resource management perspective.
Spatial Variation in Mobility-Lifetime Product in Bulk TlBr and CZT
NASA Astrophysics Data System (ADS)
Phillips, David; Haegel, Nancy; Blaine, Kevin; Kim, Hadong; Ciampi, Guido; Cirignano, Len
2012-02-01
The energy resolution of a semiconductor radiation detector depends on the charge transport properties of the semiconductor, and the mobility-lifetime (μτ) product is a key figure of merit for charge transport. In this work, we investigate the effects of two impurities, Na and Cu, on the μτ product in bulk thallium bromide (TlBr) using cathodoluminescence (CL) and transport imaging. Transport imaging uses a scanning electron microscope to generate a line of charge carriers on the surface of a bulk sample, and the intensity and spatial distribution of the recombination luminescence are recorded. A Green's function approach is used to model the generation, diffusion, and recombination of charge carriers under steady-state conditions. The luminescence distribution is fit to the model to extract the ambipolar diffusion length and the μτ product, providing a high-resolution correlation between the luminescence variations due to dopants/defects and the quantitative transport behavior. The μτ product has been mapped across a 40 μm segment of TlBr at a resolution of 2 μm. Additionally, this approach has been used to locally map variations in ambipolar diffusion length and μτ product due to extended defects in cadmium zinc telluride (CZT).
Wei, Yan-Li; Bao, Lian-Jun; Wu, Chen-Chou; Zeng, Eddy Y
2016-08-01
Anthropogenic impacts have continuously intensified in mega urban centers with increasing urbanization and growing population. The spatial distribution pattern of such impacts can be assessed with soil halogenated flame retardants (HFRs) as HFRs are mostly derived from the production and use of various consumer products. In the present study, soil samples were collected from the Pearl River Delta (PRD), a large urbanized region in southern China, and its surrounding areas and analyzed for a group of HFRs, i.e., polybrominated diphenyl ethers (PBDEs), decabromodiphenyl ethane, bis(hexachlorocyclopentadieno)cyclooctane (DP) and hexabromobenzene. The sum concentrations of HFRs and PBDEs were in the ranges of 0.66-6500 and 0.37-5700 (mean: 290 and 250) ng g(-1) dry weight, respectively, around the middle level of the global range. BDE-209 was the predominant compound likely due to the huge amounts of usage and its persistence. The concentrations of HFRs were greater in the land-use types of residency, industry and landfill than in agriculture, forestry and drinking water source, and were also greater in the central PRD than in its surrounding areas. The concentrations of HFRs were moderately significantly (r(2) = 0.32-0.57; p < 0.05) correlated with urbanization levels, population densities and gross domestic productions in fifteen administrative districts. The spatial distribution of DP isomers appeared to be stereoselective as indicated by the similarity in the spatial patterns for the ratio of anti-DP versus the sum of DP isomers (fanti-DP) and DP concentrations. Finally, the concentrations of HFRs sharply decreased with increasing distance from an e-waste recycling site, indicating that e-waste derived HFRs largely remained in local soil. Copyright © 2016 Elsevier Ltd. All rights reserved.
Andres, R. J. [Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S.; Boden, T. A. [Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S.; Marland, G. [Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S.
2012-01-01
The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2008.html) and references therein. The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signature (del 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, Thomas A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marlad, Greg [Appalachian State University, Boone, NC (USA)
2012-01-01
The annual, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1751-2009 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2012) and references therein. The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.
2015-01-01
The basic data provided in these data files are derived from time series of Global, Regional, and National Fossil-Fuel CO2 Emissions (http://cdiac.ess-dive.lbl.gov/trends/emis/overview_2011.html), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signature (del 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
NASA Astrophysics Data System (ADS)
Washington-Allen, R. A.; Therrell, M. D.; Emanuel, R. E.
2007-12-01
Herbivory, fire, and climatic events such as El Niño-Southern Oscillation (ENSO) and La Niña have been shown to have proximal and evolutionary effects on the dynamics of Dryland fauna, flora, and soils. However, spatially-explicit historical impacts of these climatic events on Dryland ecosystems is not known. Consequently, this paper has the purpose of presenting the theory and practical application for estimating the historical spatial impacts of these climatic events. We hypothesize that if remotely-sensed vegetation indices (VI) are correlated to historical tree ring data and also to functional ecosystem processes, specifically gross primary productivity (GPP) and net ecosystem production (NEP) as measured by eddy covariance flux towers, then VIs can be used to spatially and temporally distribute GPP and NEP within the species- or community-specific land cover extent over the length of the tree ring record of selected Dryland ecosystems. Secondly, the Shuttle Radar Topography Mission (SRTM) digital terrain model (DTM) data has been used to estimate tree height and in conjuction with plant allometric equations: biomass and standing carbon in various forest ecosystems. Tree height data in relation to tree ring age data and fire history can be used to reconstruct the spatial distribution of savanna demographic age structure, predict standing carbon and thus provide a complementary and independent dataset for comparison to DTMs from Multiangle Imaging Spectroradiometer (MISR), Interferometric Synthetic Aperture Radar (IFSAR), and Moderate Resolution Imaging Spectroradiometer (MODIS) derived GPP spatial maps. We developed a database consisting of a dendrochronology record, SRTM data, globa fre history data, Long term Data Record Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (LTDR AVHRR NDVI, 1981 - 2003), contemporary gridded climate data, National Land Cover Data (NLCD), and short term eddy covariance flux tower data for the California Blue Oak woodland ecosystem to estimate both regional aboveground productivity and past disturbance history relative climate, particularly droughts, for the last 500 years.
Begg, Graham S; Elliott, Martin J; Cullen, Danny W; Iannetta, Pietro P M; Squire, Geoff R
2008-10-01
The implementation of co-existence in the commercialisation of GM crops requires GM and non-GM products to be segregated in production and supply. However, maintaining segregation in oilseed rape will be made difficult by the highly persistent nature of this species. An understanding of its population dynamics is needed to predict persistence and develop potential strategies for control, while to ensure segregation is being achieved, the production of GM oilseed rape must be accompanied by the monitoring of GM levels in crop or seed populations. Heterogeneity in the spatial distribution of oilseed rape has the potential to affect both control and monitoring and, although a universal phenomenon in arable weeds and harvested seed lots, spatial heterogeneity in oilseed rape populations remains to be demonstrated and quantified. Here we investigate the distribution of crop and volunteer populations in a commercial field before and during the cultivation of the first conventional oilseed rape (winter) crop since the cultivation of a GM glufosinate-tolerant oilseed rape crop (spring) three years previously. GM presence was detected by ELISA for the PAT protein in each of three morphologically distinguishable phenotypes: autumn germinating crop-type plants (3% GM), autumn-germinating 'regrowths' (72% GM) and spring germinating 'small-type' plants (17% GM). Statistical models (Poisson log-normal and binomial logit-normal) were used to describe the spatial distribution of these populations at multiple spatial scales in the field and of GM presence in the harvested seed lot. Heterogeneity was a consistent feature in the distribution of GM and conventional oilseed rape. Large trends across the field (50 x 400 m) and seed lot (4 x 1.5 x 1.5 m) were observed in addition to small-scale heterogeneity, less than 20 m in the field and 20 cm in the seed lot. The heterogeneity was greater for the 'regrowth' and 'small' phenotypes, which were likely to be volunteers and included most of the GM plants detected, than for the largely non-GM 'crop' phenotype. The implications of the volunteer heterogeneity for field management and GM-sampling are discussed.
Monthly AOD maps combining strengths of remote sensing products
NASA Astrophysics Data System (ADS)
Kinne, Stefan
2010-05-01
The mid-visible aerosol optical depth (AOD) is the most prominent property to quantify aerosol amount the atmospheric column. Almost all aerosol retrievals of satellite sensors provide estimates for this property, however, often with limited success. As sensors differ in capabilities individual retrievals have local and regional strengths and weaknesses. Focusing on individual retrieval strengths a satellite based AOD composite has been constructed. Hereby, every retrieval performance has been assessed in statistical comparisons to ground-based sun-photometry, which provide highly accurate references though only at few globally distributed monitoring sites. Based on these comparisons, which consider bias as well as spatial patterns and seasonality, the regionally best performing satellite AOD products are combined. The resulting remote sensing AOD composite provide a general reference for the spatial and temporal AOD distribution on an (almost) global basis - solely tied to sensor data.
NASA Astrophysics Data System (ADS)
Easdale, M. H.; Bruzzone, O.
2018-03-01
Volcanic ash fallout is a recurrent environmental disturbance in forests, arid and semi-arid rangelands of Patagonia, South America. The ash deposits over large areas are responsible for several impacts on ecological processes, agricultural production and health of local communities. Public policy decision making needs monitoring information of the affected areas by ash fallout, in order to better orient social, economic and productive aids. The aim of this study was to analyze the spatial distribution of volcanic ash deposits from the eruption of Puyehue-Cordón Caulle in 2011, by identifying a sudden change in the Normalized Difference Vegetation Index (NDVI) temporal dynamics, defined as a perturbation located in the time series. We applied a sparse-wavelet transform using the Basis Pursuit algorithm to NDVI time series obtained from the Moderate Resolution Image Spectroradiometer (MODIS) sensor, to identify perturbations at a pixel level. The spatial distribution of the perturbation promoted by ash deposits in Patagonia was successfully identified and characterized by means of a perturbation in NDVI temporal dynamics. Results are encouraging for the future development of a new platform, in combination with data from forecasting models and tracking of ash cloud trajectories and dispersion, to inform stakeholders to mitigate impact of volcanic ash on agricultural production and to orient public intervention strategies after a volcanic eruption followed by ash fallout over a wide region.
NASA Astrophysics Data System (ADS)
Fung, Jonathan Winston
Carbon dioxide is taken up by crops during production and released back to the atmosphere at different geographical locations through respiration of consumed crop commodities. In this study, spatially distributed county-level US cropland net primary productivity, harvested biomass, changes in soil carbon, and human and livestock consumption data were integrated into the prior terrestrial biosphere flux generated by the Boreal Ecosystem Productivity Simulator (BEPS). A global time-dependent Bayesian synthesis inversion with a nested focus on North America was carried out based on CO2 observations at 210 stations. Overall, the inverted annual North American CO2 sink weakened by 6.5% over the period from 2002 to 2007 compared to simulations disregarding US crop statistical data. The US Midwest is found to be the major sink of 0.36±0.13 PgC yr-1 whereas the large sink in the US Southeast forests weakened to 0.16±0.12 PgC yr-1 partly due to local CO2 sources from crop consumption.
2014-01-01
Background Tick-borne diseases (TBDs) present a major economic burden to communities across East Africa. Farmers in East Africa must use acaracides to target ticks and prevent transmission of tick-borne diseases such as anaplasmosis, babesiosis, cowdriosis and theileriosis; the major causes of cattle mortality and morbidity. The costs of controlling East Coast Fever (ECF), caused by Theileria parva, in Uganda are significant and measures taken to control ticks, to be cost-effective, should take into account the burden of disease. The aim of the present work was to estimate the burden presented by T. parva and its spatial distribution in a crop-livestock production system in Eastern Uganda. Methods A cross sectional study was carried out to determine the prevalence and spatial distribution of T. parva in Tororo District, Uganda. Blood samples were taken from all cattle (n: 2,658) in 22 randomly selected villages across Tororo District from September to December 2011. Samples were analysed by PCR and T. parva prevalence and spatial distribution determined. Results The overall prevalence of T. parva was found to be 5.3%. Herd level prevalence ranged from 0% to 21% with majority of the infections located in the North, North-Eastern and South-Eastern parts of Tororo District. No statistically significant differences in risk of infection were found between age classes, sex and cattle breed. Conclusions T. parva infection is widely distributed in Tororo District, Uganda. The prevalence and distribution of T. parva is most likely determined by spatial distribution of R. appendiculatus, restricted grazing of calves and preferential tick control targeting draft animals. PMID:24589227
Jacob, Benjamin G; Griffith, Daniel A; Muturi, Ephantus J; Caamano, Erick X; Githure, John I; Novak, Robert J
2009-01-01
Background Autoregressive regression coefficients for Anopheles arabiensis aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes it difficult to identify where there are clusters of An. arabiensis aquatic habitats of acceptable prediction. It is therefore useful to conduct some form of spatial error analysis to detect clusters of An. arabiensis aquatic habitats based on uncertainty residuals from individual sampled habitats. In this research, a method of error estimation for spatial simulation models was demonstrated using autocorrelation indices and eigenfunction spatial filters to distinguish among the effects of parameter uncertainty on a stochastic simulation of ecological sampled Anopheles aquatic habitat covariates. A test for diagnostic checking error residuals in an An. arabiensis aquatic habitat model may enable intervention efforts targeting productive habitats clusters, based on larval/pupal productivity, by using the asymptotic distribution of parameter estimates from a residual autocovariance matrix. The models considered in this research extends a normal regression analysis previously considered in the literature. Methods Field and remote-sampled data were collected during July 2006 to December 2007 in Karima rice-village complex in Mwea, Kenya. SAS 9.1.4® was used to explore univariate statistics, correlations, distributions, and to generate global autocorrelation statistics from the ecological sampled datasets. A local autocorrelation index was also generated using spatial covariance parameters (i.e., Moran's Indices) in a SAS/GIS® database. The Moran's statistic was decomposed into orthogonal and uncorrelated synthetic map pattern components using a Poisson model with a gamma-distributed mean (i.e. negative binomial regression). The eigenfunction values from the spatial configuration matrices were then used to define expectations for prior distributions using a Markov chain Monte Carlo (MCMC) algorithm. A set of posterior means were defined in WinBUGS 1.4.3®. After the model had converged, samples from the conditional distributions were used to summarize the posterior distribution of the parameters. Thereafter, a spatial residual trend analyses was used to evaluate variance uncertainty propagation in the model using an autocovariance error matrix. Results By specifying coefficient estimates in a Bayesian framework, the covariate number of tillers was found to be a significant predictor, positively associated with An. arabiensis aquatic habitats. The spatial filter models accounted for approximately 19% redundant locational information in the ecological sampled An. arabiensis aquatic habitat data. In the residual error estimation model there was significant positive autocorrelation (i.e., clustering of habitats in geographic space) based on log-transformed larval/pupal data and the sampled covariate depth of habitat. Conclusion An autocorrelation error covariance matrix and a spatial filter analyses can prioritize mosquito control strategies by providing a computationally attractive and feasible description of variance uncertainty estimates for correctly identifying clusters of prolific An. arabiensis aquatic habitats based on larval/pupal productivity. PMID:19772590
Using soil residence time to delineate spatial and temporal patterns of transient landscape response
NASA Astrophysics Data System (ADS)
Almond, Peter; Roering, Josh; Hales, T. C.
2007-09-01
On hillslopes the balance between soil transport and production determines local soil thickness and the age distribution of particles that comprise the soil (where age refers to the time elapsed since detachment from bedrock). The mean of this age distribution is defined as the residence time, and in a landscape with time-invariant topography (i.e., morphologic steady state), the spatial uniformity of soil production ensures that the residence time of soils is spatially invariant. Thus, given constant soil-forming factors, spatial variation of soil properties reflects differences in residence time driven by nonuniform soil production. Spatially extensive soil databases, which are often freely available in electronic form, provide a cheap and accessible means of analyzing patterns of soil residence time and quantifying landscape dynamics. Here we use a soil chronosequence to calibrate a chronofunction describing the reddening of soils in the Oregon Coast Range, which is then used to quantify the spatial distribution of soil residence time. In contrast to the popular conception that the Oregon Coast Range experiences uniform erosion, we observe systematic variations in soil residence time driven by stream capture, deep-seated landsliding, and lateral channel migration. Large, contiguous areas with short residence time soils (hue 10YR) occur west of the Siuslaw River-Long Tom Creek drainage divide, whereas soil patches with redder hues of 7.5YR or 5YR indicate longer residence times and transient landscape conditions. These zones of red soils (5YR) occur east of the Siuslaw-Long Tom divide, coinciding with low-gradient ridge and valley topography and deeply alluviated valleys resulting from drainage reversal in the Quaternary. Patches of red soils are also associated with deep-seated landslides at various locations in our study area. Our calculated soil residence times appear subject to overestimation resulting from limitations of the simple weathering index used here and chronofunction calibration uncertainties. Nonetheless, our soil residence time estimates appear accurate to within an order of magnitude and provide a useful constraint on landscape dynamics over geomorphic timescales.
Zhang, Yueqing; Li, Qifeng; Lu, Yonglong; Jones, Kevin; Sweetman, Andrew J
2016-04-01
Hexabromocyclododecane (HBCDD) is a brominated flame retardant with a wide range of industrial applications, although little is known about its patterns of spatial distribution in soils in relation to industrial emissions. This study has undertaken a large-scale investigation around an industrialized coastal area of China, exploring the concentrations, spatial distribution and diastereoisomer profiles of HBCDD in 188 surface soils from 21 coastal cities in North China. The detection frequency was 100% and concentrations of total HBCDD in the surface soils ranged from 0.123 to 363 ng g(-1) and averaged 7.20 ng g(-1), showing its ubiquitous existence at low levels. The spatial distribution of HBCDD exhibited a correlation with the location of known manufacturing facilities in Weifang, suggesting the production of HBCDD as major emission source. Diastereoisomer profiles varied in different cities. Diastereoisomer compositions in soils were compared with emissions from HBCDD industrial activities, and correlations were found between them, which has the potential for source identification. Although the contemporary concentrations of HBCDD in soils from the study were relatively low, HBCDD-containing products (expanded/extruded polystyrene insulation boards) would be a potential source after its service life, and attention needs to be paid to prioritizing large-scale waste management efforts. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Sigler, Michael F.; Napp, Jeffrey M.; Stabeno, Phyllis J.; Heintz, Ronald A.; Lomas, Michael W.; Hunt, George L.
2016-12-01
We synthesize recent research on variation in annual production of copepods (Calanus spp.), euphausiids (Thysanoessa spp.), and juvenile walleye pollock (Gadus chalcogrammus) in the southeastern Bering Sea. We reach five conclusions: 1) the timing of the spring bloom is more important than the amount of annual primary production for the transfer of primary to secondary production (i.e., timing matters); 2) summer and fall, not just spring, matter: organisms must maximize energy intake devoted to somatic growth and storage of lipids and minimize energy expenditures during each season; 3) stored lipids are important for the overwinter survival of both zooplankton and age-0 walleye pollock; 4) variation in ice extent and timing of ice retreat affect the spatial distributions of phytoplankton, zooplankton, and age-0 walleye pollock; when these spatial distributions match in late-ice-retreat years, the annual production of copepods, euphausiids, and juvenile walleye pollock often increases (i.e., location matters); 5) if years with late ice retreat, which favor copepod, euphausiid, and juvenile walleye pollock production, occur in succession, top-down control increases. These conclusions help to explain annual variation in production of copepods, euphausiids and juvenile walleye pollock. Copepods and euphausiids often are more abundant in cold years with late ice retreat than in warm years with early ice retreat due to bloom timing and the availability of ice algae during years with late ice retreat. As a consequence, age-0 walleye pollock consume lipid-enriched prey in cold years, better preparing them for their first winter and their overwinter survival is greater. In addition, there is a spatial match of primary production, zooplankton, and age-0 walleye pollock in cold years and a mismatch in warm years.
Temporal and Spatial Analysis of Monogenetic Volcanic Fields
NASA Astrophysics Data System (ADS)
Kiyosugi, Koji
Achieving an understanding of the nature of monogenetic volcanic fields depends on identification of the spatial and temporal patterns of volcanism in these fields, and their relationships to structures mapped in the shallow crust and inferred in the deep crust and mantle through interpretation of geochemical, radiometric and geophysical data. We investigate the spatial and temporal distributions of volcanism in the Abu Monogenetic Volcano Group, Southwest Japan. E-W elongated volcano distribution, which is identified by a nonparametric kernel method, is found to be consistent with the spatial extent of P-wave velocity anomalies in the lower crust and upper mantle, supporting the idea that the spatial density map of volcanic vents reflects the geometry of a mantle diapir. Estimated basalt supply to the lower crust is constant. This observation and the spatial distribution of volcanic vents suggest stability of magma productivity and essentially constant two-dimensional size of the source mantle diapir. We mapped conduits, dike segments, and sills in the San Rafael sub-volcanic field, Utah, where the shallowest part of a Pliocene magmatic system is exceptionally well exposed. The distribution of conduits matches the major features of dike distribution, including development of clusters and distribution of outliers. The comparison of San Rafael conduit distribution and the distributions of volcanoes in several recently active volcanic fields supports the use of statistical models, such as nonparametric kernel methods, in probabilistic hazard assessment for distributed volcanism. We developed a new recurrence rate calculation method that uses a Monte Carlo procedure to better reflect and understand the impact of uncertainties of radiometric age determinations on uncertainty of recurrence rate estimates for volcanic activity in the Abu, Yucca Mountain Region, and Izu-Tobu volcanic fields. Results suggest that the recurrence rates of volcanic fields can change by more than one order of magnitude on time scales of several hundred thousand to several million years. This suggests that magma generation rate beneath volcanic fields may change over these time scales. Also, recurrence rate varies more than one order of magnitude between these volcanic fields, consistent with the idea that distributed volcanism may be influenced by both the rate of magma generation and the potential for dike interaction during ascent.
Scarpino, Samuel V.; Jansen, Patrick A.; Garzon-Lopez, Carol X.; Winkelhagen, Annemarie J. S.; Bohlman, Stephanie A.; Walsh, Peter D.
2010-01-01
Background The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama. Methodology and Principal Findings Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI. Conclusions and Significance We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI. PMID:21124927
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bernstein, Hans C.; Brislawn, Colin; Renslow, Ryan S.
Productivity is a major determinant of ecosystem diversity. Microbial ecosystems are the most diverse on the planet yet very few relationships between diversity and productivity have been reported as compared to macro-ecological studies. Here we evaluated the spatial relationships of productivity and microbiome diversity in a laboratory-cultivated photosynthetic mat. The goal was to determine how spatial diversification of microorganisms drives localized carbon and energy acquisition rates. We measured sub-millimeter depth profiles of net primary-productivity and gross oxygenic photosynthesis in the context of the localized microenvironment and community structure and observed negative correlations between species richness and productivity within the energy-replete,more » photic zone. Variations between localized community structures were associated with distinct taxa as well as environmental profiles describing a continuum of biological niches. Spatial regions corresponding to high primary productivity and photosynthesis rates had relatively low species richness and high evenness. Hence, this system exhibited negative species-productivity and species–energy relationships. These negative relationships may be indicative of photosynthetically-driven, light-controlled mat ecosystems that are able to be the most productive with a relatively smaller, even distributions of species that specialize within the highly-oxic, photic zones.« less
Hydroclimatic Controls on the Means and Variability of Vegetation Phenology and Carbon Uptake
NASA Technical Reports Server (NTRS)
Koster, Randal Dean; Walker, Gregory K.; Collatz, George J.; Thornton, Peter E.
2013-01-01
Long-term, global offline (land-only) simulations with a dynamic vegetation phenology model are used to examine the control of hydroclimate over vegetation-related quantities. First, with a control simulation, the model is shown to capture successfully (though with some bias) key observed relationships between hydroclimate and the spatial and temporal variations of phenological expression. In subsequent simulations, the model shows that: (i) the global spatial variation of seasonal phenological maxima is controlled mostly by hydroclimate, irrespective of distributions in vegetation type, (ii) the occurrence of high interannual moisture-related phenological variability in grassland areas is determined by hydroclimate rather than by the specific properties of grassland, and (iii) hydroclimatic means and variability have a corresponding impact on the spatial and temporal distributions of gross primary productivity (GPP).
Spatial distribution of arable and abandoned land across former Soviet Union countries
NASA Astrophysics Data System (ADS)
Lesiv, Myroslava; Schepaschenko, Dmitry; Moltchanova, Elena; Bun, Rostyslav; Dürauer, Martina; Prishchepov, Alexander V.; Schierhorn, Florian; Estel, Stephan; Kuemmerle, Tobias; Alcántara, Camilo; Kussul, Natalia; Shchepashchenko, Maria; Kutovaya, Olga; Martynenko, Olga; Karminov, Viktor; Shvidenko, Anatoly; Havlik, Petr; Kraxner, Florian; See, Linda; Fritz, Steffen
2018-04-01
Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others.
Using remote sensing and machine learning for the spatial modelling of a bluetongue virus vector
NASA Astrophysics Data System (ADS)
Van doninck, J.; Peters, J.; De Baets, B.; Ducheyne, E.; Verhoest, N. E. C.
2012-04-01
Bluetongue is a viral vector-borne disease transmitted between hosts, mostly cattle and small ruminants, by some species of Culicoides midges. Within the Mediterranean basin, C. imicola is the main vector of the bluetongue virus. The spatial distribution of this species is limited by a number of environmental factors, including temperature, soil properties and land cover. The identification of zones at risk of bluetongue outbreaks thus requires detailed information on these environmental factors, as well as appropriate epidemiological modelling techniques. We here give an overview of the environmental factors assumed to be constraining the spatial distribution of C. imicola, as identified in different studies. Subsequently, remote sensing products that can be used as proxies for these environmental constraints are presented. Remote sensing data are then used together with species occurrence data from the Spanish Bluetongue National Surveillance Programme to calibrate a supervised learning model, based on Random Forests, to model the probability of occurrence of the C. imicola midge. The model will then be applied for a pixel-based prediction over the Iberian peninsula using remote sensing products for habitat characterization.
Spatial distribution of arable and abandoned land across former Soviet Union countries.
Lesiv, Myroslava; Schepaschenko, Dmitry; Moltchanova, Elena; Bun, Rostyslav; Dürauer, Martina; Prishchepov, Alexander V; Schierhorn, Florian; Estel, Stephan; Kuemmerle, Tobias; Alcántara, Camilo; Kussul, Natalia; Shchepashchenko, Maria; Kutovaya, Olga; Martynenko, Olga; Karminov, Viktor; Shvidenko, Anatoly; Havlik, Petr; Kraxner, Florian; See, Linda; Fritz, Steffen
2018-04-03
Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others.
Spatial distribution of arable and abandoned land across former Soviet Union countries
Lesiv, Myroslava; Schepaschenko, Dmitry; Moltchanova, Elena; Bun, Rostyslav; Dürauer, Martina; Prishchepov, Alexander V.; Schierhorn, Florian; Estel, Stephan; Kuemmerle, Tobias; Alcántara, Camilo; Kussul, Natalia; Shchepashchenko, Maria; Kutovaya, Olga; Martynenko, Olga; Karminov, Viktor; Shvidenko, Anatoly; Havlik, Petr; Kraxner, Florian; See, Linda; Fritz, Steffen
2018-01-01
Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others. PMID:29611843
Mapping Agricultural Fields in Sub-Saharan Africa with a Computer Vision Approach
NASA Astrophysics Data System (ADS)
Debats, S. R.; Luo, D.; Estes, L. D.; Fuchs, T.; Caylor, K. K.
2014-12-01
Sub-Saharan Africa is an important focus for food security research, because it is experiencing unprecedented population growth, agricultural activities are largely dominated by smallholder production, and the region is already home to 25% of the world's undernourished. One of the greatest challenges to monitoring and improving food security in this region is obtaining an accurate accounting of the spatial distribution of agriculture. Households are the primary units of agricultural production in smallholder communities and typically rely on small fields of less than 2 hectares. Field sizes are directly related to household crop productivity, management choices, and adoption of new technologies. As population and agriculture expand, it becomes increasingly important to understand both the distribution of field sizes as well as how agricultural communities are spatially embedded in the landscape. In addition, household surveys, a common tool for tracking agricultural productivity in Sub-Saharan Africa, would greatly benefit from spatially explicit accounting of fields. Current gridded land cover data sets do not provide information on individual agricultural fields or the distribution of field sizes. Therefore, we employ cutting edge approaches from the field of computer vision to map fields across Sub-Saharan Africa, including semantic segmentation, discriminative classifiers, and automatic feature selection. Our approach aims to not only improve the binary classification accuracy of cropland, but also to isolate distinct fields, thereby capturing crucial information on size and geometry. Our research focuses on the development of descriptive features across scales to increase the accuracy and geographic range of our computer vision algorithm. Relevant data sets include high-resolution remote sensing imagery and Landsat (30-m) multi-spectral imagery. Training data for field boundaries is derived from hand-digitized data sets as well as crowdsourcing.
Spatial Distribution of Ozone Precursors in the Uinta Basin
NASA Astrophysics Data System (ADS)
Mangum, C. D.; Lyman, S. N.
2012-12-01
Wintertime ozone mixing ratios in the Uinta Basin of Utah exceeding the EPA National Ambient Air Quality Standards measured during 2010 and 2011 led to a large campaign carried out in 2012 that included a study of the spatial distribution of ozone precursors in the Basin. In this study, speciated hydrocarbon mixing ratios (compounds with 6-11 carbon atoms) were measure at 10 sites around the Uinta Basin with Radiello passive samplers, and NO2, NO, and NOx (NO2 + NO) mixing ratios were measured at 16 sites with Ogawa passive sampler and active sampling instruments. Analysis of the Radiello passive samplers was carried out by CS2 desorption and analyzed on a Shimadzu QP-2010 GCMS. Analysis of the Ogawa passive samplers was done via 18.2 megohm water extraction and analyzed with a Dionex ICS-3000 ion chromatography system. February average hydrocarbon mixing ratios were highest in the area of maximum gas production (64.5 ppb as C3), lower in areas of oil production (24.3-30.0 ppb as C3), and lowest in urban areas and on the Basin rim (1.7-17.0 ppb as C3). February average for NOx was highest in the most densely populated urban area, Vernal (11.2 ppb), lower in in the area of maximum gas production (6.1 ppb), and lower still in areas of oil production and on the Basin Rim (0.6-2.7 ppb). Hydrocarbon speciation showed significant differences in spatial distribution around the Basin. Higher mixing ratios of toluene and other aromatics were much more prevalent in gas producing areas than oil producing areas. Similar mixing ratios of straight-chain alkane were observed in both areas. Higher mixing ratios of cycloalkanes were slightly more prevalent in gas producing than oil producing areas.
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.
Temporal and spatial mapping of red grouper Epinephelus morio sound production.
Wall, C C; Simard, P; Lindemuth, M; Lembke, C; Naar, D F; Hu, C; Barnes, B B; Muller-Karger, F E; Mann, D A
2014-11-01
The goals of this project were to determine the daily, seasonal and spatial patterns of red grouper Epinephelus morio sound production on the West Florida Shelf (WFS) using passive acoustics. An 11 month time series of acoustic data from fixed recorders deployed at a known E. morio aggregation site showed that E. morio produce sounds throughout the day and during all months of the year. Increased calling (number of files containing E. morio sound) was correlated to sunrise and sunset, and peaked in late summer (July and August) and early winter (November and December). Due to the ubiquitous production of sound, large-scale spatial mapping across the WFS of E. morio sound production was feasible using recordings from shorter duration-fixed location recorders and autonomous underwater vehicles (AUVs). Epinephelus morio were primarily recorded in waters 15-93 m deep, with increased sound production detected in hard bottom areas and within the Steamboat Lumps Marine Protected Area (Steamboat Lumps). AUV tracks through Steamboat Lumps, an offshore marine reserve where E. morio hole excavations have been previously mapped, showed that hydrophone-integrated AUVs could accurately map the location of soniferous fish over spatial scales of <1 km. The results show that passive acoustics is an effective, non-invasive tool to map the distribution of this species over large spatial scales. © 2014 The Fisheries Society of the British Isles.
NASA Astrophysics Data System (ADS)
Wen, Yingrong; Schoups, Gerrit; van de Giesen, Nick
2018-01-01
In many regions of the world, intensive livestock farming has become a significant source of organic river pollution. As the international meat trade is growing rapidly, the environmental impacts of meat production within one country can occur either domestically or internationally. The goal of this paper is to quantify the impacts of the international meat trade on global organic river pollution at multiple scales (national, regional and gridded). Using the biological oxygen demand (BOD) as an overall indicator of organic river pollution, we compute the spatially distributed organic pollution in global river networks with and without a meat trade, where the without-trade scenario assumes that meat imports are replaced by local production. Our analysis reveals a reduction in the livestock population and production of organic pollutants at the global scale as a result of the international meat trade. However, the actual environmental impact of trade, as quantified by in-stream BOD concentrations, is negative; i.e. we find a slight increase in polluted river segments. More importantly, our results show large spatial variability in local (grid-scale) impacts that do not correlate with local changes in BOD loading, which illustrates: (1) the significance of accounting for the spatial heterogeneity of hydrological processes along river networks, and (2) the limited value of looking at country-level or global averages when estimating the actual impacts of trade on the environment.
Spatial pattern enhances ecosystem functioning in an African savanna.
Pringle, Robert M; Doak, Daniel F; Brody, Alison K; Jocqué, Rudy; Palmer, Todd M
2010-05-25
The finding that regular spatial patterns can emerge in nature from local interactions between organisms has prompted a search for the ecological importance of these patterns. Theoretical models have predicted that patterning may have positive emergent effects on fundamental ecosystem functions, such as productivity. We provide empirical support for this prediction. In dryland ecosystems, termite mounds are often hotspots of plant growth (primary productivity). Using detailed observations and manipulative experiments in an African savanna, we show that these mounds are also local hotspots of animal abundance (secondary and tertiary productivity): insect abundance and biomass decreased with distance from the nearest termite mound, as did the abundance, biomass, and reproductive output of insect-eating predators. Null-model analyses indicated that at the landscape scale, the evenly spaced distribution of termite mounds produced dramatically greater abundance, biomass, and reproductive output of consumers across trophic levels than would be obtained in landscapes with randomly distributed mounds. These emergent properties of spatial pattern arose because the average distance from an arbitrarily chosen point to the nearest feature in a landscape is minimized in landscapes where the features are hyper-dispersed (i.e., uniformly spaced). This suggests that the linkage between patterning and ecosystem functioning will be common to systems spanning the range of human management intensities. The centrality of spatial pattern to system-wide biomass accumulation underscores the need to conserve pattern-generating organisms and mechanisms, and to incorporate landscape patterning in efforts to restore degraded habitats and maximize the delivery of ecosystem services.
Evaluation of topographical and seasonal feature using GPM IMERG and TRMM 3B42 over Far-East Asia
NASA Astrophysics Data System (ADS)
Kim, Kiyoung; Park, Jongmin; Baik, Jongjin; Choi, Minha
2017-05-01
The acquisition of accurate precipitation data is essential for analyzing various hydrological phenomena and climate change. Recently, the Global Precipitation Measurement (GPM) satellites were launched as a next-generation rainfall mission for observing global precipitation characteristics. The main objective in this study is to assess precipitation products from GPM, especially the Integrated Multi-satellitE Retrievals (GPM-3IMERGHH) and the Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), using gauge-based precipitation data from Far-East Asia during the pre-monsoon and monsoon seasons. Evaluation was performed by focusing on three different factors: geographical aspects, seasonal factors, and spatial distributions. In both mountainous and coastal regions, the GPM-3IMERGHH product showed better performance than the TRMM 3B42 V7, although both rainfall products showed uncertainties caused by orographic convection and the land-ocean classification algorithm. GPM-3IMERGHH performed about 8% better than TRMM 3B42 V7 during the pre-monsoon and monsoon seasons due to the improvement of loaded sensor and reinforcement in capturing convective rainfall, respectively. In depicting the spatial distribution of precipitation, GPM-3IMERGHH was more accurate than TRMM 3B42 V7 because of its enhanced spatial and temporal resolutions of 10 km and 30 min, respectively. Based on these results, GPM-3IMERGHH would be helpful for not only understanding the characteristics of precipitation with high spatial and temporal resolution, but also for estimating near-real-time runoff patterns.
Landscape patterns and soil organic carbon stocks in agricultural bocage landscapes
NASA Astrophysics Data System (ADS)
Viaud, Valérie; Lacoste, Marine; Michot, Didier; Walter, Christian
2014-05-01
Soil organic carbon (SOC) has a crucial impact on global carbon storage at world scale. SOC spatial variability is controlled by the landscape patterns resulting from the continuous interactions between the physical environment and the society. Natural and anthropogenic processes occurring and interplaying at the landscape scale, such as soil redistribution in the lateral and vertical dimensions by tillage and water erosion processes or spatial differentiation of land-use and land-management practices, strongly affect SOC dynamics. Inventories of SOC stocks, reflecting their spatial distribution, are thus key elements to develop relevant management strategies to improving carbon sequestration and mitigating climate change and soil degradation. This study aims to quantify SOC stocks and their spatial distribution in a 1,000-ha agricultural bocage landscape with dairy production as dominant farming system (Zone Atelier Armorique, LTER Europe, NW France). The site is characterized by high heterogeneity on short distance due to a high diversity of soils with varying waterlogging, soil parent material, topography, land-use and hedgerow density. SOC content and stocks were measured up to 105-cm depth in 200 sampling locations selected using conditioned Latin hypercube sampling. Additive sampling was designed to specifically explore SOC distribution near to hedges: 112 points were sampled at fixed distance on 14 transects perpendicular from hedges. We illustrate the heterogeneity of spatial and vertical distribution of SOC stocks at landscape scale, and quantify SOC stocks in the various landscape components. Using multivariate statistics, we discuss the variability and co-variability of existing spatial organization of cropping systems, environmental factors, and SOM stocks, over landscape. Ultimately, our results may contribute to improving regional or national digital soil mapping approaches, by considering the distribution of SOC stocks within each modeling unit and by accounting for the impact of sensitive ecosystems.
NASA Astrophysics Data System (ADS)
Reglero, Patricia; Santos, Maria; Balbín, Rosa; Laíz-Carrión, Raul; Alvarez-Berastegui, Diego; Ciannelli, Lorenzo; Jiménez, Elisa; Alemany, Francisco
2017-06-01
Tuna spawning habitats are traditionally characterized using data sets of larvae or gonads from mature adults and concurrent environmental variables. Data on egg distributions have never previously been used since molecular analyses are mandatory to identify tuna eggs to species level. However, in this study we use molecularly derived egg distribution data, in addition to larval data, to characterize hydrographic and biological drivers of the spatial distribution of eggs and larvae of bluefin Thunnus thynnus and albacore tuna Thunnus alalunga in the Balearic Sea, a main spawning area of these species in the Mediterranean. The effects of the hydrography, characterized by salinity, temperature and geostrophic velocity, on the spatial distributions of the eggs and larvae are investigated. Three biological variables are used to describe the productivity in the area: chlorophyll a in the mixed layer, chlorophyll a in the deep chlorophyll maximum and mesozooplankton biomass in the mixed layer. Our results point to the importance of salinity fronts and temperatures above a minimum threshold in shaping the egg and larval distribution of both species. The spatial distribution of the biotic variables was very scattered, and they did not emerge as significant variables in the presence-absence models. However, they became significant when modeling egg and larval abundances. The lack of correlation between the three biotic variables challenges the use of chlorophyll a to describe trophic scenarios for the larvae and suggests that the spatial distribution of resources is not persistent in time. The different patterns in relation to biotic variables across species and stages found in this and other studies indicate a still elusive understanding of the link between trophic levels involving tuna early larval stages. Our ability to improve short-term forecasting and long-term predictions of climate effects on the egg and larval distributions is discussed based on the consistency of the environmentally driven spatial patterns for the two species.
A hydrological emulator for global applications - HE v1.0.0
NASA Astrophysics Data System (ADS)
Liu, Yaling; Hejazi, Mohamad; Li, Hongyi; Zhang, Xuesong; Leng, Guoyong
2018-03-01
While global hydrological models (GHMs) are very useful in exploring water resources and interactions between the Earth and human systems, their use often requires numerous model inputs, complex model calibration, and high computation costs. To overcome these challenges, we construct an efficient open-source and ready-to-use hydrological emulator (HE) that can mimic complex GHMs at a range of spatial scales (e.g., basin, region, globe). More specifically, we construct both a lumped and a distributed scheme of the HE based on the monthly abcd model to explore the tradeoff between computational cost and model fidelity. Model predictability and computational efficiency are evaluated in simulating global runoff from 1971 to 2010 with both the lumped and distributed schemes. The results are compared against the runoff product from the widely used Variable Infiltration Capacity (VIC) model. Our evaluation indicates that the lumped and distributed schemes present comparable results regarding annual total quantity, spatial pattern, and temporal variation of the major water fluxes (e.g., total runoff, evapotranspiration) across the global 235 basins (e.g., correlation coefficient r between the annual total runoff from either of these two schemes and the VIC is > 0.96), except for several cold (e.g., Arctic, interior Tibet), dry (e.g., North Africa) and mountainous (e.g., Argentina) regions. Compared against the monthly total runoff product from the VIC (aggregated from daily runoff), the global mean Kling-Gupta efficiencies are 0.75 and 0.79 for the lumped and distributed schemes, respectively, with the distributed scheme better capturing spatial heterogeneity. Notably, the computation efficiency of the lumped scheme is 2 orders of magnitude higher than the distributed one and 7 orders more efficient than the VIC model. A case study of uncertainty analysis for the world's 16 basins with top annual streamflow is conducted using 100 000 model simulations, and it demonstrates the lumped scheme's extraordinary advantage in computational efficiency. Our results suggest that the revised lumped abcd model can serve as an efficient and reasonable HE for complex GHMs and is suitable for broad practical use, and the distributed scheme is also an efficient alternative if spatial heterogeneity is of more interest.
Spatial distribution of ammonium and calcium in optimally fertilized pine plantation soils
Ivan Edwards; Andrew Gillespie; Jennifer Chen; Kurt Johnsen; Ronald Turco
2005-01-01
Commercial timber production is increasingly reliant on long-term fertilization to maximize stand productivity, yet we do not understand the extent to which this practice homogenizes soil properties. The effects of 16 yr of optimal fertilization and optimal fertilization with irrigation (fertigation) on forest floor depth, pH, total organic carbon (TOC) and total...
Todd A. Schroeder; Robbie Hember; Nicholas C. Coops; Shunlin Liang
2009-01-01
The magnitude and distribution of incoming shortwave solar radiation (SW) has significant influence on the productive capacity of forest vegetation. Models that estimate forest productivity require accurate and spatially explicit radiation surfaces that resolve both long- and short-term temporal climatic patterns and that account for topographic variability of the land...
NASA Astrophysics Data System (ADS)
Bormann, K.; Hedrick, A. R.; Marks, D. G.; Painter, T. H.
2017-12-01
The spatial and temporal distribution of snow water resources (SWE) in the mountains has been examined extensively through the use of models, in-situ networks and remote sensing techniques. However, until the Airborne Snow Observatory (http://aso.jpl.nasa.gov), our understanding of SWE dynamics has been limited due to a lack of well-constrained spatial distributions of SWE in complex terrain, particularly at high elevations and at regional scales (100km+). ASO produces comprehensive snow depth measurements and well-constrained SWE products providing the opportunity to re-examine our current understanding of SWE distributions with a robust and rich data source. We collected spatially-distributed snow depth and SWE data from over 150 individual ASO acquisitions spanning seven basins in California during the five-year operational period of 2013 - 2017. For each of these acquisitions, we characterized the spatial distribution of snow depth and SWE and examined how these distributions changed with time during snowmelt. We compared these distribution patterns between each of the seven basins and finally, examined the predictability of the SWE distributions using statistical extrapolations through both space and time. We compare and contrast these observationally-based characteristics with those from a physically-based snow model to highlight the strengths and weaknesses of the implementation of our understanding of SWE processes in the model environment. In practice, these results may be used to support or challenge our current understanding of mountain SWE dynamics and provide techniques for enhanced evaluation of high-resolution snow models that go beyond in-situ point comparisons. In application, this work may provide guidance on the potential of ASO to guide backfilling of sparse spaceborne measurements of snow depth and snow water equivalent.
Dusk/dawn atmospheric asymmetries on tidally-locked satellites: O2 at Europa
NASA Astrophysics Data System (ADS)
Oza, Apurva V.; Johnson, Robert E.; Leblanc, François
2018-05-01
We use a simple analytic model to examine the effect of the atmospheric source properties on the spatial distribution of a volatile in a surface-bounded atmosphere on a satellite that is tidally-locked to its planet. Spatial asymmetries in the O2 exosphere of Europa observed using the Hubble Space Telescope appear to reveal on average a dusk enhancement in the near-surface ultraviolet auroral emissions. Since the hop distances in these ballistic atmospheres are small, we use a 1-D mass conservation equation to estimate the latitudinally-averaged column densities produced by suggested O2 sources. Although spatial asymmetries in the plasma flow and in the surface properties certainly affect the spatial distribution of the near-surface aurora, the dusk enhancements at Europa can be understood using a relatively simple thermally-dependent source. Such a source is consistent with the fact that radiolytically produced O2 permeates their porous regoliths and is not so sensitive to the local production rate from ice. The size of the shift towards dusk is determined by the ratio of the rotation rate and atmospheric loss rate. A thermally-dependent source emanating from a large reservoir of O2 permeating Europa's icy regolith is consistent with the suggestion that its subsurface ocean might be oxidized by subduction of such radiolytic products.
Variability of the productive habitat in the eastern equatorial Pacific
NASA Technical Reports Server (NTRS)
Feldman, Gene Carl
1986-01-01
It is shown that satellite ocean color data can be used to define the spatial extent of the region of enhanced biological production (the productive habitat) in the eastern equatorial Pacific. The degree of interannual variability in the areal extent of the productive habitat and in the estimated primary production of the region is determined. Frequency distributions of satellite-derived pigment concentrations are used to determine whether major changes in phytoplankton biomass have taken place from one period to the next.
Distribution and interaction of white-tailed deer and cattle in a semi-arid grazing system
Susan M. Cooper; Humberto L. Perotto-Baldivieso; M. Keith Owens; Michael G. Meek; Manuel Figueroa-Pagan
2008-01-01
In order to optimize production, range managers need to understand and manage the spatial distribution of free-ranging herbivores, although this task becomes increasingly difficult as ranching operations diversify to include management of wildlife for recreational hunting. White-tailed deer are sympatric with cattle throughout much of their range and are a valuable...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Daly, Christopher; Halbleib, Michael D.; Hannaway, David B.
Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstockmore » Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.« less
Daly, Christopher; Halbleib, Michael D.; Hannaway, David B.; ...
2017-12-22
Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstockmore » Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.« less
Application of Geostatistical Simulation to Enhance Satellite Image Products
NASA Technical Reports Server (NTRS)
Hlavka, Christine A.; Dungan, Jennifer L.; Thirulanambi, Rajkumar; Roy, David
2004-01-01
With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.
Spatial modelling of disease using data- and knowledge-driven approaches.
Stevens, Kim B; Pfeiffer, Dirk U
2011-09-01
The purpose of spatial modelling in animal and public health is three-fold: describing existing spatial patterns of risk, attempting to understand the biological mechanisms that lead to disease occurrence and predicting what will happen in the medium to long-term future (temporal prediction) or in different geographical areas (spatial prediction). Traditional methods for temporal and spatial predictions include general and generalized linear models (GLM), generalized additive models (GAM) and Bayesian estimation methods. However, such models require both disease presence and absence data which are not always easy to obtain. Novel spatial modelling methods such as maximum entropy (MAXENT) and the genetic algorithm for rule set production (GARP) require only disease presence data and have been used extensively in the fields of ecology and conservation, to model species distribution and habitat suitability. Other methods, such as multicriteria decision analysis (MCDA), use knowledge of the causal factors of disease occurrence to identify areas potentially suitable for disease. In addition to their less restrictive data requirements, some of these novel methods have been shown to outperform traditional statistical methods in predictive ability (Elith et al., 2006). This review paper provides details of some of these novel methods for mapping disease distribution, highlights their advantages and limitations, and identifies studies which have used the methods to model various aspects of disease distribution. Copyright © 2011. Published by Elsevier Ltd.
NASA Astrophysics Data System (ADS)
Estima, Jacinto Paulo Simoes
Traditional geographic information has been produced by mapping agencies and corporations, using high skilled people as well as expensive precision equipment and procedures, in a very costly approach. The production of land use and land cover databases are just one example of such traditional approach. On the other side, The amount of Geographic Information created and shared by citizens through the Web has been increasing exponentially during the last decade, resulting from the emergence and popularization of technologies such as the Web 2.0, cloud computing, GPS, smart phones, among others. Such comprehensive amount of free geographic data might have valuable information to extract and thus opening great possibilities to improve significantly the production of land use and land cover databases. In this thesis we explored the feasibility of using geographic data from different user generated spatial content initiatives in the process of land use and land cover database production. Data from Panoramio, Flickr and OpenStreetMap were explored in terms of their spatial and temporal distribution, and their distribution over the different land use and land cover classes. We then proposed a conceptual model to integrate data from suitable user generated spatial content initiatives based on identified dissimilarities among a comprehensive list of initiatives. Finally we developed a prototype implementing the proposed integration model, which was then validated by using the prototype to solve four identified use cases. We concluded that data from user generated spatial content initiatives has great value but should be integrated to increase their potential. The possibility of integrating data from such initiatives in an integration model was proved. Using the developed prototype, the relevance of the integration model was also demonstrated for different use cases. None None None
NASA Astrophysics Data System (ADS)
Müller, Benjamin; Bernhardt, Matthias; Jackisch, Conrad; Schulz, Karsten
2016-09-01
For understanding water and solute transport processes, knowledge about the respective hydraulic properties is necessary. Commonly, hydraulic parameters are estimated via pedo-transfer functions using soil texture data to avoid cost-intensive measurements of hydraulic parameters in the laboratory. Therefore, current soil texture information is only available at a coarse spatial resolution of 250 to 1000 m. Here, a method is presented to derive high-resolution (15 m) spatial topsoil texture patterns for the meso-scale Attert catchment (Luxembourg, 288 km2) from 28 images of ASTER (advanced spaceborne thermal emission and reflection radiometer) thermal remote sensing. A principle component analysis of the images reveals the most dominant thermal patterns (principle components, PCs) that are related to 212 fractional soil texture samples. Within a multiple linear regression framework, distributed soil texture information is estimated and related uncertainties are assessed. An overall root mean squared error (RMSE) of 12.7 percentage points (pp) lies well within and even below the range of recent studies on soil texture estimation, while requiring sparser sample setups and a less diverse set of basic spatial input. This approach will improve the generation of spatially distributed topsoil maps, particularly for hydrologic modeling purposes, and will expand the usage of thermal remote sensing products.
Burstiness in Viral Bursts: How Stochasticity Affects Spatial Patterns in Virus-Microbe Dynamics
NASA Astrophysics Data System (ADS)
Lin, Yu-Hui; Taylor, Bradford P.; Weitz, Joshua S.
Spatial patterns emerge in living systems at the scale of microbes to metazoans. These patterns can be driven, in part, by the stochasticity inherent to the birth and death of individuals. For microbe-virus systems, infection and lysis of hosts by viruses results in both mortality of hosts and production of viral progeny. Here, we study how variation in the number of viral progeny per lysis event affects the spatial clustering of both viruses and microbes. Each viral ''burst'' is initially localized at a near-cellular scale. The number of progeny in a single lysis event can vary in magnitude between tens and thousands. These perturbations are not accounted for in mean-field models. Here we developed individual-based models to investigate how stochasticity affects spatial patterns in virus-microbe systems. We measured the spatial clustering of individuals using pair correlation functions. We found that increasing the burst size of viruses while maintaining the same production rate led to enhanced clustering. In this poster we also report on preliminary analysis on the evolution of the burstiness of viral bursts given a spatially distributed host community.
Body size distributions signal a regime shift in a lake ...
Communities of organisms, from mammals to microorganisms, have discontinuous distributions of body size. This pattern of size structuring is a conservative trait of community organization and is a product of processes that occur at multiple spatial and temporal scales. In this study, we assessed whether body size patterns serve as an indicator of a threshold between alternative regimes. Over the past 7000 years, the biological communities of Foy Lake (Montana,USA) have undergone a major regime shift owing to climate change. We used a palaeoecological record of diatom communities to estimate diatom sizes, and then analysed the discontinuous distribution of organism sizes over time. We used Bayesian classification and regression tree models to determine that all time intervals exhibited aggregations of sizes separated by gaps in the distribution and found a significant change in diatom body size distributions approximately 150 years before the identified ecosystem regime shift. We suggest that discontinuity analysis is a useful addition to the suite of tools for the detection of early warning signals of regime shifts. Communities of organisms from mammals to microorganisms have discontinuous distributions of body size. This pattern of size structuring is a conservative trait of community organization and is a product of processes that occur at discrete spatial and temporal scales within ecosystems. Here, a paleoecological record of diatom community change is use
NASA Astrophysics Data System (ADS)
Smith, Lesley Jane
2011-09-01
Spatial data and imagery generators are set to become tomorrow's key players in the information society. This is why satellite owners and operators are examining new revenue-producing models for developing space-related products and services. The use and availability of broadband internet width and satellite data-based services will continue to increase in the future. With the capacity to deliver real time precision downstream data, space agencies and the satellite industry can respond to the demand for high resolution digital space information which, with the appropriate technology, can be integrated into a variety of web-based applications. At a time when the traditional roles of space agencies are becoming more hybrid, largely as a result of the greater drive towards commercial markets, new value-added markets for space-related information products are continuing to attract attention. This paper discusses whether traditional data policies on space data access and IP licensing schemes stand to remain the feasible prototype for distributing and marketing space data, and how this growth market might benefit from looking at an 'up and running' global IP management system already operating to manage end user digital demand. PrefaceThe terminology describing the various types of spatial data and space-based information is not uniformly used within the various principles, laws and policies that govern space data. For convenience only this paper refers to primary or raw data gathered by the space-based industry as spatial or raw data, and the data as processed and sold on or distributed by ground-based companies as space information products and services. In practise, spatial data range from generic to specific data sets, digital topography, through to pictures and imagery services at various resolutions, with 3-D perspectives underway. The paper addresses general IP considerations relating to spatial data, with some reference to remote sensing itself. Exact IP details will depend at all times on the final product and service in question.
NASA Astrophysics Data System (ADS)
Anderson, T.; Jencso, K. G.; Hoylman, Z. H.; Hu, J.
2015-12-01
Characterizing the mechanisms that lead to differences in forest ecosystem productivity across complex terrain remains a challenge. This difficulty can be partially attributed to the cost of installing networks of proprietary data loggers that monitor differences in the biophysical factors contributing to tree growth. Here, we describe the development and initial application of a network of open source data loggers. These data loggers are based on the Arduino platform, but were refined into a custom printed circuit board (PCB). This reduced the cost and complexity of the data loggers, which made them cheap to reproduce and reliable enough to withstand the harsh environmental conditions experienced in Ecohydrology studies. We demonstrate the utility of these loggers for high frequency, spatially-distributed measurements of sap-flux, stem growth, relative humidity, temperature, and soil water content across 36 landscape positions in the Lubrecht Experimental Forest, MT, USA. This new data logging technology made it possible to develop a spatially distributed monitoring network within the constraints of our research budget and may provide new insights into factors affecting forest productivity across complex terrain.
Distribution ozone concentration in Klang Valley using GIS approaches
NASA Astrophysics Data System (ADS)
Sulaiman, A.; Rahman, A. A. Ab; Maulud, K. N. Abdul; Latif, M. T.; Ahmad, F.; Wahid, M. A. Abdul; Ibrahim, M. A.; Halim, N. D. Abdul
2017-05-01
Today, ozone has become one of the main air pollutants in Malaysia. The high ozone precursor concentrations have been encouraging the ozone production. The development of the Klang Valley, Malaysia has many types of physical activities such as urban commercial, industrial area, settlement area and others, which has increased the risk of atmospheric pollution. The purpose of this paper is to determine the spatial distribution between types of land use and ozone concentration that are occurred in the year 2014. The study areas for this paper include Shah Alam, Kajang, Petaling Jaya and Port Klang. Distribution of ozone concentration will be showed via spatial analysis tools in Geographic Information Systems (GIS) approached and the types of land use will be extracted using Remote Sensing technique. The result showed 97 ppb (parts-per-billion, 10-9) and 161 ppb recorded at Port Klang and Shah Alam respectively that are mainly represented by the settlement area. Therefore, the physical land use need to be monitor and controlled by the government in order to make sure the ozone production for daily per hour will not exceed the regulation allowed.
Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.
2011-01-01
The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Appalachian State University, Boone, North Carolina (USA)
2015-01-01
The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.
2013-01-01
The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Research Institute for Environment, Energy and Economics Appalachian State University Boone, North Carolina 28608 U.S.A.
2012-01-01
The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Andres, R. J. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Boden, T. A. [Carbon Dioxide Information Analysis Center Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge, Tennessee 37830-6290 U.S.A.; Marland, G. [Appalachian State University, Boone, North Carolina (USA).
2013-01-01
The monthly, isotopic (δ 13C) fossil-fuel CO2 emissions estimates from 1950-2013 provided in this database are derived from time series of global, regional, and national fossil-fuel CO2 emissions (Boden et al. 2016), the references therein, and the methodology described in Andres et al. (2011). The data accessible here take these tabular, national, mass-emissions data, multiply them by stable carbon isotopic signatures (δ 13C) as described in Andres et al. (2000), and distribute them spatially on a one degree latitude by one degree longitude grid. The within-country spatial distribution is achieved through a fixed population distribution as reported in Andres et al. (1996). Note that the mass-emissions data used here are based on fossil-fuel consumption estimates as these are more representative of within country emissions than fossil-fuel production estimates (see http://cdiac.ess-dive.lbl.gov/faq.html#Q10 for a description why emission totals based upon consumption differ from those based upon production).
Site-specific management of nematodes pitfalls and practicalities.
Evans, Ken; Webster, Richard M; Halford, Paul D; Barker, Anthony D; Russell, Michael D
2002-09-01
The greatest constraint to potato production in the United Kingdom (UK) is damage by the potato cyst nematodes (PCN) Globodera pallida and G. rostochiensis. Management of PCN depends heavily on nematicides, which are costly. Of all the inputs in UK agriculture, nematicides offer the largest potential cost savings from spatially variable application, and these savings would be accompanied by environmental benefits. We mapped PCN infestations in potato fields and monitored the changes in population density and distribution that occurred when susceptible potato crops were grown. The inverse relationship between population density before planting and multiplication rate of PCN makes it difficult to devise reliable spatial nematicide application procedures, especially when the pre-planting population density is just less than the detection threshold. Also, the spatial dependence found suggests that the coarse sampling grids used commercially are likely to produce misleading distribution maps.
Phase-space analysis of the Schwinger effect in inhomogeneous electromagnetic fields
NASA Astrophysics Data System (ADS)
Kohlfürst, Christian
2018-05-01
Schwinger pair production in spatially and temporally inhomogeneous electric and magnetic fields is studied. The focus is on the particle phase-space distribution within a high-intensity few-cycle pulse. Accurate numerical solutions of a quantum kinetic theory (DHW formalism) are presented in momentum space and, with the aid of coarse-graining techniques, in a mixed spatial-momentum representation. Additionally, signatures of the carrier-envelope phase as well as spin-field interactions are discussed on the basis of a trajectory-based model taking into account instantaneous pair production and relativistic single-particle dynamics. Although our simple semi-classical single-particle model cannot describe every aspect of the particle production process (quantum interferences), essential features such as spin-field interactions are captured.
NASA Technical Reports Server (NTRS)
Pahlevan, Nima; Sarkar, Sudipta; Devadiga, Sadashiva; Wolfe, Robert E.; Roman, Miguel; Vermote, Eric; Lin, Guoqing; Xiong, Xiaoxiong
2016-01-01
With the increasing need to construct long-term climate-quality data records to understand, monitor, and predict climate variability and change, it is vital to continue systematic satellite measurements along with the development of new technology for more quantitative and accurate observations. The Suomi National Polar-orbiting Partnership mission provides continuity in monitoring the Earths surface and its atmosphere in a similar fashion as the heritage MODIS instruments onboard the National Aeronautics and Space Administrations Terra and Aqua satellites. In this paper, we aim at quantifying the consistency of Aqua MODIS and Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Reflectance (LSR) and NDVI products as related to their inherent spatial sampling characteristics. To avoid interferences from sources of measurement and/or processing errors other than spatial sampling, including calibration, atmospheric correction, and the effects of the bidirectional reflectance distribution function, the MODIS and VIIRSLSR products were simulated using the Landsat-8s Operational Land Imager (OLI) LSR products. The simulations were performed using the instruments point spread functions on a daily basis for various OLI scenes over a 16-day orbit cycle. It was found that the daily mean differences due to discrepancies in spatial sampling remain below 0.0015 (1) in absolute surface reflectance at subgranule scale (i.e., OLI scene size).We also found that the MODISVIIRS product intercomparisons appear to be minimally impacted when differences in the corresponding view zenith angles (VZAs) are within the range of -15deg to -35deg (VZA(sub v) - VZA(sub m)), where VIIRS and MODIS footprints resemble in size. In general, depending on the spatial heterogeneity of the OLI scene contents, per-grid-cell differences can reach up to 20.Further spatial analysis of the simulated NDVI and LSR products revealed that, depending on the user accuracy requirements for product intercomparisons, spatial aggregations may be used. It was found that if per-grid-cell differences on the order of 10(in LSR or NDVI) are tolerated, the product intercomparisons are expected to be immune from differences in spatial sampling.
A high resolution spatial population database of Somalia for disease risk mapping.
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
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
USDA-ARS?s Scientific Manuscript database
Grassland ecosystems in North America are primarily composed of C3 and C4 plant functional types (PFTs) with their relative cover varying spatially and temporally. This study used 500-m MODIS surface reflectance products (MOD09A1) from 2000 to 2009 to extract an NDVI time series of C3 and C4 PFTs in...
A Spatio-Temporal Approach for Global Validation and Analysis of MODIS Aerosol Products
NASA Technical Reports Server (NTRS)
Ichoku, Charles; Chu, D. Allen; Mattoo, Shana; Kaufman, Yoram J.; Remer, Lorraine A.; Tanre, Didier; Slutsker, Ilya; Holben, Brent N.; Lau, William K. M. (Technical Monitor)
2001-01-01
With the launch of the MODIS sensor on the Terra spacecraft, new data sets of the global distribution and properties of aerosol are being retrieved, and need to be validated and analyzed. A system has been put in place to generate spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of the MODIS aerosol parameters over more than 100 validation sites spread around the globe. Corresponding statistics are also computed from temporal subsets of AERONET-derived aerosol data. The means and standard deviations of identical parameters from MOMS and AERONET are compared. Although, their means compare favorably, their standard deviations reveal some influence of surface effects on the MODIS aerosol retrievals over land, especially at low aerosol loading. The direction and rate of spatial variation from MODIS are used to study the spatial distribution of aerosols at various locations either individually or comparatively. This paper introduces the methodology for generating and analyzing the data sets used by the two MODIS aerosol validation papers in this issue.
Lateral weathering gradients in glaciated catchments
NASA Astrophysics Data System (ADS)
McGuire, K. J.; Bailey, S. W.; Ross, D. S.; Strahm, B. D.; Schreiber, M. E.
2016-12-01
Mineral dissolution and the distribution of weathering products are fundamental processes that drive development and habitability of the Earth's critical zone; yet, the spatial configuration of these processes in some systems is not well understood. Feedbacks between hydrologic flows and weathering fluxes are necessary to understanding how the critical zone develops. In upland glaciated catchments of the northeastern USA, primary mineral dissolution and the distribution of weathering products are spatially distinct and predictable over short distances. Hillslopes, where shallow soils force lateral hydrologic fluxes through accumulated organic matter, produce downslope gradients in mineral depletion, weathering product accumulation, soil development, and solute chemistry. We propose that linked gradients in hydrologic flow paths, soil depth, and vegetation lead to predictable differences in the location and extent of mineral dissolution in regolith (soil, subsoil, and rock fragments) and bedrock, and that headwater catchments within the upland glaciated northeast show a common architecture across hillslopes as a result. Examples of these patterns and processes will be illustrated using observations from the Hubbard Brook Experimental Forest in New Hampshire where laterally distinct soils with strong morphological and biogeochemical gradients have been documented. Patterns in mineral depletion and product accumulation are essential in predicting how ecosystems will respond to stresses, disturbance, and management.
Mark Coleman
2007-01-01
In forest trees, roots mediate such significant carbon fluxes as primary production and soil C02 efflux. Despite the central role of roots in these critical processes, information on root distribution during stand establishment is limited, yet must be described to accurately predict how various forest types, which are growing with a range of...
Chen, J. M.; Fung, J. W.; Mo, G.; ...
2015-01-19
In order to improve quantification of the spatial distribution of carbon sinks and sources in the conterminous US, we conduct a nested global atmospheric inversion with detailed spatial information on crop production and consumption. County-level cropland net primary productivity, harvested biomass, soil carbon change, and human and livestock consumption data over the conterminous US are used for this purpose. Time-dependent Bayesian synthesis inversions are conducted based on CO₂ observations at 210 stations to infer CO₂ fluxes globally at monthly time steps with a nested focus on 30 regions in North America. Prior land surface carbon fluxes are first generated usingmore » a biospheric model, and the inversions are constrained using prior fluxes with and without adjustments for crop production and consumption over the 2002–2007 period. After these adjustments, the inverted regional carbon sink in the US Midwest increases from 0.25 ± 0.03 to 0.42 ± 0.13 Pg C yr⁻¹, whereas the large sink in the US southeast forest region is weakened from 0.41 ± 0.12 to 0.29 ± 0.12 Pg C yr⁻¹. These adjustments also reduce the inverted sink in the west region from 0.066 ± 0.04 to 0.040 ± 0.02 Pg C yr⁻¹ because of high crop consumption and respiration by humans and livestock. The general pattern of sink increases in crop production areas and sink decreases (or source increases) in crop consumption areas highlights the importance of considering the lateral carbon transfer in crop products in atmospheric inverse modeling, which provides a reliable atmospheric perspective of the overall carbon balance at the continental scale but is unreliable for separating fluxes from different ecosystems.« less
Spatial and Statistical Analysis of Leptospirosis in Guilan Province, Iran
NASA Astrophysics Data System (ADS)
Nia, A. Mohammadi; Alimohammadi, A.; Habibi, R.; Shirzadi, M. R.
2015-12-01
The most underdiagnosed water-borne bacterial zoonosis in the world is Leptospirosis which especially impacts tropical and humid regions. According to World Health Organization (WHO), the number of human cases is not known precisely. Available reports showed that worldwide incidences vary from 0.1-1 per 100 000 per year in temperate climates to 10-100 per 100 000 in the humid tropics. Pathogenic bacteria that is spread by the urines of rats is the main reason of water and soil infections. Rice field farmers who are in contact with infected water or soil, contain the most burden of leptospirosis prevalence. In recent years, this zoonotic disease have been occurred in north of Iran endemically. Guilan as the second rice production province (average=750 000 000 Kg, 40% of country production) after Mazandaran, has one of the most rural population (Male=487 679, Female=496 022) and rice workers (47 621 insured workers) among Iran provinces. The main objectives of this study were to analyse yearly spatial distribution and the possible spatial clusters of leptospirosis to better understand epidemiological aspects of them in the province. Survey was performed during the period of 2009-2013 at rural district level throughout the study area. Global clustering methods including the average nearest neighbour distance, Moran's I and General G indices were utilized to investigate the annual spatial distribution of diseases. At the end, significant spatial clusters have been detected with the objective of informing priority areas for public health planning and resource allocation.
Wu, Jidong; Li, Ying; Li, Ning; Shi, Peijun
2018-01-01
The extent of economic losses due to a natural hazard and disaster depends largely on the spatial distribution of asset values in relation to the hazard intensity distribution within the affected area. Given that statistical data on asset value are collected by administrative units in China, generating spatially explicit asset exposure maps remains a key challenge for rapid postdisaster economic loss assessment. The goal of this study is to introduce a top-down (or downscaling) approach to disaggregate administrative-unit level asset value to grid-cell level. To do so, finding the highly correlated "surrogate" indicators is the key. A combination of three data sets-nighttime light grid, LandScan population grid, and road density grid, is used as ancillary asset density distribution information for spatializing the asset value. As a result, a high spatial resolution asset value map of China for 2015 is generated. The spatial data set contains aggregated economic value at risk at 30 arc-second spatial resolution. Accuracy of the spatial disaggregation reflects redistribution errors introduced by the disaggregation process as well as errors from the original ancillary data sets. The overall accuracy of the results proves to be promising. The example of using the developed disaggregated asset value map in exposure assessment of watersheds demonstrates that the data set offers immense analytical flexibility for overlay analysis according to the hazard extent. This product will help current efforts to analyze spatial characteristics of exposure and to uncover the contributions of both physical and social drivers of natural hazard and disaster across space and time. © 2017 Society for Risk Analysis.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Efroymson, Rebecca Ann; Dale, Virginia H; Kline, Keith L
Indicators of the environmental sustainability of biofuel production, distribution, and use should be selected, measured, and interpreted with respect to the context in which they are used. These indicators include measures of soil quality, water quality and quantity, greenhouse-gas emissions, biodiversity, air quality, and vegetation productivity. Contextual considerations include the purpose for the sustainability analysis, the particular biofuel production and distribution system (including supply chain, management aspects, and system viability), policy conditions, stakeholder values, location, temporal influences, spatial scale, baselines, and reference scenarios. Recommendations presented in this paper include formulating the problem for particular analyses, selecting appropriate context-specific indicators ofmore » environmental sustainability, and developing indicators that can reflect multiple environmental properties at low cost within a defined context. In addition, contextual considerations such as technical objectives, varying values and perspectives of stakeholder groups, and availability and reliability of data need to be understood and considered. Sustainability indicators for biofuels are most useful if adequate historical data are available, information can be collected at appropriate spatial and temporal scales, organizations are committed to use indicator information in the decision-making process, and indicators can effectively guide behavior toward more sustainable practices.« less
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.
NASA Astrophysics Data System (ADS)
Oda, Tomohiro; Maksyutov, Shamil; Andres, Robert J.
2018-01-01
The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) is a global high-spatial-resolution gridded emissions data product that distributes carbon dioxide (CO2) emissions from fossil fuel combustion. The emissions spatial distributions are estimated at a 1 × 1 km spatial resolution over land using power plant profiles (emissions intensity and geographical location) and satellite-observed nighttime lights. This paper describes the year 2016 version of the ODIAC emissions data product (ODIAC2016) and presents analyses that help guide data users, especially for atmospheric CO2 tracer transport simulations and flux inversion analysis. Since the original publication in 2011, we have made modifications to our emissions modeling framework in order to deliver a comprehensive global gridded emissions data product. Major changes from the 2011 publication are (1) the use of emissions estimates made by the Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory (ORNL) by fuel type (solid, liquid, gas, cement manufacturing, gas flaring, and international aviation and marine bunkers); (2) the use of multiple spatial emissions proxies by fuel type such as (a) nighttime light data specific to gas flaring and (b) ship/aircraft fleet tracks; and (3) the inclusion of emissions temporal variations. Using global fuel consumption data, we extrapolated the CDIAC emissions estimates for the recent years and produced the ODIAC2016 emissions data product that covers 2000-2015. Our emissions data can be viewed as an extended version of CDIAC gridded emissions data product, which should allow data users to impose global fossil fuel emissions in a more comprehensive manner than the original CDIAC product. Our new emissions modeling framework allows us to produce future versions of the ODIAC emissions data product with a timely update. Such capability has become more significant given the CDIAC/ORNL's shutdown. The ODIAC data product could play an important role in supporting carbon cycle science, especially modeling studies with space-based CO2 data collected in near real time by ongoing carbon observing missions such as the Japanese Greenhouse gases Observing SATellite (GOSAT), NASA's Orbiting Carbon Observatory-2 (OCO-2), and upcoming future missions. The ODIAC emissions data product including the latest version of the ODIAC emissions data (ODIAC2017, 2000-2016) is distributed from http://db.cger.nies.go.jp/dataset/ODIAC/ with a DOI (https://doi.org/10.17595/20170411.001).
NASA Astrophysics Data System (ADS)
Anghileri, D.; Kaelin, A.; Peleg, N.; Fatichi, S.; Molnar, P.; Roques, C.; Longuevergne, L.; Burlando, P.
2017-12-01
Hydrological modeling in poorly gauged basins can benefit from the use of remote sensing datasets although there are challenges associated with the mismatch in spatial and temporal scales between catchment scale hydrological models and remote sensing products. We model the hydrological processes and long-term water budget of the Lake Turkana catchment, a transboundary basin between Kenya and Ethiopia, by integrating several remote sensing products into a spatially distributed and physically explicit model, Topkapi-ETH. Lake Turkana is the world largest desert lake draining a catchment of 145'500 km2. It has three main contributing rivers: the Omo river, which contributes most of the annual lake inflow, the Turkwel river, and the Kerio rivers, which contribute the remaining part. The lake levels have shown great variations in the last decades due to long-term climate fluctuations and the regulation of three reservoirs, Gibe I, II, and III, which significantly alter the hydrological seasonality. Another large reservoir is planned and may be built in the next decade, generating concerns about the fate of Lake Turkana in the long run because of this additional anthropogenic pressure and increasing evaporation driven by climate change. We consider different remote sensing datasets, i.e., TRMM-V7 for precipitation, MERRA-2 for temperature, as inputs to the spatially distributed hydrological model. We validate the simulation results with other remote sensing datasets, i.e., GRACE for total water storage anomalies, GLDAS-NOAH for soil moisture, ERA-Interim/Land for surface runoff, and TOPEX/Poseidon for satellite altimetry data. Results highlight how different remote sensing products can be integrated into a hydrological modeling framework accounting for their relative uncertainties. We also carried out simulations with the artificial reservoirs planned in the north part of the catchment and without any reservoirs, to assess their impacts on the catchment hydrological regime and the Lake Turkana level variability.
Kim, Intae; Hahm, Doshik; Park, Keyhong; Lee, Youngju; Choi, Jung-Ok; Zhang, Miming; Chen, Liqi; Kim, Hyun-Cheol; Lee, SangHoon
2017-04-15
We investigated horizontal and vertical distributions of DMS in the upper water column of the Amundsen Sea Polynya and Pine Island Polynya during the austral summer (January-February) of 2016 using a membrane inlet mass spectrometer (MIMS) onboard the Korean icebreaker R/V Araon. The surface water concentrations of DMS varied from <1 to 400nM. The highest DMS (up to 300nM) were observed in sea ice-polynya transition zones and near the Getz ice shelf, where both the first local ice melting and high plankton productivity were observed. In other regions, high DMS concentration was generally accompanied by higher chlorophyll and ΔO 2 /Ar. The large spatial variability of DMS and primary productivity in the surface water of the Amundsen Sea seems to be attributed to melting conditions of sea ice, relative dominance of Phaeocystis Antarctica as a DMS producer, and timing differences between bloom and subsequent DMS productions. The depth profiles of DMS and ΔO 2 /Ar were consistent with the horizontal surface data, showing noticeable spatial variability. However, despite the large spatial variability, in contrast to the previous results from 2009, DMS concentrations and ΔO 2 /Ar in the surface water were indistinct between the two major domains: the sea ice zone and polynya region. The discrepancy may be associated with inter-annual variations of phytoplankton assemblages superimposed on differences in sea-ice conditions, blooming period, and spatial coverage along the vast surface area of the Amundsen Sea. Copyright © 2017 Elsevier B.V. All rights reserved.
Lu, Shaoping; Sturtevant, Drew; Aziz, Mina; Jin, Cheng; Li, Qing; Chapman, Kent D; Guo, Liang
2018-06-01
Despite the importance of oilseeds to worldwide human nutrition, and more recently to the production of bio-based diesel fuels, the detailed mechanisms regulating seed oil biosynthesis remain only partly understood, especially from a tissue-specific perspective. Here, we investigated the spatial distributions of lipid metabolites and transcripts involved in oil biosynthesis from seeds of two low-erucic acid genotypes of Brassica napus with high and low seed-oil content. Integrated results from matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) of lipids in situ, lipidome profiling of extracts from seed tissues, and tissue-specific transcriptome analysis revealed complex spatial distribution patterns of lipids and transcripts. In general, it appeared that many triacylglycerol and phosphatidylcholine species distributed heterogeneously throughout the embryos. Tissue-specific transcriptome analysis identified key genes involved in de novo fatty acid biosynthesis in plastid, triacylglycerols assembly and lipid droplet packaging in the endoplasmic reticulum (ER) that may contribute to the high or low oil phenotype and heterogeneity of lipid distribution. Our results imply that transcriptional regulation represents an important means of impacting lipid compartmentalization in oil seeds. While much information remains to be learned about the intricacies of seed oil accumulation and distribution, these studies highlight the advances that come from evaluating lipid metabolism within a spatial context and with multiple omics level datasets. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.
A Biophysical Modeling Framework for Assessing the Environmental Impact of Biofuel Production
NASA Astrophysics Data System (ADS)
Zhang, X.; Izaurradle, C.; Manowitz, D.; West, T. O.; Post, W. M.; Thomson, A. M.; Nichols, J.; Bandaru, V.; Williams, J. R.
2009-12-01
Long-term sustainability of a biofuel economy necessitates environmentally friendly biofuel production systems. We describe a biophysical modeling framework developed to understand and quantify the environmental value and impact (e.g. water balance, nutrients balance, carbon balance, and soil quality) of different biomass cropping systems. This modeling framework consists of three major components: 1) a Geographic Information System (GIS) based data processing system, 2) a spatially-explicit biophysical modeling approach, and 3) a user friendly information distribution system. First, we developed a GIS to manage the large amount of geospatial data (e.g. climate, land use, soil, and hydrograhy) and extract input information for the biophysical model. Second, the Environmental Policy Integrated Climate (EPIC) biophysical model is used to predict the impact of various cropping systems and management intensities on productivity, water balance, and biogeochemical variables. Finally, a geo-database is developed to distribute the results of ecosystem service variables (e.g. net primary productivity, soil carbon balance, soil erosion, nitrogen and phosphorus losses, and N2O fluxes) simulated by EPIC for each spatial modeling unit online using PostgreSQL. We applied this framework in a Regional Intensive Management Area (RIMA) of 9 counties in Michigan. A total of 4,833 spatial units with relatively homogeneous biophysical properties were derived using SSURGO, Crop Data Layer, County, and 10-digit watershed boundaries. For each unit, EPIC was executed from 1980 to 2003 under 54 cropping scenarios (eg. corn, switchgrass, and hybrid poplar). The simulation results were compared with historical crop yields from USDA NASS. Spatial mapping of the results show high variability among different cropping scenarios in terms of the simulated ecosystem services variables. Overall, the framework developed in this study enables the incorporation of environmental factors into economic and life-cycle analysis in order to optimize biomass cropping production scenarios.
Spatial distribution of sporocarps of stipitate hydnoid fungi and their belowground mycelium.
van der Linde, Sietse; Alexander, Ian J; Anderson, Ian C
2009-09-01
Interest in stipitate hydnoid fungi of the genera Bankera, Hydnellum, Phellodon and Sarcodon has increased due to the decline in numbers of sporocarps in Europe. Conservation of these fungi is hindered by a lack of understanding of their basic ecology. In particular, a better understanding of their belowground ecology is required. Real-time PCR in conjunction with spatially explicit sampling was used to quantify the relationship between sporocarps and mycelium of Hydnellum peckii and Phellodon tomentosus. Species-specific DNA of the target species was quantified in 100 soil samples collected on a 360 x 360 cm grid at five locations where sporocarps were present. All sporocarps within the grid and up to 2 m around the grid were mapped. Sporocarp production did not occur over the whole extent of the belowground mycelium of these two species, and mycelium extended up to 330 cm away from the immediate site of sporocarp production. Spatial analyses using Kernel-smoothing and Moran's I correlograms showed that, with a single exception, there was no quantitative relationship between sporocarp distribution and the belowground abundance of mycelium. These findings have important implications for the conservation of this rare group of fungi.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jager, Yetta; Efroymson, Rebecca Ann; Sublette, K.
Quantitative tools are needed to evaluate the ecological effects of increasing petroleum production. In this article, we describe two stochastic models for simulating the spatial distribution of brine spills on a landscape. One model uses general assumptions about the spatial arrangement of spills and their sizes; the second model distributes spills by siting rectangular well complexes and conditioning spill probabilities on the configuration of pipes. We present maps of landscapes with spills produced by the two methods and compare the ability of the models to reproduce a specified spill area. A strength of the models presented here is their abilitymore » to extrapolate from the existing landscape to simulate landscapes with a higher (or lower) density of oil wells.« less
Spatial fragment distribution from a therapeutic pencil-like carbon beam in water.
Matsufuji, Naruhiro; Komori, Masataka; Sasaki, Hitomi; Akiu, Kengo; Ogawa, Masako; Fukumura, Akifumi; Urakabe, Eriko; Inaniwa, Taku; Nishio, Teiji; Kohno, Toshiyuki; Kanai, Tatsuaki
2005-07-21
The latest heavy ion therapy tends to require information about the spatial distribution of the quality of radiation in a patient's body in order to make the best use of any potential advantage of swift heavy ions for the therapeutic treatment of a tumour. The deflection of incident particles is described well by Molière's multiple-scattering theory of primary particles; however, the deflection of projectile fragments is not yet thoroughly understood. This paper reports on our investigation of the spatial distribution of fragments produced from a therapeutic carbon beam through nuclear reactions in thick water. A DeltaE-E counter telescope system, composed of a plastic scintillator, a gas-flow proportional counter and a BGO scintillator, was rotated around a water target in order to measure the spatial distribution of the radiation quality. The results revealed that the observed deflection of fragment particles exceeded the multiple scattering effect estimated by Molière's theory. However, the difference can be sufficiently accounted for by considering one term involved in the multiple-scattering formula; this term corresponds to a lateral 'kick' at the point of production of the fragment. This kick is successfully explained as a transfer of the intra-nucleus Fermi momentum of a projectile to the fragment; the extent of the kick obeys the expectation derived from the Goldhaber model.
Sparrevik, Erik; Leonardsson, Kjell
1995-02-01
We performed laboratory experiments to investigate the effects of predator avoidance and numerical effects of predation on spatial distribution of small Saduria entomon (Isopoda) and Monoporeia affinis (Amphipoda), with large S. entomon as predators. The horizontal distribution and mortality of the prey species, separately and together, were studied in aquaria with a spatial horizontal refuge. We also estimated effects of refuge on mortality of small S. entomon and M. affinis by experiments without the refuge net. In addition, we investigated whether predation risk from large S. entomon influenced the swimming activity of M. affinis, to clarify the mechanisms behind the spatial distribution. Both small S. entomon and M. affinis avoided large S. entomon. The avoidance behaviour of M. fffinis contributed about 10 times more to the high proportion in the refuge than numerical effects of predation. Due to the low mortality of small S. entomon the avoidance behaviour of this species was even more important for the spatial distribution. The combined effect of avoidance behaviour and predation in both species was aggregation, producting a positive correlation between the species in density. M. affinis showed two types of avoidance behaviour. In the activity experiments they reduced activity by 36% and buried themselves in the sediment. In the refuge experiments we also observed avoidance behaviour with the emigration rate from the predator compartment being twice the immigration rate. The refuge did not lower predation mortality in M. affinis, probably due to the small scale of the experimental units in relation to the mobility of the species. Predation mortality in small S. entomon was higher in absence of a refuge and especially high in absence of M. affinis.
Simulation of multispectral multisource for device of consumer and medicine products analysis
NASA Astrophysics Data System (ADS)
Korolev, Timofey K.; Peretyagin, Vladimir S.
2017-06-01
One of the results of intensive development of led technology was the creation of a multi-component, managed devices and illumination/irradiation used in various fields of production (e.g., food industry analysis, food quality). The use of LEDs has become possible due to their structure determining spatial, energy, electrical, thermal and other characteristics. However, the development of the devices for illumination/irradiation require closer attention in the case if you want to provide precise illumination to the area of analysis, located at a specified distance from the radiation source. The present work is devoted to the development and modelling of a specialized source of radiation intended for solving problems of analysis of food products, medicines and water for suitability in drinking. In this work, we provided a mathematical model of spatial and spectral distribution of irridation from the source of infrared radiation ring structure. When you create this kind of source, you address factors such spectral component, the power settings, the spatial and energy components of the diodes.
Solution of multi-element LED light sources development automation problem
NASA Astrophysics Data System (ADS)
Chertov, Aleksandr N.; Gorbunova, Elena V.; Korotaev, Valery V.; Peretyagin, Vladimir S.
2014-09-01
The intensive development of LED technologies resulted in the creation of multicomponent light sources in the form of controlled illumination devices based on usage of mentioned LED technologies. These light sources are used in different areas of production (for example, in the food industry for sorting products or in the textile industry for quality control, etc.). The use of LED lighting products in the devices used in specialized lighting, became possible due to wide range of colors of light, LED structures (which determines the direction of radiation, the spatial distribution and intensity of the radiation, electrical, heat, power and other characteristics), and of course, the possibility of obtaining any shade in a wide dynamic range of brightness values. LED-based lighting devices are notable for the diversity of parameters and characteristics, such as color radiation, location and number of emitters, etc. Although LED technologies have several advantages, however, they require more attention if you need to ensure a certain character of illumination distribution and/or distribution of the color picture at a predetermined distance (for example, at flat surface, work zone, area of analysis or observation). This paper presents software designed for the development of the multicomponent LED light sources. The possibility of obtaining the desired color and energy distribution at the zone of analysis by specifying the spatial parameters of the created multicomponent light source and using of real power, spectral and color parameters and characteristics of the LEDs is shown as well.
Intertidal habitat utilization patterns of birds in a Northeast Pacific estuary
A habitat-based framework is a practical method for developing models (or, ecological production functions, EPFs) to describe the spatial distribution of ecosystem services. To generate EPFs for Yaquina estuary, Oregon, USA, we compared bird use patterns among intertidal habitats...
Anisotropy in Fracking: A Percolation Model for Observed Microseismicity
NASA Astrophysics Data System (ADS)
Norris, J. Quinn; Turcotte, Donald L.; Rundle, John B.
2015-01-01
Hydraulic fracturing (fracking), using high pressures and a low viscosity fluid, allow the extraction of large quantiles of oil and gas from very low permeability shale formations. The initial production of oil and gas at depth leads to high pressures and an extensive distribution of natural fractures which reduce the pressures. With time these fractures heal, sealing the remaining oil and gas in place. High volume fracking opens the healed fractures allowing the oil and gas to flow to horizontal production wells. We model the injection process using invasion percolation. We use a 2D square lattice of bonds to model the sealed natural fractures. The bonds are assigned random strengths and the fluid, injected at a point, opens the weakest bond adjacent to the growing cluster of opened bonds. Our model exhibits burst dynamics in which the clusters extend rapidly into regions with weak bonds. We associate these bursts with the microseismic activity generated by fracking injections. A principal object of this paper is to study the role of anisotropic stress distributions. Bonds in the y-direction are assigned higher random strengths than bonds in the x-direction. We illustrate the spatial distribution of clusters and the spatial distribution of bursts (small earthquakes) for several degrees of anisotropy. The results are compared with observed distributions of microseismicity in a fracking injection. Both our bursts and the observed microseismicity satisfy Gutenberg-Richter frequency-size statistics.
Adjemian, Jennifer C Z; Girvetz, Evan H; Beckett, Laurel; Foley, Janet E
2006-01-01
More than 20 species of fleas in California are implicated as potential vectors of Yersinia pestis. Extremely limited spatial data exist for plague vectors-a key component to understanding where the greatest risks for human, domestic animal, and wildlife health exist. This study increases the spatial data available for 13 potential plague vectors by using the ecological niche modeling system Genetic Algorithm for Rule-Set Production (GARP) to predict their respective distributions. Because the available sample sizes in our data set varied greatly from one species to another, we also performed an analysis of the robustness of GARP by using the data available for flea Oropsylla montana (Baker) to quantify the effects that sample size and the chosen explanatory variables have on the final species distribution map. GARP effectively modeled the distributions of 13 vector species. Furthermore, our analyses show that all of these modeled ranges are robust, with a sample size of six fleas or greater not significantly impacting the percentage of the in-state area where the flea was predicted to be found, or the testing accuracy of the model. The results of this study will help guide the sampling efforts of future studies focusing on plague vectors.
Estimation of Global 1km-grid Terrestrial Carbon Exchange Part II: Evaluations and Applications
NASA Astrophysics Data System (ADS)
Murakami, K.; Sasai, T.; Kato, S.; Niwa, Y.; Saito, M.; Takagi, H.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.; Yokota, T.
2015-12-01
Global terrestrial carbon cycle largely depends on a spatial pattern in land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.Global terrestrial carbon cycle largely depends on a spatial pattern of land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.
Digital Archive Issues from the Perspective of an Earth Science Data Producer
NASA Technical Reports Server (NTRS)
Barkstrom, Bruce R.
2004-01-01
Contents include the following: Introduction. A Producer Perspective on Earth Science Data. Data Producers as Members of a Scientific Community. Some Unique Characteristics of Scientific Data. Spatial and Temporal Sampling for Earth (or Space) Science Data. The Influence of the Data Production System Architecture. The Spatial and Temporal Structures Underlying Earth Science Data. Earth Science Data File (or Relation) Schemas. Data Producer Configuration Management Complexities. The Topology of Earth Science Data Inventories. Some Thoughts on the User Perspective. Science Data User Communities. Spatial and Temporal Structure Needs of Different Users. User Spatial Objects. Data Search Services. Inventory Search. Parameter (Keyword) Search. Metadata Searches. Documentation Search. Secondary Index Search. Print Technology and Hypertext. Inter-Data Collection Configuration Management Issues. An Archive View. Producer Data Ingest and Production. User Data Searching and Distribution. Subsetting and Supersetting. Semantic Requirements for Data Interchange. Tentative Conclusions. An Object Oriented View of Archive Information Evolution. Scientific Data Archival Issues. A Perspective on the Future of Digital Archives for Scientific Data. References Index for this paper.
Mutel, Christopher L; Pfister, Stephan; Hellweg, Stefanie
2012-01-17
We describe a new methodology for performing regionalized life cycle assessment and systematically choosing the spatial scale of regionalized impact assessment methods. We extend standard matrix-based calculations to include matrices that describe the mapping from inventory to impact assessment spatial supports. Uncertainty in inventory spatial data is modeled using a discrete spatial distribution function, which in a case study is derived from empirical data. The minimization of global spatial autocorrelation is used to choose the optimal spatial scale of impact assessment methods. We demonstrate these techniques on electricity production in the United States, using regionalized impact assessment methods for air emissions and freshwater consumption. Case study results show important differences between site-generic and regionalized calculations, and provide specific guidance for future improvements of inventory data sets and impact assessment methods.
Howard, Daniel M.; Wylie, Bruce K.; Tieszen, Larry L.
2012-01-01
With an ever expanding population, potential climate variability and an increasing demand for agriculture-based alternative fuels, accurate agricultural land-cover classification for specific crops and their spatial distributions are becoming critical to researchers, policymakers, land managers and farmers. It is important to ensure the sustainability of these and other land uses and to quantify the net impacts that certain management practices have on the environment. Although other quality crop classification products are often available, temporal and spatial coverage gaps can create complications for certain regional or time-specific applications. Our goal was to develop a model capable of classifying major crops in the Greater Platte River Basin (GPRB) for the post-2000 era to supplement existing crop classification products. This study identifies annual spatial distributions and area totals of corn, soybeans, wheat and other crops across the GPRB from 2000 to 2009. We developed a regression tree classification model based on 2.5 million training data points derived from the National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) in relation to a variety of other relevant input environmental variables. The primary input variables included the weekly 250 m US Geological Survey Earth Observing System Moderate Resolution Imaging Spectroradiometer normalized differential vegetation index, average long-term growing season temperature, average long-term growing season precipitation and yearly start of growing season. An overall model accuracy rating of 78% was achieved for a test sample of roughly 215 000 independent points that were withheld from model training. Ten 250 m resolution annual crop classification maps were produced and evaluated for the GPRB region, one for each year from 2000 to 2009. In addition to the model accuracy assessment, our validation focused on spatial distribution and county-level crop area totals in comparison with the NASS CDL and county statistics from the US Department of Agriculture (USDA) Census of Agriculture. The results showed that our model produced crop classification maps that closely resembled the spatial distribution trends observed in the NASS CDL and exhibited a close linear agreement with county-by-county crop area totals from USDA census data (R 2 = 0.90).
Dauner, Ana Lúcia L; Martins, César C
2015-12-01
Guaratuba Bay, a subtropical estuary located in the SW Atlantic, is under variable anthropogenic pressure throughout the year. Samples of surficial suspended particulate matter (SPM) were collected at 22 sites during three different periods to evaluate the temporal and spatial variability of aliphatic hydrocarbons (AHs) and linear alkylbenzenes (LABs). These compounds were determined by gas chromatography with flame ionization detection (GC-FID) and mass spectrometry (GC/MS). The spatial distributions of both compound classes were similar and varied among the sampling campaigns. Generally, the highest concentrations were observed during the austral summer, highlighting the importance of the increased human influence during this season. The compound distributions were also affected by the natural geochemical processes of organic matter accumulation. AHs were associated with petroleum, derived from boat and vehicle traffic, and biogenic sources, related to mangrove forests and autochthonous production. The LAB composition evidenced preferential degradation processes during the austral summer. Copyright © 2015 Elsevier B.V. All rights reserved.
A hydrological emulator for global applications – HE v1.0.0
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Yaling; Hejazi, Mohamad; Li, Hongyi
While global hydrological models (GHMs) are very useful in exploring water resources and interactions between the Earth and human systems, their use often requires numerous model inputs, complex model calibration, and high computation costs. To overcome these challenges, we construct an efficient open-source and ready-to-use hydrological emulator (HE) that can mimic complex GHMs at a range of spatial scales (e.g., basin, region, globe). More specifically, we construct both a lumped and a distributed scheme of the HE based on the monthly abcd model to explore the tradeoff between computational cost and model fidelity. Model predictability and computational efficiency are evaluatedmore » in simulating global runoff from 1971 to 2010 with both the lumped and distributed schemes. The results are compared against the runoff product from the widely used Variable Infiltration Capacity (VIC) model. Our evaluation indicates that the lumped and distributed schemes present comparable results regarding annual total quantity, spatial pattern, and temporal variation of the major water fluxes (e.g., total runoff, evapotranspiration) across the global 235 basins (e.g., correlation coefficient r between the annual total runoff from either of these two schemes and the VIC is > 0.96), except for several cold (e.g., Arctic, interior Tibet), dry (e.g., North Africa) and mountainous (e.g., Argentina) regions. Compared against the monthly total runoff product from the VIC (aggregated from daily runoff), the global mean Kling–Gupta efficiencies are 0.75 and 0.79 for the lumped and distributed schemes, respectively, with the distributed scheme better capturing spatial heterogeneity. Notably, the computation efficiency of the lumped scheme is 2 orders of magnitude higher than the distributed one and 7 orders more efficient than the VIC model. A case study of uncertainty analysis for the world's 16 basins with top annual streamflow is conducted using 100 000 model simulations, and it demonstrates the lumped scheme's extraordinary advantage in computational efficiency. Lastly, our results suggest that the revised lumped abcd model can serve as an efficient and reasonable HE for complex GHMs and is suitable for broad practical use, and the distributed scheme is also an efficient alternative if spatial heterogeneity is of more interest.« less
Spatial Downscaling of TRMM Precipitation using MODIS product in the Korean Peninsula
NASA Astrophysics Data System (ADS)
Cho, H.; Choi, M.
2013-12-01
Precipitation is a major driving force in the water cycle. But, it is difficult to provide spatially distributed precipitation data from isolated individual in situ. The Tropical Rainfall Monitoring Mission (TRMM) satellite can provide precipitation data with relatively coarse spatial resolution (0.25° scale) at daily basis. In order to overcome the coarse spatial resolution of TRMM precipitation products, we conducted a downscaling technique using a scaling parameter from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor. In this study, statistical relations between precipitation estimates derived from the TRMM satellite and the normalized difference vegetation index (NDVI) which is obtained from the MODIS sensor in TERRA satellite are found for different spatial scales on the Korean peninsula in northeast Asia. We obtain the downscaled precipitation mapping by regression equation between yearly TRMM precipitations values and annual average NDVI aggregating 1km to 25 degree. The downscaled precipitation is validated using time series of the ground measurements precipitation dataset provided by Korea Meteorological Organization (KMO) from 2002 to 2005. To improve the spatial downscaling of precipitation, we will conduct a study about correlation between precipitation and land surface temperature, perceptible water and other hydrological parameters.
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.
Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui
2016-04-19
Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province.
Zhao, Yan; Bai, Linyan; Feng, Jianzhong; Lin, Xiaosong; Wang, Li; Xu, Lijun; Ran, Qiyun; Wang, Kui
2016-01-01
Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province. PMID:27104536
Turner, D.P.; Dodson, R.; Marks, D.
1996-01-01
Spatially distributed biogeochemical models may be applied over grids at a range of spatial resolutions, however, evaluation of potential errors and loss of information at relatively coarse resolutions is rare. In this study, a georeferenced database at the 1-km spatial resolution was developed to initialize and drive a process-based model (Forest-BGC) of water and carbon balance over a gridded 54976 km2 area covering two river basins in mountainous western Oregon. Corresponding data sets were also prepared at 10-km and 50-km spatial resolutions using commonly employed aggregation schemes. Estimates were made at each grid cell for climate variables including daily solar radiation, air temperature, humidity, and precipitation. The topographic structure, water holding capacity, vegetation type and leaf area index were likewise estimated for initial conditions. The daily time series for the climatic drivers was developed from interpolations of meteorological station data for the water year 1990 (1 October 1989-30 September 1990). Model outputs at the 1-km resolution showed good agreement with observed patterns in runoff and productivity. The ranges for model inputs at the 10-km and 50-km resolutions tended to contract because of the smoothed topography. Estimates for mean evapotranspiration and runoff were relatively insensitive to changing the spatial resolution of the grid whereas estimates of mean annual net primary production varied by 11%. The designation of a vegetation type and leaf area at the 50-km resolution often subsumed significant heterogeneity in vegetation, and this factor accounted for much of the difference in the mean values for the carbon flux variables. Although area wide means for model outputs were generally similar across resolutions, difference maps often revealed large areas of disagreement. Relatively high spatial resolution analyses of biogeochemical cycling are desirable from several perspectives and may be particularly important in the study of the potential impacts of climate change.
Singh, Anuradha; Mantri, Shrikant; Sharma, Monica; Chaudhury, Ashok; Tuli, Rakesh; Roy, Joy
2014-01-16
The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT-PCR. Therefore, this study identified several quality related key genes including many other genes, their interactions (quality x development) and temporal and spatial distributions. The candidate genes identified for processing quality and information on temporal and spatial distributions of their expressions would be useful for designing wheat improvement programs for processing quality either by changing their expression or development of single nucleotide polymorphisms (SNPs) markers.
2014-01-01
Background The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. Results Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT-PCR. Therefore, this study identified several quality related key genes including many other genes, their interactions (quality x development) and temporal and spatial distributions. Conclusions The candidate genes identified for processing quality and information on temporal and spatial distributions of their expressions would be useful for designing wheat improvement programs for processing quality either by changing their expression or development of single nucleotide polymorphisms (SNPs) markers. PMID:24433256
Guarini, Jean-Marc; Cloern, James E.; Edmunds, Jody L.; Gros, Philippe
2002-01-01
In this paper we describe a three-step procedure to infer the spatial heterogeneity in microphytobenthos primary productivity at the scale of tidal estuaries and embayments. The first step involves local measurement of the carbon assimilation rate of benthic microalgae to determine the parameters of the photosynthesis-irradiance (P-E) curves (using non-linear optimization methods). In the next step, a resampling technique is used to rebuild pseudo-sampling distributions of the local productivity estimates; these provide error estimates for determining the significance level of differences between sites. The third step combines the previous results with deterministic models of tidal elevation and solar irradiance to compute mean and variance of the daily areal primary productivity over an entire intertidal mudflat area within each embayment. This scheme was applied on three different intertidal mudflat regions of the San Francisco Bay estuary during autumn 1998. Microphytobenthos productivity exhibits strong (ca. 3-fold) significant differences among the major sub-basins of San Francisco Bay. This spatial heterogeneity is attributed to two main causes: significant differences in the photosynthetic competence (P-E parameters) of the microphytobenthos in the different sub-basins, and spatial differences in the phase shifts between the tidal and solar cycles controlling the exposure of intertidal areas to sunlight. The procedure is general and can be used in other estuaries to assess the magnitude and patterns of spatial variability of microphytobenthos productivity at the level of the ecosystems.
Guarini, J.-M.; Cloern, James E.; Edmunds, J.
2002-01-01
In this paper we describe a three-step procedure to infer the spatial heterogeneity in microphytobenthos primary productivity at the scale of tidal estuaries and embayments. The first step involves local measurement of the carbon assimilation rate of benthic microalgae to determine the parameters of the photosynthesis-irradiance (P-E) curves (using non-linear optimization methods). In the next step, a resampling technique is used to rebuild pseudo-sampling distributions of the local productivity estimates; these provide error estimates for determining the significance level of differences between sites. The third step combines the previous results with deterministic models of tidal elevation and solar irradiance to compute mean and variance of the daily areal primary productivity over an entire intertidal mudflat area within each embayment. This scheme was applied on three different intertidal mudflat regions of the San Francisco Bay estuary during autumn 1998. Microphytobenthos productivity exhibits strong (ca. 3-fold) significant differences among the major sub-basins of San Francisco Bay. This spatial heterogeneity is attributed to two main causes: significant differences in the photosynthetic competence (P-E parameters) of the microphytobenthos in the different sub-basins, and spatial differences in the phase shifts between the tidal and solar cycles controlling the exposure of intertidal areas to sunlight. The procedure is general and can be used in other estuaries to assess the magnitude and patterns of spatial variability of microphytobenthos productivity at the level of the ecosystems.
NASA Astrophysics Data System (ADS)
Bookhagen, B.; Boers, N.; Marwan, N.; Malik, N.; Kurths, J.
2013-12-01
Monsoonal rainfall is the crucial component for more than half of the world's population. Runoff associated with monsoon systems provide water resources for agriculture, hydropower, drinking-water generation, recreation, and social well-being and are thus a fundamental part of human society. However, monsoon systems are highly stochastic and show large variability on various timescales. Here, we use various rainfall datasets to characterize spatiotemporal rainfall patterns using traditional as well as new approaches emphasizing nonlinear spatial correlations from a complex networks perspective. Our analyses focus on the South American (SAMS) and Indian (ISM) Monsoon Systems on the basis of Tropical Rainfall Measurement Mission (TRMM) using precipitation radar and passive-microwave products with horizontal spatial resolutions of ~5x5 km^2 (products 2A25, 2B31) and 25x25 km^2 (3B42) and interpolated rainfall-gauge data for the ISM (APHRODITE, 25x25 km^2). The eastern slopes of the Andes of South America and the southern front of the Himalaya are characterized by significant orographic barriers that intersect with the moisture-bearing, monsoonal wind systems. We demonstrate that topography exerts a first-order control on peak rainfall amounts on annual timescales in both mountain belts. Flooding in the downstream regions is dominantly caused by heavy rainfall storms that propagate deep into the mountain range and reach regions that are arid and without vegetation cover promoting rapid runoff. These storms exert a significantly different spatial distribution than average-rainfall conditions and assessing their recurrence intervals and prediction is key in understanding flooding for these regions. An analysis of extreme-value distributions of our high-spatial resolution data reveal that semi-arid areas are characterized by low-frequency/high-magnitude events (i.e., are characterized by a ';heavy tail' distribution), whereas regions with high mean annual rainfall have a less skewed distribution. In a second step, an analysis of the spatial characteristics of extreme rainfall synchronicity by means of complex networks reveals patterns of the propagation of extreme rainfall events. These patterns differ substantially from those obtained from the mean annual rainfall distribution. In addition, we have developed a scheme to predict rainfall extreme events in the eastern Central Andes based on event synchronization and spatial patterns of complex networks. The presented methods and result will allow to critically evaluate data and models in space and time.
Landscape-Scale water balance of cotton fields
USDA-ARS?s Scientific Manuscript database
Information on the temporal and spatial distribution of the components of the water balance of a production field is necessary to manage agronomic inputs. Furthermore, factors that determine crop yield require knowledge of the energy, water, nutrient and carbon balance and their interaction. The in...
A Satellite-Based Lagrangian View on Phytoplankton Dynamics
NASA Astrophysics Data System (ADS)
Lehahn, Yoav; d'Ovidio, Francesco; Koren, Ilan
2018-01-01
The well-lit upper layer of the open ocean is a dynamical environment that hosts approximately half of global primary production. In the remote parts of this environment, distant from the coast and from the seabed, there is no obvious spatially fixed reference frame for describing the dynamics of the microscopic drifting organisms responsible for this immense production of organic matter—the phytoplankton. Thus, a natural perspective for studying phytoplankton dynamics is to follow the trajectories of water parcels in which the organisms are embedded. With the advent of satellite oceanography, this Lagrangian perspective has provided valuable information on different aspects of phytoplankton dynamics, including bloom initiation and termination, spatial distribution patterns, biodiversity, export of carbon to the deep ocean, and, more recently, bottom-up mechanisms that affect the distribution and behavior of higher-trophic-level organisms. Upcoming submesoscale-resolving satellite observations and swarms of autonomous platforms open the way to the integration of vertical dynamics into the Lagrangian view of phytoplankton dynamics.
A Satellite-Based Lagrangian View on Phytoplankton Dynamics.
Lehahn, Yoav; d'Ovidio, Francesco; Koren, Ilan
2018-01-03
The well-lit upper layer of the open ocean is a dynamical environment that hosts approximately half of global primary production. In the remote parts of this environment, distant from the coast and from the seabed, there is no obvious spatially fixed reference frame for describing the dynamics of the microscopic drifting organisms responsible for this immense production of organic matter-the phytoplankton. Thus, a natural perspective for studying phytoplankton dynamics is to follow the trajectories of water parcels in which the organisms are embedded. With the advent of satellite oceanography, this Lagrangian perspective has provided valuable information on different aspects of phytoplankton dynamics, including bloom initiation and termination, spatial distribution patterns, biodiversity, export of carbon to the deep ocean, and, more recently, bottom-up mechanisms that affect the distribution and behavior of higher-trophic-level organisms. Upcoming submesoscale-resolving satellite observations and swarms of autonomous platforms open the way to the integration of vertical dynamics into the Lagrangian view of phytoplankton dynamics.
NASA Astrophysics Data System (ADS)
McGuire, K. J.; Bailey, S. W.; Ross, D. S.
2017-12-01
Heterogeneity in biophysical properties within catchments challenges how we quantify and characterize biogeochemical processes and interpret catchment outputs. Interactions between the spatiotemporal variability of hydrological states and fluxes and soil development can spatially structure catchments, leading to a framework for understanding patterns in biogeochemical processes. In an upland, glaciated landscape at the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, we are embracing the structure and organization of soils to understand the spatial relations between runoff production zones, distinct soil-biogeochemical environments, and solute retention and release. This presentation will use observations from the HBEF to demonstrate that a soil-landscape framework is essential in understanding the spatial and temporal variability of biogeochemical processes in this catchment. Specific examples will include how laterally developed soils reveal the location of active runoff production zones and lead to gradients in primary mineral dissolution and the distribution of weathering products along hillslopes. Soil development patterns also highlight potential carbon and nitrogen cycling hotspots, differentiate acidic conditions, and affect the regulation of surface water quality. Overall, this work demonstrates the importance of understanding the landscape-level structural organization of soils in characterizing the variation and extent of biogeochemical processes that occur in catchments.
Ou, Jinpei; Liu, Xiaoping; Li, Xia; Li, Meifang; Li, Wenkai
2015-01-01
Recently, the stable light products and radiance calibrated products from Defense Meteorological Satellite Program's (DMSP) Operational Linescan System (OLS) have been useful for mapping global fossil fuel carbon dioxide (CO2) emissions at fine spatial resolution. However, few studies on this subject were conducted with the new-generation nighttime light data from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite, which has a higher spatial resolution and a wider radiometric detection range than the traditional DMSP-OLS nighttime light data. Therefore, this study performed the first evaluation of the potential of NPP-VIIRS data in estimating the spatial distributions of global CO2 emissions (excluding power plant emissions). Through a disaggregating model, three global emission maps were then derived from population counts and three different types of nighttime lights data (NPP-VIIRS, the stable light data and radiance calibrated data of DMSP-OLS) for a comparative analysis. The results compared with the reference data of land cover in Beijing, Shanghai and Guangzhou show that the emission areas of map from NPP-VIIRS data have higher spatial consistency of the artificial surfaces and exhibit a more reasonable distribution of CO2 emission than those of other two maps from DMSP-OLS data. Besides, in contrast to two maps from DMSP-OLS data, the emission map from NPP-VIIRS data is closer to the Vulcan inventory and exhibits a better agreement with the actual statistical data of CO2 emissions at the level of sub-administrative units of the United States. This study demonstrates that the NPP-VIIRS data can be a powerful tool for studying the spatial distributions of CO2 emissions, as well as the socioeconomic indicators at multiple 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.
Ou, Jinpei; Liu, Xiaoping; Li, Xia; Li, Meifang; Li, Wenkai
2015-01-01
Recently, the stable light products and radiance calibrated products from Defense Meteorological Satellite Program’s (DMSP) Operational Linescan System (OLS) have been useful for mapping global fossil fuel carbon dioxide (CO2) emissions at fine spatial resolution. However, few studies on this subject were conducted with the new-generation nighttime light data from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite, which has a higher spatial resolution and a wider radiometric detection range than the traditional DMSP-OLS nighttime light data. Therefore, this study performed the first evaluation of the potential of NPP-VIIRS data in estimating the spatial distributions of global CO2 emissions (excluding power plant emissions). Through a disaggregating model, three global emission maps were then derived from population counts and three different types of nighttime lights data (NPP-VIIRS, the stable light data and radiance calibrated data of DMSP-OLS) for a comparative analysis. The results compared with the reference data of land cover in Beijing, Shanghai and Guangzhou show that the emission areas of map from NPP-VIIRS data have higher spatial consistency of the artificial surfaces and exhibit a more reasonable distribution of CO2 emission than those of other two maps from DMSP-OLS data. Besides, in contrast to two maps from DMSP-OLS data, the emission map from NPP-VIIRS data is closer to the Vulcan inventory and exhibits a better agreement with the actual statistical data of CO2 emissions at the level of sub-administrative units of the United States. This study demonstrates that the NPP-VIIRS data can be a powerful tool for studying the spatial distributions of CO2 emissions, as well as the socioeconomic indicators at multiple scales. PMID:26390037
Tracking historical increases in nitrogen-driven crop production possibilities
NASA Astrophysics Data System (ADS)
Mueller, N. D.; Lassaletta, L.; Billen, G.; Garnier, J.; Gerber, J. S.
2015-12-01
The environmental costs of nitrogen use have prompted a focus on improving the efficiency of nitrogen use in the global food system, the primary source of nitrogen pollution. Typical approaches to improving agricultural nitrogen use efficiency include more targeted field-level use (timing, placement, and rate) and modification of the crop mix. However, global efficiency gains can also be achieved by improving the spatial allocation of nitrogen between regions or countries, due to consistent diminishing returns at high nitrogen use. This concept is examined by constructing a tradeoff frontier (or production possibilities frontier) describing global crop protein yield as a function of applied nitrogen from all sources, given optimal spatial allocation. Yearly variation in country-level input-output nitrogen budgets are utilized to parameterize country-specific hyperbolic yield-response models. Response functions are further characterized for three ~15-year eras beginning in 1961, and series of calculations uses these curves to simulate optimal spatial allocation in each era and determine the frontier. The analyses reveal that excess nitrogen (in recent years) could be reduced by ~40% given optimal spatial allocation. Over time, we find that gains in yield potential and in-country nitrogen use efficiency have led to increases in the global nitrogen production possibilities frontier. However, this promising shift has been accompanied by an actual spatial distribution of nitrogen use that has become less optimal, in an absolute sense, relative to the frontier. We conclude that examination of global production possibilities is a promising approach to understanding production constraints and efficiency opportunities in the global food system.
Wang, Chengdong; Zhang, Shenyan; Yan, Wanglin; Wang, Renqing; Liu, Jian; Wang, Yutao
2016-11-18
Renewable natural resources, such as solar radiation, rainfall, wind, and geothermal heat, together with ecosystem services, provide the elementary supports for the sustainable development of human society. To improve regional sustainability, we studied the spatial distributions and quantities of renewable natural resources and net primary productivity (NPP) in Hokkaido, which is the second largest island of Japan. With the help of Geographic Information System (GIS) software, distribution maps for each type of renewable natural resource were generated by kriging interpolation based on statistical records. A composite map of the flow of all types of renewable natural resources was also generated by map layer overlapping. Additionally, we utilized emergy analysis to convert each renewable flow with different attributes into a unified unit (i.e., solar equivalent joules [sej]). As a result, the spatial distributions of the flow of renewable natural resources of the Hokkaido region are presented in the form of thematic emergy maps. Thus, the areas with higher renewable emergy can be easily visualized and identified. The dominant renewable flow in certain areas can also be directly distinguished. The results can provide useful information for regional sustainable development, environmental conservation and ecological management.
Wang, Chengdong; Zhang, Shenyan; Yan, Wanglin; Wang, Renqing; Liu, Jian; Wang, Yutao
2016-01-01
Renewable natural resources, such as solar radiation, rainfall, wind, and geothermal heat, together with ecosystem services, provide the elementary supports for the sustainable development of human society. To improve regional sustainability, we studied the spatial distributions and quantities of renewable natural resources and net primary productivity (NPP) in Hokkaido, which is the second largest island of Japan. With the help of Geographic Information System (GIS) software, distribution maps for each type of renewable natural resource were generated by kriging interpolation based on statistical records. A composite map of the flow of all types of renewable natural resources was also generated by map layer overlapping. Additionally, we utilized emergy analysis to convert each renewable flow with different attributes into a unified unit (i.e., solar equivalent joules [sej]). As a result, the spatial distributions of the flow of renewable natural resources of the Hokkaido region are presented in the form of thematic emergy maps. Thus, the areas with higher renewable emergy can be easily visualized and identified. The dominant renewable flow in certain areas can also be directly distinguished. The results can provide useful information for regional sustainable development, environmental conservation and ecological management. PMID:27857230
Magalhães, A; Costa, R M; Liang, T H; Pereira, L C C; Ribeiro, M J S
2006-05-01
Spatial and temporal density and biomass distribution of the planktonic copepods Pseudodiaptomus richardi and P. acutus along a salinity gradient were investigated in the Caeté River Estuary (North-Brazil) in June and December, 1998 (dry season) and in February and May, 1999 (rainy season). Copepod biomass was estimated using regression parameters based on the relation of dry weight and body length (prosome) of adult organisms. The Caeté River Estuary was characterized by high spatial and temporal variations in salinity (0.8-37.2). Exponential length-weight relationships were observed for both Pseudodiaptomus species. Density and biomass values oscillated between 0.28-46.18 ind. m-3 and 0.0022-0.3507 mg DW. m-3 for P. richardi; and between 0.01-17.02 ind. m-3 and 0.0005-0.7181 mg DW. m-3 for P. acutus. The results showed that the contribution of P. richardi for the secondary production in the Caeté River Estuary is more important in the limnetic zone than in other zones where euhaline-polyhaline regimes were predominant. However, it was not possible to observe a clear pattern of spatial and temporal distribution for P. acutus.
Tao, Shu; Li, Xinrong; Yang, Yu; Coveney, Raymond M; Lu, Xiaoxia; Chen, Haitao; Shen, Weiran
2006-08-01
A USEPA, procedure, ISCLT3 (Industrial Source Complex Long-Term), was applied to model the spatial distribution of polycyclic aromatic hydrocarbons (PAHs) emitted from various sources including coal, petroleum, natural gas, and biomass into the atmosphere of Tianjin, China. Benzo[a]pyrene equivalent concentrations (BaPeq) were calculated for risk assessment. Model results were provisionally validated for concentrations and profiles based on the observed data at two monitoring stations. The dominant emission sources in the area were domestic coal combustion, coke production, and biomass burning. Mainly because of the difference in the emission heights, the contributions of various sources to the average concentrations at receptors differ from proportions emitted. The shares of domestic coal increased from approximately 43% at the sources to 56% at the receptors, while the contributions of coking industry decreased from approximately 23% at the sources to 7% at the receptors. The spatial distributions of gaseous and particulate PAHs were similar, with higher concentrations occurring within urban districts because of domestic coal combustion. With relatively smaller contributions, the other minor sources had limited influences on the overall spatial distribution. The calculated average BaPeq value in air was 2.54 +/- 2.87 ng/m3 on an annual basis. Although only 2.3% of the area in Tianjin exceeded the national standard of 10 ng/m3, 41% of the entire population lives within this area.
NASA Astrophysics Data System (ADS)
Othman, A.; Sultan, M.; Ahmed, M.; Alharbi, T.; Gebremichael, E.; Emil, M.
2015-12-01
Recent land subsidence incidences in the Kingdom of Saudi Arabia (KSA) resulted in loss in life and property. In this study, an integrated approach is adopted to accomplish the following: (1) map the spatial distribution of areas that are witnessing land subsidence, (2) quantify the rates of land subsidence, and (3) identify the factors causing the observed subsidence. A three-fold approach is applied: (1) use of interferometric techniques to assess the spatial distribution of land subsidence and to quantify the rates of subsidence, (2) generate a GIS database to encompass all relevant data and derived products, and (3) correlate findings from the radar exercise with relevant spatial and temporal datasets (e.g., remote sensing, geology, fluid extraction rates, distribution of urban areas, etc.). Three main areas were selected: (1) central and northern parts of the KSA, (2) areas surrounding the Ghawar oil/gas field, and (3) the Harrat Lunayyir volcanic field. Applications of two-pass, three-pass, and SBAS radar interferometric techniques over central KSA revealed the following: (1) subsidence rates of up to -15 mm/yr were detected; the spatial distribution of the subsided areas that were extracted using the various interferometric techniques are similar, (2) subsided areas correlated spatially with the distribution of: (a) areas with high groundwater extraction rates as evidenced from the analysis of field and Gravity Recovery and Climate Experiment (GRACE) data, (b) agricultural plantations as evidenced from the analysis of field and temporal Landsat data, (c) urban areas (e.g., Buraydah City), (d) outcrops of carbonates and anhydrite formations (e.g., Khuff and Jilh formations), (3) subsidence could be related to more than one parameter. Similar research activities are underway in northern KSA and in areas surrounding the Ghawar oil/gas and the Harrat Lunayyir volcanic fields to assess the distribution and factors controlling land deformation in those areas.
NASA Astrophysics Data System (ADS)
Priegnitz, Mike; Thaler, Jan; Spangenberg, Erik; Schicks, Judith M.; Abendroth, Sven
2014-05-01
The German gas hydrate project SUGAR studies innovative methods and approaches to be applied in the production of methane from hydrate-bearing reservoirs. To enable laboratory studies in pilot scale, a large reservoir simulator (LARS) was realized allowing for the formation and dissociation of gas hydrates under simulated in-situ conditions. LARS is equipped with a series of sensors. This includes a cylindrical electrical resistance tomography (ERT) array composed of 25 electrode rings featuring 15 electrodes each. The high-resolution ERT array is used to monitor the spatial distribution of the electrical resistivity during hydrate formation and dissociation experiments over time. As the present phases of poorly conducting sediment, well conducting pore fluid, non-conducting hydrates, and isolating free gas cover a wide range of electrical properties, ERT measurements enable us to monitor the spatial distribution of these phases during the experiments. In order to investigate the hydrate dissociation and the resulting fluid flow, we simulated a hydrate production test in LARS that was based on the Mallik gas hydrate production test (see abstract Heeschen et al., this volume). At first, a hydrate phase was produced from methane saturated saline water. During the two months of gas hydrate production we measured the electrical properties within the sediment sample every four hours. These data were used to establish a routine estimating both the local degrees of hydrate saturation and the resulting local permeabilities in the sediment's pore space from the measured resistivity data. The final gas hydrate saturation filled 89.5% of the total pore space. During hydrate dissociation, ERT data do not allow for a quantitative determination of free gas and remaining gas hydrates since both phases are electrically isolating. However, changes are resolved in the spatial distribution of the conducting liquid and the isolating phase with gas being the only mobile isolating phase. Hence, it is possible to detect areas in the sediment sample where free gas is released due to hydrate dissociation and displaces the liquid phase. Combined with measurements and numerical simulation of the total two-phase fluxes from the sediment sample (see abstract Abendroth et al., this volume), the LARS experiments allow for detailed information on the dissociation process during hydrate production. Here we present the workflow and first results estimating local hydrate saturations and permeabilities during hydrate formation and the movement of liquid and gas phases during hydrate dissociation, respectively.
Ponderomotive effects in multiphoton pair production
NASA Astrophysics Data System (ADS)
Kohlfürst, Christian; Alkofer, Reinhard
2018-02-01
The Dirac-Heisenberg-Wigner formalism is employed to investigate electron-positron pair production in cylindrically symmetric but otherwise spatially inhomogeneous, oscillating electric fields. The oscillation frequencies are hereby tuned to obtain multiphoton pair production in the nonperturbative threshold regime. An effective mass, as well as a trajectory-based semiclassical analysis, is introduced in order to interpret the numerical results for the distribution functions as well as for the particle yields and spectra. The results, including the asymptotic particle spectra, display clear signatures of ponderomotive forces.
Wolcott, J.; Aliaga, L.; Altinok, O.; ...
2016-09-01
Here, the MINERvA experiment observes an excess of events containing electromagnetic showers relative to the expectation from Monte Carlo simulations in neutral-current neutrino interactions with mean beam energy of 4.5 GeV on a hydrocarbon target. The excess is characterized and found to be consistent with neutral-current π 0 production with a broad energy distribution peaking at 7 GeV and a total cross section of 0.26more » $$\\pm$$ 0.02 (stat) $$\\pm$$ 0.08 (sys) x $$10^{-39} cm^{2}$$. The angular distribution, electromagnetic shower energy, and spatial distribution of the energy depositions of the excess are consistent with expectations from neutrino neutral-current diffractive neutral pion production from hydrogen in the hydrocarbon target. These data comprise the first direct experimental observation and constraint for a reaction that poses an important background process in neutrino oscillation experiments searching for $$\
Seismicity and source spectra analysis in Salton Sea Geothermal Field
NASA Astrophysics Data System (ADS)
Cheng, Y.; Chen, X.
2016-12-01
The surge of "man-made" earthquakes in recent years has led to considerable concerns about the associated hazards. Improved monitoring of small earthquakes would significantly help understand such phenomena and the underlying physical mechanisms. In the Salton Sea Geothermal field in southern California, open access of a local borehole network provides a unique opportunity to better understand the seismicity characteristics, the related earthquake hazards, and the relationship with the geothermal system, tectonic faulting and other physical conditions. We obtain high-resolution earthquake locations in the Salton Sea Geothermal Field, analyze characteristics of spatiotemporal isolated earthquake clusters, magnitude-frequency distributions and spatial variation of stress drops. The analysis reveals spatial coherent distributions of different types of clustering, b-value distributions, and stress drop distribution. The mixture type clusters (short-duration rapid bursts with high aftershock productivity) are predominately located within active geothermal field that correlate with high b-value, low stress drop microearthquake clouds, while regular aftershock sequences and swarms are distributed throughout the study area. The differences between earthquakes inside and outside of geothermal operation field suggest a possible way to distinguish directly induced seismicity due to energy operation versus typical seismic slip driven sequences. The spatial coherent b-value distribution enables in-situ estimation of probabilities for M≥3 earthquakes, and shows that the high large-magnitude-event (LME) probability zones with high stress drop are likely associated with tectonic faulting. The high stress drop in shallow (1-3 km) depth indicates the existence of active faults, while low stress drops near injection wells likely corresponds to the seismic response to fluid injection. I interpret the spatial variation of seismicity and source characteristics as the result of fluid circulation, the fracture network, and tectonic faulting.
Estimation of Fractional Plant Lifeform Cover Using Landsat and Airborne LiDAR/hyperspectral Data
NASA Astrophysics Data System (ADS)
Parra, A. S.; Xu, Q.; Dilts, T.; Weisberg, P.; Greenberg, J. A.
2017-12-01
Land-cover change has generally been understood as the result of local, landscape or regional-scale processes with most studies focusing on case-study landscapes or smaller regions. However, as we observe similar types of land-cover change occurring across different biomes worldwide, it becomes clear that global-scale processes such as climate change and CO2 fertilization, in interaction with local influences, are underlying drivers in land-cover change patterns. Prior studies on global land-cover change may not have had a suitable spatial, temporal and thematic resolution for allowing the identification of such patterns. Furthermore, the lack of globally consistent spatial data products also constitutes a limiting factor in evaluating both proximate and ultimate causes of land-cover change. In this study, we derived a global model for broadleaf tree, needleleaf tree, shrub, herbaceous, and "other" fractional cover using Landsat imagery. Combined LiDAR/hyperspectral data sets were used for calibration and validation of the Landsat-derived products. Spatially explicit uncertainties were also created as part of the data products. Our results highlight the potential for large-scale studies that model local and global influences on land-cover transition types and rates at fine thematic, spatial, and temporal resolutions. These spatial data products are relevant for identifying patterns in land-cover change due to underlying global-scale processes and can provide valuable insights into climatic and land-use factors determining vegetation distributions.
Predator-guided sampling reveals biotic structure in the bathypelagic.
Benoit-Bird, Kelly J; Southall, Brandon L; Moline, Mark A
2016-02-24
We targeted a habitat used differentially by deep-diving, air-breathing predators to empirically sample their prey's distributions off southern California. Fine-scale measurements of the spatial variability of potential prey animals from the surface to 1,200 m were obtained using conventional fisheries echosounders aboard a surface ship and uniquely integrated into a deep-diving autonomous vehicle. Significant spatial variability in the size, composition, total biomass, and spatial organization of biota was evident over all spatial scales examined and was consistent with the general distribution patterns of foraging Cuvier's beaked whales (Ziphius cavirostris) observed in separate studies. Striking differences found in prey characteristics between regions at depth, however, did not reflect differences observed in surface layers. These differences in deep pelagic structure horizontally and relative to surface structure, absent clear physical differences, change our long-held views of this habitat as uniform. The revelation that animals deep in the water column are so spatially heterogeneous at scales from 10 m to 50 km critically affects our understanding of the processes driving predator-prey interactions, energy transfer, biogeochemical cycling, and other ecological processes in the deep sea, and the connections between the productive surface mixed layer and the deep-water column. © 2016 The Author(s).
A dam-reservoir module for a semi-distributed hydrological model
NASA Astrophysics Data System (ADS)
de Lavenne, Alban; Thirel, Guillaume; Andréassian, Vazken; Perrin, Charles; Ramos, Maria-Helena
2017-04-01
Developing modeling tools that help to assess the spatial distribution of water resources is a key issue to achieve better solutions for the optimal management of water availability among users in a river basin. Streamflow dynamics depends on (i) the spatial variability of rainfall, (ii) the heterogeneity of catchment behavior and response, and (iii) local human regulations (e.g., reservoirs) that store and control surface water. These aspects can be successfully handled by distributed or semi-distributed hydrological models. In this study, we develop a dam-reservoir module within a semi-distributed rainfall-runoff model (de Lavenne et al. 2016). The model runs at the daily time step, and has five parameters for each sub-catchment as well as a streamflow velocity parameter for flow routing. Its structure is based on two stores, one for runoff production and one for routing. The calibration of the model is performed from upstream to downstream sub-catchments, which efficiently uses spatially-distributed streamflow measurements. In a previous study, Payan et al. (2008) described a strategy to implement a dam module within a lumped rainfall-runoff model. Here we propose to adapt this strategy to a semi-distributed hydrological modelling framework. In this way, the specific location of existing reservoirs inside a river basin is explicitly accounted for. Our goal is to develop a tool that can provide answers to the different issues involved in spatial water management in human-influenced contexts and at large modelling scales. The approach is tested for the Seine basin in France. Results are shown for model performance with and without the dam module. Also, a comparison with the lumped GR5J model highlights the improvements obtained in model performance by considering human influences more explicitly, and by facilitating parameter identifiability. This work opens up new perspectives for streamflow naturalization analyses and scenario-based spatial assessment of water resources under global change. References de Lavenne, A.; Thirel, G.; Andréassian, V.; Perrin, C. & Ramos, M.-H. (2016), 'Spatial variability of the parameters of a semi-distributed hydrological model', PIAHS 373, 87-94. Payan, J.-L.; Perrin, C.; Andréassian, V. & Michel, C. (2008), 'How can man-made water reservoirs be accounted for in a lumped rainfall-runoff model?', Water Resour. Res. 44(3), W03420.
[Territory and decentralization in the agenda for productive transformation with equity].
Sojo, A
1991-08-01
The regional perspective and the decentralization in Latin American and Caribbean countries was examined in light of technological changes and transformation of economic production to boost productivity. National population policies were not the major cause of redistribution of the population, rather such transformation significantly changed the comparative regional and urban advantages in the use of territory affecting the spatial distribution of the population. Hypotheses were advanced using the transformation of production, regional development, and decentralization on the retention, attraction, and migration of population in different areas with varying economic conditions. Spurious competitiveness means global strategies of enterprises that establish foreign operations by means of factor sourcing. Flexible specialization is a company strategy of permanent innovation based on flexible equipment and a qualified work force. The increasing transnationalization of capital is the source of skills and technology that sustain competitive advantages. Decentralization can resolve local demand, facilitate access to information, mobilize resources, and exercise control over local operations. In Japan, Germany, and Italy vs. the US and France there is a social contract among companies, trade unions, universities, and regional administrations in the interest of capital and the work force. There is no direct relationship between technology and region, the industrial cluster exhibits systemic competitiveness in developed countries (the Emilian model in Italy affirms the ability of small enterprises to develop new products), the regional impact is diverse relative to new technologies (some deprived rural economic areas have potential as in central and northern Italy), and population and region are linked (regional and rural-urban differences in the growth of population and migratory flows account for spatial distribution of the population). Decentralization and systemic competitiveness concern productivity and regional policies (spatial diversity for increased productivity) and technology and human resources are interdependent (technical progress is determined by the level of qualification of the population).
Morales-Soto, Nydia; Dunham, Sage J B; Baig, Nameera F; Ellis, Joseph F; Madukoma, Chinedu S; Bohn, Paul W; Sweedler, Jonathan V; Shrout, Joshua D
2018-03-27
There is a general lack of understanding about how communities of bacteria respond to exogenous toxins such as antibiotics. Most of our understanding of community-level stress responses comes from the study of stationary biofilm communities. Although several community behaviors and production of specific biomolecules affecting biofilm development and associated behavior have been described for Pseudomonas aeruginosa and other bacteria, we have little appreciation for the production and dispersal of secreted metabolites within the 2D and 3D spaces they occupy as they colonize, spread, and grow on surfaces. Here we specifically studied the phenotypic responses and spatial variability of alkyl quinolones, including the Pseudomonas quinolone signal (PQS) and members of the alkyl hydroxyquinoline (AQNO) subclass, in P. aeruginosa plate-assay swarming communities. We found that PQS production was not a universal signaling response to antibiotics as tobramycin elicited an alkyl quinolone response while carbenicillin did not. We also found that PQS and AQNO profiles in response to tobramycin were markedly distinct and influenced these swarms on different spatial scales. The distribution of alkyl quinolones varied by several orders of magnitude within the same swarm. At some tobramycin exposures, P. aeruginosa swarms produced alkyl quinolones in the range of 150 µM PQS and 400 µM AQNO that accumulated as aggregates. Our collective findings show that the distribution of alkyl quinolones can vary by several orders of magnitude within the same swarming community. More notably, our results suggest that multiple intercellular signals acting on different spatial scales can be triggered by one common cue. Published under license by The American Society for Biochemistry and Molecular Biology, Inc.
NASA Astrophysics Data System (ADS)
Wright, W. J.; Shahan, T.; Sharp, N.; Comas, X.
2015-12-01
Peat soils are known to release globally significant amounts of methane (CH4) and carbon dioxide (CO2) to the atmosphere. However, uncertainties still remain regarding the spatio-temporal distribution of gas accumulations and triggering mechanisms of gas releasing events. Furthermore, most research on peatland gas dynamics has traditionally been focused on high latitude peatlands. Therefore, understanding gas dynamics in low-latitude peatlands (e.g. the Florida Everglades) is key to global climate research. Recent studies in the Everglades have demonstrated that biogenic gas flux values may vary when considering different temporal and spatial scales of measurements. The work presented here targets spatial variability in gas production and release at the plot scale in an approximately 85 m2 area, and targets temporal variability with data collected during the spring months of two different years. This study is located in the Loxahatchee Impoundment Landscape Assessment (LILA), a hydrologically controlled, landscape scale (30 Ha) model of the Florida Everglades. Ground penetrating radar (GPR) has been used in the past to investigate biogenic gas dynamics in peat soils, and is used in this study to monitor changes of in situ gas storage. Each year, a grid of GPR profiles was collected to image changes in gas distribution in 2d on a weekly basis, and several flux chambers outfitted with time-lapse cameras captured high resolution (hourly) gas flux measurements inside the GPR grid. Combining these methods allows us to use a mass balance approach to estimate spatial variability in gas production rates, and capture temporal variability in gas flux rates.
Verification of NWP Cloud Properties using A-Train Satellite Observations
NASA Astrophysics Data System (ADS)
Kucera, P. A.; Weeks, C.; Wolff, C.; Bullock, R.; Brown, B.
2011-12-01
Recently, the NCAR Model Evaluation Tools (MET) has been enhanced to incorporate satellite observations for the verification of Numerical Weather Prediction (NWP) cloud products. We have developed tools that match fields spatially (both in the vertical and horizontal dimensions) to compare NWP products with satellite observations. These matched fields provide diagnostic evaluation of cloud macro attributes such as vertical distribution of clouds, cloud top height, and the spatial and seasonal distribution of cloud fields. For this research study, we have focused on using CloudSat, CALIPSO, and MODIS observations to evaluate cloud fields for a variety of NWP fields and derived products. We have selected cases ranging from large, mid-latitude synoptic systems to well-organized tropical cyclones. For each case, we matched the observed cloud field with gridded model and/or derived product fields. CloudSat and CALIPSO observations and model fields were matched and compared in the vertical along the orbit track. MODIS data and model fields were matched and compared in the horizontal. We then use MET to compute the verification statistics to quantify the performance of the models in representing the cloud fields. In this presentation we will give a summary of our comparison and show verification results for both synoptic and tropical cyclone cases.
NASA Astrophysics Data System (ADS)
Yang, X.; Thornton, P. E.; Ricciuto, D. M.; Shi, X.; Xu, M.; Hoffman, F. M.; Norby, R. J.
2017-12-01
Tropical forests play a crucial role in the global carbon cycle, accounting for one third of the global NPP and containing about 25% of global vegetation biomass and soil carbon. This is particularly true for tropical forests in the Amazon region, as it comprises approximately 50% of the world's tropical forests. It is therefore important for us to understand and represent the processes that determine the fluxes and storage of carbon in these forests. In this study, we show that the implementation of phosphorus (P) cycle and P limitation in the ACME Land Model (ALM) improves simulated spatial pattern of NPP. The P-enabled ALM is able to capture the west-to-east gradient of productivity, consistent with field observations. We also show that by improving the representation of mortality processes, ALM is able to reproduce the observed spatial pattern of above ground biomass across the Amazon region.
NASA Astrophysics Data System (ADS)
Pásztor, L.; Szabó, J.; Bakacsi, Zs.; Laborczi, A.
2009-04-01
One of the main objectives of the EU's Common Agricultural Policy is to encourage maintaining agricultural production in less favorable areas (LFA) in order (among others) to sustain agricultural production and use natural resources, in such a way to secure both stable production and income to farmers and to protect the environment. LFA assignment has both ecological and severe economical aspects. Delimitation of LFAs can be carried out by using biophysical diagnostic criteria on low soil productivity and poor climate conditions. Identification of low-productivity areas requires regionalization of soil functions related to food and other biomass production. This process can be carried out in different scales from national to local level, but always requires map-based pedological and further environmental information with appropriate spatial resolution. For the regionalization of less productive areas in national scale a functional approach was used which integrates the knowledge on soil degradation processes in nationwide level. Specific soil threats were classified into ranked categories. Supposing (quasi)uniform distribution of vulnerability measure along these classes, we introduced a "standardized" value as a ratio of the class order to the maximum class order expressed in percentage. For the overall spatial characterization of degradation status, spatial information was integrated in a result map by summarizing the degradation specific "standardized" cell values. This map in one hand has been used for the delineation of soil degradation regions. On the other hand appropriate spatial aggregation of index values on geographical and administrative regions is suitable for their quantitative comparison thus they can be ranked and this feature can be used for the identification of less favorable areas. At the more detailed, county level the Digital Kreybig Soil Information System was used as a tool of the regionalization of soil functions related to soil productivity. Concurrent spatial analysis of the suitability of soils for agricultural use and their sensitivity to physical and chemical degradation were carried out which resulted in a so-called ecotype-based characterization of land. As a spin-off, this classification was used for the designation of low productive areas suitable for hypogenous and cap fungi plantations as landuse alternative for croplands.
Evolution of In-Situ Generated Reinforcement Precipitates in Metal Matrix Composites
NASA Technical Reports Server (NTRS)
Sen, S.; Kar, S. K.; Catalina, A. V.; Stefanescu, D. M.; Dhindaw, B. K.
2004-01-01
Due to certain inherent advantages, in-situ production of Metal Matrix Composites (MMCs) have received considerable attention in the recent past. ln-situ techniques typically involve a chemical reaction that results in precipitation of a ceramic reinforcement phase. The size and spatial distribution of these precipitates ultimately determine the mechanical properties of these MMCs. In this paper we will investigate the validity of using classical growth laws and analytical expressions to describe the interaction between a precipitate and a solid-liquid interface (SLI) to predict the size and spatial evolution of the in-situ generated precipitates. Measurements made on size and distribution of Tic precipitates in a Ni&I matrix will be presented to test the validity of such an approach.
Spatial Distribution of Triclosan in Sediments and Water of an Urbanized Estuarine Embayment
Triclosan (TCS) is a broad spectrum anti-microbial compound found in many consumer and personal care products. TCS enters water bodies primarily through wastewater treatment plant (WWTP) effluent and may also be introduced by combined sewer overflows or surface water runoff. TC...
Durkan, C; Wang, N
2014-12-01
To investigate the effect of different washing regimes on the surface of human hair at the nanometre scale - comparable to the size of typical deposits left behind by commercial products. Atomic force microscopy (AFM) and related techniques. It can be directly seen that washing hair using commercial hair care products removes deposits that naturally form on the shaft, revealing the underlying structure of the hair, whereas in many cases leaving new deposits behind. The spatial distribution of these deposits is explored and quantified. The spatial distribution of the surface charge of pristine hair is mapped, and the electrical screening effect of deposits is directly observed. We also show that the roughness of the treated hair depends directly on the type of product used, with a marked difference between shampoo and conditioner. Some products leave isolated deposits behind, whereas others leave layers of material behind which wet the hair surface. Atomic force microscopy and the related techniques we have employed in a forensic approach is able to distinguish between different hair care products on the basis of the deposits they leave behind. This opens up the capability of further analysis tools to complement already existing techniques. © 2014 Society of Cosmetic Scientists and the Société Française de Cosmétologie.
NASA Astrophysics Data System (ADS)
Bekti, Rokhana Dwi; Nurhadiyanti, Gita; Irwansyah, Edy
2014-10-01
The diarrhea case pattern information, especially for toddler, is very important. It is used to show the distribution of diarrhea in every region, relationship among that locations, and regional economic characteristic or environmental behavior. So, this research uses spatial pattern to perform them. This method includes: Moran's I, Spatial Autoregressive Models (SAR), and Local Indicator of Spatial Autocorrelation (LISA). It uses sample from 23 sub districts of Bekasi Regency, West Java, Indonesia. Diarrhea case, regional economic, and environmental behavior of households have a spatial relationship among sub district. SAR shows that the percentage of Regional Gross Domestic Product is significantly effect on diarrhea at α = 10%. Therefore illiteracy and health center facilities are significant at α = 5%. With LISA test, sub districts in southern Bekasi have high dependencies with Cikarang Selatan, Serang Baru, and Setu. This research also builds development application that is based on java and R to support data analysis.
Droughts in India from 1981 to 2013 and Implications to Wheat Production
NASA Astrophysics Data System (ADS)
Zhang, Xiang; Obringer, Renee; Wei, Chehan; Chen, Nengcheng; Niyogi, Dev
2017-03-01
Understanding drought from multiple perspectives is critical due to its complex interactions with crop production, especially in India. However, most studies only provide singular view of drought and lack the integration with specific crop phenology. In this study, four time series of monthly meteorological, hydrological, soil moisture, and vegetation droughts from 1981 to 2013 were reconstructed for the first time. The wheat growth season (from October to April) was particularly analyzed. In this study, not only the most severe and widespread droughts were identified, but their spatial-temporal distributions were also analyzed alone and concurrently. The relationship and evolutionary process among these four types of droughts were also quantified. The role that the Green Revolution played in drought evolution was also studied. Additionally, the trends of drought duration, frequency, extent, and severity were obtained. Finally, the relationship between crop yield anomalies and all four kinds of drought during the wheat growing season was established. These results provide the knowledge of the most influential drought type, conjunction, spatial-temporal distributions and variations for wheat production in India. This study demonstrates a novel approach to study drought from multiple views and integrate it with crop growth, thus providing valuable guidance for local drought mitigation.
Sun, Yu-Xin; Zhang, Zai-Wang; Xu, Xiang-Rong; Hao, Qin-Wei; Hu, Yong-Xia; Zheng, Xiao-Bo; Luo, Xiao-Jun; Diao, Zeng-Hui; Mai, Bi-Xian
2016-10-01
Thirty surface sediments and three sediment cores were collected from mangrove wetlands in the Pearl River Estuary of South China to investigate the spatial and vertical distribution of Dechlorane Plus (DP). DP concentrations in the mangrove surface sediments ranged from 0.0130 to 1.504 ng/g dry weight (dw). DP concentrations in sediments from Shenzhen were significantly greater than those from Guangzhou and Zhuhai. Anti-Cl11-DP, the dechlorinated product of anti-DP, was also detected in the mangrove sediments with concentrations ranged from not detected to 0.0198 ng/g dw. Significant positive relationship between anti-Cl11-DP and anti-DP levels was observed in the mangrove sediments, suggesting that photo and/or microbial degradation of anti-DP might occur in the sediments. The f anti values in the mangrove sediments were close to those in the technical DP products, suggesting that stereoselective enrichment of anti-DP may not exist in the mangrove sediments. DP concentrations in the mangrove sediment cores generally showed an increasing trend from the bottom to top layers. This is the first study to report the occurrence of DP and its degradation product in the mangrove wetlands.
Microbial Activity and Depositional System Dynamics: Linking Scales With The Aid of New Technology
NASA Astrophysics Data System (ADS)
Defew, E. C.; Hagerthey, S. E.; Honeywill, C.; Perkins, R. G.; Black, K. S.; Paterson, D. M.
The dynamics of estuarine depositional systems are influenced by sediment-dwelling microphytobenthic assemblages. These assemblages produce extracellular polymeric substances (EPS), which are known to be important in the process of sediment biosta- bilisation. However, these communities are generally studied on very small spatial scales making the prediction of primary productivity and their importance in terms of sediment stability over large areas uncertain. Recent advances in our knowledge of the biostabilisation process have allowed the establishment of links between EPS produc- tion, spatial distribution of algal biomass and their primary productivity over much larger spatial scales. For example, during the multidisciplinary BIOPTIS project, re- mote sensing (RS) was combined with ground-truthing measurements of physical and biological parameters to produce synoptic maps leading to a better understanding of system dynamics and the potential effects of environmental perturbations such as cli- mate change. Recent work using low-temperature scanning electron microscopy (LT- SEM) and in-line laser holography has measured the influence of EPS on the erosional behaviour of sediment flocs and particles and has shown that an increase in the con- centration of EPS determines the nature of the eroded floc material and the critical threshold for sediment erosion. This provides the mechanistic link required between EPS concentration and sediment stability. Whilst it is not yet possible to discern EPS concentration directly by RS studies, we know that EPS concentrations in sediments co-vary with chlorophyll a content, and are closely related to algal productivity. There- fore, RS studies which provide large-scale spatial information of chlorophyll a distri- bution may be used to model the stability and productivity of intertidal depositional systems. This paper introduces the basis of these linkages from the cellular level (in situ chlorophyll fluorescence), the ground-truthing approach (sediment stability, struc- ture, pigment distribution, in situ chlorophyll fluorescence) and investigates the poten- tial of a RS approach in a case study of a Scottish Estuary.
Phosphorus in agricultural soils: drivers of its distribution at the global scale
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ringeval, Bruno; Augusto, Laurent; Monod, Herve
Phosphorus (P) availability in soils limits crop yields in many regions of the world, while excess of soil P triggers aquatic eutrophication in other regions. Numerous processes drive the global spatial distribution of P in agricultural soils, but their relative roles remain unclear. Here, we combined several global datasets describing these drivers with a soil P dynamics model to simulate the distribution of P in agricultural soils and to assess the contributions of the different drivers at the global scale. We analyzed both the labile inorganic P (P ILAB), a proxy of the pool involved in plant nutrition and themore » total soil P (P TOT). We found that the soil biogeochemical background (BIOG) and farming practices (FARM) were the main drivers of the spatial variability in cropland soil P content but that their contribution varied between P TOT vs P ILAB. Indeed, 97% of the P TOT spatial variability could be explained by BIOG, while BIOG and FARM explained 41% and 58% of P ILAB spatial variability, respectively. Other drivers such as climate, soil erosion, atmospheric P deposition and soil buffering capacity made only very small contribution. Lastly, our study is a promising approach to investigate the potential effect of P as a limiting factor for agricultural ecosystems and for global food production. Additionally, we quantified the anthropogenic perturbation of P cycle and demonstrated how the different drivers are combined to explain the global distribution of agricultural soil P.« less
Miller, Ek Fillatre; Bradbury, Ir; Heath, Dd
2011-12-01
Allochronic divergence, like spatial isolation, may contribute to population diversity and adaptation, however the challenges for tracking habitat utilization in shared environments are far greater. Adult Klukshu River (Yukon, Canada) sockeye salmon, Oncorhynchus nerka, return as genetically distinct "early" and "late" runs. Early and late adult spawning populations (1999 and 2000) and their subsequent fry (sampled at 7 sites in 2000 and at 8 sites in 2001 throughout Klukshu Lake and River) were genotyped at eight microsatellite loci. Bayesian assignment was used to determine the spatial distribution of early versus late fry; although intermixed, the distribution of fry significantly differed in Klukshu Lake and in the Klukshu River in 2001, based on crosstab analyses. Late-run fry predominated in Klukshu Lake at all sites, while early-run fry were most common in the north and south of Klukshu Lake and in Klukshu River. Early-run spawners had significantly higher relative productivity (early life survival) than late-run fish (2.9 times more fry produced per early-run adult in 2000, and 9.2 times more in 2001). This study demonstrates spatial habitat partitioning and differences in the contribution of allochronically isolated populations to fry abundance, and highlights annual variability that likely contributes to recruitment variation.
Miller, EK Fillatre; Bradbury, IR; Heath, DD
2011-01-01
Allochronic divergence, like spatial isolation, may contribute to population diversity and adaptation, however the challenges for tracking habitat utilization in shared environments are far greater. Adult Klukshu River (Yukon, Canada) sockeye salmon, Oncorhynchus nerka, return as genetically distinct “early” and “late” runs. Early and late adult spawning populations (1999 and 2000) and their subsequent fry (sampled at 7 sites in 2000 and at 8 sites in 2001 throughout Klukshu Lake and River) were genotyped at eight microsatellite loci. Bayesian assignment was used to determine the spatial distribution of early versus late fry; although intermixed, the distribution of fry significantly differed in Klukshu Lake and in the Klukshu River in 2001, based on crosstab analyses. Late-run fry predominated in Klukshu Lake at all sites, while early-run fry were most common in the north and south of Klukshu Lake and in Klukshu River. Early-run spawners had significantly higher relative productivity (early life survival) than late-run fish (2.9 times more fry produced per early-run adult in 2000, and 9.2 times more in 2001). This study demonstrates spatial habitat partitioning and differences in the contribution of allochronically isolated populations to fry abundance, and highlights annual variability that likely contributes to recruitment variation. PMID:22393527
A global approach to estimate irrigated areas - a comparison between different data and statistics
NASA Astrophysics Data System (ADS)
Meier, Jonas; Zabel, Florian; Mauser, Wolfram
2018-02-01
Agriculture is the largest global consumer of water. Irrigated areas constitute 40 % of the total area used for agricultural production (FAO, 2014a) Information on their spatial distribution is highly relevant for regional water management and food security. Spatial information on irrigation is highly important for policy and decision makers, who are facing the transition towards more efficient sustainable agriculture. However, the mapping of irrigated areas still represents a challenge for land use classifications, and existing global data sets differ strongly in their results. The following study tests an existing irrigation map based on statistics and extends the irrigated area using ancillary data. The approach processes and analyzes multi-temporal normalized difference vegetation index (NDVI) SPOT-VGT data and agricultural suitability data - both at a spatial resolution of 30 arcsec - incrementally in a multiple decision tree. It covers the period from 1999 to 2012. The results globally show a 18 % larger irrigated area than existing approaches based on statistical data. The largest differences compared to the official national statistics are found in Asia and particularly in China and India. The additional areas are mainly identified within already known irrigated regions where irrigation is more dense than previously estimated. The validation with global and regional products shows the large divergence of existing data sets with respect to size and distribution of irrigated areas caused by spatial resolution, the considered time period and the input data and assumption made.
NASA Astrophysics Data System (ADS)
Dukhovskoy, D. S.; Bourassa, M. A.
2016-12-01
The study compares and analyses the characteristics of synoptic storms in the Subpolar North Atlantic over the time period from 2000 through 2009 derived from reanalysis data sets and scatterometer-based gridded wind products. The analysis is performed for ocean 10-m winds derived from the following wind data sets: NCEP/DOE AMIP-II reanalysis (NCEPR2), NCAR/CFSR, Arctic System Reanalysis (ASR) version 1, Cross-Calibrated Multi-Platform (CCMP) wind product versions 1.1 and recently released version 2.0 prepared by the Remote Sensing Systems, and QuikSCAT. A cyclone tracking algorithm employed in this study for storm identification is based on average vorticity fields derived from the wind data. The study discusses storm characteristics such as storm counts, trajectories, intensity, integrated kinetic energy, spatial scale. Interannal variability of these characteristics in the data sets is compared. The analyses demonstrates general agreement among the wind data products on the characteristics of the storms, their spatial distribution and trajectories. On average, the NCEPR2 storms are more energetic mostly due to large spatial scales and stronger winds. There is noticeable interannual variability in the storm characteristics, yet no obvious trend in storms is observed in the data sets.
Russo, Tommaso; Parisi, Antonio; Garofalo, Germana; Gristina, Michele; Cataudella, Stefano; Fiorentino, Fabio
2014-01-01
Management of catches, effort and exploitation pattern are considered the most effective measures to control fishing mortality and ultimately ensure productivity and sustainability of fisheries. Despite the growing concerns about the spatial dimension of fisheries, the distribution of resources and fishing effort in space is seldom considered in assessment and management processes. Here we propose SMART (Spatial MAnagement of demersal Resources for Trawl fisheries), a tool for assessing bio-economic feedback in different management scenarios. SMART combines information from different tasks gathered within the European Data Collection Framework on fisheries and is composed of: 1) spatial models of fishing effort, environmental characteristics and distribution of demersal resources; 2) an Artificial Neural Network which captures the relationships among these aspects in a spatially explicit way and uses them to predict resources abundances; 3) a deterministic module which analyzes the size structure of catches and the associated revenues, according to different spatially-based management scenarios. SMART is applied to demersal fishery in the Strait of Sicily, one of the most productive fisheries of the Mediterranean Sea. Three of the main target species are used as proxies for the whole range exploited by trawlers. After training, SMART is used to evaluate different management scenarios, including spatial closures, using a simulation approach that mimics the recent exploitation patterns. Results evidence good model performance, with a noteworthy coherence and reliability of outputs for the different components. Among others, the main finding is that a partial improvement in resource conditions can be achieved by means of nursery closures, even if the overall fishing effort in the area remains stable. Accordingly, a series of strategically designed areas of trawling closures could significantly improve the resource conditions of demersal fisheries in the Strait of Sicily, also supporting sustainable economic returns for fishermen if not applied simultaneously for different species. PMID:24465971
Triclosan is an anti-microbial agent commonly used in the formulation of many personal care and consumer products. Much of the triclosan used by consumers enters the aqueous waste stream following use and is partially removed in waste water treatment plants (WWTP). However, the...
A diagnostic model evaluation effort has been performed to focus on photochemical ozone formation and the horizontal transport process since they strongly impact the temporal evolution and spatial distribution of ozone (O3) within the lower troposphere. Results from th...
Evapotranspiration estimates derived using multi-platform remote sensing in a semiarid region
USDA-ARS?s Scientific Manuscript database
Evapotranspiration (ET) is a key component of the water balance, especially in arid and semiarid regions. The current study takes advantage of spatially-distributed, near real-time information provided by satellite remote sensing to develop a regional scale ET product derived from remotely-sensed ob...
Tidal wetlands support important ecosystem functions along the coast of the Pacific Northwest such as primary production and nutrient transformation. Sea-level rise (SLR) and elevated salinity due to climate change may affect the abundance, distribution, and diversity of plants a...
USDA-ARS?s Scientific Manuscript database
Timely reflectance data from cotton (Gossypium hirsutum L.) production fields provide a useful tool for crop health assessment and site-specific crop management decisions. This field study investigated the relationships among site-specific normalized difference vegetation index (NDVI), soil physical...
Use of NDVI and land surface temperature for assessing vegetation health: merits and limitations
USDA-ARS?s Scientific Manuscript database
To date, most drought indices used in drought monitoring are based on precipitation and meteorological data collected on the ground from distributed monitoring networks. Few satellite-based drought indices are currently in production, although these afford better spatial and temporal coverage and r...
Spatial Burnout in Water Reactors with Nonuniform Startup Distributions of Uranium and Boron
NASA Technical Reports Server (NTRS)
Fox, Thomas A.; Bogart, Donald
1955-01-01
Spatial burnout calculations have been made of two types of water moderated cylindrical reactor using boron as a burnable poison to increase reactor life. Specific reactors studied were a version of the Submarine Advanced Reactor (sAR) and a supercritical water reactor (SCW) . Burnout characteristics such as reactivity excursion, neutron-flux and heat-generation distributions, and uranium and boron distributions have been determined for core lives corresponding to a burnup of approximately 7 kilograms of fully enriched uranium. All reactivity calculations have been based on the actual nonuniform distribution of absorbers existing during intervals of core life. Spatial burnout of uranium and boron and spatial build-up of fission products and equilibrium xenon have been- considered. Calculations were performed on the NACA nuclear reactor simulator using two-group diff'usion theory. The following reactor burnout characteristics have been demonstrated: 1. A significantly lower excursion in reactivity during core life may be obtained by nonuniform rather than uniform startup distribution of uranium. Results for SCW with uranium distributed to provide constant radial heat generation and a core life corresponding to a uranium burnup of 7 kilograms indicated a maximum excursion in reactivity of 2.5 percent. This compared to a maximum excursion of 4.2 percent obtained for the same core life when w'anium was uniformly distributed at startup. Boron was incorporated uniformly in these cores at startup. 2. It is possible to approach constant radial heat generation during the life of a cylindrical core by means of startup nonuniform radial and axial distributions of uranium and boron. Results for SCW with nonuniform radial distribution of uranium to provide constant radial heat generation at startup and with boron for longevity indicate relatively small departures from the initially constant radial heat generation distribution during core life. Results for SAR with a sinusoidal distribution rather than uniform axial distributions of boron indicate significant improvements in axial heat generation distribution during the greater part of core life. 3. Uranium investments for cylindrical reactors with nonuniform radial uranium distributions which provide constant radial heat generation per unit core volume are somewhat higher than for reactors with uniform uranium concentration at startup. On the other hand, uranium investments for reactors with axial boron distributions which approach constant axial heat generation are somewhat smaller than for reactors with uniform boron distributions at startup.
Contributions to Climate Research Using the AIRS Science Team Version-5 Products
NASA Technical Reports Server (NTRS)
Susskind, Joel; Molnar, Gyula; Iredell, Lena
2011-01-01
This paper compares recent spatial anomaly time series of OLR (Outgoing Longwave Radiation) and OLRCLR (Clear Sky OLR) as determined using CERES and AIRS observations over the time period September 2002 through June 2010. We find excellent agreement in OLR anomaly time series of both data sets in almost every detail, down to the 1 x 1 spatial grid point level. This extremely close agreement of OLR anomaly time series derived from observations by two different instruments implies that both sets of results must be highly stable. This agreement also validates to some extent the anomaly time series of the AIRS derived products used in the computation of the AIRS OLR product. The paper then examines anomaly time series of AIRS derived products over the extended time period September 2002 through April 2011. We show that OLR anomalies during this period are closely in phase with those of an El Nino index, and that recent global and tropical mean decreases in OLR and OLR(sub CLR) are a result of a transition from an El Nino condition at the beginning of the data record to La Nina conditions toward the end of the data period. This relationship can be explained by temporal changes of the distribution of mid-tropospheric water vapor and cloud cover in two spatial regions that are in direct response to El Nino/La Nina activity which occurs outside these spatial regions
Hanson, Roger B.; Lowery, H. Kenneth
1985-01-01
We examined the spatial distributions of picoplankton, nanoplankton, and microplankton biomass and physiological state relative to the hydrography of the Southern Ocean along 90° W longitude and across the Drake Passage in the late austral winter. The eastern South Pacific Ocean showed some large-scale biogeographical differences and size class variability. Microbial ATP biomass was greatest in euphotic surface waters. The horizontal distributions of microbial biomass and physiological state (adenylate energy charge ratio) coincided with internal currents (fronts) of the Antarctic Circumpolar Current. In the Drake Passage, the biological scales in the euphotic and aphotic zones were complex, and ATP, total adenylate, and adenylate energy charge ratio isopleths were compressed due to the extension of the sea ice from Antarctica and constriction of the Circumpolar Current through the narrow passage. The physiological state of microbial assemblages and biomass were much higher in the Drake Passage than in the eastern South Pacific Ocean. The temperature of Antarctic waters, not dissolved organic carbon, was the major variable controlling picoplankton growth. Estimates of picoplankton production based on ATP increments with time suggest that production under reduced predation pressure was 1 to 10 μg of carbon per liter per day. Our results demonstrate the influence of large-scale hydrographic processes on the distribution and structure of microplankton, nanoplankton, and picoplankton across the Southern Ocean. PMID:16346777
Combining a Spatial Model and Demand Forecasts to Map Future Surface Coal Mining in Appalachia
Strager, Michael P.; Strager, Jacquelyn M.; Evans, Jeffrey S.; Dunscomb, Judy K.; Kreps, Brad J.; Maxwell, Aaron E.
2015-01-01
Predicting the locations of future surface coal mining in Appalachia is challenging for a number of reasons. Economic and regulatory factors impact the coal mining industry and forecasts of future coal production do not specifically predict changes in location of future coal production. With the potential environmental impacts from surface coal mining, prediction of the location of future activity would be valuable to decision makers. The goal of this study was to provide a method for predicting future surface coal mining extents under changing economic and regulatory forecasts through the year 2035. This was accomplished by integrating a spatial model with production demand forecasts to predict (1 km2) gridded cell size land cover change. Combining these two inputs was possible with a ratio which linked coal extraction quantities to a unit area extent. The result was a spatial distribution of probabilities allocated over forecasted demand for the Appalachian region including northern, central, southern, and eastern Illinois coal regions. The results can be used to better plan for land use alterations and potential cumulative impacts. PMID:26090883
NASA Astrophysics Data System (ADS)
Aneiros, Fernando; Rubal, Marcos; Troncoso, Jesús S.; Bañón, Rafael
2015-11-01
The Ría de Vigo is a semi-enclosed bay with high primary productivity due to the influence of coastal upwelling-downwelling dynamics. The area is heavily populated and affected by numerous human activities, which lead to sediment modification. Epibenthic megafauna from the non-estuarine zones of this bay has been studied in order to describe its spatial distribution, testing possible differences between inner and outer areas. With that purpose, 75 sites have been sampled by means of a towing dredge. Megafauna was identified to the lowest taxonomic level possible, and each taxon counted and weighted. 113 different taxa were identified and a high spatial heterogeneity was observed in terms of abundance, biomass, taxa richness, diversity and evenness. Suspension-feeding molluscs dominated the innermost part of the studied area, and were substituted by echinoderms towards the external zones; this spatial pattern was also reflected in the results of multivariate analyses. These shifts in taxonomic and trophic guild composition of the assemblages have been tentatively related to differences in pollution levels and primary productivity along the main axis of the bay.
NASA Astrophysics Data System (ADS)
Hatton, Pierre-Joseph; Remusat, Laurent; Brewer, Elizabeth; Derrien, Delphine
2014-05-01
While soil microorganisms are increasingly seen as shaping stable soil organic matter (OM) formation, the mechanisms controlling the attachment of microbial metabolites to soil particles are not fully understood yet. We investigate the spatial distribution of freshly produced microbial products among density-isolated fractions of soil using stable C and N isotopes and Nano-scale secondary ion mass spectrometry (NanoSIMS). A surface forest soil was amended with uniformly 13C/15N labeled glycine and incubated for 8 hours in gamma-irradiated and non-sterile soils. Sequential density fractionation was then performed to isolate various classes of aggregates and of single mineral particles. Eight hours after the labeled glycine addition, 7 % of the 13C and 15N was tightly bound to soil assemblages. Comparison of sterile and non-sterile treatments revealed that microbial activity was almost completely responsible for this rapid association (>85 %). The distributions of glycine-derived 13C and 15N, considered as markers of new microbial products, were mapped on particles of the non-sterile treatment using NanoSIMS. New microbial products were heterogeneously distributed and spatially decoupled at the surface of on soil particles. 13C microbial products were scarce and presumably within or in the vicinity of microbial cells. In contrast, 15N microbial products seemed evenly spread at the surface of soil particles, likely as soluble exoenzymes diffusing away from their parent cell. Macroscopic measurements among density fractions suggested that the diffusion of such 15N microbial products was spatially limited yet, because of pore space architecture. NanoSIMS images further allowed gaining insight into the attachment of the new microbial products on particle surfaces already covered by OM, in a multilayer fashion. Using an internal calibration method to determine C/N ratios of NanoSIMS images, we showed the preferential attachment of soluble microbial N-metabolites to N-rich mineral-attached OM (C/N ratios mostly < 16). Exceptions were found in dense particles, supposed to contained aluminium and iron (hydr)oxides, with the microbial N-metabolites apparently preferentially attached to C-rich mineral-attached OM (C/N ratios > 80). This work provided visual evidences that the attachment of new microbial products to the soil matrix is mediated by distinct processes for N-rich and C-rich metabolites. It also demonstrated that the pore space architecture has impact on the formation of stable OM by limiting the diffusion of soluble microbial metabolites and their access to reactive and stabilising surfaces.
Miki, Shigehito; Yamashita, Taro; Wang, Zhen; Terai, Hirotaka
2014-04-07
We present the characterization of two-dimensionally arranged 64-pixel NbTiN superconducting nanowire single-photon detector (SSPD) array for spatially resolved photon detection. NbTiN films deposited on thermally oxidized Si substrates enabled the high-yield production of high-quality SSPD pixels, and all 64 SSPD pixels showed uniform superconducting characteristics within the small range of 7.19-7.23 K of superconducting transition temperature and 15.8-17.8 μA of superconducting switching current. Furthermore, all of the pixels showed single-photon sensitivity, and 60 of the 64 pixels showed a pulse generation probability higher than 90% after photon absorption. As a result of light irradiation from the single-mode optical fiber at different distances between the fiber tip and the active area, the variations of system detection efficiency (SDE) in each pixel showed reasonable Gaussian distribution to represent the spatial distributions of photon flux intensity.
The Node Deployment of Intelligent Sensor Networks Based on the Spatial Difference of Farmland Soil.
Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun
2015-11-11
Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop conditions are influenced by the spatial distribution of soil nutrients. If the nutrients are distributed evenly, the crop conditions are expected to be approximately uniform with little difference; on the contrary, there will be great differences in crop conditions. In accordance with the differences in the spatial distribution of soil information in farmland, fuzzy c-means clustering was applied to divide the farmland into several areas, where the soil fertility of each area is nearly uniform. Then the crop growth information in the area could be monitored with complete coverage by deploying a sensor node there, which could greatly decrease the deployed sensor nodes. Moreover, in order to accurately judge the optimal cluster number of fuzzy c-means clustering, a discriminant function for Normalized Intra-Cluster Coefficient of Variation (NICCV) was established. The sensitivity analysis indicates that NICCV is insensitive to the fuzzy weighting exponent, but it shows a strong sensitivity to the number of clusters.
2013-01-01
Introduction Sociality has evolved independently multiple times across the spider phylogeny, and despite wide taxonomic and geographical breadth the social species are characterized by a common geographical constrain to tropical and subtropical areas. Here we investigate the environmental factors that drive macro-ecological patterns in social and solitary species in a genus that shows a Mediterranean–Afro-Oriental distribution (Stegodyphus). Both selected drivers (productivity and seasonality) may affect the abundance of potential prey insects, but seasonality may further directly affect survival due to mortality caused by extreme climatic events. Based on a comprehensive dataset including information about the distribution of three independently derived social species and 13 solitary congeners we tested the hypotheses that the distribution of social Stegodyphus species relative to solitary congeners is: (1) restricted to habitats of high vegetation productivity and (2) constrained to areas with a stable climate (low precipitation seasonality). Results Using spatial logistic regression modelling and information-theoretic model selection, we show that social species occur at higher vegetation productivity than solitary, while precipitation seasonality received limited support as a predictor of social spider occurrence. An analysis of insect biomass data across the Stegodyphus distribution range confirmed that vegetation productivity is positively correlated to potential insect prey biomass. Conclusions Habitat productivity constrains the distribution of social spiders across continents compared to their solitary congeners, with group-living in spiders being restricted to areas with relatively high vegetation productivity and insect prey biomass. As known for other taxa, permanent sociality likely evolves in response to high predation pressure and imposes within-group competition for resources. Our results suggest that group living is contingent upon productive environmental conditions where elevated prey abundance meet the increased demand for food of social groups. PMID:23433065
Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate.
Beer, Christian; Reichstein, Markus; Tomelleri, Enrico; Ciais, Philippe; Jung, Martin; Carvalhais, Nuno; Rödenbeck, Christian; Arain, M Altaf; Baldocchi, Dennis; Bonan, Gordon B; Bondeau, Alberte; Cescatti, Alessandro; Lasslop, Gitta; Lindroth, Anders; Lomas, Mark; Luyssaert, Sebastiaan; Margolis, Hank; Oleson, Keith W; Roupsard, Olivier; Veenendaal, Elmar; Viovy, Nicolas; Williams, Christopher; Woodward, F Ian; Papale, Dario
2010-08-13
Terrestrial gross primary production (GPP) is the largest global CO(2) flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.
Can we improve streamflow simulation by using higher resolution rainfall information?
NASA Astrophysics Data System (ADS)
Lobligeois, Florent; Andréassian, Vazken; Perrin, Charles
2013-04-01
The catchment response to rainfall is the interplay between space-time variability of precipitation, catchment characteristics and antecedent hydrological conditions. Precipitation dominates the high frequency hydrological response, and its simulation is thus dependent on the way rainfall is represented. One of the characteristics which distinguishes distributed from lumped models is their ability to represent explicitly the spatial variability of precipitation and catchment characteristics. The sensitivity of runoff hydrographs to the spatial variability of forcing data has been a major concern of researchers over the last three decades. However, although the literature on the relationship between spatial rainfall and runoff response is abundant, results are contrasted and sometimes contradictory. Several studies concluded that including information on rainfall spatial distribution improves discharge simulation (e.g. Ajami et al., 2004, among others) whereas other studies showed the lack of significant improvement in simulations with better information on rainfall spatial pattern (e.g. Andréassian et al., 2004, among others). The difficulties to reach a clear consensus is mainly due to the fact that each modeling study is implemented only on a few catchments whereas the impact of the spatial distribution of rainfall on runoff is known to be catchment and event characteristics-dependent. Many studies are virtual experiments and only compare flow simulations, which makes it difficult to reach conclusions transposable to real-life case studies. Moreover, the hydrological rainfall-runoff models differ between the studies and the parameterization strategies sometimes tend to advantage the distributed approach (or the lumped one). Recently, Météo-France developed a rainfall reanalysis over the whole French territory at the 1-kilometer resolution and the hourly time step over a 10-year period combining radar data and raingauge measurements: weather radar data were corrected and adjusted with both hourly and daily raingauge data. Based on this new high resolution product, we propose a framework to evaluate the improvements in streamflow simulation by using higher resolution rainfall information. Semi-distributed modelling is performed for different spatial resolution of precipitation forcing: from lumped to semi-distributed simulations. Here we do not work on synthetic (simulated) streamflow, but with actual measurements, on a large set of 181 French catchments representing a variety of size and climate. The rainfall-runoff model is re-calibrated for each resolution of rainfall spatial distribution over a 5-year sub-period and evaluated on the complementary sub-period in validation mode. The results are analysed by catchment classes based on catchment area and for various types of rainfall events based on the spatial variability of precipitation. References Ajami, N. K., Gupta, H. V, Wagener, T. & Sorooshian, S. (2004) Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology 298(1-4), 112-135. Andréassian, V., Oddos, A., Michel, C., Anctil, F., Perrin, C. & Loumagne, C. (2004) Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall-runoff models: A theoretical study using chimera watersheds. Water Resources Research 40(5), 1-9.
Grigolli, J F J; Souza, L A; Fernandes, M G; Busoli, A C
2017-08-01
The cotton boll weevil Anthonomus grandis Boheman (Coleoptera: Curculionidae) is the main pest in cotton crop around the world, directly affecting cotton production. In order to establish a sequential sampling plan, it is crucial to understand the spatial distribution of the pest population and the damage it causes to the crop through the different developmental stages of cotton plants. Therefore, this study aimed to investigate the spatial distribution of adults in the cultivation area and their oviposition and feeding behavior throughout the development of the cotton plants. The experiment was conducted in Maracaju, Mato Grosso do Sul, Brazil, in the 2012/2013 and 2013/2014 growing seasons, in an area of 10,000 m 2 , planted with the cotton cultivar FM 993. The experimental area was divided into 100 plots of 100 m 2 (10 × 10 m) each, and five plants per plot were sampled weekly throughout the crop cycle. The number of flower buds with feeding and oviposition punctures and of adult A. grandis was recorded throughout the crop cycle in five plants per plot. After determining the aggregation indices (variance/mean ratio, Morisita's index, exponent k of the negative binomial distribution, and Green's coefficient) and adjusting the frequencies observed in the field to the distribution of frequencies (Poisson, negative binomial, and positive binomial) using the chi-squared test, it was observed that flower buds with punctures derived from feeding, oviposition, and feeding + oviposition showed an aggregated distribution in the cultivation area until 85 days after emergence and a random distribution after this stage. The adults of A. grandis presented a random distribution in the cultivation area.
Teresa E. Jordan
2016-08-18
*These files add to and replace same-named files found within Submission 559 (https://gdr.openei.org/submissions/559)* The files included in this submission contain all data pertinent to the methods and results of a cohesive multi-state analysis of all known potential geothermal reservoirs in sedimentary rocks in the Appalachian Basin region, ranked by their potential favorability. Favorability is quantified using three metrics: Reservoir Productivity Index for water; Reservoir Productivity Index; Reservoir Flow Capacity. The metrics are explained in the Reservoirs Methodology Memo (included in zip file). The product represents a minimum spatial extent of potential sedimentary rock geothermal reservoirs. Only natural porosity and permeability were analyzed. Shapefile and images of the spatial distributions of these reservoir quality metrics and of the uncertainty on these metrics are included as well. UPDATE: Accompanying geologic reservoirs data may be found at: https://gdr.openei.org/submissions/881 (linked below).
NASA Technical Reports Server (NTRS)
Abbott, M. R.
1984-01-01
Within the framework of global biogeochemical cycles and ocean productivity, there are two areas that will be of particular interest to biological oceanography in the 1990s. The first is the mapping in space time of the biomass and productivity of phytoplankton in the world ocean. The second area is the coupling of biological and physical processes as it affects the distribution and growth rate of phytoplankton biomass. Certainly other areas will be of interest to biological oceanographers, but these two areas are amenable to observations from satellites. Temporal and spatial variability is a regular feature of marine ecosystems. The temporal and spatial variability of phytoplankton biomass and productivity which is ubiquitous at all time and space scales in the ocean must be characterized. Remote sensing from satellites addresses these problems with global observations of mesocale (2 to 20 days, 10 to 200 km) features over a long period of time.
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.
Spatial distribution of nematodes in soil cultivated with sugarcane under different uses
NASA Astrophysics Data System (ADS)
Cardoso, M. O.; Pedrosa, E. M. R.; Vicente, T. F. S.; Siqueira, G. M.; Montenegro, A. A. A.
2012-04-01
Sugarcane is a crop of major importance within the Brazilian economy, being an activity that generates energy and with high capacity to develop various economic sectors. Currently the greatest challenge is to maximize productivity and minimize environmental impacts. The plant-parasites nematodes have great expression, because influence directly the productive potential of sugarcane crops. Accordingly, little research has been devoted to the study of spatial variability of nematodes. Thus, the purpose of this work is to analyze the spatial distribution of nematodes in a soil cultivated with sugarcane in areas with and without irrigation, with distinct spacing of sampling to determine the differences between the sampling scales. The study area is located in the municipality of Goiana (Pernambuco State, Brazil). The experiment was conducted in two areas with 40 hectares each, being collected 90 samples at different spacing: 18 samples with spacing of 200.00 x 200.00 m, 36 samples with spacing of 20.00 m x 20.00 m and 36 samples with spacing of 2.00 m x 2.00 m. Soil samples were collected at deep of 0.00-0.20 m and nematodes were extracted per 300 cm3 of soil through centrifugal flotation in sucrose being quantified, classified according trophic habit (plant-parasites, fungivores, bacterivores, omnivores and predators) and identified in level of genus or family. In irrigated area the amount of water applied was determined considering the evapotranspiration of culture. The data were analyzed using classical statistics and geostatistics. The results demonstrated that the data showed high values of coefficient of variation in both study areas. All attributes studied showed log normal frequency distribution. The area B (irrigated) has a population of nematodes more stable than the area A (non-irrigated), a fact confirmed by its mean value of the total population of nematodes (282.45 individuals). The use of geostatistics not allowed to assess the spatial distribution of populations of nematodes even with the data being collected at different scales, describing the spatial variability of groups of nematodes present in the areas evaluated is smaller than the smallest spacing used. Even with the data showing pure nugget effect was possible to verify the semivariogram for the groups of nematodes in the area A, where pairs of semivariance showed great dispersion.
Grosse, Guido; Robinson, Joel E.; Bryant, Robin; Taylor, Maxwell D.; Harper, William; DeMasi, Amy; Kyker-Snowman, Emily; Veremeeva, Alexandra; Schirrmeister, Lutz; Harden, Jennifer
2013-01-01
This digital database is the product of collaboration between the U.S. Geological Survey, the Geophysical Institute at the University of Alaska, Fairbanks; the Los Altos Hills Foothill College GeoSpatial Technology Certificate Program; the Alfred Wegener Institute for Polar and Marine Research, Potsdam, Germany; and the Institute of Physical Chemical and Biological Problems in Soil Science of the Russian Academy of Sciences. The primary goal for creating this digital database is to enhance current estimates of soil organic carbon stored in deep permafrost, in particular the late Pleistocene syngenetic ice-rich permafrost deposits of the Yedoma Suite. Previous studies estimated that Yedoma deposits cover about 1 million square kilometers of a large region in central and eastern Siberia, but these estimates generally are based on maps with scales smaller than 1:10,000,000. Taking into account this large area, it was estimated that Yedoma may store as much as 500 petagrams of soil organic carbon, a large part of which is vulnerable to thaw and mobilization from thermokarst and erosion. To refine assessments of the spatial distribution of Yedoma deposits, we digitized 11 Russian Quaternary geologic maps. Our study focused on extracting geologic units interpreted by us as late Pleistocene ice-rich syngenetic Yedoma deposits based on lithology, ground ice conditions, stratigraphy, and geomorphological and spatial association. These Yedoma units then were merged into a single data layer across map tiles. The spatial database provides a useful update of the spatial distribution of this deposit for an approximately 2.32 million square kilometers land area in Siberia that will (1) serve as a core database for future refinements of Yedoma distribution in additional regions, and (2) provide a starting point to revise the size of deep but thaw-vulnerable permafrost carbon pools in the Arctic based on surface geology and the distribution of cryolithofacies types at high spatial resolution. However, we recognize that the extent of Yedoma deposits presented in this database is not complete for a global assessment, because Yedoma deposits also occur in the Taymyr lowlands and Chukotka, and in parts of Alaska and northwestern Canada.
Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks
NASA Astrophysics Data System (ADS)
Miller, B. A.; Koszinski, S.; Wehrhan, M.; Sommer, M.
2015-03-01
The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which is to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m-2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.
Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks
NASA Astrophysics Data System (ADS)
Miller, B. A.; Koszinski, S.; Wehrhan, M.; Sommer, M.
2014-11-01
The distribution of soil organic carbon (SOC) can be variable at small analysis scales, but consideration of its role in regional and global issues demands the mapping of large extents. There are many different strategies for mapping SOC, among which are to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research is to compare direct and indirect approaches to mapping SOC stocks from rule-based, multiple linear regression models applied at the landscape scale via spatial association. The final products for both strategies are high-resolution maps of SOC stocks (kg m-2), covering an area of 122 km2, with accompanying maps of estimated error. For the direct modelling approach, the estimated error map was based on the internal error estimations from the model rules. For the indirect approach, the estimated error map was produced by spatially combining the error estimates of component models via standard error propagation equations. We compared these two strategies for mapping SOC stocks on the basis of the qualities of the resulting maps as well as the magnitude and distribution of the estimated error. The direct approach produced a map with less spatial variation than the map produced by the indirect approach. The increased spatial variation represented by the indirect approach improved R2 values for the topsoil and subsoil stocks. Although the indirect approach had a lower mean estimated error for the topsoil stock, the mean estimated error for the total SOC stock (topsoil + subsoil) was lower for the direct approach. For these reasons, we recommend the direct approach to modelling SOC stocks be considered a more conservative estimate of the SOC stocks' spatial distribution.
Triclosan (TCS) is a broad spectrum anti-microbial compound added to many consumer and personal care products. TCS enters water bodies primarily through wastewater treatment plant (WWTP) effluent and may be introduced by combined sewer overflows or surface water runoff. In estu...
The use of personal care products (PCPs) has resulted in the release and accumulation of a diverse assemblage of emerging chemicals in the environment. Many PCPs incorporate triclosan (TCS), an antimicrobial compound, within their formulations and as a result, TCS is frequently ...
Increase in the use of personal care products (PCPs) has resulted in the release and accumulation of a diverse assemblage of emerging chemicals in the environment. One such chemical, triclosan (TCS), an antimicrobial compound, has been incorporated into many PCPs for approximate...
Belowground competition for nutrients and water is considered a key factor affecting spatial organization and productivity of individual stems within forest stands, yet there are almost no data describing the lateral extent and overlap of competing root systems. We quantified th...
Spatial and temporal quantification of forest residue volumes and delivered costs
Lucas A. Wells; Woodam Chung; Nathaniel M. Anderson; John S. Hogland
2016-01-01
Growing demand for bioenergy, biofuels, and bioproducts has increased interests in the utilization of biomass residues from forest treatments as feedstock. In areas with limited history of industrial biomass utilization, uncertainties in the quantity, distribution, and cost of biomass production and logistics can hinder the development of new bio-based...
Spatial and temporal distribution of trunk-injected 14C-Imidacloprid in Fraxinus trees
Sara R. Tanis; Bert M. Cregg; David Mota-Sanchez; Deborah G. McCullough; Therese M. Poland
2012-01-01
BACKGROUND: Since the discovery of Agrilus planipennis Fairmaire (emerald ash borer) in 2002, researchers have tested several methods of chemical control. Soil drench or trunk injection products containing imidacloprid are commonly used to control adults. However, efficacy can be highly variable andmay be due to uneven translocation of systemic...
Electrochemical camera chip for simultaneous imaging of multiple metabolites in biofilms
Bellin, Daniel L.; Sakhtah, Hassan; Zhang, Yihan; Price-Whelan, Alexa; Dietrich, Lars E. P.; Shepard, Kenneth L.
2016-01-01
Monitoring spatial distribution of metabolites in multicellular structures can enhance understanding of the biochemical processes and regulation involved in cellular community development. Here we report on an electrochemical camera chip capable of simultaneous spatial imaging of multiple redox-active phenazine metabolites produced by Pseudomonas aeruginosa PA14 colony biofilms. The chip features an 8 mm × 8 mm array of 1,824 electrodes multiplexed to 38 parallel output channels. Using this chip, we demonstrate potential-sweep-based electrochemical imaging of whole-biofilms at measurement rates in excess of 0.2 s per electrode. Analysis of mutants with various capacities for phenazine production reveals distribution of phenazine-1-carboxylic acid (PCA) throughout the colony, with 5-methylphenazine-1-carboxylic acid (5-MCA) and pyocyanin (PYO) localized to the colony edge. Anaerobic growth on nitrate confirms the O2-dependence of PYO production and indicates an effect of O2 availability on 5-MCA synthesis. This integrated-circuit-based technique promises wide applicability in detecting redox-active species from diverse biological samples. PMID:26813638
NASA Astrophysics Data System (ADS)
Meile, C. D.; Dwyer, I.; Zhu, Q.; Polerecky, L.; Volkenborn, N.
2017-12-01
Mineralization of organic matter in marine sediments leads to the depletion of oxygen, while activities of infauna introduce oxygenated seawater to the subsurface. In permeable sediments solutes can be transported from animals and their burrows into the surrounding sediment through advection over several centimeters. The intermittency of pumping leads to a spatially heterogeneous distribution of oxidants, with the temporal dynamics depending on sediment reactivity and activity patterns of the macrofauna. Here, we present results from a series of experiments in which these dynamics are studied at high spatial and temporal resolution using planar optodes. From O2, pH and pCO2 optode data, we quantify rates of O2 consumption and dissolved inorganic carbon production, as well alkalinity dynamics, with millimeter-scale resolution. Simulating intermittent irrigation by imposed pumping patterns in thin aquaria, we derive porewater flow patterns, which together with the production and consumption rates cause the chemical distributions and the establishment of reaction fronts. Our analysis thus establishes a quantitative connection between the locally dynamic redox conditions relevant for biogeochemical transformations and macroscopic observations commonly made with sediment cores.
[Poles of American tegumentary leishmaniasis production in northern Paraná State, Brazil].
Monteiro, Wuelton Marcelo; Neitzke, Herintha Coeto; Silveira, Thaís Gomes Verzignassi; Lonardoni, Maria Valdrinez Campana; Teodoro, Ueslei; Ferreira, Maria Eugênia Moreira Costa
2009-05-01
American tegumentary leishmaniasis is endemic in the State of Paraná, with 99.3% of the cases reported in the South of Brazil. Spatial distribution of the disease in northern Paraná was verified, identifying the most relevant geographic areas in epidemiological terms. The study used data recorded on epidemiological forms from the Teaching and Research Clinical Test Laboratory of the State University in Maringá, from 1987 to 2004. The study only included individuals that were infected in the municipalities (counties) in northern Paraná. Identification of the epidemiological units (poles and circuits) was based on spatial density of cases, according to the model proposed by the National Health Foundation, considering the most likely infection sites. Considering 1,933 reported cases, 1,611 were infected in northern Paraná. American tegumentary leishmaniasis distribution in Paraná State suggests two circuits for production of the disease: Paraná-Paranapanema, highlighting the Cinzas-Laranjinha, Tibagi, Ivaí-Pirapó, Piquiri, and Baixo Iguaçu poles, and Ribeira, highlighting the Alto Ribeira pole.
Xian, George; Homer, Collin G.; Granneman, Brian; Meyer, Debra K.
2012-01-01
Remote sensing information has been widely used to monitor vegetation condition and variations in a variety of ecosystems, including shrublands. Careful application of remotely sensed imagery can provide additional spatially explicit, continuous, and extensive data on the composition and condition of shrubland ecosystems. Historically, the most widely available remote sensing information has been collected by Landsat, which has offered large spatial coverage and moderate spatial resolution data globally for nearly three decades. Such medium-resolution satellite remote sensing information can quantify the distribution and variation of terrestrial ecosystems. Landsat imagery has been frequently used with other high-resolution remote sensing data to classify sagebrush components and quantify their spatial distributions (Ramsey and others, 2004; Seefeldt and Booth, 2004; Stow and others, 2008; Underwood and others, 2007). Modeling algorithms have been developed to use field measurements and satellite remote sensing data to quantify the extent and evaluate the quality of shrub ecosystem components in large geographic areas (Homer and others, 2009). The percent cover of sagebrush ecosystem components, including bare-ground, herbaceous, litter, sagebrush, and shrub, have been quantified for entire western states (Homer and others, 2012). Furthermore, research has demonstrated the use of current measurements with historical archives of Landsat imagery to quantify the variations of these components for the last two decades (Xian and others, 2012). The modeling method used to quantify the extent and spatial distribution of sagebrush components over a large area also has required considerable amounts of training data to meet targeted accuracy requirements. These training data have maintained product accuracy by ensuring that they are derived from good quality field measurements collected during appropriate ecosystem phenology and subsequently maximized by extrapolation on high-resolution remote sensing data (Homer and others, 2012). This method has proven its utility; however, to develop these products across even larger areas will require additional cost efficiencies to ensure that an adequate product can be developed for the lowest cost possible. Given the vast geographic extent of shrubland ecosystems in the western United States, identifying cost efficiencies with optimal training data development and subsequent application to medium resolution satellite imagery provide the most likely areas for methodological efficiency gains. The primary objective of this research was to conduct a series of sensitivity tests to evaluate the most optimal and practical way to develop Landsat scale information for estimating the extent and distribution of sagebrush ecosystem components over large areas in the conterminous United States. An existing dataset of sagebrush components developed from extensive field measurements, high-resolution satellite imagery, and medium resolution Landsat imagery in Wyoming was used as the reference database (Homer and others, 2012). Statistical analysis was performed to analyze the relation between the accuracy of sagebrush components and the amount and distribution of training data on Landsat scenes needed to obtain accurate predictions.
Lü, Changwei; He, Jiang; Wang, Bing
2018-02-01
The chemistry of sedimentary organic phosphorus (OP) and its fraction distribution in sediments are greatly influenced by environmental conditions such as terrestrial inputs and runoffs. The linkage of OP with environmental conditions was analyzed on the basis of OP spatial and historical distributions in lake sediments. The redundancy analysis and OP spatial distribution results suggested that both NaOH-OP (OP extracted by NaOH) and Re-OP (residual OP) in surface sediments from the selected 13 lakes reflected the gradient effects of environmental conditions and the autochthonous and/or allochthonous inputs driven by latitude zonality in China. The lake level and salinity of Lake Hulun and the runoff and precipitation of its drainage basin were reconstructed on the basis of the geochemistry index. This work showed that a gradient in weather conditions presented by the latitude zonality in China impacts the OP accumulation through multiple drivers and in many ways. The drivers are mainly precipitation and temperature, governing organic matter (OM) production, degradation rate and transportation in the watershed. Over a long temporal dimension (4000years), the vertical distributions of Re-OP and NaOH-OP based on a dated sediment profile from HLH were largely regulated by the autochthonous and/or allochthonous inputs, which depended on the environmental and climate conditions and anthropogenic activities in the drainage basin. This work provides useful environmental geochemistry information to understand the inherent linkage of OP fractionation with environmental conditions and lake evolution. Copyright © 2017. Published by Elsevier B.V.
Neutron-skin effect in direct-photon and charged-hadron production in Pb+Pb collisions at the LHC
NASA Astrophysics Data System (ADS)
Helenius, Ilkka; Paukkunen, Hannu; Eskola, Kari J.
2017-03-01
A well-established observation in nuclear physics is that in neutron-rich spherical nuclei the distribution of neutrons extends farther than the distribution of protons. In this work, we scrutinize the influence of this so called neutron-skin effect on the centrality dependence of high-p_T direct-photon and charged-hadron production. We find that due to the estimated spatial dependence of the nuclear parton distribution functions, it will be demanding to unambiguously expose the neutron-skin effect with direct photons. However, when taking a ratio between the cross sections for negatively and positively charged high-p_T hadrons, even centrality-dependent nuclear-PDF effects cancel, making this observable a better handle on the neutron skin. Up to 10% effects can be expected for the most peripheral collisions in the measurable region.
Sakellaris, T; Spyrou, G; Tzanakos, G; Panayiotakis, G
2007-11-07
Materials such as a-Se, a-As(2)Se(3), GaSe, GaAs, Ge, CdTe, CdZnTe, Cd(0.8)Zn(0.2)Te, ZnTe, PbO, TlBr, PbI(2) and HgI(2) are potential candidates as photoconductors in direct detectors for digital mammography. The x-ray induced primary electrons inside a photoconductor's bulk comprise the initial signal that propagates and forms the final signal (image) on the detector's electrodes. An already developed model for a-Se has been properly extended to simulate the primary electron production in the materials mentioned. Primary electron characteristics, such as their energy, angular and spatial distributions that strongly influence the characteristics of the final image, were studied for both monoenergetic and polyenergetic x-ray spectra in the mammographic energy range. The characteristic feature in the electron energy distributions for PbI(2) and HgI(2) is the atomic deexcitation peaks, whereas for the rest of the materials their shape can also be influenced by the electrons produced from primary photons. The electrons have a small tendency to be forward ejected whereas they prefer to be ejected perpendicular (theta = pi/2) to the incident beam's axis and at two lobes around phi = 0 and phi = pi. At practical mammographic energies (15-40 keV) a-Se, a-As(2)Se(3) and Ge have the minimum azimuthal uniformity whereas CdZnTe, Cd(0.8)Zn(0.2)Te and CdTe the maximum one. The spatial distributions for a-Se, a-As(2)Se(3), GaSe, GaAs, Ge, PbO and TlBr are almost independent of the polyenergetic spectrum, while those for CdTe, CdZnTe, Cd(0.8)Zn(0.2)Te, ZnTe, PbI(2) and HgI(2) have a spectrum dependence. In the practical mammographic energy range and at this primitive stage of primary electron production, a-Se has the best inherent spatial resolution as compared to the rest of the photoconductors. PbO has the minimum bulk space in which electrons can be produced whereas CdTe has the maximum one.
NASA Astrophysics Data System (ADS)
Sturm, K.; Helmschrot, J.
2013-12-01
Snow and its spatial and temporal patterns are important for catchment hydrology in the semi-arid eastern Mediterranean. Since most of the annual rainfall is stored as snow during winter and released during drier conditions in spring and summer, downstream regions of the Taurus Mountains relying on snow water temporarily stored in reservoirs for agricultural use are heavily dependent on the timing of snowmelt discharge. Runoff is controlled by the amount of accumulated snow, its distribution, and the climatic conditions controlling spring snowmelt. Thus, knowledge about spatial and temporal snow cover dynamics is essential for sustainable water resources management. The lack of observations in high-altitude regions reinforces the application of different snow products for a better assessment of spatio-temporal snow cover patterns. To better assess the quality of such products, simulated daily snow cover and EO-based snow cover products were compared for the Egribuk subcatchment, in the Central Taurus Mountains, Turkey. Daily information on snow cover, depths, and snow water equivalent was derived from distributed hydrological modeling using the J2000 model. Furthermore, 8-day MODIS snow cover data from Terra (MOD10A2) and Aqua (MYD10A2) satellites at a spatial resolution of 500 m were synchronized to receive cloud-free images. From this effort, 253 images covering the period between 07/04/2002 and 12/27/2007 were used for further analyses. The products were analyzed individually to determine the number of snow-covered days in relation to freezing days, spring snowmelt onsets, and temporal patterns, reflecting the effect of altitude on the percentage snow-covered area (SCA) along a topographic gradient at various time-steps. Monthly and 8-day spatial patterns of a single snow season were also examined. When SCA peaks at all altitudes, in February and March, the results of both products show a good agreement regarding SCA extent. In contrast, the extent of SCA differs notably during snow accumulation and ablation periods, the highest deviations occurring in December, April, and May. The highest SCA inconsistencies are observed in the low and mid altitudes, whereas the higher elevations are snow-covered very early in the snow season as modeled by J2000. During these periods, J2000 simulates a significantly larger SCA than MODIS. The analysis of individual time steps suggests that the J2000 daily model does capture individual snow events, whereas the MODIS products fail to do so due to their temporal resolution. Furthermore, acquisition time and inner-daily melt and re-freezing effects may affect SCA estimates from MODIS data. In other cases, differences can clearly be associated to insufficient model input data, primarily due to limited spatial precipitation and temperature data. Our study indicates that individual products might provide inconsistent information on temporal and spatial snow cover. We recommend considering a combined analysis of different snow products in order to provide reliable information on snow cover dynamics, in particular in eastern Mediterranean high-altitude environments.
Zooplankton and the oceanography of the eastern tropical Pacific: A review
NASA Astrophysics Data System (ADS)
Fernández-Álamo, María Ana; Färber-Lorda, Jaime
2006-05-01
We review the spatial and temporal patterns of zooplankton in the eastern tropical Pacific Ocean and relationships with oceanographic factors that affect zooplankton distribution, abundance and trophic relationships. Large-scale spatial patterns of some zooplankton groups show broad coincidence with surface water masses, circulation, and upwelling regions, in agreement with an ecological and dynamic partitioning of the pelagic ecosystem. The papers reviewed and a new compilation of zooplankton volume data at large-scale show that abundance patterns of zooplankton biomass have their highest values in the upwelling regions, including the Gulf of Tehuantepec, the Costa Rica Dome, the equatorial cold tongue, and the coast of Peru. Some of the first studies of zooplankton vertical distribution were done in this region, and a general review of the topic is presented. The possible physiological implications of vertical migration in zooplankton and the main hypotheses are described, with remarks on the importance of the oxygen minimum zone (OMZ) as a barrier to both the vertical distribution and migration of zooplankton in the region. Recent results, using multiple-net gear, show that vertical distribution is more complex than previously thought. There are some well-adapted species that do live and migrate within the OMZ. Temporal patterns are reviewed and summarized with historical data. Seasonal variations in zooplankton biomass follow productivity cycles in upwelling areas. No zooplankton time series exist to resolve ENSO effects in oceanic regions, but some El Niño events have had effects in the Peru Current ecosystem. Multidecadal periods of up to 50 years show a shift from a warm sardine regime with a low zooplankton biomass to a cool anchovy regime in the eastern Pacific with higher zooplankton biomasses. However, zooplankton volume off Peru has remained at low values since the 1972 El Niño, a trend opposite to that of anchoveta biomass since 1984. Studies of trophic relations emphasize the difference in the productivity cycle in the eastern tropical Pacific compared to temperate or polar ecosystems, with no particular peaks in the stocks of either zooplankton or phytoplankton. Productivity is more dependent on local events like coastal upwelling or water circulation, especially in the equatorial countercurrent and around the equatorial cool-tongue. Micrograzers are very important in the tropics as are predatory mesozooplankton. Up to 70% of the daily primary productivity is consumed by microzooplankton, which thus regulates the phytoplankton stocks. Micrograzers are an important link between primary producers, including bacteria, and mesozooplankton, constituting up to 80% of mesozooplankton food. Oceanography affects zooplankton trophic relationships through spatial-temporal effects on primary productivity and on the distributions of metabolic factors, food organisms, and predators. This paper is part of a comprehensive review of the oceanography of the eastern tropical Pacific.
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.
Shifts in wind energy potential following land-use driven vegetation dynamics in complex terrain.
Fang, Jiannong; Peringer, Alexander; Stupariu, Mihai-Sorin; Pǎtru-Stupariu, Ileana; Buttler, Alexandre; Golay, Francois; Porté-Agel, Fernando
2018-10-15
Many mountainous regions with high wind energy potential are characterized by multi-scale variabilities of vegetation in both spatial and time dimensions, which strongly affect the spatial distribution of wind resource and its time evolution. To this end, we developed a coupled interdisciplinary modeling framework capable of assessing the shifts in wind energy potential following land-use driven vegetation dynamics in complex mountain terrain. It was applied to a case study area in the Romanian Carpathians. The results show that the overall shifts in wind energy potential following the changes of vegetation pattern due to different land-use policies can be dramatic. This suggests that the planning of wind energy project should be integrated with the land-use planning at a specific site to ensure that the expected energy production of the planned wind farm can be reached over its entire lifetime. Moreover, the changes in the spatial distribution of wind and turbulence under different scenarios of land-use are complex, and they must be taken into account in the micro-siting of wind turbines to maximize wind energy production and minimize fatigue loads (and associated maintenance costs). The proposed new modeling framework offers, for the first time, a powerful tool for assessing long-term variability in local wind energy potential that emerges from land-use change driven vegetation dynamics over complex terrain. Following a previously unexplored pathway of cause-effect relationships, it demonstrates a new linkage of agro- and forest policies in landscape development with an ultimate trade-off between renewable energy production and biodiversity targets. Moreover, it can be extended to study the potential effects of micro-climatic changes associated with wind farms on vegetation development (growth and patterning), which could in turn have a long-term feedback effect on wind resource distribution in mountainous regions. Copyright © 2018 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Matsui, H.; Koike, M.; Kondo, Y.; Takegawa, N.; Kita, K.; Miyazaki, Y.; Hu, M.; Chang, S.; Blake, D. R.; Fast, J. D.; Zaveri, R. A.; Streets, D. G.; Zhang, Q.; Zhu, T.
2009-12-01
Regional aerosol model calculations were made using the WRF-CMAQ and WRF-chem models to study spatial and temporal variations of aerosols around Beijing, China, in the summer of 2006, when the CAREBEIJING-2006 intensive campaign was conducted. Model calculations captured temporal variations of primary (such as elemental carbon, EC) and secondary (such as sulfate) aerosols observed in and around Beijing. The spatial distributions of aerosol optical depth observed by the MODIS satellite sensors were also reproduced over northeast China. Model calculations showed distinct differences in spatial distributions between primary and secondary aerosols in association with synoptic-scale meteorology. Secondary aerosols increased in air around Beijing on a scale of about 1000 x 1000 km2 under an anticyclonic pressure system. This airmass was transported northward from the high anthropogenic emission area extending south of Beijing with continuous photochemical production. Subsequent cold front passage brought clean air from the north, and polluted air around Beijing was swept to the south of Beijing. This cycle was repeated about once a week and was found to be responsible for observed enhancements/reductions of aerosols at the intensive measurement sites. In contrast to secondary aerosols, the spatial distributions of primary aerosols (EC) reflected those of emissions, resulting in only slight variability despite the changes in synoptic-scale meteorology. In accordance with these results, source apportionment simulations revealed that primary aerosols around Beijing were controlled by emissions within 100 km around Beijing within the preceding 24 hours, while emissions as far as 500 km and within the preceding 3 days were found to affect secondary aerosols.
NASA Astrophysics Data System (ADS)
De Vleeschouwer, N.; Verhoest, N.; Pauwels, V. R. N.
2015-12-01
The continuous monitoring of soil moisture in a permanent network can yield an interesting data product for use in hydrological data assimilation. Major advantages of in situ observations compared to remote sensing products are the potential vertical extent of the measurements, the finer temporal resolution of the observation time series, the smaller impact of land cover variability on the observation bias, etc. However, two major disadvantages are the typical small integration volume of in situ measurements and the often large spacing between monitoring locations. This causes only a small part of the modelling domain to be directly observed. Furthermore, the spatial configuration of the monitoring network is typically temporally non-dynamic. Therefore two questions can be raised. Do spatially sparse in situ soil moisture observations contain a sufficient data representativeness to successfully assimilate them into the largely unobserved spatial extent of a distributed hydrological model? And if so, how is this assimilation best performed? Consequently two important factors that can influence the success of assimilating in situ monitored soil moisture are the spatial configuration of the monitoring network and the applied assimilation algorithm. In this research the influence of those factors is examined by means of synthetic data-assimilation experiments. The study area is the ± 100 km² catchment of the Bellebeek in Flanders, Belgium. The influence of the spatial configuration is examined by varying the amount of locations and their position in the landscape. The latter is performed using several techniques including temporal stability analysis and clustering. Furthermore the observation depth is considered by comparing assimilation of surface layer (5 cm) and deeper layer (50 cm) observations. The impact of the assimilation algorithm is assessed by comparing the performance obtained with two well-known algorithms: Newtonian nudging and the Ensemble Kalman Filter.
NASA Astrophysics Data System (ADS)
Castanho, A. D. D. A.; Coe, M. T.; Maia Andrade, E.; Walker, W.; Baccini, A.; Brando, P. M.; Farina, M.
2017-12-01
The Caatinga found in the semiarid region in northeastern Brazil is the largest continuous seasonally dry tropical forest in South America. The region has for centuries been subject to anthropogenic activities of land conversion, abandonment, and regrowth. The region also has a large spatial variability of edaphic-climatic properties. These effects together contribute to a wide variability of plant physiognomies and biomass concentration. In addition to land use change due to anthropogenic activities the region is exposed in the near and long term to dryer conditions. The main goal of this work was to validate a high spatial resolution (30 m) map of above ground biomass, understand the climatic role in the biomass spatial variability in the present, and the potential threat to vegetation for future climatic shifts. Satellite-derived biomass products are advanced tools that can address spatial changes in forest structure for an extended region. Here we combine a compilation of published field phytosociological observations across the region with a new 30-meter spatial resolution satellite biomass product. Climate data used for this analyses were based on the CRU (Climate Research Unit, UEA) for the historical time period and for the future a mean and 25-75% quantiles of the CMIP Global Climate model estimates for the RCP scenarios of 4.5 and 8.5 W/m2. The high heterogeneity in the biomass and physiognomy distribution across the Caatinga region is mostly explained by the climatic space defined by the precipitation and dryness index. The Caatinga region has historically already been exposed to shift in its climatic properties, driving all the physiognomies, to a dryer climatic space within the last decade. Future climate intensify the observed trends. This study provides a clearer understanding of the spatial distribution of Caatinga vegetation, its biomass, and relationships to climate, which are essential for strategic development planning, preservation of the biome functions, human services, and biodiversity, face future climate scenarios.
The assessment of spatial distribution of soil salinity risk using neural network.
Akramkhanov, Akmal; Vlek, Paul L G
2012-04-01
Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km(2)) results were used to upscale soil salinity to a district area (∼300 km(2)). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m(-1)). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70-90% of locations were correctly estimated.
Xue, Hong; Cheng, Xi; Zhang, Qi; Wang, Huijun; Zhang, Bing; Qu, Weidong; Wang, Youfa
2017-09-01
The fast food (FF) industry has expanded rapidly in China during the past two decades, in parallel with an increase in the prevalence of obesity. Using government-reported longitudinal data from 21 provinces and cities in China, this study examined the growth over time and the spatial distribution patterns of the FF industry as well as the key social economic factors involved. We visualized the temporal and geographic distributions of FF industry development and conducted cross-sectional and longitudinal spatial analysis to assess associations between macroeconomic conditions, population dynamics, and the growth and distributional changes of the industry. It grew faster in the southeast coastal (more economically developed) areas since 2005 than in other regions. The industry was: 1) highly correlated with Gross Domestic Product; 2) highly correlated with per capita disposable income for urban residents; 3) moderately correlated with urban population; and 4) not correlated with an increase of population size. The mean center of the FF industry shifted westward as the mean center of the GDP moved in the same direction, while the mean center of the population shifted eastward. The results suggest that the rapid FF industry expansion in China was closely associated with economic growth and that improving the food environment should be a major component in local economic development planning. Copyright © 2017 Elsevier Inc. All rights reserved.
McClellan, Catherine M.; Brereton, Tom; Dell'Amico, Florence; Johns, David G.; Cucknell, Anna-C.; Patrick, Samantha C.; Penrose, Rod; Ridoux, Vincent; Solandt, Jean-Luc; Stephan, Eric; Votier, Stephen C.; Williams, Ruth; Godley, Brendan J.
2014-01-01
The temperate waters of the North-Eastern Atlantic have a long history of maritime resource richness and, as a result, the European Union is endeavouring to maintain regional productivity and biodiversity. At the intersection of these aims lies potential conflict, signalling the need for integrated, cross-border management approaches. This paper focuses on the marine megafauna of the region. This guild of consumers was formerly abundant, but is now depleted and protected under various national and international legislative structures. We present a meta-analysis of available megafauna datasets using presence-only distribution models to characterise suitable habitat and identify spatially-important regions within the English Channel and southern bight of the North Sea. The integration of studies from dedicated and opportunistic observer programmes in the United Kingdom and France provide a valuable perspective on the spatial and seasonal distribution of various taxonomic groups, including large pelagic fishes and sharks, marine mammals, seabirds and marine turtles. The Western English Channel emerged as a hotspot of biodiversity for megafauna, while species richness was low in the Eastern English Channel. Spatial conservation planning is complicated by the highly mobile nature of marine megafauna, however they are important components of the marine environment and understanding their distribution is a first crucial step toward their inclusion into marine ecosystem management. PMID:24586985
The Spatiotemporal pattern and driving forces of the paddy in the Northeastern China
NASA Astrophysics Data System (ADS)
Du, G.; Li, Q.; Chun, X.
2017-12-01
The cropland is the production place that protects the regional food security, and the paddy is the main part of the cropland. Since the 21st century, the China's socio-economy has been grown, the structure of the cropland has significantly changed. The Northeast region has gradually become one of the major commodity grain production bases. Meanwhile, the paddy also has gradually increased year by year. Therefore, it is necessary that analyze the tempo-spatial characteristics and the influencing factors of the northeast in China, and the results provide the basis that reveals the change of cropland structure and its causes.In this study, we use the spatial models of GIS and mathematical statistics methods to analyze the tempo-spatial characteristics and the influencing facts of the paddy in the Northeastern China with the spatial data from 2000 to 2015. In order to fully characterize the spatiotemporal characteristics of the paddy, we choose single land use type dynamic degree and land use extension index to quantitatively describe the change degree and the speed of the regional paddy, and the characteristics are visualized with "3S" means. Meanwhile, the relative change rate and the center of gravity model are chosen to explore the region differences and the distribution of the distribution center of paddy field change in Northeast China. In addition, in order to further reveal the cause of the paddy change, we use the OLS, SAM or SEM models to analyze the main influencing factors of spatiotemporal variation of the paddy field.
NASA Astrophysics Data System (ADS)
Itoh, M.; Kosugi, Y.; Takanashi, S.; Hayashi, Y.; Kanemitsu, S.; Osaka, K.; Tani, M.; Nik, A. R.
2010-09-01
To clarify the factors controlling temporal and spatial variations of soil carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes, we investigated these gas fluxes and environmental factors in a tropical rainforest in Peninsular Malaysia. Temporal variation of CO2 flux in a 2-ha plot was positively related to soil water condition and rainfall history. Spatially, CO2 flux was negatively related to soil water condition. When CO2 flux hotspots were included, no other environmental factors such as soil C or N concentrations showed any significant correlation. Although the larger area sampled in the present study complicates explanations of spatial variation of CO2 flux, our results support a previously reported bipolar relationship between the temporal and spatial patterns of CO2 flux and soil water condition observed at the study site in a smaller study plot. Flux of CH4 was usually negative with little variation, resulting in the soil at our study site functioning as a CH4 sink. Both temporal and spatial variations of CH4 flux were positively related to the soil water condition. Soil N concentration was also related to the spatial distribution of CH4 flux. Some hotspots were observed, probably due to CH4 production by termites, and these hotspots obscured the relationship between both temporal and spatial variations of CH4 flux and environmental factors. Temporal variation of N2O flux and soil N2O concentration was large and significantly related to the soil water condition, or in a strict sense, to rainfall history. Thus, the rainfall pattern controlled wet season N2O production in soil and its soil surface flux. Spatially, large N2O emissions were detected in wet periods at wetter and anaerobic locations, and were thus determined by soil physical properties. Our results showed that, even in Southeast Asian rainforests where distinct dry and wet seasons do not exist, variation in the soil water condition related to rainfall history controlled the temporal variations of soil CO2 flux, CH4 uptake, and N2O emission. The soil water condition associated with soil hydraulic properties was also the important controlling factor of the spatial distributions of these gas fluxes.
NMR relaxation in natural soils: Fast Field Cycling and T1-T2 Determination by IR-MEMS
NASA Astrophysics Data System (ADS)
Haber-Pohlmeier, S.; Pohlmeier, A.; Stapf, S.; van Dusschoten, D.
2009-04-01
Soils are natural porous media of highest importance for food production and sustainment of water resources. For these functions, prominent properties are their ability of water retainment and transport, which are mainly controlled by pore size distribution. The latter is related to NMR relaxation times of water molecules, of which the longitudinal relaxation time can be determined non-invasively by fast-field cycling relaxometry (FFC) and both are obtainable by inversion recovery - multi-echo- imaging (IR-MEMS) methods. The advantage of the FFC method is the determination of the field dependent dispersion of the spin-lattice relaxation rate, whereas MRI at high field is capable of yielding spatially resolved T1 and T2 times. Here we present results of T1- relaxation time distributions of water in three natural soils, obtained by the analysis of FFC data by means of the inverse Laplace transformation (CONTIN)1. Kaldenkirchen soil shows relatively broad bimodal distribution functions D(T1) which shift to higher relaxation rates with increasing relaxation field. These data are compared to spatially resolved T1- and T2 distributions, obtained by IR-MEMS. The distribution of T1 corresponds well to that obtained by FFC.
Droughts in India from 1981 to 2013 and Implications to Wheat Production
Zhang, Xiang; Obringer, Renee; Wei, Chehan; Chen, Nengcheng; Niyogi, Dev
2017-01-01
Understanding drought from multiple perspectives is critical due to its complex interactions with crop production, especially in India. However, most studies only provide singular view of drought and lack the integration with specific crop phenology. In this study, four time series of monthly meteorological, hydrological, soil moisture, and vegetation droughts from 1981 to 2013 were reconstructed for the first time. The wheat growth season (from October to April) was particularly analyzed. In this study, not only the most severe and widespread droughts were identified, but their spatial-temporal distributions were also analyzed alone and concurrently. The relationship and evolutionary process among these four types of droughts were also quantified. The role that the Green Revolution played in drought evolution was also studied. Additionally, the trends of drought duration, frequency, extent, and severity were obtained. Finally, the relationship between crop yield anomalies and all four kinds of drought during the wheat growing season was established. These results provide the knowledge of the most influential drought type, conjunction, spatial-temporal distributions and variations for wheat production in India. This study demonstrates a novel approach to study drought from multiple views and integrate it with crop growth, thus providing valuable guidance for local drought mitigation. PMID:28294189
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.
NASA Astrophysics Data System (ADS)
Pakhomov, E. A.; Froneman, P. W.; Perissinotto, R.
Available data on the spatial distribution and feeding ecophysiology of Antarctic krill, Euphausia superba, and the tunicate, Salpa thompsoni, in the Southern Ocean are summarized in this study. Antarctic krill and salps generally display pronounced spatial segregation at all spatial scales. This appears to be the result of a clear biotopical separation of these key species in the Antarctic pelagic food web. Krill and salps are found in different water masses or water mass modifications, which are separated by primary or secondary frontal features. On the small-scale (<100 km), Antarctic krill and salps are usually restricted to the specific water parcels, or are well segregated vertically. Krill and salp grazing rates estimated using the in situ gut fluorescence technique are among the highest recorded in the Antarctic pelagic food web. Although krill and salps at times may remove the entire daily primary production, generally their grazing impact is moderate (⩽50% of primary production). The regional ecological consequences of years of high salp densities may be dramatic. If the warming trend, which is observed around the Antarctic Peninsula and in the Southern Ocean, continues, salps may become a more prominent player in the trophic structure of the Antarctic marine ecosystem. This likely would be coupled with a dramatic decrease in krill productivity, because of a parallel decrease in the spatial extension of the krill biotope. The high Antarctic regions, particularly the Marginal Ice Zone, have, however, effective physiological mechanisms that may provide protection against the salp invasion.
NASA Technical Reports Server (NTRS)
Colliander, Andreas; Cosh, Michael H.; Misra, Sidharth; Jackson, Thomas J.; Crow, Wade T.; Chan, Steven; Bindlish, Rajat; Chae, Chun; Holifield Collins, Chandra; Yueh, Simon H.
2017-01-01
The NASA SMAP (Soil Moisture Active Passive) mission conducted the SMAP Validation Experiment 2015 (SMAPVEX15) in order to support the calibration and validation activities of SMAP soil moisture data products. The main goals of the experiment were to address issues regarding the spatial disaggregation methodologies for improvement of soil moisture products and validation of the in situ measurement upscaling techniques. To support these objectives high-resolution soil moisture maps were acquired with the airborne PALS (Passive Active L-band Sensor) instrument over an area in southeast Arizona that includes the Walnut Gulch Experimental Watershed (WGEW), and intensive ground sampling was carried out to augment the permanent in situ instrumentation. The objective of the paper was to establish the correspondence and relationship between the highly heterogeneous spatial distribution of soil moisture on the ground and the coarse resolution radiometer-based soil moisture retrievals of SMAP. The high-resolution mapping conducted with PALS provided the required connection between the in situ measurements and SMAP retrievals. The in situ measurements were used to validate the PALS soil moisture acquired at 1-km resolution. Based on the information from a dense network of rain gauges in the study area, the in situ soil moisture measurements did not capture all the precipitation events accurately. That is, the PALS and SMAP soil moisture estimates responded to precipitation events detected by rain gauges, which were in some cases not detected by the in situ soil moisture sensors. It was also concluded that the spatial distribution of the soil moisture resulted from the relatively small spatial extents of the typical convective storms in this region was not completely captured with the in situ stations. After removing those cases (approximately10 of the observations) the following metrics were obtained: RMSD (root mean square difference) of0.016m3m3 and correlation of 0.83. The PALS soil moisture was also compared to SMAP and in situ soil moisture at the 36-km scale, which is the SMAP grid size for the standard product. PALS and SMAP soil moistures were found to be very similar owing to the close match of the brightness temperature measurements and the use of a common soil moisture retrieval algorithm. Spatial heterogeneity, which was identified using the high-resolution PALS soil moisture and the intensive ground sampling, also contributed to differences between the soil moisture estimates. In general, discrepancies found between the L-band soil moisture estimates and the 5-cm depth in situ measurements require methodologies to mitigate the impact on their interpretations in soil moisture validation and algorithm development. Specifically, the metrics computed for the SMAP radiometer-based soil moisture product over WGEW will include errors resulting from rainfall, particularly during the monsoon season when the spatial distribution of soil moisture is especially heterogeneous.
Yang, Jichao; Wang, Weiguo; Zhao, Mengwei; Chen, Bin; Dada, Olusegun A; Chu, Zhihui
2015-02-15
The concentrations of As, Sb, Hg, Pb, Cd, and Ba in the surface and core sediments of the oil and gas producing region of the Beibu Gulf were measured by Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES), Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Atomic Fluorescence Spectrometry (AFS), and the spatial distribution and historical trends of these elements are discussed. The results show that the concentrations of these elements are highest near the platforms. The results of Enrichment Factor (EF) and Potential Ecological Risk Index (PERI) also reveal significantly higher enrichment around the platforms, which imply that the offshore petroleum production was the cause of the unusual distribution and severe enrichment of these elements in the study area. The environment around the platforms was highly laden with toxic elements, thereby representing a very high ecological risk to the environment of the study area. Copyright © 2014 Elsevier Ltd. All rights reserved.
Kotzagianni, Maria; Kakkava, Eirini; Couris, Stelios
2016-04-01
Laser-induced breakdown spectroscopy (LIBS) is used for the mapping of local structures (i.e., reactants and products zones) and for the determination of fuel distribution by means of the local equivalence ratio ϕ in laminar, premixed air-hydrocarbon flames. The determination of laser threshold energy to induce breakdown in the different zones of flames is employed for the identification and demarcation of the local structures of a premixed laminar flame, while complementary results about fuel concentration were obtained from measurements of the cyanogen (CN) band Β(2)Σ(+)--Χ(2)Σ(+), (Δυ = 0) at 388.3 nm and the ratio of the atomic lines of hydrogen (Hα) and oxygen (O(I)), Hα/O. The combination of these LIBS-based methods provides a relatively simple to use, rapid, and accurate tool for online and in situ combustion diagnostics, providing valuable information about the fuel distribution and the spatial variations of the local structures of a flame. © The Author(s) 2016.
Dynamically assisted Schwinger effect beyond the spatially-uniform-field approximation
NASA Astrophysics Data System (ADS)
Aleksandrov, I. A.; Plunien, G.; Shabaev, V. M.
2018-06-01
We investigate the phenomenon of electron-positron pair production from vacuum in the presence of a strong electric field superimposed by a weak but fast varying pulse which substantially increases the total particle yield. We employ a nonperturbative numerical technique and perform the calculations beyond the spatially-uniform-field approximation, i.e., dipole approximation, taking into account the coordinate dependence of the fast component. The analysis of the main characteristics of the pair-production process (momentum spectra of particles and total amount of pairs) reveals a number of important features which are absent within the previously used approximation. In particular, the structure of the momentum distribution is modified both qualitatively and quantitatively, and the total number of pairs created as well as the enhancement factor due to dynamical assistance become significantly smaller.
Evolution of the potential distribution area of french mediterranean forests under global warming
NASA Astrophysics Data System (ADS)
Gaucherel, C.; Guiot, J.; Misson, L.
2008-02-01
This work aims at understanding future spatial and temporal distributions of tree species in the Mediterranean region of France under various climates. We focused on two different species (Pinus Halepensis and Quercus Ilex) and compared their growth under the IPCC-B2 climate scenario in order to quantify significant changes between present and future. The influence of environmental factors such as atmospheric CO2 increase and topography on the tree growth has also been quantified. We modeled species growths with the help of a process-based model (MAIDEN), previously calibrated over measured ecophysiological and dendrochronological series with a Bayesian scheme. The model was fed with the ARPEGE - MeteoFrance climate model, combined with an explicit increase in CO2 atmospheric concentration. The main output of the model gives the carbon allocation in boles and thus tree production. Our results show that the MAIDEN model is correctly able to simulate pine and oak production in space and time, after detailed calibration and validation stages. Yet, these simulations, mainly based on climate, are indicative and not predictive. The comparison of simulated growth at end of 20 and 21 centuries, show a shift of the pine production optimum from about 650 to 950 m due to 2.5°K temperature increase, while no optimum has been found for oak. With the direct effect of CO2 increase taken into account, both species show a significant increase in productivity (+26 and +43% for pine and oak, respectively) at the end of the 21 century. While both species have complementary growth mechanisms, they have a good chance to extend their spatial distribution and their elevation in the Alps during the 21 century under the IPCC-B2 climate scenario. This extension is mainly due to the CO2 fertilization effect.
NASA Astrophysics Data System (ADS)
Berman, S. L.; Frey, K. E.; Shake, K. L.; Cooper, L. W.; Grebmeier, J. M.
2014-12-01
Dissolved organic matter (DOM) plays an important role in marine ecosystems as both a carbon source for the microbial food web (and thus a source of CO2 to the atmosphere) and as a light inhibitor in marine environments. The presence of chromophoric dissolved organic matter (CDOM; the optically active portion of total DOM) can have significant controlling effects on transmittance of sunlight through the water column and therefore on primary production as well as the heat balance of the upper ocean. However, CDOM is also susceptible to photochemical degradation, which decreases the flux of solar radiation that is absorbed. Knowledge of the current spatial and temporal distribution of CDOM in marine environments is thus critical for understanding how ongoing and future changes in climate may impact these biological, biogeochemical, and physical processes. We describe the quantity and quality of CDOM along five key productive transects across a developing Distributed Biological Observatory (DBO) in the Pacific Arctic region. The samples were collected onboard the CCGS Sir Wilfred Laurier in July 2013 and 2014. Monitoring of the variability of CDOM along transects of high productivity can provide important insights into biological and biogeochemical cycling across the region. Our analyses include overall concentrations of CDOM, as well as proxy information such as molecular weight, lability, and source (i.e., autochthonous vs. allochthonous) of organic matter. We utilize these field observations to compare with satellite-derived CDOM concentrations determined from the Aqua MODIS satellite platform, which ultimately provides a spatially and temporally continuous synoptic view of CDOM concentrations throughout the region. Examining the current relationships among CDOM, sea ice variability, biological productivity, and biogeochemical cycling in the Pacific Arctic region will likely provide key insights for how ecosystems throughout the region will respond in future scenarios of climate change.
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].
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.
Morelle, Jérôme; Schapira, Mathilde; Claquin, Pascal
2017-10-01
Exopolysaccharides (EPS) play an important role in the carbon flux and may be directly linked to phytoplankton and microphytobenthos production, most notably in estuarine systems. However the temporal and spatial dynamics of estuarine EPS are still not well understood, nor how primary productivity triggers this variability at these different scales. The aim of this study was to investigate the primary productivity of phytoplankton and EPS dynamics in the Seine estuary over a tidal cycle in three different haline zones over two contrasted seasons. The other objectives was to investigate the origin of pools of soluble carbohydrates (S-EPS) and transparent exopolymeric particles (TEP) in phytoplankton, microphytobenthos or other compartments. High frequency measurements of productivity were made in winter and summer 2015. Physical and chemical parameters, biomass and EPS were measured at hourly intervals in sub-surface waters and just above the water sediment-interface. Our results confirmed that high frequency measurements improve the accuracy of primary productivity estimations and associated carbon fluxes in estuaries. The photosynthetic parameters were shown to be strongly controlled by salinity and by the concentrations of suspended particle matter at the smallest temporal and at spatial scales. At these scales, our results showed an inverse relationship between EPS concentrations and biomass and productivity, and a positive relationship with sediment resuspension. Additionally, the distribution of EPS appears to be linked to hydrodynamics with the tide at daily scale and with the winter at seasonal scale. At spatial scale, the maximum turbidity zone played an important role in the distribution of TEP. Our results suggest that, in the Seine estuary, between 9% and 33% of the S-EPS pool in the water column can be attributed to phytoplankton excretion, while only 0.4%-1.6% (up to 6.14% in exceptional conditions) originates from the microphytobenthos compartments. Most EPS was attributed to remobilization of detrital carbon pools in the maximum turbidity zone and in the sediment or allochthonous origin. Copyright © 2017 Elsevier Ltd. All rights reserved.
Importance of spatial autocorrelation in modeling bird distributions at a continental scale
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.
Evidence for simultaneous production of $$J/\\psi$$ and $$\\Upsilon$$ mesons
DOE Office of Scientific and Technical Information (OSTI.GOV)
Abazov, Victor Mukhamedovich
We report evidence for the simultaneous production of J/ψ and Υ mesons in 8.1 fb -1 of data collected at √s =1.96 TeV by the D0 experiment at the Fermilab pp - Tevatron Collider. Events with these characteristics are expected to be produced predominantly by gluon-gluon interactions. In our analysis, we extract the effective cross section characterizing the initial parton spatial distribution, σ eff = 2.2 ± 0.7 (stat) ± 0.9 (syst) mb.
Evidence for simultaneous production of $$J/\\psi$$ and $$\\Upsilon$$ mesons
Abazov, Victor Mukhamedovich
2016-02-25
We report evidence for the simultaneous production of J/ψ and Υ mesons in 8.1 fb -1 of data collected at √s =1.96 TeV by the D0 experiment at the Fermilab pp - Tevatron Collider. Events with these characteristics are expected to be produced predominantly by gluon-gluon interactions. In our analysis, we extract the effective cross section characterizing the initial parton spatial distribution, σ eff = 2.2 ± 0.7 (stat) ± 0.9 (syst) mb.
Production of slow protonium in vacuum
NASA Astrophysics Data System (ADS)
Zurlo, N.; Rizzini, E. Lodi; Venturelli, L.; Amoretti, M.; Carraro, C.; Lagomarsino, V.; Macrì, M.; Manuzio, G.; Testera, G.; Variola, A.; Amsler, C.; Pruys, H.; Regenfus, C.; Bonomi, G.; Fontana, A.; Genova, P.; Montagna, P.; Rotondi, A.; Cesar, C. L.; Charlton, M.; Mitchard, D.; Jørgensen, L. V.; Madsen, N.; Van der Werf, D. P.; Doser, M.; Kellerbauer, A.; Landua, R.; Funakoshi, R.; Hayano, R. S.; Posada, L. G.; Yamazaki, Y.
We describe how protonium, the quasi-stable antiproton-proton bound system, has been synthesized following the interaction of antiprotons with the molecular ion H{2/+} in a nested Penning trap environment. From a careful analysis of the spatial distributions of antiproton annihilation events in the ATHENA experiment, evidence is presented for protonium production with sub-eV kinetic energies in states around n = 70, with iow angular momenta. This work provides a new two-body system for studies using laser spectroscopic techniques.
Evidence For The Production Of Slow Antiprotonic Hydrogen In Vacuum
NASA Astrophysics Data System (ADS)
Zurlo, N.; Amoretti, M.; Amsler, C.; Bonomi, G.; Carraro, C.; Cesar, C. L.; Charlton, M.; Doser, M.; Fontana, A.; Funakoshi, R.; Genova, P.; Hayano, R. S.; Jørgensen, L. V.; Kellerbauer, A.; Lagomarsino, V.; Landua, R.; Rizzini, E. Lodi; Macrì, M.; Madsen, N.; Manuzio, G.; Mitchard, D.; Montagna, P.; Posada, L. G.; Pruys, H.; Regenfus, C.; Rotondi, A.; Testera, G.; der Werf, D. P. Van; Variola, A.; Venturelli, L.; Yamazaki, Y.
2006-10-01
We present evidence showing how antiprotonic hydrogen, the quasistable antiproton (p¯)-proton bound system, has been synthesized following the interaction of antiprotons with the molecular ion H2+ in a nested Penning trap environment. From a careful analysis of the spatial distributions of antiproton annihilation events, evidence is presented for antiprotonic hydrogen production with sub-eV kinetic energies in states around n=70, and with low angular momenta. The slow antiprotonic hydrogen may be studied using laser spectroscopic techniques.
Production of slow protonium in vacuum
NASA Astrophysics Data System (ADS)
Zurlo, N.; Amoretti, M.; Amsler, C.; Bonomi, G.; Carraro, C.; Cesar, C. L.; Charlton, M.; Doser, M.; Fontana, A.; Funakoshi, R.; Genova, P.; Hayano, R. S.; Jørgensen, L. V.; Kellerbauer, A.; Lagomarsino, V.; Landua, R.; Lodi Rizzini, E.; Macrì, M.; Madsen, N.; Manuzio, G.; Mitchard, D.; Montagna, P.; Posada, L. G.; Pruys, H.; Regenfus, C.; Rotondi, A.; Testera, G.; van der Werf, D. P.; Variola, A.; Venturelli, L.; Yamazaki, Y.
2006-09-01
We descrbe how protonium, the quasi-stable antiproton-proton bound system, has been synthesized following the interaction of antiprotons with the molecular ion H_2^+ in a nested Penning trap environment. From a careful analysis of the spatial distributions of antiproton annihilation events in the ATHENA experiment, evidence is presented for protonium production with sub-eV kinetic energies in states around n = 70, with low angular momenta. This work provides a new two-body system for studies using laser spectroscopic techniques.
Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun
2014-01-01
Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.
Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun
2014-01-01
Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760
The Spatial Variability of Organic Matter and Decomposition Processes at the Marsh Scale
NASA Astrophysics Data System (ADS)
Yousefi Lalimi, Fateme; Silvestri, Sonia; D'Alpaos, Andrea; Roner, Marcella; Marani, Marco
2017-04-01
Coastal salt marshes sequester carbon as they respond to the local Rate of Relative Sea Level Rise (RRSLR) and their accretion rate is governed by inorganic soil deposition, organic soil production, and soil organic matter (SOM) decomposition. It is generally recognized that SOM plays a central role in marsh vertical dynamics, but while existing limited observations and modelling results suggest that SOME varies widely at the marsh scale, we lack systematic observations aimed at understanding how SOM production is modulated spatially as a result of biomass productivity and decomposition rate. Marsh topography and distance to the creek can affect biomass and SOM production, while a higher topographic elevation increases drainage, evapotranspiration, aeration, thereby likely inducing higher SOM decomposition rates. Data collected in salt marshes in the northern Venice Lagoon (Italy) show that, even though plant productivity decreases in the lower areas of a marsh located farther away from channel edges, the relative contribution of organic soil production to the overall vertical soil accretion tends to remain constant as the distance from the channel increases. These observations suggest that the competing effects between biomass production and aeration/decomposition determine a contribution of organic soil to total accretion which remains approximately constant with distance from the creek, in spite of the declining plant productivity. Here we test this hypothesis using new observations of SOM and decomposition rates from marshes in North Carolina. The objective is to fill the gap in our understanding of the spatial distribution, at the marsh scale, of the organic and inorganic contributions to marsh accretion in response to RRSLR.
Modeling landscape net ecosystem productivity (LandNEP) under alternative management regimes
Eugenie S. Euskirchen; Jiquan Chen; Harbin Li; Eric J. Gustafson; Thomas R. Crow
2002-01-01
Forests have been considered as a major carbon sink within the global carbon budget. However, a fragmented forest landscape varies significantly in its composition and age structure, and the amount of carbon sequestered at this level remains generally unknown to the scientific community. More precisely, the temporal dynamics and spatial distribution of net ecosystem...
USDA-ARS?s Scientific Manuscript database
Background: Luminal bacteria and/or their products play a pivotal role in the pathogenesis of chronic intestinal inflammation associated with inflammatory bowel diseases (IBD). While host responses to resident flora may initiate IBD, the subsets of bacteria responsible for mediating inflammation in ...
USDA-ARS?s Scientific Manuscript database
Accurately predicting phenology in crop simulation models is critical for correctly simulating crop production. While extensive work in modeling phenology has focused on the temperature response function (resulting in robust phenology models), limited work on quantifying the phenological responses t...
Development effects on private forest management: a critical look at the evidence.
J.D. Kline
2007-01-01
The timber production and ecological effects of forest land development are influenced by both the rate and spatial distribution of forest land development, and how remaining undeveloped forest lands are managed. Regarding effects on management, research conducted in the U.S. South and in Oregon suggests that development can reduce the intensity with which landowners...
C.W. Woodall; C.E. Fiedler; R.E. McRoberts
2009-01-01
Forest ecosystems may be actively managed toward heterogeneous stand structures to provide both economic (e.g., wood production and carbon credits) and environmental benefits (e.g., invasive pest resistance). In order to facilitate wider adoption of possibly more sustainable forest stand structures, defining growth expectations among alternative management scenarios is...
Merging Areas In Timber Mart South Data
Jeffrey P. Prestemon; John M. Pye
1999-01-01
For over twenty years, Timber Mart-South (TMS) has been distributing prices of various wood products from Southern forests. These long-term price series have been a critical resource for research into timber price and supply trends in the southern United States. Such analyses rely on consistent temporal and spatial reporting units, but these units have not always been...
Kleta, Sylvia; Hammerl, Jens Andre; Dieckmann, Ralf; Malorny, Burkhard; Borowiak, Maria; Halbedel, Sven; Prager, Rita; Trost, Eva; Flieger, Antje; Wilking, Hendrik; Vygen-Bonnet, Sabine; Busch, Ulrich; Messelhäußer, Ute; Horlacher, Sabine; Schönberger, Katharina; Lohr, Dorothee; Aichinger, Elisabeth; Luber, Petra; Hensel, Andreas; Al Dahouk, Sascha
2017-10-01
We investigated 543 Listeria monocytogenes isolates from food having a temporal and spatial distribution compatible with that of the invasive listeriosis outbreak occurring 2012-2016 in southern Germany. Using forensic microbiology, we identified several products from 1 manufacturer contaminated with the outbreak genotype. Continuous molecular surveillance of food isolates could prevent such outbreaks.
Dome diagnostics system of optical parameters and characteristics of LEDs
NASA Astrophysics Data System (ADS)
Peretyagin, Vladimir S.; Pavlenko, Nikita A.
2017-09-01
Scientific and technological progress of recent years in the production of the light emitting diodes (LEDs) has led to the expansion of areas of their application from the simplest systems to high precision lighting devices used in various fields of human activity. However, development and production (especially mass production) of LED lighting devices are impossible without a thorough analysis of its parameters and characteristics. There are many ways and devices for analysis the spatial, energy and colorimetric parameters of LEDs. The most methods are intended for definition only one parameter (for example, luminous flux) or one characteristic (for example, the angular distribution of energy or the spectral characteristics). Besides, devices used these methods are intended for measuring parameters in only one point or plane. This problem can be solved by using a dome diagnostics system of optical parameters and characteristics of LEDs, developed by specialists of the department OEDS chair of ITMO University in Russia. The paper presents the theoretical aspects of the analysis of LED's spatial (angular), energy and color parameters by using mentioned of diagnostics system. The article also presents the results of spatial), energy and color parameters measurements of some LEDs brands.
NASA Astrophysics Data System (ADS)
Tang, Wei; Liao, Mingsheng; Zhang, Lu; Li, Wei; Yu, Weimin
2016-09-01
A high spatial and temporal resolution of the precipitable water vapour (PWV) in the atmosphere is a key requirement for the short-scale weather forecasting and climate research. The aim of this work is to derive temporally differenced maps of the spatial distribution of PWV by analysing the tropospheric delay "noise" in interferometric synthetic aperture radar (InSAR). Time series maps of differential PWV were obtained by processing a set of ENVISAT ASAR (Advanced Synthetic Aperture Radar) images covering the area of southern California, USA from 6 October 2007 to 29 November 2008. To get a more accurate PWV, the component of hydrostatic delay was calculated and subtracted by using ERA-Interim reanalysis products. In addition, the ERA-Interim was used to compute the conversion factors required to convert the zenith wet delay to water vapour. The InSAR-derived differential PWV maps were calibrated by means of the GPS PWV measurements over the study area. We validated our results against the measurements of PWV derived from the Medium Resolution Imaging Spectrometer (MERIS) which was located together with the ASAR sensor on board the ENVISAT satellite. Our comparative results show strong spatial correlations between the two data sets. The difference maps have Gaussian distributions with mean values close to zero and standard deviations below 2 mm. The advantage of the InSAR technique is that it provides water vapour distribution with a spatial resolution as fine as 20 m and an accuracy of ˜ 2 mm. Such high-spatial-resolution maps of PWV could lead to much greater accuracy in meteorological understanding and quantitative precipitation forecasts. With the launch of Sentinel-1A and Sentinel-1B satellites, every few days (6 days) new SAR images can be acquired with a wide swath up to 250 km, enabling a unique operational service for InSAR-based water vapour maps with unprecedented spatial and temporal resolution.
Temporal and Spatial Aspects of Gas Release During the 2010 Apparition of Comet 103P/Hartley-2
NASA Technical Reports Server (NTRS)
Mumma, M. J.; Bonev, B. P.; Villanueva, G. L.; Paganini, L.; DiSanti, M. A.; Gibb, E. L.; Keane, J. V.; Meech, K. J.; Blake, G. A.; Ellis, R. S.;
2011-01-01
We report measurements of eight primary volatiles (H2O, HCN, CH4, C2H6, CH3OH, C2H2, H2CO, and NH3) and two product species (OH and NH2) in comet lO3P/Hartley-2 using high dispersion infrared spectroscopy. We quantified the long- and short-term behavior of volatile release over a three-month interval that encompassed the comet's close approach to Earth, its perihelion passage, and flyby of the comet by the Deep Impact spacecraft during the EPOXI mission. We present production rates for individual species, their mixing ratios relative to water, and their spatial distributions in the coma on multiple dates. The production rates for water, ethane, HCN, and methanol vary in a manner consistent with independent measures of nucleus rotation, but mixing ratios for HCN, C2H6, & CH3OH are independent of rotational phase. Our results demonstrate that the ensemble average composition of gas released from the nucleus is well defined, and relatively constant over the three-month interval (September 18 through December 1,7). If individual vents vary in composition, enough diverse vents must be active simultaneously to approximate (in sum) the bulk composition of the nucleus. The released primary volatiles exhibit diverse spatial properties which favor the presence of separate polar and apolar ice phases in the nucleus, establish dust and gas release from icy clumps, and from the nucleus, and provide insights into the driver for the cyanogen (CN) polar jet. The spatial distributions of C2H6 & HCN along the near-polar jet (UT 19.5 October) and nearly orthogonal to it (UT 22.5 October) are discussed relative to the origin of CN. The ortho-para ratio (OPR) of water was 2.85 +/- 0.20; the lower bound (2.65) defines T(sub spin) > 32 K. These values are consistent with results returned from ISO in 1997 .
Mortillaro, Jean-Michel; Rigal, François; Rybarczyk, Hervé; Bernardes, Marcelo; Abril, Gwenaël; Meziane, Tarik
2012-01-01
One of the greatest challenges in understanding the Amazon basin functioning is to ascertain the role played by floodplains in the organic matter (OM) cycle, crucial for a large spectrum of ecological mechanisms. Fatty acids (FAs) were combined with environmental descriptors and analyzed through multivariate and spatial tools (asymmetric eigenvector maps, AEM and principal coordinates of neighbor matrices, PCNM). This challenge allowed investigating the distribution of suspended particulate organic matter (SPOM), in order to trace its seasonal origin and quality, along a 800 km section of the Amazon river-floodplain system. Statistical analysis confirmed that large amounts of saturated FAs (15:0, 18:0, 24:0, 25:0 and 26:0), an indication of refractory OM, were concomitantly recorded with high pCO2 in rivers, during the high water season (HW). Contrastingly, FAs marker which may be attributed in this ecosystem to aquatic plants (18:2ω6 and 18:3ω3) and cyanobacteria (16:1ω7), were correlated with higher O2, chlorophyll a and pheopigments in floodplains, due to a high primary production during low waters (LW). Decreasing concentrations of unsaturated FAs, that characterize labile OM, were recorded during HW, from upstream to downstream. Furthermore, using PCNM and AEM spatial methods, FAs compositions of SPOM displayed an upstream-downstream gradient during HW, which was attributed to OM retention and the extent of flooded forest in floodplains. Discrimination of OM quality between the Amazon River and floodplains corroborate higher autotrophic production in the latter and transfer of OM to rivers at LW season. Together, these gradients demonstrate the validity of FAs as predictors of spatial and temporal changes in OM quality. These spatial and temporal trends are explained by 1) downstream change in landscape morphology as predicted by the River Continuum Concept; 2) enhanced primary production during LW when the water level decreased and its residence time increased as predicted by the Flood Pulse Concept. PMID:23029412
NASA Astrophysics Data System (ADS)
Abitew, T. A.; van Griensven, A.; Bauwens, W.
2015-12-01
Evapotranspiration is the main process in hydrology (on average around 60%), though has not received as much attention in the evaluation and calibration of hydrological models. In this study, Remote Sensing (RS) derived Evapotranspiration (ET) is used to improve the spatially distributed processes of ET of SWAT model application in the upper Mara basin (Kenya) and the Blue Nile basin (Ethiopia). The RS derived ET data is obtained from recently compiled global datasets (continuously monthly data at 1 km resolution from MOD16NBI,SSEBop,ALEXI,CMRSET models) and from regionally applied Energy Balance Models (for several cloud free days). The RS-RT data is used in different forms: Method 1) to evaluate spatially distributed evapotransiration model resultsMethod 2) to calibrate the evotranspiration processes in hydrological modelMethod 3) to bias-correct the evapotranpiration in hydrological model during simulation after changing the SWAT codesAn inter-comparison of the RS-ET products shows that at present there is a significant bias, but at the same time an agreement on the spatial variability of ET. The ensemble mean of different ET products seems the most realistic estimation and was further used in this study.The results show that:Method 1) the spatially mapped evapotranspiration of hydrological models shows clear differences when compared to RS derived evapotranspiration (low correlations). Especially evapotranspiration in forested areas is strongly underestimated compared to other land covers.Method 2) Calibration allows to improve the correlations between the RS and hydrological model results to some extent.Method 3) Bias-corrections are efficient in producing (sesonal or annual) evapotranspiration maps from hydrological models which are very similar to the patterns obtained from RS data.Though the bias-correction is very efficient, it is advised to improve the model results by better representing the ET processes by improved plant/crop computations, improved agricultural management practices or by providing improved meteorological data.
NASA Astrophysics Data System (ADS)
Ferrant, S.; Gascoin, S.; Veloso, A.; Salmon-Monviola, J.; Claverie, M.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, J.-L.; Durand, P.; Bustillo, V.
2014-12-01
The growing availability of high-resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the possibilities offered for improving crop-growth dynamic simulation with the distributed agro-hydrological model: topography-based nitrogen transfer and transformation (TNT2). We used a leaf area index (LAI) map series derived from 105 Formosat-2 (F2) images covering the period 2006-2010. The TNT2 model (Beaujouan et al., 2002), calibrated against discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2005-2010 data set (climate, land use, agricultural practices, and discharge and nitrate fluxes at the outlet). Data from the first year (2005) were used to initialize the hydrological model. A priori agricultural practices obtained from an extensive field survey, such as seeding date, crop cultivar, and amount of fertilizer, were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop-field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics using the a priori input parameters displayed temporal shifts from those observed LAI profiles that are irregularly distributed in space (between field crops) and time (between years). By resetting the seeding date at the crop-field level, we have developed an optimization method designed to efficiently minimize this temporal shift and better fit the crop growth against both the spatial observations and crop production. This optimization of simulated LAI has a negligible impact on water budgets at the catchment scale (1 mm yr-1 on average) but a noticeable impact on in-stream nitrogen fluxes (around 12%), which is of interest when considering nitrate stream contamination issues and the objectives of TNT2 modeling. This study demonstrates the potential contribution of the forthcoming high spatial and temporal resolution products from the Sentinel-2 satellite mission for improving agro-hydrological modeling by constraining the spatial representation of crop productivity.
NASA Astrophysics Data System (ADS)
Ferrant, S.; Gascoin, S.; Veloso, A.; Salmon-Monviola, J.; Claverie, M.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, J.-L.; Durand, P.; Bustillo, V.
2014-07-01
The recent and forthcoming availability of high resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the perspective offered by improving the crop growth dynamic simulation using the distributed agro-hydrological model, Topography based Nitrogen transfer and Transformation (TNT2), using LAI map series derived from 105 Formosat-2 (F2) images during the period 2006-2010. The TNT2 model (Beaujouan et al., 2002), calibrated with discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2006-2010 dataset (climate, land use, agricultural practices, discharge and nitrate fluxes at the outlet). A priori agricultural practices obtained from an extensive field survey such as seeding date, crop cultivar, and fertilizer amount were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics with a priori input parameters showed an temporal shift with observed LAI profiles irregularly distributed in space (between field crops) and time (between years). By re-setting seeding date at the crop field level, we proposed an optimization method to minimize efficiently this temporal shift and better fit the crop growth against the spatial observations as well as crop production. This optimization of simulated LAI has a negligible impact on water budget at the catchment scale (1 mm yr-1 in average) but a noticeable impact on in-stream nitrogen fluxes (around 12%) which is of interest considering nitrate stream contamination issues and TNT2 model objectives. This study demonstrates the contribution of forthcoming high spatial and temporal resolution products of Sentinel-2 satellite mission in improving agro-hydrological modeling by constraining the spatial representation of crop productivity.
NASA Technical Reports Server (NTRS)
Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Chien, Janet Y. L.; Houser, Paul R. (Technical Monitor)
2001-01-01
Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover maps have been available since September 13, 2000. These products, at 500 m spatial resolution, are available through the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado. By the 2001-02 winter, 5 km climate-modeling grid (CMG) products will be available for presentation of global views of snow cover and for use in climate models. All MODIS snow-cover products are produced from automated algorithms that map snow in an objective manner. In this paper, we describe the MODIS snow products, and show snow maps from the fall of 2000 in North America.
NASA Technical Reports Server (NTRS)
Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Chien, Y. L.; Houser, Paul R. (Technical Monitor)
2001-01-01
Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover maps have been available since September 13, 2000. These products, at 500-m spatial resolution, are available through the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado. By the 2001-02 winter, 5-km climate-modeling grid (CMG) products will be available for presentation of global views of snow cover and for use in climate models. All MODIS snow-cover products are produced from automated algorithms that map snow in an objective manner. In this paper, we describe the MODIS snow products, and show snow maps from the fall of 2000 in North America.
Spatial Variability in Biodegradation Rates as Evidenced by Methane Production from an Aquifer
Adrian, Neal R.; Robinson, Joseph A.; Suflita, Joseph M.
1994-01-01
Accurate predictions of carbon and energy cycling rates in the environment depend on sampling frequencies and on the spatial variability associated with biological activities. We examined the variability associated with anaerobic biodegradation rates at two sites in an alluvial sand aquifer polluted by municipal landfill leachate. In situ rates of methane production were measured for almost a year, using anaerobic wells installed at two sites. Methane production ranged from 0 to 560 μmol · m-2 · day-1 at one site (A), while a range of 0 to 120,000 μmol · m-2 · day-1 was measured at site B. The mean and standard deviations associated with methane production at site A were 17 and 57 μmol · m-2 · day-1, respectively. The comparable summary statistics for site B were 2,000 and 9,900 μmol · m-2 · day-1. The coefficients of variation at sites A and B were 340 and 490%, respectively. Despite these differences, the two sites had similar seasonal trends, with the maximal rate of methane production occurring in summer. However, the relative variability associated with the seasonal rates changed very little. Our results suggest that (i) two spatially distinct sites exist in the aquifer, (ii) methanogenesis is a highly variable process, (iii) the coefficient of variation varied little with the rate of methane production, and (iv) in situ anaerobic biodegradation rates are lognormally distributed. PMID:16349410
Time reversibility and nonequilibrium thermodynamics of second-order stochastic processes.
Ge, Hao
2014-02-01
Nonequilibrium thermodynamics of a general second-order stochastic system is investigated. We prove that at steady state, under inversion of velocities, the condition of time reversibility over the phase space is equivalent to the antisymmetry of spatial flux and the symmetry of velocity flux. Then we show that the condition of time reversibility alone cannot always guarantee the Maxwell-Boltzmann distribution. Comparing the two conditions together, we find that the frictional force naturally emerges as the unique odd term of the total force at thermodynamic equilibrium, and is followed by the Einstein relation. The two conditions respectively correspond to two previously reported different entropy production rates. In the case where the external force is only position dependent, the two entropy production rates become one. We prove that such an entropy production rate can be decomposed into two non-negative terms, expressed respectively by the conditional mean and variance of the thermodynamic force associated with the irreversible velocity flux at any given spatial coordinate. In the small inertia limit, the former term becomes the entropy production rate of the corresponding overdamped dynamics, while the anomalous entropy production rate originates from the latter term. Furthermore, regarding the connection between the first law and second law, we find that in the steady state of such a limit, the anomalous entropy production rate is also the leading order of the Boltzmann-factor weighted difference between the spatial heat dissipation densities of the underdamped and overdamped dynamics, while their unweighted difference always tends to vanish.
Schaffrath, David; Bernhofer, Christian
2013-01-01
Grasslands in Inner Mongolia are important for livestock farming while ecosystem functioning and water consumption are dominated by evapotranspiration (ET). In this paper we studied the spatiotemporal distribution and variability of ET and its components in Inner Mongolian grasslands over a period of 10 years, from 2002 to 2011. ET was modelled pixel-wise for more than 3000 1 km(2) pixels with the physically-based hydrological model BROOK90. The model was parameterised from eddy-covariance measurements and daily input was generated from MODIS leaf area index and surface temperatures. Modelled ET was also compared with the ET provided by the MODIS MOD16 ET data. The study showed ET to be highly variable in both time and space in Inner Mongolian grasslands. The mean coefficient of variation of 8-day ET in the study area varied between 25% and 40% and was up to 75% for individual pixels indicating a high innerannual variability of ET. Generally, ET equals or exceeds P during the vegetation period, but high precipitation in 2003 clearly exceeded ET in this year indicating a recharge of soil moisture and groundwater. Despite the high interannual and innerannual variations of spatial ET, the study also showed the existence of an intrinsic long-term spatial pattern of ET distribution, which can be explained partly by altitude and longitude (R(2) = 0.49). In conclusion, the results of this research suggest the development of dynamic and productive rangeland management systems according to the inherent variability of rainfall, productivity and ET in order to restore and protect Inner Mongolian grasslands.
Villa-Mancera, Abel; Pastelín-Rojas, César; Olivares-Pérez, Jaime; Córdova-Izquierdo, Alejandro; Reynoso-Palomar, Alejandro
2018-05-01
This study investigated the prevalence, production losses, spatial clustering, and predictive risk mapping in different climate zones in five states of Mexico. The bulk tank milk samples obtained between January and April 2015 were analyzed for antibodies against Ostertagia ostertagi using the Svanovir ELISA. A total of 1204 farm owners or managers answered the questionnaire. The overall herd prevalence and mean optical density ratio (ODR) of parasite were 61.96% and 0.55, respectively. Overall, the production loss was approximately 0.542 kg of milk per parasited cow per day (mean ODR = 0.92, 142 farms, 11.79%). The spatial disease cluster analysis using SatScan software indicated that two high-risk clusters were observed. In the multivariable analysis, three models were tested for potential association with the ELISA results supported by climatic, environmental, and management factors. The final logistic regression model based on both climatic/environmental and management variables included the factors rainfall, elevation, land surface temperature (LST) day, and parasite control program that were significantly associated with an increased risk of infection. Geostatistical kriging was applied to generate a risk map for the presence of parasite in dairy cattle herds in Mexico. The results indicate that climatic and meteorological factors had a higher potential impact on the spatial distribution of O. ostertagi than the management factors.
Spatial and Temporal Variation of Land Surface Temperature in Fujian Province from 2001 TO 2015
NASA Astrophysics Data System (ADS)
Li, Y.; Wang, X.; Ding, Z.
2018-04-01
Land surface temperature (LST) is an essential parameter in the physics of land surface processes. The spatiotemporal variations of LST on the Fujian province were studied using AQUA Moderate Resolution Imaging Spectroradiometer LST data. Considering the data gaps in remotely sensed LST products caused by cloud contamination, the Savitzky-Golay (S-G) filter method was used to eliminate the influence of cloud cover and to describe the periodical signals of LST. Observed air temperature data from 27 weather stations were employed to evaluate the fitting performance of the S-G filter method. Results indicate that S-G can effectively fit the LST time series and remove the influence of cloud cover. Based on the S-G-derived result, Spatial and temporal Variations of LST in Fujian province from 2001 to 2015 are analysed through slope analysis. The results show that: 1) the spatial distribution of annual mean LST generally exhibits consistency with altitude in the study area and the average of LST was much higher in the east than in the west. 2) The annual mean temperature of LST declines slightly among 15 years in Fujian. 3) Slope analysis reflects the spatial distribution characteristics of LST changing trend in Fujian.Improvement areas of LST are mainly concentrated in the urban areas of Fujian, especially in the eastern urban areas. Apparent descent areas are mainly distributed in the area of Zhangzhou and eastern mountain area.
Tisseuil, Clément; Velo, Enkelejda; Bino, Silvia; Kadriaj, Perparim; Mersini, Kujtim; Shukullari, Ada; Simaku, Artan; Rogozi, Elton; Caputo, Beniamino; Ducheyne, Els; Della Torre, Alessandra; Reiter, Paul; Gilbert, Marius
2018-02-01
The increasing spread of the Asian tiger mosquito, Aedes albopictus, in Europe and US raises public health concern due to the species competence to transmit several exotic human arboviruses, among which dengue, chikungunya and Zika, and urges the development of suitable modeling approach to forecast the spatial and temporal distribution of the mosquito. Here we developed a dynamical species distribution modeling approach forecasting Ae. albopictus eggs abundance at high spatial (0.01 degree WGS84) and temporal (weekly) resolution over 10 Balkan countries, using temperature times series of Modis data products and altitude as input predictors. The model was satisfactorily calibrated and validated over Albania based observed eggs abundance data weekly monitored during three years. For a given week of the year, eggs abundance was mainly predicted by the number of eggs and the mean temperature recorded in the preceding weeks. That is, results are in agreement with the biological cycle of the mosquito, reflecting the effect temperature on eggs spawning, maturation and hatching. The model, seeded by initial egg values derived from a second model, was then used to forecast the spatial and temporal distribution of eggs abundance over the selected Balkan countries, weekly in 2011, 2012 and 2013. The present study is a baseline to develop an easy-handling forecasting model able to provide information useful for promoting active surveillance and possibly prevention of Ae. albopictus colonization in presently non-infested areas in the Balkans as well as in other temperate regions.
The Node Deployment of Intelligent Sensor Networks Based on the Spatial Difference of Farmland Soil
Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun
2015-01-01
Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop conditions are influenced by the spatial distribution of soil nutrients. If the nutrients are distributed evenly, the crop conditions are expected to be approximately uniform with little difference; on the contrary, there will be great differences in crop conditions. In accordance with the differences in the spatial distribution of soil information in farmland, fuzzy c-means clustering was applied to divide the farmland into several areas, where the soil fertility of each area is nearly uniform. Then the crop growth information in the area could be monitored with complete coverage by deploying a sensor node there, which could greatly decrease the deployed sensor nodes. Moreover, in order to accurately judge the optimal cluster number of fuzzy c-means clustering, a discriminant function for Normalized Intra-Cluster Coefficient of Variation (NICCV) was established. The sensitivity analysis indicates that NICCV is insensitive to the fuzzy weighting exponent, but it shows a strong sensitivity to the number of clusters. PMID:26569243
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.
NASA Astrophysics Data System (ADS)
Casey, J. G.; Collier, A. M.; Hannigan, M.; Piedrahita, R.; Vaughn, B. H.; Sherwood, O.
2015-12-01
In recent years, aided by the advent of horizontal drilling used in conjunction with hydraulic fracturing, oil and gas production in basins around the United States has increased significantly. A study was conducted in two oil and gas basins during the spring and summer of 2015 to investigate the spatial and temporal variability of several atmospheric trace gases that can be influenced by oil and gas extraction including methane, ozone, and carbon dioxide. Fifteen air quality monitors were distributed across the Denver Julesburg Basin in Northeast Colorado, and the San Juan Basin, which stretches from Southwest Colorado into Northwest New Mexico in Four Corners Region. Spatial variability in ozone was observed across each basin. The presence of dynamic short-term trends observed in the mole fraction of methane and carbon dioxide indicate the extent to which each site is uniquely impacted by local emission sources. Diurnal trends of these two constituents lead toward a better understanding of local pooling of emissions that can be influenced by topography, the planetary boundary layer height, atmospheric stability, as well as the composition and flux of local and regional emissions sources.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hornibrook, E.R.C.; Longstaffe, F.J.; Fyfe, W.S.
The identity and distribution of substrates that support CH{sub 4} production in wetlands is poorly known at present. Organic compounds are the primary methanogenic precursor at all depths within anoxic wetland soils; however, the distribution of microbial processes by which these compounds are ultimately converted to CH{sub 4} is uncertain. Based on stable isotope measurements of CH{sub 4} and {Sigma}CO{sub 2} extracted from soil porewaters in two temperate zone wetlands, we present evidence that a systematic spatial distribution of microbial methanogenic pathways can exist in certain anoxic, organic-rich soils. CH{sub 4} production by the acetate fermentation pathway is favored inmore » the shallow subsurface. while methanogenesis from the reduction of CO{sub 2} with H{sub 2} becomes more predominant in older, less reactive peat at depth. This distribution can account for many of the reported CH{sub 4} emission characteristics of wetlands, in particular, their sensitivity to changes in primary productivity, temperature, and hydrology. These factors play an important role in controlling the short-term supply of labile substrates to fermentive methanogens in the shallow subsurface where the most intense CH{sub 4} production occurs. Predominance of the CO{sub 2}-reduction pathway at depth may help to explain reports of CH{sub 4} with a semifossil age in lower peat layers. 60 refs., 7 figs., 1 tab.« less
Increased food production and reduced water use through optimized crop distribution
NASA Astrophysics Data System (ADS)
Davis, Kyle Frankel; Rulli, Maria Cristina; Seveso, Antonio; D'Odorico, Paolo
2017-12-01
Growing demand for agricultural commodities for food, fuel and other uses is expected to be met through an intensification of production on lands that are currently under cultivation. Intensification typically entails investments in modern technology — such as irrigation or fertilizers — and increases in cropping frequency in regions suitable for multiple growing seasons. Here we combine a process-based crop water model with maps of spatially interpolated yields for 14 major food crops to identify potential differences in food production and water use between current and optimized crop distributions. We find that the current distribution of crops around the world neither attains maximum production nor minimum water use. We identify possible alternative configurations of the agricultural landscape that, by reshaping the global distribution of crops within current rainfed and irrigated croplands based on total water consumption, would feed an additional 825 million people while reducing the consumptive use of rainwater and irrigation water by 14% and 12%, respectively. Such an optimization process does not entail a loss of crop diversity, cropland expansion or impacts on nutrient and feed availability. It also does not necessarily invoke massive investments in modern technology that in many regions would require a switch from smallholder farming to large-scale commercial agriculture with important impacts on rural livelihoods.
Neutron-skin effect in direct-photon and charged-hadron production in Pb+Pb collisions at the LHC.
Helenius, Ilkka; Paukkunen, Hannu; Eskola, Kari J
2017-01-01
A well-established observation in nuclear physics is that in neutron-rich spherical nuclei the distribution of neutrons extends farther than the distribution of protons. In this work, we scrutinize the influence of this so called neutron-skin effect on the centrality dependence of high-[Formula: see text] direct-photon and charged-hadron production. We find that due to the estimated spatial dependence of the nuclear parton distribution functions, it will be demanding to unambiguously expose the neutron-skin effect with direct photons. However, when taking a ratio between the cross sections for negatively and positively charged high-[Formula: see text] hadrons, even centrality-dependent nuclear-PDF effects cancel, making this observable a better handle on the neutron skin. Up to 10% effects can be expected for the most peripheral collisions in the measurable region.
The Potential for Spatial Distribution Indices to Signal Thresholds in Marine Fish Biomass
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.
Briki, Meryem; Ji, Hongbing; Li, Cai; Ding, Huaijian; Gao, Yang
2015-12-01
Mining and smelting have been releasing huge amount of toxic substances into the environment. In the present study, agricultural soil and different agricultural products (potato, Chinese cabbage, garlic bolt, corn) were analyzed to examine the source, spatial distribution, and risk of 12 elements (As, Be, Bi, Cd, Co, Cr, Cu, Hg, Ni, Pb, Sb, and Zn) in agricultural soil near mine fields, smelting fields, and mountain field around Hezhang County, west of Guizhou Province, China. Multivariate statistical analysis indicated that in mining area, As, Bi, Cd, Cu, Hg, Pb, Sb, and Zn were generated from anthropogenic sources; in smelting area, As, Be, Cd, Co, Cu, Pb, Sb, and Zn were derived from anthropogenic sources through zinc smelting ceased in 2004. The enrichment factors (EFs) and ecological risk index (RI) of soil in mining area are the most harmful, showing extremely high enrichment and very high ecological risk of As, Bi, Cd, Cu, Hg, Pb, Sb, and Zn. Zinc is the most significant enriched in the smelting area; however, mountain area has a moderate enrichment and ecological risk and do not present any ecological risk. According to spatial distribution, the concentrations depend on the nearby mining and smelting activities. Transfer factors (TFs) in the smelting area and mountain are high, implying a threat for human consumption. Therefore, further studies should be carried out taking into account the harm of those heavy metals and potential negative health effects from the consumption of agricultural products in these circumstances.
Large Scale Relationship between Aquatic Insect Traits and Climate.
Bhowmik, Avit Kumar; Schäfer, Ralf B
2015-01-01
Climate is the predominant environmental driver of freshwater assemblage pattern on large spatial scales, and traits of freshwater organisms have shown considerable potential to identify impacts of climate change. Although several studies suggest traits that may indicate vulnerability to climate change, the empirical relationship between freshwater assemblage trait composition and climate has been rarely examined on large scales. We compared the responses of the assumed climate-associated traits from six grouping features to 35 bioclimatic indices (~18 km resolution) for five insect orders (Diptera, Ephemeroptera, Odonata, Plecoptera and Trichoptera), evaluated their potential for changing distribution pattern under future climate change and identified the most influential bioclimatic indices. The data comprised 782 species and 395 genera sampled in 4,752 stream sites during 2006 and 2007 in Germany (~357,000 km² spatial extent). We quantified the variability and spatial autocorrelation in the traits and orders that are associated with the combined and individual bioclimatic indices. Traits of temperature preference grouping feature that are the products of several other underlying climate-associated traits, and the insect order Ephemeroptera exhibited the strongest response to the bioclimatic indices as well as the highest potential for changing distribution pattern. Regarding individual traits, insects in general and ephemeropterans preferring very cold temperature showed the highest response, and the insects preferring cold and trichopterans preferring moderate temperature showed the highest potential for changing distribution. We showed that the seasonal radiation and moisture are the most influential bioclimatic aspects, and thus changes in these aspects may affect the most responsive traits and orders and drive a change in their spatial distribution pattern. Our findings support the development of trait-based metrics to predict and detect climate-related changes of freshwater assemblages.
Application of satellite products and hydrological modelling for flood early warning
NASA Astrophysics Data System (ADS)
Koriche, Sifan A.; Rientjes, Tom H. M.
2016-06-01
Floods have caused devastating impacts to the environment and society in Awash River Basin, Ethiopia. Since flooding events are frequent, this marks the need to develop tools for flood early warning. In this study, we propose a satellite based flood index to identify the runoff source areas that largely contribute to extreme runoff production and floods in the basin. Satellite based products used for development of the flood index are CMORPH (Climate Prediction Center MORPHing technique: 0.25° by 0.25°, daily) product for calculation of the Standard Precipitation Index (SPI) and a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) for calculation of the Topographic Wetness Index (TWI). Other satellite products used in this study are for rainfall-runoff modelling to represent rainfall, potential evapotranspiration, vegetation cover and topography. Results of the study show that assessment of spatial and temporal rainfall variability by satellite products may well serve in flood early warning. Preliminary findings on effectiveness of the flood index developed in this study indicate that the index is well suited for flood early warning. The index combines SPI and TWI, and preliminary results illustrate the spatial distribution of likely runoff source areas that cause floods in flood prone areas.
Bioeconomic modeling for a small-scale sea cucumber fishery in Yucatan, Mexico
Hernández-Flores, Alvaro; Cuevas-Jiménez, Alfonso; Condal, Alfonso; Espinoza-Méndez, Juan Carlos
2018-01-01
Due to the heavy exploitation of holothurians over the last few decades, it is necessary to implement fishing regulations aimed at reversing this situation. Holothurians require specific regulations that take into account their biology and ecology. Their behavior to group and form patches as a strategy for feeding, defense and reproduction, makes them vulnerable to overfishing. The higher the population density, the higher the catchability coefficient, and because they are sedentary organisms, the catchability does not change significantly until the density is very low. Hence, the stock assessment of holothurians can be improved by analyzing their spatial distribution. This paper proposes a stock assessment technique that considers the spatial distribution pattern of the sea cucumber Isostichopus badionotus from Yucatan, Mexico. A bioeconomic spatial model was developed to explain the interactions between fishing effort allocation, quasi-profits and the population in the short term. Because of the high price of the species and the low production costs, artisanal fishers preferred to maximize short-term quasi-profits, rather than the long-term benefits they could gain with low fishing mortality rates. PMID:29315339
Bioeconomic modeling for a small-scale sea cucumber fishery in Yucatan, Mexico.
Hernández-Flores, Alvaro; Cuevas-Jiménez, Alfonso; Poot-Salazar, Alicia; Condal, Alfonso; Espinoza-Méndez, Juan Carlos
2018-01-01
Due to the heavy exploitation of holothurians over the last few decades, it is necessary to implement fishing regulations aimed at reversing this situation. Holothurians require specific regulations that take into account their biology and ecology. Their behavior to group and form patches as a strategy for feeding, defense and reproduction, makes them vulnerable to overfishing. The higher the population density, the higher the catchability coefficient, and because they are sedentary organisms, the catchability does not change significantly until the density is very low. Hence, the stock assessment of holothurians can be improved by analyzing their spatial distribution. This paper proposes a stock assessment technique that considers the spatial distribution pattern of the sea cucumber Isostichopus badionotus from Yucatan, Mexico. A bioeconomic spatial model was developed to explain the interactions between fishing effort allocation, quasi-profits and the population in the short term. Because of the high price of the species and the low production costs, artisanal fishers preferred to maximize short-term quasi-profits, rather than the long-term benefits they could gain with low fishing mortality rates.
NASA Astrophysics Data System (ADS)
Barette, Florian; Poppe, Sam; Smets, Benoît; Benbakkar, Mhammed; Kervyn, Matthieu
2017-10-01
We present an integrated, spatially-explicit database of existing geochemical major-element analyses available from (post-) colonial scientific reports, PhD Theses and international publications for the Virunga Volcanic Province, located in the western branch of the East African Rift System. This volcanic province is characterised by alkaline volcanism, including silica-undersaturated, alkaline and potassic lavas. The database contains a total of 908 geochemical analyses of eruptive rocks for the entire volcanic province with a localisation for most samples. A preliminary analysis of the overall consistency of the database, using statistical techniques on sets of geochemical analyses with contrasted analytical methods or dates, demonstrates that the database is consistent. We applied a principal component analysis and cluster analysis on whole-rock major element compositions included in the database to study the spatial variation of the chemical composition of eruptive products in the Virunga Volcanic Province. These statistical analyses identify spatially distributed clusters of eruptive products. The known geochemical contrasts are highlighted by the spatial analysis, such as the unique geochemical signature of Nyiragongo lavas compared to other Virunga lavas, the geochemical heterogeneity of the Bulengo area, and the trachyte flows of Karisimbi volcano. Most importantly, we identified separate clusters of eruptive products which originate from primitive magmatic sources. These lavas of primitive composition are preferentially located along NE-SW inherited rift structures, often at distance from the central Virunga volcanoes. Our results illustrate the relevance of a spatial analysis on integrated geochemical data for a volcanic province, as a complement to classical petrological investigations. This approach indeed helps to characterise geochemical variations within a complex of magmatic systems and to identify specific petrologic and geochemical investigations that should be tackled within a study area.
Directional spatial frequency analysis of lipid distribution in atherosclerotic plaque
NASA Astrophysics Data System (ADS)
Korn, Clyde; Reese, Eric; Shi, Lingyan; Alfano, Robert; Russell, Stewart
2016-04-01
Atherosclerosis is characterized by the growth of fibrous plaques due to the retention of cholesterol and lipids within the artery wall, which can lead to vessel occlusion and cardiac events. One way to evaluate arterial disease is to quantify the amount of lipid present in these plaques, since a higher disease burden is characterized by a higher concentration of lipid. Although therapeutic stimulation of reverse cholesterol transport to reduce cholesterol deposits in plaque has not produced significant results, this may be due to current image analysis methods which use averaging techniques to calculate the total amount of lipid in the plaque without regard to spatial distribution, thereby discarding information that may have significance in marking response to therapy. Here we use Directional Fourier Spatial Frequency (DFSF) analysis to generate a characteristic spatial frequency spectrum for atherosclerotic plaques from C57 Black 6 mice both treated and untreated with a cholesterol scavenging nanoparticle. We then use the Cauchy product of these spectra to classify the images with a support vector machine (SVM). Our results indicate that treated plaque can be distinguished from untreated plaque using this method, where no difference is seen using the spatial averaging method. This work has the potential to increase the effectiveness of current in-vivo methods of plaque detection that also use averaging methods, such as laser speckle imaging and Raman spectroscopy.
Liu, Yi; Li, Yuefen; Harris, Paul; Cardenas, Laura M; Dunn, Robert M; Sint, Hadewij; Murray, Phil J; Lee, Michael R F; Wu, Lianhai
2018-04-01
In this study, we evaluated the ability of the SPACSYS model to simulate water run-off, soil moisture, N 2 O fluxes and grass growth using data generated from a field of the North Wyke Farm Platform. The field-scale model is adapted via a linked and grid-based approach (grid-to-grid) to account for not only temporal dynamics but also the within-field spatial variation in these key ecosystem indicators. Spatial variability in nutrient and water presence at the field-scale is a key source of uncertainty when quantifying nutrient cycling and water movement in an agricultural system. Results demonstrated that the new spatially distributed version of SPACSYS provided a worthy improvement in accuracy over the standard (single-point) version for biomass productivity. No difference in model prediction performance was observed for water run-off, reflecting the closed-system nature of this variable. Similarly, no difference in model prediction performance was found for N 2 O fluxes, but here the N 2 O predictions were noticeably poor in both cases. Further developmental work, informed by this study's findings, is proposed to improve model predictions for N 2 O. Soil moisture results with the spatially distributed version appeared promising but this promise could not be objectively verified.
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.
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.
Yang, Sheng-long; Jin, Shao-fei; Hua, Cheng-jun; Dai, Yang
2015-02-01
In order to analyze the correlation between spatial-temporal distribution of the bigeye tuna ( Thunnus obesus) and subsurface factors, the study explored the isothermal distribution of subsurface temperatures in the bigeye tuna fishing grounds in the tropical Atlantic Ocean, and built up the spatial overlay chart of the isothermal lines of 9, 12, 13 and 15 °C and monthly CPUE (catch per unit effort) from bigeye tuna long-lines. The results showed that the bigeye tuna mainly distributed in the water layer (150-450 m) below the lower boundary depth of thermocline. At the isothermal line of 12 °C, the bigeye tuna mainly lived in the water layer of 190-260 m, while few individuals were found at water depth more than 400 m. As to the 13 °C isothermal line, high CPUE often appeared at water depth less than 250 m, mainly between 150-230 m, while no CPUE appeared at water depth more than 300 m. The optimum range of subsurface factors calculated by frequency analysis and empirical cumulative distribution function (ECDF) exhibited that the optimum depth range of 12 °C isothermal depth was 190-260 m and the 13 °C isothermal depth was 160-240 m, while the optimum depth difference range of 12 °C isothermal depth was -10 to 100 m and the 13 °C isothermal depth was -40 to 60 m. The study explored the optimum range of subsurface factors (water temperature and depth) that drive horizontal and vertical distribution of bigeye tuna. The preliminary result would help to discover the central fishing ground, instruct fishing depth, and provide theoretical and practical references for the longline production and resource management of bigeye tuna in the Atlantic Ocean.
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.
NASA Astrophysics Data System (ADS)
Schmidt, Carl; Johnson, Robert E.; Baumgardner, Jeffrey; Mendillo, Michael
2014-11-01
At a solar distance of 0.44 AU, Oort cloud comet C/2012 S1 (ISON) exhibited an outburst phase that was observed by small telescopes at the McDonald Observatory. In conjunction with narrow-band (14Å) imaging over a wide-field, an image-slicer spectrograph ( 20,000) simultaneously measured the spatial distribution of ISON’s coma over a 1.6 x 2.7 arcminute field made up of 246 individual spectra. More than fifty emission lines from C2, NH2, CO, H2O+ and Na were observed within a single Echelle order spanning 5868Å to 5930Å. Spatial reconstructions of these species reveal that ISON’s coma was quite elongated several thousand km along the axis perpendicular to its motion. The ion tail appeared distinctly broader than the neutral Na tail, providing strong evidence that Na in the coma did not originate by dissociative recombination of a sodium bearing molecular ion. Production rates increased from 1.6 ± 0.3 x 1023 to 5.8 ± 1 x 1023 Na atoms/s within 24 hours, outgassing much less than comparable comets relative to ISON’s water production. The anti-sunward Na tail was imaged >106 km from the nucleus. Its distribution indicates origins both near the nucleus and in the dust tail, with the ratio of these Na sources varying on hourly timescales due to outburst activity.
Towards Understanding the Timing and Frequency of Rain-on-Snow (ROS) Events in Alaska
NASA Astrophysics Data System (ADS)
Pan, C.; Kirchner, P. B.; Kimball, J. S.; Kim, Y.; Kamp, U.
2017-12-01
Rain-on-snow (ROS) events affect ecosystem processes at multiple spatial and temporal scales including hydrology, carbon cycling, wildlife movement and human transportation and result in marked changes to snowpack processes including enhanced snow melt, surface albedo and energy balance. Changes in the surface structure of the snowpack are visible through optical remote sensing and changes in the relative content and distribution of water, air and ice in the snowpack are detectable using passive microwave remote sensing. This project aims to develop ROS products to elucidate changes in frequency and distribution in ROS events using satellite data products derived from both optical and passive microwave satellite records. To detect ROS events, we use downscaled brightness temperature measurements derived from vertical and horizontal polarizations at 19 and 37 GHz from the Advanced Microwave Scanning Radiometer (AMSR-E/2) passive microwave satellites. Preliminary results indicate an overall classification accuracy of 77.6% relative to in situ weather observations including surface air temperature, precipitation, and snow depth. ROS events are spatially distributed largely to elevations below 500 m and occur most frequently on northern to western aspects in addition to southeastern. Regional ROS hot spots occur in southwest Alaska characterized by warmer climates and transient snowcover. The seasonal timing of ROS events indicates increasing frequency during the fall and spring months.
NASA Technical Reports Server (NTRS)
Gamon, John A.; Huemmrich, K. Fred; Stone, Robert S.; Tweedie, Craig E.
2015-01-01
In the Arctic, earlier snowmelt and longer growing seasons due to warming have been hypothesized to increase vegetation productivity. Using the Normalized Difference Vegetation Index (NDVI) from both field and satellite measurements as an indicator of vegetation phenology and productivity, we monitored spatial and temporal patterns of vegetation growth for a coastal wet sedge tundra site near Barrow, Alaska over three growing seasons (2000-2002). Contrary to expectation, earlier snowmelt did not lead to increased productivity. Instead, productivity was associated primarily with precipitation and soil moisture, and secondarily with growing degree days, which, during this period, led to reduced growth in years with earlier snowmelt. Additional moisture effects on productivity and species distribution, operating over a longer time scale, were evident in spatial NDVI patterns associated with microtopography. Lower, wetter regions dominated by graminoids were more productive than higher, drier locations having a higher percentage of lichens and mosses, despite the earlier snowmelt at the more elevated sites. These results call into question the oft-stated hypothesis that earlier arctic growing seasons will lead to greater vegetation productivity. Rather, they agree with an emerging body of evidence from recent field studies indicating that early-season, local environmental conditions, notably moisture and temperature, are primary factors determining arctic vegetation productivity. For this coastal arctic site, early growing season conditions are strongly influenced by microtopography, hydrology, and regional sea ice dynamics, and may not be easily predicted from snowmelt date or seasonal average air temperatures alone. Our comparison of field to satellite NDVI also highlights the value of in-situ monitoring of actual vegetation responses using field optical sampling to obtain detailed information on surface conditions not possible from satellite observations alone.
NASA Astrophysics Data System (ADS)
Barnes, M.; Moore, D. J.; Scott, R. L.; MacBean, N.; Ponce-Campos, G. E.; Breshears, D. D.
2017-12-01
Both satellite observations and eddy covariance estimates provide crucial information about the Earth's carbon, water and energy cycles. Continuous measurements from flux towers facilitate exploration of the exchange of carbon dioxide, water and energy between the land surface and the atmosphere at fine temporal and spatial scales, while satellite observations can fill in the large spatial gaps of in-situ measurements and provide long-term temporal continuity. The Southwest (Southwest United States and Northwest Mexico) and other semi-arid regions represent a key uncertainty in interannual variability in carbon uptake. Comparisons of existing global upscaled gross primary production (GPP) products with flux tower data at sites across the Southwest show widespread mischaracterization of seasonality in vegetation carbon uptake, resulting in large (up to 200%) errors in annual carbon uptake estimates. Here, remotely sensed and distributed meteorological inputs are used to upscale GPP estimates from 25 Ameriflux towers across the Southwest to the regional scale using a machine learning approach. Our random forest model incorporates two novel features that improve the spatial and temporal variability in GPP. First, we incorporate a multi-scalar drought index at multiple timescales to account for differential seasonality between ecosystem types. Second, our machine learning algorithm was trained on twenty five ecologically diverse sites to optimize both the monthly variability in and the seasonal cycle of GPP. The product and its components will be used to examine drought impacts on terrestrial carbon cycling across the Southwest including the effects of drought seasonality and on carbon uptake. Our spatially and temporally continuous upscaled GPP product drawing from both ground and satellite data over the Southwest region helps us understand linkages between the carbon and water cycles in semi-arid ecosystems and informs predictions of vegetation response to future climate conditions.
NASA Astrophysics Data System (ADS)
Holz, Philipp; Lutz, Christian; Brandenburg, Albrecht
2017-06-01
We present a new optical setup, which uses scanning mirrors in combination with laser induced fluorescence to monitor the spatial distribution of lubricant on metal sheets. Current trends in metal processing industry require forming procedures with increasing deformations. Thus a welldefined amount of lubricant is necessary to prevent the material from rupture, to reduce the wearing of the manufacturing tool as well as to prevent problems in post-deforming procedures. Therefore spatial resolved analysis of the thickness of lubricant layers is required. Current systems capture the lubricant distribution by moving sensor heads over the object along a linear axis. However the spatial resolution of these systems is insufficient at high strip speeds, e.g. at press plants. The presented technology uses fast rotating scanner mirrors to deflect a laser beam on the surface. This 405 nm laser light excites the autofluorescence of the investigated lubricants. A coaxial optic collects the fluorescence signal which is then spectrally filtered and recorded using a photomultiplier. From the acquired signal a two dimensional image is reconstructed in real time. This paper presents the sensor setup as well as its characterization. For the calibration of the system reference targets were prepared using an ink jet printer. The presented technology for the first time allows a spatial resolution in the millimetre range at production speed. The presented test system analyses an area of 300 x 300 mm² at a spatial resolution of 1.1 mm in less than 20 seconds. Despite this high speed of the measurement the limit of detection of the system described in this paper is better than 0.05 g/m² for the certified lubricant BAM K-009.
NASA Astrophysics Data System (ADS)
Matsui, H.; Koike, M.; Kondo, Y.; Takegawa, N.; Kita, K.; Miyazaki, Y.; Hu, M.; Chang, S.-Y.; Blake, D. R.; Fast, J. D.; Zaveri, R. A.; Streets, D. G.; Zhang, Q.; Zhu, T.
2009-01-01
Regional aerosol model calculations were made using the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) and WRF-chem models to study spatial and temporal variations of aerosols around Beijing, China, in the summer of 2006, when the Campaigns of Air Quality Research in Beijing and Surrounding Region 2006 (CAREBeijing) intensive campaign was conducted. Model calculations captured temporal variations of primary (such as elemental carbon (EC)) and secondary (such as sulfate) aerosols observed in and around Beijing. The spatial distributions of aerosol optical depth observed by the MODIS satellite sensors were also reproduced over northeast China. Model calculations showed distinct differences in spatial distributions between primary and secondary aerosols in association with synoptic-scale meteorology. Secondary aerosols increased in air around Beijing on a scale of about 1000 × 1000 km2 under an anticyclonic pressure system. This air mass was transported northward from the high anthropogenic emission area extending south of Beijing with continuous photochemical production. Subsequent cold front passage brought clean air from the north, and polluted air around Beijing was swept to the south of Beijing. This cycle was repeated about once a week and was found to be responsible for observed enhancements/reductions of aerosols at the intensive measurement sites. In contrast to secondary aerosols, the spatial distributions of primary aerosols (EC) reflected those of emissions, resulting in only slight variability despite the changes in synoptic-scale meteorology. In accordance with these results, source apportionment simulations revealed that primary aerosols around Beijing were controlled by emissions within 100 km around Beijing within the preceding 24 h, while emissions as far as 500 km and within the preceding 3 days were found to affect secondary aerosols.
NASA Astrophysics Data System (ADS)
Lee, Tong
2017-04-01
Understanding the accuracies of satellite-derived sea surface salinity (SSS) measurements in depicting temporal changes and the dependence of the accuracies on spatiotemporal scales are important to capability assessment, future mission design, and applications to study oceanic phenomena of different spatiotemporal scales. This study quantifies the consistency between Aquarius Version-4 monthly gridded SSS (released in late 2015) with two widely used Argo monthly gridded near-surface salinity products. The analysis focused on their consistency in depicting temporal changes (including seasonal and non-seasonal) on various spatial scales: 1˚ x1˚ , 3˚ x3˚ , and 10˚ x10˚ . Globally averaged standard deviation (STD) values for Aquarius-Argo salinity differences on these three spatial scales are 0.16, 0.14, 0.09 psu, compared to those between the two Argo products of 0.10, 0.09, and 0.04 psu. Aquarius SSS compare better with Argo data on non-seasonal (e.g., interannual and intraseasonal) than for seasonal time scales. The seasonal Aquarius-Argo SSS differences are mostly concentrated at high latitudes. The Aquarius team is making active efforts to further reduce these high-latitude seasonal biases. The consistency between Aquarius and Argo salinity is similar to that between the two Argo products in the tropics and subtropics for non-seasonal signals, and in the tropics for seasonal signals. Therefore, the representativeness errors of the Argo products for various spatial scales (related to sampling and gridding) need to be taken into account when estimating the uncertainty of Aquarius SSS. The globally averaged uncertainty of large-scale (10˚ x10˚ ) non-seasonal Aquarius SSS is approximately 0.04 psu. These estimates reflect the significant improvements of Aquarius Version-4 SSS over the previous versions. The estimates can be used as baseline requirements for future ocean salinity missions from space. The spatial distribution of the uncertainty estimates is also useful for assimilation of Aquarius SSS.
Collective behavior in the spatial spreading of obesity
Gallos, Lazaros K.; Barttfeld, Pablo; Havlin, Shlomo; Sigman, Mariano; Makse, Hernán A.
2012-01-01
Obesity prevalence is increasing in many countries at alarming levels. A difficulty in the conception of policies to reverse these trends is the identification of the drivers behind the obesity epidemics. Here, we implement a spatial spreading analysis to investigate whether obesity shows spatial correlations, revealing the effect of collective and global factors acting above individual choices. We find a regularity in the spatial fluctuations of their prevalence revealed by a pattern of scale-free long-range correlations. The fluctuations are anomalous, deviating in a fundamental way from the weaker correlations found in the underlying population distribution indicating the presence of collective behavior, i.e., individual habits may have negligible influence in shaping the patterns of spreading. Interestingly, we find the same scale-free correlations in economic activities associated with food production. These results motivate future interventions to investigate the causality of this relation providing guidance for the implementation of preventive health policies. PMID:22822425
Collective behavior in the spatial spreading of obesity
NASA Astrophysics Data System (ADS)
Gallos, Lazaros K.; Barttfeld, Pablo; Havlin, Shlomo; Sigman, Mariano; Makse, Hernán A.
2012-06-01
Obesity prevalence is increasing in many countries at alarming levels. A difficulty in the conception of policies to reverse these trends is the identification of the drivers behind the obesity epidemics. Here, we implement a spatial spreading analysis to investigate whether obesity shows spatial correlations, revealing the effect of collective and global factors acting above individual choices. We find a regularity in the spatial fluctuations of their prevalence revealed by a pattern of scale-free long-range correlations. The fluctuations are anomalous, deviating in a fundamental way from the weaker correlations found in the underlying population distribution indicating the presence of collective behavior, i.e., individual habits may have negligible influence in shaping the patterns of spreading. Interestingly, we find the same scale-free correlations in economic activities associated with food production. These results motivate future interventions to investigate the causality of this relation providing guidance for the implementation of preventive health policies.
Critiquing ';pore connectivity' as basis for in situ flow in geothermal systems
NASA Astrophysics Data System (ADS)
Kenedi, C. L.; Leary, P.; Malin, P.
2013-12-01
Geothermal system in situ flow systematics derived from detailed examination of grain-scale structures, fabrics, mineral alteration, and pore connectivity may be extremely misleading if/when extrapolated to reservoir-scale flow structure. In oil/gas field clastic reservoir operations, it is standard to assume that small scale studies of flow fabric - notably the Kozeny-Carman and Archie's Law treatments at the grain-scale and well-log/well-bore sampling of formations/reservoirs at the cm-m scale - are adequate to define the reservoir-scale flow properties. In the case of clastic reservoirs, however, a wide range of reservoir-scale data wholly discredits this extrapolation: Well-log data show that grain-scale fracture density fluctuation power scales inversely with spatial frequency k, S(k) ~ 1/k^β, 1.0 < β < 1.2, 1cycle/km < k < 1cycle/cm; the scaling is a ';universal' feature of well-logs (neutron porosity, sonic velocity, chemical abundance, mass density, resistivity, in many forms of clastic rock and instances of shale bodies, for both horizontal and vertical wells). Grain-scale fracture density correlates with in situ porosity; spatial fluctuations of porosity φ in well-core correlate with spatial fluctuations in the logarithm of well-core permeability, δφ ~ δlog(κ) with typical correlation coefficient ~ 85%; a similar relation is observed in consolidating sediments/clays, indicating a generic coupling between fluid pressure and solid deformation at pore sites. In situ macroscopic flow systems are lognormally distributed according to κ ~ κ0 exp(α(φ-φ0)), α >>1 an empirical parameter for degree of in situ fracture connectivity; the lognormal distribution applies to well-productivities in US oil fields and NZ geothermal fields, ';frack productivity' in oil/gas shale body reservoirs, ore grade distributions, and trace element abundances. Although presently available evidence for these properties in geothermal reservoirs is limited, there are indications that geothermal system flow essentially obeys the same ';universal' in situ flow rules as does clastic rock: Well-log data from Los Azufres, MX, show power-law scaling S(k) ~ 1/k^β, 1.2 < β < 1.4, for spatial frequency range 2cycles/km to 0.5cycle/m; higher β-values are likely due to the relatively fresh nature of geothermal systems; Well-core at Bulalo (PH) and Ohaaki (NZ) show statistically significant spatial correlation, δφ ~ δlog(κ) Well productivity at Ohaaki/Ngawha (NZ) and in geothermal systems elsewhere are lognormally distributed; K/Th/U abundances lognormally distributed in Los Azufres well-logs We therefore caution that small-scale evidence for in situ flow fabric in geothermal systems that is interpreted in terms of ';pore connectivity' may in fact not reflect how small-scale chemical processes are integrated into a large-scale geothermal flow structure. Rather such small scale studies should (perhaps) be considered in term of the above flow rules. These flow rules are easily incorporated into standard flow simulation codes, in particular the OPM = Open Porous Media open-source industry-standard flow code. Geochemical transport data relevant to geothermal systems can thus be expected to be well modeled by OPM or equivalent (e.g., INL/LANL) codes.
NASA Astrophysics Data System (ADS)
Zhang, Z.; Zimmermann, N. E.; Poulter, B.
2015-12-01
Simulations of the spatial-temporal dynamics of wetlands is key to understanding the role of wetland biogeochemistry under past and future climate variability. Hydrologic inundation models, such as TOPMODEL, are based on a fundamental parameter known as the compound topographic index (CTI) and provide a computationally cost-efficient approach to simulate global wetland dynamics. However, there remains large discrepancy in the implementations of TOPMODEL in land-surface models (LSMs) and thus their performance against observations. This study describes new improvements to TOPMODEL implementation and estimates of global wetland dynamics using the LPJ-wsl DGVM, and quantifies uncertainties by comparing three digital elevation model products (HYDRO1k, GMTED, and HydroSHEDS) at different spatial resolution and accuracy on simulated inundation dynamics. We found that calibrating TOPMODEL with a benchmark dataset can help to successfully predict the seasonal and interannual variations of wetlands, as well as improve the spatial distribution of wetlands to be consistent with inventories. The HydroSHEDS DEM, using a river-basin scheme for aggregating the CTI, shows best accuracy for capturing the spatio-temporal dynamics of wetland among three DEM products. This study demonstrates the feasibility to capture spatial heterogeneity of inundation and to estimate seasonal and interannual variations in wetland by coupling a hydrological module in LSMs with appropriate benchmark datasets. It additionally highlight the importance of an adequate understanding of topographic indices for simulating global wetlands and show the opportunity to converge wetland estimations in LSMs by identifying the uncertainty associated with existing wetland products.
Accounting for Forest Harvest and Wildfire in a Spatially-distributed Carbon Cycle Process Model
NASA Astrophysics Data System (ADS)
Turner, D. P.; Ritts, W.; Kennedy, R. E.; Yang, Z.; Law, B. E.
2009-12-01
Forests are subject to natural disturbances in the form of wildfire, as well as management-related disturbances in the form of timber harvest. These disturbance events have strong impacts on local and regional carbon budgets, but quantifying the associated carbon fluxes remains challenging. The ORCA Project aims to quantify regional net ecosystem production (NEP) and net biome production (NBP) in Oregon, California, and Washington, and we have adopted an integrated approach based on Landsat imagery and ecosystem modeling. To account for stand-level carbon fluxes, the Biome-BGC model has been adapted to simulate multiple severities of fire and harvest. New variables include snags, direct fire emissions, and harvest removals. New parameters include fire-intensity-specific combustion factors for each carbon pool (based on field measurements) and proportional removal rates for harvest events. To quantify regional fluxes, the model is applied in a spatially-distributed mode over the domain of interest, with disturbance history derived from a time series of Landsat images. In stand-level simulations, the post disturbance transition from negative (source) to positive (sink) NEP is delayed approximately a decade in the case of high severity fire compared to harvest. Simulated direct pyrogenic emissions range from 11 to 25 % of total non-soil ecosystem carbon. In spatial mode application over Oregon and California, the sum of annual pyrogenic emissions and harvest removals was generally less that half of total NEP, resulting in significant carbon sequestration on the land base. Spatially and temporally explicit simulation of disturbance-related carbon fluxes will contribute to our ability to evaluate effects of management on regional carbon flux, and in our ability to assess potential biospheric feedbacks to climate change mediated by changing disturbance regimes.
The effects of oil spills on marine fish: Implications of spatial variation in natural mortality.
Langangen, Ø; Olsen, E; Stige, L C; Ohlberger, J; Yaragina, N A; Vikebø, F B; Bogstad, B; Stenseth, N C; Hjermann, D Ø
2017-06-15
The effects of oil spills on marine biological systems are of great concern, especially in regions with high biological production of harvested resources such as in the Northeastern Atlantic. The scientific studies of the impact of oil spills on fish stocks tend to ignore that spatial patterns of natural mortality may influence the magnitude of the impact over time. Here, we first illustrate how spatial variation in natural mortality may affect the population impact by considering a thought experiment. Second, we consider an empirically based example of Northeast Arctic cod to extend the concept to a realistic setting. Finally, we present a scenario-based investigation of how the degree of spatial variation in natural mortality affects the impact over a gradient of oil spill sizes. Including the effects of spatial variations in natural mortality tends to widen the impact distribution, hence increasing the probability of both high and low impact events. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Links between global meat trade and organic river pollution
NASA Astrophysics Data System (ADS)
Wen, Yingrong; Schoups, Gerrit; van de Giesen, Nick
2017-04-01
Rising demand of meat boosts livestock farming intensification. Due to international meat trade, the environmental costs of production are becoming increasingly separated from where the meat is consumed. However, little is known about the impact of trade on the environment for both importers and exporters. Combining multi-scale (national, regional and gridded) data, we present a new method to quantify the impacts of international meat trade on global river organic pollution. We computed spatially distributed organic pollution in global river networks with and without meat trade, where the without-trade scenario assumes that meat imports are replaced by local production. Our analysis indicates high potential savings of livestock population and pollutants production at the global scale due to the international meat trade. The spatially detailed analysis shows that current trade contributes to organic pollution reductions in meat importing regions, especially in rich nations. The deterioration of river water quality, especially in developing regions, points to an urgent need for affordable infrastructure and technology development and wastewater solutions.
A parallel-processing approach to computing for the geographic sciences
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.
NASA Astrophysics Data System (ADS)
Flynn, Brendan P.; D'Souza, Alisha V.; Kanick, Stephen C.; Maytin, Edward; Hasan, Tayyaba; Pogue, Brian W.
2013-03-01
Aminolevulinic acid (ALA)-induced Protoporphyrin IX (PpIX)-based photodynamic therapy (PDT) is an effective treatment for skin cancers including basal cell carcinoma (BCC). Topically applied ALA promotes PpIX production preferentially in tumors, and many strategies have been developed to increase PpIX distribution and PDT treatment efficacy at depths > 1mm is not fully understood. While surface imaging techniques provide useful diagnosis, dosimetry, and efficacy information for superficial tumors, these methods cannot interrogate deeper tumors to provide in situ insight into spatial PpIX distributions. We have developed an ultrasound-guided, white-light-informed, tomographics spectroscopy system for the spatial measurement of subsurface PpIX. Detailed imaging system specifications, methodology, and optical-phantom-based characterization will be presented separately. Here we evaluate preliminary in vivo results using both full tomographic reconstruction and by plotting individual tomographic source-detector pair data against US images.
Increase in the use of personal care products (PCPs) has resulted in the release and accumulation of a diverse assemblage of emerging chemicals in the environment. Triclosan (TCS) is an antimicrobial compound being increasingly used in PCPs over the last 40 years, and as a resul...
Quantifying the influence of sediment source area sampling on detrital thermochronometer data
NASA Astrophysics Data System (ADS)
Whipp, D. M., Jr.; Ehlers, T. A.; Coutand, I.; Bookhagen, B.
2014-12-01
Detrital thermochronology offers a unique advantage over traditional bedrock thermochronology because of its sensitivity to sediment production and transportation to sample sites. In mountainous regions, modern fluvial sediment is often collected and dated to determine the past (105 to >107 year) exhumation history of the upstream drainage area. Though potentially powerful, the interpretation of detrital thermochronometer data derived from modern fluvial sediment is challenging because of spatial and temporal variations in sediment production and transport, and target mineral concentrations. Thermochronometer age prediction models provide a quantitative basis for data interpretation, but it can be difficult to separate variations in catchment bedrock ages from the effects of variable basin denudation and sediment transport. We present two examples of quantitative data interpretation using detrital thermochronometer data from the Himalaya, focusing on the influence of spatial and temporal variations in basin denudation on predicted age distributions. We combine age predictions from the 3D thermokinematic numerical model Pecube with simple models for sediment sampling in the upstream drainage basin area to assess the influence of variations in sediment production by different geomorphic processes or scaled by topographic metrics. We first consider a small catchment from the central Himalaya where bedrock landsliding appears to have affected the observed muscovite 40Ar/39Ar age distributions. Using a simple model of random landsliding with a power-law landslide frequency-area relationship we find that the sediment residence time in the catchment has a major influence on predicted age distributions. In the second case, we compare observed detrital apatite fission-track age distributions from 16 catchments in the Bhutan Himalaya to ages predicted using Pecube and scaled by various topographic metrics. Preliminary results suggest that predicted age distributions scaled by the rock uplift rate in Pecube are statistically equivalent to the observed age distributions for ~75% of the catchments, but may improve when scaled by local relief or specific stream power weighted by satellite-derived precipitation. Ongoing work is exploring the effect of scaling by other topographic metrics.
NASA Astrophysics Data System (ADS)
Watson, James R.; Stock, Charles A.; Sarmiento, Jorge L.
2015-11-01
Modeling the dynamics of marine populations at a global scale - from phytoplankton to fish - is necessary if we are to quantify how climate change and other broad-scale anthropogenic actions affect the supply of marine-based food. Here, we estimate the abundance and distribution of fish biomass using a simple size-based food web model coupled to simulations of global ocean physics and biogeochemistry. We focus on the spatial distribution of biomass, identifying highly productive regions - shelf seas, western boundary currents and major upwelling zones. In the absence of fishing, we estimate the total ocean fish biomass to be ∼ 2.84 ×109 tonnes, similar to previous estimates. However, this value is sensitive to the choice of parameters, and further, allowing fish to move had a profound impact on the spatial distribution of fish biomass and the structure of marine communities. In particular, when movement is implemented the viable range of large predators is greatly increased, and stunted biomass spectra characterizing large ocean regions in simulations without movement, are replaced with expanded spectra that include large predators. These results highlight the importance of considering movement in global-scale ecological models.
Global Aerosol Remote Sensing from MODIS
NASA Technical Reports Server (NTRS)
Ichoku, Charles; Kaufman, Yoram J.; Remer, Lorraine A.; Chu, D. Allen; Mattoo, Shana; Tanre, Didier; Levy, Robert; Li, Rong-Rong; Martins, Jose V.; Lau, William K. M. (Technical Monitor)
2002-01-01
The physical characteristics, composition, abundance, spatial distribution and dynamics of global aerosols are still very poorly known, and new data from satellite sensors have long been awaited to improve current understanding and to give a boost to the effort in future climate predictions. The derivation of aerosol parameters from the MODerate resolution Imaging Spectro-radiometer (MODIS) sensors aboard the Earth Observing System (EOS) Terra and Aqua polar-orbiting satellites ushers in a new era in aerosol remote sensing from space. Terra and Aqua were launched on December 18, 1999 and May 4, 2002 respectively, with daytime equator crossing times of approximately 10:30 am and 1:30 pm respectively. Several aerosol parameters are retrieved at 10-km spatial resolution (level 2) from MODIS daytime data. The MODIS aerosol algorithm employs different approaches to retrieve parameters over land and ocean surfaces, because of the inherent differences in the solar spectral radiance interaction with these surfaces. The parameters retrieved include: aerosol optical thickness (AOT) at 0.47, 0.55 and 0.66 micron wavelengths over land, and at 0.47, 0.55, 0.66, 0.87, 1.2, 1.6, and 2.1 micron over ocean; Angstrom exponent over land and ocean; and effective radii, and the proportion of AOT contributed by the small mode aerosols over ocean. To ensure the quality of these parameters, a substantial part of the Terra-MODIS aerosol products were validated globally and regionally, based on cross correlation with corresponding parameters derived from ground-based measurements from AERONET (AErosol RObotic NETwork) sun photometers. Similar validation efforts are planned for the Aqua-MODIS aerosol products. The MODIS level 2 aerosol products are operationally aggregated to generate global daily, eight-day (weekly), and monthly products at one-degree spatial resolution (level 3). MODIS aerosol data are used for the detailed study of local, regional, and global aerosol concentration, distribution, and temporal dynamics, as well as for radiative forcing calculations. We show several examples of these results and comparisons with model output.
[Natural forming causes of China population distribution].
Fang, Yu; Ouyang, Zhi-Yun; Zheng, Hua; Xiao, Yi; Niu, Jun-Feng; Chen, Sheng-Bin; Lu, Fei
2012-12-01
The diverse natural environment in China causes the spatial heterogeneity of China population distribution. It is essential to understand the interrelations between the population distribution pattern and natural environment to enhance the understanding of the man-land relationship and the realization of the sustainable management for the population, resources, and environment. This paper analyzed the China population distribution by adopting the index of population density (PD) in combining with spatial statistic method and Lorenz curve, and discussed the effects of the natural factors on the population distribution and the interrelations between the population distribution and 16 indices including average annual precipitation (AAP), average annual temperature (AAT), average annual sunshine duration (AASD), precipitation variation (PV), temperature variation (TV), sunshine duration variation (SDV), relative humidity (RH), aridity index (AI), warmth index ( WI), > or = 5 degrees C annual accumulated temperature (AACT), average elevation (AE), relative height difference (RHD), surface roughness (SR), water system density (WSD), net primary productivity (NPP), and shortest distance to seashore (SDTS). There existed an obvious aggregation phenomenon in the population distribution in China. The PD was high in east China, medium in central China, and low in west China, presenting an obvious positive spatial association. The PD was significantly positively correlated with WSD, AAT, AAP, NPP, AACT, PV, RH, and WI, and significantly negatively correlated with RHD, AE, SDV, SR, and SDTS. The climate factors (AAT, WI, PV, and NPP), topography factors (SR and RHD), and water system factor (WSD) together determined the basic pattern of the population distribution in China. It was suggested that the monitoring of the eco-environment in the east China of high population density should be strengthened to avoid the eco-environmental degradation due to the expanding population, and the conservation of the eco-environment in the central and west China with vulnerable eco-environment should also be strengthened to enhance the population carrying ability of these regions and to mitigate the eco-environmental pressure in the east China of high population density.
Frank, R R; Cipullo, S; Garcia, J; Davies, S; Wagland, S T; Villa, R; Trois, C; Coulon, F
2017-05-01
The aim of this study was to evaluate the spatial distribution of the paper and fines across seven landfill sites (LFS) and assess the relationship between waste physicochemical properties and biogas production. Physicochemical analysis of the waste samples demonstrated that there were no clear trends in the spatial distribution of total solids (TS), moisture content (MC) and waste organic strength (VS) across all LFS. There was however noticeable difference between samples from the same landfill site. The effect of landfill age on waste physicochemical properties showed no clear relationship, thus, providing evidence that waste remains dormant and non-degraded for long periods of time. Landfill age was however directly correlated with the biochemical methane potential (BMP) of waste; with the highest BMP obtained from the most recent LFS. BMP was also correlated with depth as the average methane production decreased linearly with increasing depth. There was also a high degree of correlation between the Enzymatic Hydrolysis Test (EHT) and BMP test results, which motivates its potential use as an alternative to the BMP test method. Further to this, there were also positive correlations between MC and VS, VS and biogas volume and biogas volume and CH 4 content. Outcomes of this work can be used to inform waste degradation and methane enhancement strategies for improving recovery of methane from landfills. Copyright © 2016 Elsevier Ltd. All rights reserved.
Photosymbiotic giant clams are transformers of solar flux.
Holt, Amanda L; Vahidinia, Sanaz; Gagnon, Yakir Luc; Morse, Daniel E; Sweeney, Alison M
2014-12-06
'Giant' tridacnid clams have evolved a three-dimensional, spatially efficient, photodamage-preventing system for photosymbiosis. We discovered that the mantle tissue of giant clams, which harbours symbiotic nutrition-providing microalgae, contains a layer of iridescent cells called iridocytes that serve to distribute photosynthetically productive wavelengths by lateral and forward-scattering of light into the tissue while back-reflecting non-productive wavelengths with a Bragg mirror. The wavelength- and angle-dependent scattering from the iridocytes is geometrically coupled to the vertically pillared microalgae, resulting in an even re-distribution of the incoming light along the sides of the pillars, thus enabling photosynthesis deep in the tissue. There is a physical analogy between the evolved function of the clam system and an electric transformer, which changes energy flux per area in a system while conserving total energy. At incident light levels found on shallow coral reefs, this arrangement may allow algae within the clam system to both efficiently use all incident solar energy and avoid the photodamage and efficiency losses due to non-photochemical quenching that occur in the reef-building coral photosymbiosis. Both intra-tissue radiometry and multiscale optical modelling support our interpretation of the system's photophysics. This highly evolved 'three-dimensional' biophotonic system suggests a strategy for more efficient, damage-resistant photovoltaic materials and more spatially efficient solar production of algal biofuels, foods and chemicals.
Phosphorus Import Dependency and Recycling Potential in the Global Phosphorus Mosaic
NASA Astrophysics Data System (ADS)
Powers, S. M.
2017-12-01
Nations differ widely in terms of recent P consumption trends and fertilizer trade dependencies, reflecting dynamic and globally uneven P fertilizer production, consumption, export, and import. Recovered P from urban and agricultural wastes can provide renewable sources that supplant the need to import P fertilizer, but to date, research on P recycling potential has been highly spatially segregated. Understanding of the global distribution of P recycling potential and options, and how these intersect with P import dependencies, could be used to guide long-term, spatially-prioritized planning for P, food, and water security. We integrated recent data on national P fertilizer flows, subnational P use, and landscape features within a global grid to understand how these constraints on future options for P use are distributed worldwide. This analysis illustrates several regions where combinations of high population density, cropland extent, and manure P production provide islands of opportunity for P recycling in mixed crop-livestock and populous agricultural areas. At the same time, nations with lower import ratios (net P import:consumption) contained a disproportionately large share of manure-rich croplands and populous croplands. As a further demonstration of the kinds of integrated comparisons that are possible using global land use data sets in combination with P, worldwide similarities and distinctions for P emerged from a cluster analysis. These kinds of socioeconomic-geographic patterns may foretell distinct P futures as societies address spatially uneven options for P, food, and water security.
Modeling tree crown dynamics with 3D partial differential equations.
Beyer, Robert; Letort, Véronique; Cournède, Paul-Henry
2014-01-01
We characterize a tree's spatial foliage distribution by the local leaf area density. Considering this spatially continuous variable allows to describe the spatiotemporal evolution of the tree crown by means of 3D partial differential equations. These offer a framework to rigorously take locally and adaptively acting effects into account, notably the growth toward light. Biomass production through photosynthesis and the allocation to foliage and wood are readily included in this model framework. The system of equations stands out due to its inherent dynamic property of self-organization and spontaneous adaptation, generating complex behavior from even only a few parameters. The density-based approach yields spatially structured tree crowns without relying on detailed geometry. We present the methodological fundamentals of such a modeling approach and discuss further prospects and applications.
NASA Astrophysics Data System (ADS)
Sasai, Takahiro; Obikawa, Hiroki; Murakami, Kazutaka; Kato, Soushi; Matsunaga, Tsuneo; Nemani, Ramakrishna R.
2016-06-01
The terrestrial carbon cycle in Asia is highly uncertain, and it affects our understanding of global warming. One of the important issues is the need for an enhancement of spatial resolution, since local regions in Asia are heterogeneous with regard to meteorology, land form, and land cover type, which greatly impacts the detailed spatial patterns in its ecosystem. Thus, an important goal of this study is to reasonably reproduce the heterogeneous biogeochemical patterns in Asia by enhancing the spatial resolution of the ecosystem model biosphere model integrating eco-physiological and mechanistic approaches using satellite data (BEAMS). We estimated net ecosystem production (NEP) over eastern Asia and examined the spatial differences in the factors controlling NEP by using a 10 km grid-scale approach over two different decades (2001-2010 and 2091-2100). The present and future meteorological inputs were derived from satellite observations and the downscaled Coupled Model Intercomparison Project Phase 5 (CMIP5) data set, respectively. The results showed that the present NEP in whole eastern Asia was carbon source (-214.9 TgC yr-1) and in future scenarios, the greatest positive (76.4 TgC yr-1) and least negative (-95.9 TgC yr-1) NEPs were estimated from the Representative Concentration Pathways (RCP) 6.0 and RCP8.5 scenarios, respectively. Calculated annual NEP in RCP8.5 was mostly positive in the southern part of East Asia and Southeast Asia and negative in northern and central parts of East Asia. Under the RCP scenario with higher greenhouse gases emission (RCP8.5), deciduous needleleaf and mixed forests distributed in the middle and high latitudes served as carbon source. In contrast, evergreen broadleaf forests distributed in low latitudes served as carbon sink. The sensitivity study demonstrated that the spatial tendency of NEP was largely influenced by atmospheric CO2 and temperature.
[Spatial distribution pattern of Pontania dolichura larvae and sampling technique].
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
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
NASA Astrophysics Data System (ADS)
Xing, Lei; Hou, Di; Wang, Xinchen; Li, Li; Zhao, Meixun
2016-07-01
To evaluate the applicability of source proxies and to assess the sources of sedimentary organic matter in the Bohai Sea (BS) and the northern Yellow Sea (NYS), we analyzed total organic carbon (TOC), total nitrogen (TN), δ13C of TOC, n-alkanes, phytoplankton biomarkers, and glycerol dialkyl glycerol tetraethers (GDGTs) including branched GDGTs (brGDGTs) in 60 surface sediment samples covering the BS and the NYS. Spatial distribution comparison and principal component analysis indicate that with the exception of brGDGTs, terrestrial biomarkers have different spatial distribution pattern from marine biomarkers, suggesting that the sources control the distributions of these biomarkers in spite of hydrodynamic forcing. Significantly positive correlation (R2 = 0.5) between TOC normalized brGDGTs content and TOC normalized crenarchaeol content suggested in situ production of brGDGTs in the BS and the NYS. The δ13C values, TMBR [terrestrial and marine biomarker ratio: (C27 + C29 + C31n-alkanes)/[(C27 + C29 + C31n-alkanes) + (brassicasterol + dinosterol + alkenones)] ] and BIT (branched isoprenoid tetratether index) proxy indicated high terrestrial organic matter (TOM) input near the Huanghe River Estuary, while TOC/TON did not reveal similar distribution pattern. Quantitative estimates of TOM using a binary model revealed much higher TOM percentage from δ13C (avg. 58%) and TMBR (avg. 31%) than from BIT (avg. 7.4%). Our results suggest that, owing to significant in situ production of brGDGTs, the BIT is not a good proxy for indicating soil OM contribution in marine sediments from the BS and the NYS.
Modeling α- and β-diversity in a tropical forest from remotely sensed and spatial data
NASA Astrophysics Data System (ADS)
Hernández-Stefanoni, J. Luis; Gallardo-Cruz, J. Alberto; Meave, Jorge A.; Rocchini, Duccio; Bello-Pineda, Javier; López-Martínez, J. Omar
2012-10-01
Comprehensive information on species distribution and species composition patterns of plant communities is required for effective conservation and management of biodiversity. Remote sensing offers an inexpensive means of attaining complete spatial coverage for large areas, at regular time intervals, and can therefore be extremely useful for estimating both species richness and spatial variation of species composition (α- and β-diversity). An essential step to map such attributes is to identify and understand their main drivers. We used remotely sensed data as a surrogate of plant productivity and habitat structure variables for explaining α- and β-diversity, and evaluated the relative roles of productivity-habitat structure and spatial variables in explaining observed patterns of α- and β-diversity by using a Principal Coordinates of Neighbor Matrices analysis. We also examined the relationship between remotely sensed and field data, in order to map α- and β-diversity at the landscape-level in the Yucatan Peninsula, using a regression kriging procedure. These two procedures integrate the relationship of species richness and spatial species turnover both with remotely sensed data and spatial structure. The empirical models so obtained can be used to predict species richness and variation in species composition, and they can be regarded as valuable tools not only for identifying areas with high local species richness (α-diversity), but also areas with high species turnover (β-diversity). Ultimately, information obtained in this way can help maximize the number of species preserved in a landscape.
a Comparative Analysis of Five Cropland Datasets in Africa
NASA Astrophysics Data System (ADS)
Wei, Y.; Lu, M.; Wu, W.
2018-04-01
The food security, particularly in Africa, is a challenge to be resolved. The cropland area and spatial distribution obtained from remote sensing imagery are vital information. In this paper, according to cropland area and spatial location, we compare five global cropland datasets including CCI Land Cover, GlobCover, MODIS Collection 5, GlobeLand30 and Unified Cropland in circa 2010 of Africa in terms of cropland area and spatial location. The accuracy of cropland area calculated from five datasets was analyzed compared with statistic data. Based on validation samples, the accuracies of spatial location for the five cropland products were assessed by error matrix. The results show that GlobeLand30 has the best fitness with the statistics, followed by MODIS Collection 5 and Unified Cropland, GlobCover and CCI Land Cover have the lower accuracies. For the accuracy of spatial location of cropland, GlobeLand30 reaches the highest accuracy, followed by Unified Cropland, MODIS Collection 5 and GlobCover, CCI Land Cover has the lowest accuracy. The spatial location accuracy of five datasets in the Csa with suitable farming condition is generally higher than in the Bsk.
Evidence for Simultaneous Production of J/ψ and Υ Mesons
DOE Office of Scientific and Technical Information (OSTI.GOV)
Abazov, V. M.; Abbott, B.; Acharya, B. S.
2016-02-25
We report evidence for the simultaneous production of J/ψ and Υ mesons in 8.1 fbmore » $$^{-1}$$of data collected at $$\\sqrt{s}$$ = 1.96 TeV by the D0 experiment at the Fermilab $$p\\bar{p}$$ Tevatron Collider. Events with these characteristics are expected to be produced predominantly by gluon-gluon interactions. In this analysis, we extract the effective cross section characterizing the initial parton spatial distribution, σ$$_{eff}$$=2.2±0.7(stat)±0.9(syst) mb.« less
Application of evolutionary games to modeling carcinogenesis.
Swierniak, Andrzej; Krzeslak, Michal
2013-06-01
We review a quite large volume of literature concerning mathematical modelling of processes related to carcinogenesis and the growth of cancer cell populations based on the theory of evolutionary games. This review, although partly idiosyncratic, covers such major areas of cancer-related phenomena as production of cytotoxins, avoidance of apoptosis, production of growth factors, motility and invasion, and intra- and extracellular signaling. We discuss the results of other authors and append to them some additional results of our own simulations dealing with the possible dynamics and/or spatial distribution of the processes discussed.
NASA Astrophysics Data System (ADS)
Jin, Huaan; Li, Ainong; Bian, Jinhu; Nan, Xi; Zhao, Wei; Zhang, Zhengjian; Yin, Gaofei
2017-03-01
The validation study of leaf area index (LAI) products over rugged surfaces not only gives additional insights into data quality of LAI products, but deepens understanding of uncertainties regarding land surface process models depended on LAI data over complex terrain. This study evaluated the performance of MODIS and GLASS LAI products using the intercomparison and direct validation methods over southwestern China. The spatio-temporal consistencies, such as the spatial distributions of LAI products and their statistical relationship as a function of topographic indices, time, and vegetation types, respectively, were investigated through intercomparison between MODIS and GLASS products during the period 2011-2013. The accuracies and change ranges of these two products were evaluated against available LAI reference maps over 10 sampling regions which standed for typical vegetation types and topographic gradients in southwestern China. The results show that GLASS LAI exhibits higher percentage of good quality data (i.e. successful retrievals) and smoother temporal profiles than MODIS LAI. The percentage of successful retrievals for MODIS and GLASS is vulnerable to topographic indices, especially to relief amplitude. Besides, the two products do not capture seasonal dynamics of crop, especially in spring over heterogeneously hilly regions. The yearly mean LAI differences between MODIS and GLASS are within ±0.5 for 64.70% of the total retrieval pixels over southwestern China. The spatial distribution of mean differences and temporal profiles of these two products are inclined to be dominated by vegetation types other than topographic indices. The spatial and temporal consistency of these two products is good over most area of grasses/cereal crops; however, it is poor for evergreen broadleaf forest. MODIS presents more reliable change range of LAI than GLASS through comparison with fine resolution reference maps over most of sampling regions. The accuracies of direct validation are obtained for GLASS LAI (r = 0.35, RMSE = 1.72, mean bias = -0.71) and MODIS LAI (r = 0.49, RMSE = 1.75, mean bias = -0.67). GLASS performs similarly to MODIS, but may be marginally inferior to MODIS based on our direct validation results. The validation experience demonstrates the necessity and importance of topographic consideration for LAI estimation over mountain areas. Considerable attention will be paid to the improvements of surface reflectance, retrieval algorithm and land cover types so as to enhance the quality of LAI products in topographically complex terrain.
NASA Astrophysics Data System (ADS)
Garay, Michael J.; Kalashnikova, Olga V.; Bull, Michael A.
2017-04-01
Since early 2000, the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra satellite has been acquiring data that have been used to produce aerosol optical depth (AOD) and particle property retrievals at 17.6 km spatial resolution. Capitalizing on the capabilities provided by multi-angle viewing, the current operational (Version 22) MISR algorithm performs well, with about 75 % of MISR AOD retrievals globally falling within 0.05 or 20 % × AOD of paired validation data from the ground-based Aerosol Robotic Network (AERONET). This paper describes the development and assessment of a prototype version of a higher-spatial-resolution 4.4 km MISR aerosol optical depth product compared against multiple AERONET Distributed Regional Aerosol Gridded Observations Network (DRAGON) deployments around the globe. In comparisons with AERONET-DRAGON AODs, the 4.4 km resolution retrievals show improved correlation (r = 0. 9595), smaller RMSE (0.0768), reduced bias (-0.0208), and a larger fraction within the expected error envelope (80.92 %) relative to the Version 22 MISR retrievals.
NASA Astrophysics Data System (ADS)
Moharana, S.; Dutta, S.
2016-12-01
Abstract : The mapping and analysis of spatial variability within the field is a challenging task. However, field variability of a single vegetation cover does not give satisfactory results mainly due to low spectral resolution and non-availability of remote sensing data. From the NASA Earth Observing-1 (EO-1) satellite data, spatial distribution of biophysical parameters like chlorophyll and relative water content in a rice agriculture system is carried out in the present study. Hyperion L1R product composed of 242 spectral bands with 30m spatial resolution was acquired for Assam, India. This high dimensional data is allowed for pre-processing to get an atmospherically corrected imagery. Moreover, ground based hyperspectral measurements are collected from experimental rice fields from the study site using hand held ASD spectroradiometer (350-1050 nm). Published indices specifically designed for chlorophyll (OASVI, mSR, and MTCI indices) and water content (WI and WBI indices) are selected based on stastical performance of the in-situ hyperspectral data. Index models are established for the respective biophysical parameters and observed that the aforementioned indices followed different linear and nonlinear relationships which are completely different from the published indices. By employing the presently developed relationships, spatial variation of total chlorophyll and water stress are mapped for a rice agriculture system from Hyperion imagery. The findings showed that, the variation of chlorophyll and water content ranged from 1.77-10.61mg/g and 40-90% respectively for the studied rice agriculture system. The spatial distribution of these parameters resulted from presently developed index models are well captured from Hyperion imagery and they have good agreement with observed field based chlorophyll (1.14-7.26 mg/g) and water content (60-95%) of paddy crop. This study can be useful in providing essential information to assess the paddy field heterogeneity in an agriculture system. Keywords: Paddy crop, vegetation index, hyperspectral data, chlorophyll, water content
NASA Technical Reports Server (NTRS)
Moustafa, Samiah E.; Rennermalm, Asa K.; Roman, Miguel O.; Wang, Zhuosen; Schaaf, Crystal B.; Smith, Laurence C.; Koenig, Lora S.; Erb, Angela
2017-01-01
MODerate resolution Imaging Spectroradiometer (MODIS) albedo products have been validated over spatially uniform, snow-covered areas of the Greenland ice sheet (GrIS) using the so-called single 'point-to-pixel' method. This study expands on this methodology by applying a 'multiple-point-to-pixel' method and examination of spatial autocorrelation (here using semivariogram analysis) by using in situ observations, high-resolution World- View-2 (WV-2) surface reflectances, and MODIS Collection V006 daily blue-sky albedo over a spatially heterogeneous surfaces in the lower ablation zone in southwest Greenland. Our results using 232 ground-based samples within two MODIS pixels, one being more spatial heterogeneous than the other, show little difference in accuracy among narrow and broad band albedos (except for Band 2). Within the more homogenous pixel area, in situ and MODIS albedos were very close (error varied from -4% to +7%) and within the range of ASD standard errors. The semivariogram analysis revealed that the minimum observational footprint needed for a spatially representative sample is 30 m. In contrast, over the more spatially heterogeneous surface pixel, a minimum footprint size was not quantifiable due to spatial autocorrelation, and far exceeds the effective resolution of the MODIS retrievals. Over the high spatial heterogeneity surface pixel, MODIS is lower than ground measurements by 4-7%, partly due to a known in situ undersampling of darker surfaces that often are impassable by foot (e.g., meltwater features and shadowing effects over crevasses). Despite the sampling issue, our analysis errors are very close to the stated general accuracy of the MODIS product of 5%. Thus, our study suggests that the MODIS albedo product performs well in a very heterogeneous, low-albedo, area of the ice sheet ablation zone. Furthermore, we demonstrate that single 'point-to-pixel' methods alone are insufficient in characterizing and validating the variation of surface albedo displayed in the lower ablation area. This is true because the distribution of in situ data deviations from MODIS albedo show a substantial range, with the average values for the 10th and 90th percentiles being -0.30 and 0.43 across all bands. Thus, if only single point is taken for ground validation, and is randomly selected from either distribution tails, the error would appear to be considerable. Given the need for multiple in-situ points, concurrent albedo measurements derived from existing AWSs, (low-flying vehicles (airborne or unmanned) and high-resolution imagery (WV-2)) are needed to resolve high sub-pixel variability in the ablation zone, and thus, further improve our characterization of Greenland's surface albedo.
The Spatial Distribution of C2, C3, and NH in Comet 2P/Encke
NASA Astrophysics Data System (ADS)
Dorman, Garrett; Pierce, Donna M.; Cochran, Anita L.
2013-12-01
We examine the spatial distribution of C2, C3, and NH radicals in the coma of comet Encke in order to understand their abundances and distributions in the coma. The observations were obtained from 2003 October 22-24, using the 2.7 m telescope at McDonald Observatory. Building on our original study of CN and OH, we have used our modified version of the vectorial model, which treats the coma as one large cone, in order to reproduce Encke's highly aspherical and asymmetric coma. Our results suggest that NH can be explained by the photodissociation of NH2, assuming that NH2 is produced rapidly from NH3 in the innermost coma. Our modeling of C2 and C3 suggests a multi-generational photodissociation process may be required for their production. Using the results of our previous study, we also obtain abundance ratios with respect to OH and CN. Overall, we find that Encke exhibits typical carbon-chain abundances, and the results are consistent with other studies of comet Encke.
Measurements and modelling of fast-ion redistribution due to resonant MHD instabilities in MAST
NASA Astrophysics Data System (ADS)
Jones, O. M.; Cecconello, M.; McClements, K. G.; Klimek, I.; Akers, R. J.; Boeglin, W. U.; Keeling, D. L.; Meakins, A. J.; Perez, R. V.; Sharapov, S. E.; Turnyanskiy, M.; the MAST Team
2015-12-01
The results of a comprehensive investigation into the effects of toroidicity-induced Alfvén eigenmodes (TAE) and energetic particle modes on the NBI-generated fast-ion population in MAST plasmas are reported. Fast-ion redistribution due to frequency-chirping TAE in the range 50 kHz-100 kHz and frequency-chirping energetic particle modes known as fishbones in the range 20 kHz-50 kHz, is observed. TAE and fishbones are also observed to cause losses of fast ions from the plasma. The spatial and temporal evolution of the fast-ion distribution is determined using a fission chamber, a radially-scanning collimated neutron flux monitor, a fast-ion deuterium alpha spectrometer and a charged fusion product detector. Modelling using the global transport analysis code Transp, with ad hoc anomalous diffusion and fishbone loss models introduced, reproduces the coarsest features of the affected fast-ion distribution in the presence of energetic particle-driven modes. The spectrally and spatially resolved measurements show, however, that these models do not fully capture the effects of chirping modes on the fast-ion distribution.
Macrophytobenthos of the Caspian Sea: Diversity, distribution, and productivity
NASA Astrophysics Data System (ADS)
Stepanian, O. V.
2016-05-01
In the Russian sector of the northern and middle Caspian Sea, 36 species of macroalgae have been identified. The green and red algae from the mesosaprobic group are dominant. An increase in the number of green algae species is revealed. The distribution of macroalgae is inhomogeneous. It is confined to the solid substrate and epiphyton. The biomass of seaweeds reaches 1.5 kg/m2. Climate change has little influence on the appearance of new species in the northern Caspian Sea, but new invaders can appear in the Middle and Southern Caspian. The distribution of aquatic and coastal hygrophytic vegetation shows considerable spatial dynamics due to fluctuations in the level and salinity of the Caspian Sea. The biomass of aquatic vegetation varies in a wide range from 0.5 to 10.0 kg/m2. Spatially detailed mathematical models adequately reflect the changes in key species of aquatic plants in space and time. It is shown that expansion of the zone of the seagrass Zostera noltii to shallow water areas is occurring at present, as well as shrinkage of the range of the dominant littoral aquatic plant Phragmites australis.
NASA Astrophysics Data System (ADS)
Harrison, W. G.; Arístegui, J.; Head, E. J. H.; Li, W. K. W.; Longhurst, A. R.; Sameoto, D. D.
Three trans-Atlantic oceanographic surveys (Nova Scotia to Canary Islands) were carried out during fall 1992 and spring 1993 to describe the large-scale variability in hydrographic, chemical and biological properties of the upper water column of the subtropical gyre and adjacent waters. Significant spatial and temporal variability characterized a number of the biological pools and rate processes whereas others were relatively invariant. Systematic patterns were observed in the zonal distribution of some properties. Most notable were increases (eastward) in mixed-layer temperature and salinity, depths of the nitracline and chlorophyll- a maximum, regenerated production (NH 4 uptake) and bacterial production. Dissolved inorganic carbon (DIC) concentrations, phytoplankton biomass, mesozooplankton biomass and new production (NO 3 uptake) decreased (eastward). Bacterial biomass, primary production, and community respiration exhibited no discernible zonal distribution patterns. Seasonal variability was most evident in hydrography (cooler/fresher mixed-layer in spring), and chemistry (mixed-layer DIC concentration higher and nitracline shallower in spring) although primary production and bacterial production were significantly higher in spring than in fall. In general, seasonal variability was greater in the west than in the east; seasonality in most properties was absent west of Canary Islands (˜20°W). The distribution of autotrophs could be reasonably well explained by hydrography and nutrient structure, independent of location or season. Processes underlying the distribution of the microheterophs, however, were less clear. Heterotrophic biomass and metabolism was less variable than autotrophs and appeared to dominate the upper ocean carbon balance of the subtropical North Atlantic in both fall and spring. Geographical patterns in distribution are considered in the light of recent efforts to partition the ocean into distinct "biogeochemical provinces".
Metabolic Flexibility as a Major Predictor of Spatial Distribution in Microbial Communities
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
NASA Astrophysics Data System (ADS)
Auvet, B.; Lidon, B.; Kartiwa, B.; Le Bissonnais, Y.; Poussin, J.-C.
2015-09-01
This paper presents an approach to model runoff and erosion risk in a context of data scarcity, whereas the majority of available models require large quantities of physical data that are frequently not accessible. To overcome this problem, our approach uses different sources of data, particularly on agricultural practices (tillage and land cover) and farmers' perceptions of runoff and erosion. The model was developed on a small (5 ha) cultivated watershed characterized by extreme conditions (slopes of up to 55 %, extreme rainfall events) on the Merapi volcano in Indonesia. Runoff was modelled using two versions of STREAM. First, a lumped version was used to determine the global parameters of the watershed. Second, a distributed version used three parameters for the production of runoff (slope, land cover and roughness), a precise DEM, and the position of waterways for runoff distribution. This information was derived from field observations and interviews with farmers. Both surface runoff models accurately reproduced runoff at the outlet. However, the distributed model (Nash-Sutcliffe = 0.94) was more accurate than the adjusted lumped model (N-S = 0.85), especially for the smallest and biggest runoff events, and produced accurate spatial distribution of runoff production and concentration. Different types of erosion processes (landslides, linear inter-ridge erosion, linear erosion in main waterways) were modelled as a combination of a hazard map (the spatial distribution of runoff/infiltration volume provided by the distributed model), and a susceptibility map combining slope, land cover and tillage, derived from in situ observations and interviews with farmers. Each erosion risk map gives a spatial representation of the different erosion processes including risk intensities and frequencies that were validated by the farmers and by in situ observations. Maps of erosion risk confirmed the impact of the concentration of runoff, the high susceptibility of long steep slopes, and revealed the critical role of tillage direction. Calibrating and validating models using in situ measurements, observations and farmers' perceptions made it possible to represent runoff and erosion risk despite the initial scarcity of hydrological data. Even if the models mainly provided orders of magnitude and qualitative information, they significantly improved our understanding of the watershed dynamics. In addition, the information produced by such models is easy for farmers to use to manage runoff and erosion by using appropriate agricultural practices.
Power quality analysis based on spatial correlation
NASA Astrophysics Data System (ADS)
Li, Jiangtao; Zhao, Gang; Liu, Haibo; Li, Fenghou; Liu, Xiaoli
2018-03-01
With the industrialization and urbanization, the status of electricity in the production and life is getting higher and higher. So the prediction of power quality is the more potential significance. Traditional power quality analysis methods include: power quality data compression, disturbance event pattern classification, disturbance parameter calculation. Under certain conditions, these methods can predict power quality. This paper analyses the temporal variation of power quality of one provincial power grid in China from time angle. The distribution of power quality was analyzed based on spatial autocorrelation. This paper tries to prove that the research idea of geography is effective for mining the potential information of power quality.
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.
Abraham, Jerrold L.; Chandra, Subhash; Agrawal, Anoop
2014-01-01
Recently, a report raised the possibility of shrapnel-induced chronic beryllium disease (CBD) from long-term exposure to the surface of retained aluminum shrapnel fragments in the body. Since the shrapnel fragments contained trace beryllium, methodological developments were needed for beryllium quantification and to study its spatial distribution in relation to other matrix elements, such as aluminum and iron, in metallurgic samples. In this work, we developed methodology for quantification of trace beryllium in samples of shrapnel fragments and other metallurgic sample-types with main matrix of aluminum (aluminum cans from soda, beer, carbonated water, and aluminum foil). Sample preparation procedures were developed for dissolving beryllium for its quantification with the fluorescence detection method for homogenized measurements. The spatial distribution of trace beryllium on the sample surface and in 3D was imaged with a dynamic secondary ion mass spectrometry (SIMS) instrument, CAMECA IMS 3f SIMS ion microscope. The beryllium content of shrapnel (~100 ppb) was the same as the trace quantities of beryllium found in aluminum cans. The beryllium content of aluminum foil (~25 ppb) was significantly lower than cans. SIMS imaging analysis revealed beryllium to be distributed in the form of low micron-sized particles and clusters distributed randomly in X-Y-and Z dimensions, and often in association with iron, in the main aluminum matrix of cans. These observations indicate a plausible formation of Be-Fe or Al-Be alloy in the matrix of cans. Further observations were made on fluids (carbonated water) for understanding if trace beryllium in cans leached out and contaminated the food product. A direct comparison of carbonated water in aluminum cans and plastic bottles revealed that beryllium was below the detection limits of the fluorescence detection method (~0.01 ppb). These observations indicate that beryllium present in aluminum matrix was either present in an immobile form or its mobilization into the food product was prevented by a polymer coating on the inside of cans, a practice used in food industry to prevent contamination of food products. The lack of such coating in retained shrapnel fragments renders their surface a possible source of contamination for long-term exposure of tissues and fluids and induction of disease, as characterized in a recent study. Methodological developments reported here can be extended to studies of beryllium in electronics devices and components. PMID:25146877
Abraham, J L; Chandra, S; Agrawal, A
2014-11-01
Recently, a report raised the possibility of shrapnel-induced chronic beryllium disease from long-term exposure to the surface of retained aluminum shrapnel fragments in the body. Since the shrapnel fragments contained trace beryllium, methodological developments were needed for beryllium quantification and to study its spatial distribution in relation to other matrix elements, such as aluminum and iron, in metallurgic samples. In this work, we developed methodology for quantification of trace beryllium in samples of shrapnel fragments and other metallurgic sample-types with main matrix of aluminum (aluminum cans from soda, beer, carbonated water and aluminum foil). Sample preparation procedures were developed for dissolving beryllium for its quantification with the fluorescence detection method for homogenized measurements. The spatial distribution of trace beryllium on the sample surface and in 3D was imaged with a dynamic secondary ion mass spectrometry instrument, CAMECA IMS 3f secondary ion mass spectrometry ion microscope. The beryllium content of shrapnel (∼100 ppb) was the same as the trace quantities of beryllium found in aluminum cans. The beryllium content of aluminum foil (∼25 ppb) was significantly lower than cans. SIMS imaging analysis revealed beryllium to be distributed in the form of low micron-sized particles and clusters distributed randomly in X-Y- and Z dimensions, and often in association with iron, in the main aluminum matrix of cans. These observations indicate a plausible formation of Be-Fe or Al-Be alloy in the matrix of cans. Further observations were made on fluids (carbonated water) for understanding if trace beryllium in cans leached out and contaminated the food product. A direct comparison of carbonated water in aluminum cans and plastic bottles revealed that beryllium was below the detection limits of the fluorescence detection method (∼0.01 ppb). These observations indicate that beryllium present in aluminum matrix was either present in an immobile form or its mobilization into the food product was prevented by a polymer coating on the inside of cans, a practice used in food industry to prevent contamination of food products. The lack of such coating in retained shrapnel fragments renders their surface a possible source of contamination for long-term exposure of tissues and fluids and induction of disease, as characterized in a recent study. Methodological developments reported here can be extended to studies of beryllium in electronics devices and components. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.
Emery, Isaac; Mueller, Steffen; Qin, Zhangcai; Dunn, Jennifer B
2017-01-03
Land availability for growing feedstocks at scale is a crucial concern for the bioenergy industry. Feedstock production on land not well-suited to growing conventional crops, or marginal land, is often promoted as ideal, although there is a poor understanding of the qualities, quantity, and distribution of marginal lands in the United States. We examine the spatial distribution of land complying with several key marginal land definitions at the United States county, agro-ecological zone, and national scales, and compare the ability of both marginal land and land cover data sets to identify regions for feedstock production. We conclude that very few land parcels comply with multiple definitions of marginal land. Furthermore, to examine possible carbon-flow implications of feedstock production on land that could be considered marginal per multiple definitions, we model soil carbon changes upon transitions from marginal cropland, grassland, and cropland-pastureland to switchgrass production for three marginal land-rich counties. Our findings suggest that total soil organic carbon changes per county are small, and generally positive, and can influence life-cycle greenhouse gas emissions of switchgrass ethanol.
NASA Astrophysics Data System (ADS)
Padhee, S. K.; Nikam, B. R.; Aggarwal, S. P.; Garg, V.
2014-11-01
Drought is an extreme condition due to moisture deficiency and has adverse effect on society. Agricultural drought occurs when restraining soil moisture produces serious crop stress and affects the crop productivity. The soil moisture regime of rain-fed agriculture and irrigated agriculture behaves differently on both temporal and spatial scale, which means the impact of meteorologically and/or hydrological induced agriculture drought will be different in rain-fed and irrigated areas. However, there is a lack of agricultural drought assessment system in Indian conditions, which considers irrigated and rain-fed agriculture spheres as separate entities. On the other hand recent advancements in the field of earth observation through different satellite based remote sensing have provided researchers a continuous monitoring of soil moisture, land surface temperature and vegetation indices at global scale, which can aid in agricultural drought assessment/monitoring. Keeping this in mind, the present study has been envisaged with the objective to develop agricultural drought assessment and prediction technique by spatially and temporally assimilating effective drought index (EDI) with remote sensing derived parameters. The proposed technique takes in to account the difference in response of rain-fed and irrigated agricultural system towards agricultural drought in the Bundelkhand region (The study area). The key idea was to achieve the goal by utilizing the integrated scenarios from meteorological observations and soil moisture distribution. EDI condition maps were prepared from daily precipitation data recorded by Indian Meteorological Department (IMD), distributed within the study area. With the aid of frequent MODIS products viz. vegetation indices (VIs), and land surface temperature (LST), the coarse resolution soil moisture product from European Space Agency (ESA) were downscaled using linking model based on Triangle method to a finer resolution soil moisture product. EDI and spatially downscaled soil moisture products were later used with MODIS 16 days NDVI product as key elements to assess and predict agricultural drought in irrigated and rain-fed agricultural systems in Bundelkhand region of India. Meteorological drought, soil moisture deficiency and NDVI degradation were inhabited for each and every pixel of the image in GIS environment, for agricultural impact assessment at a 16 day temporal scale for Rabi seasons (October-April) between years 2000 to 2009. Based on the statistical analysis, good correlations were found among the parameters EDI and soil moisture anomaly; NDVI anomaly and soil moisture anomaly lagged to 16 days and these results were exploited for the development of a linear prediction model. The predictive capability of the developed model was validated on the basis of spatial distribution of predicted NDVI which was compared with MODIS NDVI product in the beginning of preceding Rabi season (Oct-Dec of 2010).The predictions of the model were based on future meteorological data (year 2010) and were found to be yielding good results. The developed model have good predictive capability based on future meteorological data (rainfall data) availability, which enhances its utility in analyzing future Agricultural conditions if meteorological data is available.
NASA Astrophysics Data System (ADS)
Li, X.; Omara, M.; Adams, P. J.; Presto, A. A.
2017-12-01
Methane is the second most powerful greenhouse gas after Carbon Dioxide. The natural gas production and distribution accounts for 23% of the total anthropogenic methane emissions in the United States. The boost of natural gas production in U.S. in recent years poses a potential concern of increased methane emissions from natural gas production and distribution. The Emission Database for Global Atmospheric Research (Edgar) v4.2 and the EPA Greenhouse Gas Inventory (GHGI) are currently the most commonly used methane emission inventories. However, recent studies suggested that both Edgar v4.2 and the EPA GHGI largely underestimated the methane emission from natural gas production and distribution in U.S. constrained by both ground and satellite measurements. In this work, we built a gridded (0.1° Latitude ×0.1° Longitude) methane emission inventory of natural gas production and distribution over the contiguous U.S. using emission factors measured by our mobile lab in the Marcellus Shale, the Denver-Julesburg Basin, and the Uintah Basin, and emission factors reported from other recent field studies for other natural gas production regions. The activity data (well location and count) are mostly obtained from the Drillinginfo, the EPA Greenhouse Gas Reporting Program (GHGRP) and the U.S. Energy Information Administration (EIA). Results show that the methane emission from natural gas production and distribution estimated by our inventory is about 20% higher than the EPA GHGI, and in some major natural gas production regions, methane emissions estimated by the EPA GHGI are significantly lower than our inventory. For example, in the Marcellus Shale, our estimated annual methane emission in 2015 is 600 Gg higher than the EPA GHGI. We also ran the GEOS-Chem methane simulation to estimate the methane concentration in the atmosphere with our built inventory, the EPA GHGI and the Edgar v4.2 over the nested North American Domain. These simulation results showed differences in some major gas production regions. The simulated methane concentrations will be compared with the GOSAT satellite data to explore whether our built inventory could potentially improve the prediction of regional methane concentrations in the atmosphere.
O'Sullivan, Daniel J.; O'Sullivan, Orla; McSweeney, Paul L. H.; Sheehan, Jeremiah J.
2015-01-01
We sought to determine if the time, within a production day, that a cheese is manufactured has an influence on the microbial community present within that cheese. To facilitate this, 16S rRNA amplicon sequencing was used to elucidate the microbial community dynamics of brine-salted continental-type cheese in cheeses produced early and late in the production day. Differences in the microbial composition of the core and rind of the cheese were also investigated. Throughout ripening, it was apparent that cheeses produced late in the day had a more diverse microbial population than their early equivalents. Spatial variation between the cheese core and rind was also noted in that cheese rinds were initially found to have a more diverse microbial population but thereafter the opposite was the case. Interestingly, the genera Thermus, Pseudoalteromonas, and Bifidobacterium, not routinely associated with a continental-type cheese produced from pasteurized milk, were detected. The significance, if any, of the presence of these genera will require further attention. Ultimately, the use of high-throughput sequencing has facilitated a novel and detailed analysis of the temporal and spatial distribution of microbes in this complex cheese system and established that the period during a production cycle at which a cheese is manufactured can influence its microbial composition. PMID:25636841
Wang, P; Sun, R; Hu, J; Zhu, Q; Zhou, Y; Li, L; Chen, J M
2007-11-01
Large scale process-based modeling is a useful approach to estimate distributions of global net primary productivity (NPP). In this paper, in order to validate an existing NPP model with observed data at site level, field experiments were conducted at three sites in northern China. One site is located in Qilian Mountain in Gansu Province, and the other two sites are in Changbaishan Natural Reserve and Dunhua County in Jilin Province. Detailed field experiments are discussed and field data are used to validate the simulated NPP. Remotely sensed images including Landsat Enhanced Thematic Mapper plus (ETM+, 30 m spatial resolution in visible and near infrared bands) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER, 15m spatial resolution in visible and near infrared bands) are used to derive maps of land cover, leaf area index, and biomass. Based on these maps, field measured data, soil texture and daily meteorological data, NPP of these sites are simulated for year 2001 with the boreal ecosystem productivity simulator (BEPS). The NPP in these sites ranges from 80 to 800 gCm(-2)a(-1). The observed NPP agrees well with the modeled NPP. This study suggests that BEPS can be used to estimate NPP in northern China if remotely sensed images of high spatial resolution are available.
High-Resolution Atmospheric Emission Inventory of the Argentine Enery Sector
NASA Astrophysics Data System (ADS)
Puliafito, Salvador Enrique; Castesana, Paula; Allende, David; Ruggeri, Florencia; Pinto, Sebastián; Pascual, Romina; Bolaño Ortiz, Tomás; Fernandez, Rafael Pedro
2017-04-01
This study presents a high-resolution spatially disaggregated inventory (2.5 km x 2.5 km), updated to 2014, of the main emissions from energy activities in Argentina. This inventory was created with the purpose of improving air quality regional models. The sub-sectors considered are public electricity and heat production, cement production, domestic aviation, road and rail transportation, inland navigation, residential and commercial, and fugitive emissions from refineries and fuel expenditure. The pollutants considered include greenhouse gases and ozone precursors: CO2, CH4, NOx, N2O VOC; and other gases specifically related to air quality including PM10, PM2.5, SOx, Pb and POPs. The uncertainty analysis of the inventories resulted in a variability of 3% for public electricity generation, 3-6% in the residential, commercial sector, 6-12% terrestrial transportation sector, 10-20% in oil refining and cement production according to the considered pollutant. Aviation and maritime navigation resulted in a higher variability reaching more than 60%. A comparison with the international emission inventory EDGAR shows disagreements in the spatial distribution of emissions, probably due to the finer resolution of the map presented here, particularly as a result of the use of new spatially disaggregated data of higher resolution that is currently available.
NASA Astrophysics Data System (ADS)
Motew, M.; Kucharik, C. J.
2011-12-01
While much attention is focused on future impacts of climate change on ecosystems, much can be learned about the previous interactions of ecosystems with recent climate change. In this study, we investigated the impacts of climate change on potential vegetation distributions (i.e. grasses, trees, and shrubs) and carbon and water cycling across the Upper Midwest USA from 1948-2007 using the Agro-IBIS dynamic vegetation model. We drove the model using a historical, gridded daily climate data set (temperature, precipitation, humidity, solar radiation, and wind speed) at a spatial resolution of 5 min x 5 min. While trends in climate variables exhibited heterogeneous spatial patterns over the study period, the overall impact of climate change on vegetation productivity was positive. We observed total increases in net primary productivity (NPP) ranging from 20-150 g C m-2, based on linear regression analysis. We determined that increased summer relative humidity, increased annual precipitation and decreased mean maximum summer temperatures were key variables contributing to these positive trends, likely through a reduction in soil moisture stress (e.g., increased available water) and heat stress. Model simulations also illustrated an increase in annual drainage throughout the region of 20-140 mm yr-1, driven by substantial increases in annual precipitation. Evapotranspiration had a highly variable spatial trend over the 60-year period, with total change over the study period ranging between -100 and +100 mm yr-1. We also analyzed potential changes in plant functional type (PFT) distributions at the biome level, but hypothesize that the model may be unable to adequately capture competitive interactions among PFTs as well as the dynamics between upper and lower canopies consisting of trees, grasses and shrubs. An analysis of the bioclimatic envelopes for PFTs common to the region revealed no significant change to the boreal conifer tree climatic domain over the study period, yet did reveal a slightly expanded domain for temperate deciduous broadleaf trees. The location of the Tension Zone, a broad ecotone dividing mixed forests in the north and southern hardwood forests and prairies in the south, was not observed to shift using analyses of both meteorological variables and through the results of simulated vegetation distributions. In general, our results supported the idea that climate change is spatially variable in nature, having significant effects on ecosystem structure and function. Our analysis also revealed interesting relationships among the key climatic quantities driving plant productivity and hydrology in the region. Most notably, while the model suggested that potential biome and PFT distributions have not likely shifted significantly in the past 60 years, climate change has contributed to substantial changes in coupled carbon, water, and energy exchange in natural ecosystems of the Upper Midwest US. We conclude that incorporating recent, high-resolution climate records into ecological studies offers valuable insight into the heterogeneous nature of climate change and its impacts on ecosystems at the local level.
Distribution, behavior, and condition of herbivorous fishes on coral reefs track algal resources.
Tootell, Jesse S; Steele, Mark A
2016-05-01
Herbivore distribution can impact community structure and ecosystem function. On coral reefs, herbivores are thought to play an important role in promoting coral dominance, but how they are distributed relative to algae is not well known. Here, we evaluated whether the distribution, behavior, and condition of herbivorous fishes correlated with algal resource availability at six sites in the back reef environment of Moorea, French Polynesia. Specifically, we tested the hypotheses that increased algal turf availability would coincide with (1) increased biomass, (2) altered foraging behavior, and (3) increased energy reserves of herbivorous fishes. Fish biomass and algal cover were visually estimated along underwater transects; behavior of herbivorous fishes was quantified by observations of focal individuals; fish were collected to assess their condition; and algal turf production rates were measured on standardized tiles. The best predictor of herbivorous fish biomass was algal turf production, with fish biomass increasing with algal production. Biomass of herbivorous fishes was also negatively related to sea urchin density, suggesting competition for limited resources. Regression models including both algal turf production and urchin density explained 94 % of the variation in herbivorous fish biomass among sites spread over ~20 km. Behavioral observations of the parrotfish Chlorurus sordidus revealed that foraging area increased as algal turf cover decreased. Additionally, energy reserves increased with algal turf production, but declined with herbivorous fish density, implying that algal turf is a limited resource for this species. Our findings support the hypothesis that herbivorous fishes can spatially track algal resources on coral reefs.
The pollutants from livestock and poultry farming in China-geographic distribution and drivers.
Gan, Ling; Hu, Xisheng
2016-05-01
Livestock and poultry farming is a major source of agricultural pollution. However, our knowledge of the constraining factors of the geographic distribution of pollutants from livestock and poultry farming is still limited. In this study, using the optimized pollutant generation coefficients, we estimated the annual pollutant productions of eight livestock and poultry species at the provincial level in 2005 and 2013 and their growth rates during the study period in China; using canonical correlation analysis, we also explored the association between the eight pollutant measurements as dependent variables and 14 factors (including resource endowment, developmental level, and economic structure factors) as independent variables. Results indicate that there exist spatial disparity in the distribution of pollutants from livestock and poultry farming across regions, with provinces in the Huang-Huai-Hai region and the southwestern region accounting for approximately 50 % of the total productions in the nation. Cattle, pig, and poultry constitute the primary pollution sources in terms of livestock and poultry farming not only at the national level but also at the province level. While the species constitute and their respective growth rates of the pollutants can be also characterized by spatial disparity across regions, canonical correlation analysis shows that the observed regional patterns of the pollutants can be largely explained by the resource endowment factors (positive effects) and the developmental level factors (negative effects). In addition, we found that the development of livestock and poultry farming is negatively associated with the growing rate of both the resource endowment and the socioeconomic factors. This indicates that there exist different driving patterns in the gross and increment of the pollutant productions. Our research has significant implications for the appropriate environmental protection policy formulation and implementation in livestock sector.
NASA Astrophysics Data System (ADS)
Wang, Z.; Roman, M. O.; Pahlevan, N.; Stachura, M.; McCorkel, J.; Bland, G.; Schaaf, C.
2016-12-01
Albedo is a key climate forcing variable that governs the absorption of incoming solar radiation and its ultimate transfer to the atmosphere. Albedo contributes significant uncertainties in the simulation of climate changes; and as such, it is defined by the Global Climate Observing System (GCOS) as a terrestrial essential climate variable (ECV) required by global and regional climate and biogeochemical models. NASA's Goddard Space Flight Center's Multi AngLe Imaging Bidirectional Reflectance Distribution Function small-UAS (MALIBU) is part of a series of pathfinder missions to develop enhanced multi-angular remote sensing techniques using small Unmanned Aircraft Systems (sUAS). The MALIBU instrument package includes two multispectral imagers oriented at two different viewing geometries (i.e., port and starboard sides) capture vegetation optical properties and structural characteristics. This is achieved by analyzing the surface reflectance anisotropy signal (i.e., BRDF shape) obtained from the combination of surface reflectance from different view-illumination angles and spectral channels. Satellite measures of surface albedo from MODIS, VIIRS, and Landsat have been evaluated by comparison with spatially representative albedometer data from sparsely distributed flux towers at fixed heights. However, the mismatch between the footprint of ground measurements and the satellite footprint challenges efforts at validation, especially for heterogeneous landscapes. The BRDF (Bidirectional Reflectance Distribution Function) models of surface anisotropy have only been evaluated with airborne BRDF data over a very few locations. The MALIBU platform that acquires extremely high resolution sub-meter measures of surface anisotropy and surface albedo, can thus serve as an important source of reference data to enable global land product validation efforts, and resolve the errors and uncertainties in the various existing products generated by NASA and its national and international partners.
WAGNER, JEFF; GHOSAL, SUTAPA; WHITEHEAD, TODD; METAYER, CATHERINE
2013-01-01
We characterized flame retardant (FR) morphologies and spatial distributions in 7 consumer products and 7 environmental dusts to determine their implications for transfer mechanisms, human exposure, and the reproducibility of gas chromatography-mass spectrometry (GC-MS) dust measurements. We characterized individual particles using scanning electron microscopy / energy dispersive x-ray spectroscopy (SEM/EDS) and Raman micro-spectroscopy (RMS). Samples were screened for the presence of 3 FR constituents (bromine, phosphorous, non-salt chlorine) and 2 metal synergists (antimony and bismuth). Subsequent analyses of select samples by RMS enabled molecular identification of the FR compounds and matrix materials. The consumer products and dust samples possessed FR elemental weight percents of up to 36% and 31%, respectively. We identified 24 FR-containing particles in the dust samples and classified them into 9 types based on morphology and composition. We observed a broad range of morphologies for these FR-containing particles, suggesting FR transfer to dust via multiple mechanisms. We developed an equation to describe the heterogeneity of FR-containing particles in environmental dust samples. The number of individual FR-containing particles expected in a 1-mg dust sample with a FR concentration of 100 ppm ranged from <1 to >1000 particles. The presence of rare, high-concentration bromine particles was correlated with decabromodiphenyl ether concentrations obtained via GC-MS. When FRs are distributed heterogeneously in highly concentrated dust particles, human exposure to FRs may be characterized by high transient exposures interspersed by periods of low exposure, and GC-MS FR concentrations may exhibit large variability in replicate subsamples. Current limitations of this SEM/EDS technique include potential false negatives for volatile and chlorinated FRs and greater quantitation uncertainty for brominated FR in aluminum-rich matrices. PMID:23739093
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
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.
NASA Astrophysics Data System (ADS)
Hu, Z.
2017-12-01
Climate change is predicted to cause dramatic variability in precipitation regime, not only in terms of change in annual precipitation amount, but also in precipitation seasonal distribution and precipitation event characteristics (high frenquency extrem precipitation, larger but fewer precipitation events), which combined to influence productivity of grassland in arid and semiarid regions. In this study, combining remote sensing products with in-situ measurements of aboveground net primary productivity (ANPP) and gross primary productivity (GPP) data from eddy covariance system in grassland of northern China, we quantified the effects of spatio-temporal vairation in precipitation on productivity from local sites to region scale. We found that, for an individual precipitation event, the duration of GPP-response to the individual precipitation event and the maximum absolute GPP response induced by the individual precipitation event increased linearly with the size of precipitation events. Comparison of the productivity-precipitation relationships between multi-sites determined that the predominant characteristics of precipitation events (PEC) that affected GPP differed remarkably between the water-limited temperate steppe and the temperature-limited alpine meadow. The number of heavy precipitation events (>10 mm d-1) was the most important PEC to impact GPP in the temperate steppe through affecting soil moisture at different soil profiles, while precipitation interval was the factor that affected GPP most in the alpine meadow via its effects on temperature. At the region scale, shape of ANPP-precipitation relationship varies with distinct spatial scales, and besides annual precipitation, precipitation seasonal distribution also has comparable impacts on spatial variation in ANPP. Temporal variability in ANPP was lower at both the dry and wet end, and peaked at a precipitation of 243.1±3.5mm, which is the transition region between typical steppe and desert steppe. Our work has important implications to obtain an advanced understanding of productivity-response of grassland ecosystems to altered precipitation regimes.
Mauser, Wolfram; Klepper, Gernot; Zabel, Florian; Delzeit, Ruth; Hank, Tobias; Putzenlechner, Birgitta; Calzadilla, Alvaro
2015-01-01
Global biomass demand is expected to roughly double between 2005 and 2050. Current studies suggest that agricultural intensification through optimally managed crops on today's cropland alone is insufficient to satisfy future demand. In practice though, improving crop growth management through better technology and knowledge almost inevitably goes along with (1) improving farm management with increased cropping intensity and more annual harvests where feasible and (2) an economically more efficient spatial allocation of crops which maximizes farmers' profit. By explicitly considering these two factors we show that, without expansion of cropland, today's global biomass potentials substantially exceed previous estimates and even 2050s' demands. We attribute 39% increase in estimated global production potentials to increasing cropping intensities and 30% to the spatial reallocation of crops to their profit-maximizing locations. The additional potentials would make cropland expansion redundant. Their geographic distribution points at possible hotspots for future intensification. PMID:26558436
Mauser, Wolfram; Klepper, Gernot; Zabel, Florian; Delzeit, Ruth; Hank, Tobias; Putzenlechner, Birgitta; Calzadilla, Alvaro
2015-11-12
Global biomass demand is expected to roughly double between 2005 and 2050. Current studies suggest that agricultural intensification through optimally managed crops on today's cropland alone is insufficient to satisfy future demand. In practice though, improving crop growth management through better technology and knowledge almost inevitably goes along with (1) improving farm management with increased cropping intensity and more annual harvests where feasible and (2) an economically more efficient spatial allocation of crops which maximizes farmers' profit. By explicitly considering these two factors we show that, without expansion of cropland, today's global biomass potentials substantially exceed previous estimates and even 2050s' demands. We attribute 39% increase in estimated global production potentials to increasing cropping intensities and 30% to the spatial reallocation of crops to their profit-maximizing locations. The additional potentials would make cropland expansion redundant. Their geographic distribution points at possible hotspots for future intensification.
Predicting temporal variation in zooplankton beta diversity is challenging
Castelo Branco, Christina W.; Kozlowsky-Suzuki, Betina; Sousa-Filho, Izidro F.; Souza, Leonardo Coimbra e; Bini, Luis Mauricio
2017-01-01
Beta diversity, the spatial variation in species composition, has been related to different explanatory variables, including environmental heterogeneity, productivity and connectivity. Using a long-term time series of zooplankton data collected over 62 months in a tropical reservoir (Ribeirão das Lajes Reservoir, Rio de Janeiro State, Brazil), we tested whether beta diversity (as measured across six sites distributed along the main axis of the reservoir) was correlated with environmental heterogeneity (spatial environmental variation in a given month), chlorophyll-a concentration (a surrogate for productivity) and water level. We did not found evidence for the role of these predictors, suggesting the need to reevaluate predictions or at least to search for better surrogates of the processes that hypothetically control beta diversity variation. However, beta diversity declined over time, which is consistent with the process of biotic homogenization, a worldwide cause of concern. PMID:29095892
Predicting temporal variation in zooplankton beta diversity is challenging.
Lopes, Vanessa Guimarães; Castelo Branco, Christina W; Kozlowsky-Suzuki, Betina; Sousa-Filho, Izidro F; Souza, Leonardo Coimbra E; Bini, Luis Mauricio
2017-01-01
Beta diversity, the spatial variation in species composition, has been related to different explanatory variables, including environmental heterogeneity, productivity and connectivity. Using a long-term time series of zooplankton data collected over 62 months in a tropical reservoir (Ribeirão das Lajes Reservoir, Rio de Janeiro State, Brazil), we tested whether beta diversity (as measured across six sites distributed along the main axis of the reservoir) was correlated with environmental heterogeneity (spatial environmental variation in a given month), chlorophyll-a concentration (a surrogate for productivity) and water level. We did not found evidence for the role of these predictors, suggesting the need to reevaluate predictions or at least to search for better surrogates of the processes that hypothetically control beta diversity variation. However, beta diversity declined over time, which is consistent with the process of biotic homogenization, a worldwide cause of concern.
D.P. Turner; W.D. Ritts; J.M. Styles; Z. Yang; W.B. Cohen; B.E. Law; P.E. Thornton
2006-01-01
Net ecosystem production (NEP) was estimated over a 10.9 x 104 km2 forested region in western Oregon USA for 2 yr (2002-2003) using a combination of remote sensing, distributed meteorological data, and a carbon cycle model (CFLUX). High spatial resolution satellite data (Landsat, 30 m) provided information on land cover and...
Anthropogenic Moisture production and its effect on boundary-layer circulations over New York City
Robert D. Bornstein; Yam-Tong Tam
1977-01-01
A heat and moisture excess over New York City is shown to exist by the analysis of helicopter soundings of temperature and wet-bulb depression. The magnitude of the temporal and spatial distribution of anthropogenic moisture emissions in New York City were estimated from fuel-usage data. The URBMET urban boundary-layer model was used to evaluate the effects on the...
Watanabe, Kohei; Kouzaki, Motoki; Merletti, Roberto; Fujibayashi, Mami; Moritani, Toshio
2012-02-01
The aim of the present study was to compare spatial electromyographic (EMG) potential distribution during force production between elderly and young individuals using multi-channel surface EMG (SEMG). Thirteen elderly (72-79years) and 13 young (21-27years) healthy male volunteers performed ramp submaximal contraction during isometric knee extension from 0% to 65% of maximal voluntary contraction. During contraction, multi-channel EMG was recorded from the vastus lateralis muscle. To evaluate alteration in heterogeneity and pattern in spatial EMG potential distribution, coefficient of variation (CoV), modified entropy and correlation coefficients with initial torque level were calculated from multi-channel SEMG at 5% force increment. Increase in CoV and decrease in modified entropy of RMS with increase of exerted torque were significantly smaller in elderly group (p<0.05) and correlation coefficients with initial torque level were significantly higher in elderly group than in young group at moderate torque levels (p<0.05). These data suggest that the increase of heterogeneity and the change in the activation pattern are smaller in elderly individuals than in young individuals. We speculated that multi-channel SEMG pattern in elderly individual reflects neuromuscular activation strategy regulated predominantly by clustering of similar type of muscle fibers in aged muscle. Copyright © 2011 Elsevier Ltd. All rights reserved.
Spatial Distribution of Fate and Transport Parameters Using Cxtfit in a Karstified Limestone Model
NASA Astrophysics Data System (ADS)
Toro, J.; Padilla, I. Y.
2017-12-01
Karst environments have a high capacity to transport and store large amounts of water. This makes karst aquifers a productive resource for human consumption and ecological integrity, but also makes them vulnerable to potential contamination of hazardous chemical substances. High heterogeneity and anisotropy of karst aquifer properties make them very difficult to characterize for accurate prediction of contaminant mobility and persistence in groundwater. Current technologies to characterize and quantify flow and transport processes at field-scale is limited by low resolution of spatiotemporal data. To enhance this resolution and provide the essential knowledge of karst groundwater systems, studies at laboratory scale can be conducted. This work uses an intermediate karstified lab-scale physical model (IKLPM) to study fate and transport processes and assess viable tools to characterize heterogeneities in karst systems. Transport experiments are conducted in the IKLPM using step injections of calcium chloride, uranine, and rhodamine wt tracers. Temporal concentration distributions (TCDs) obtained from the experiments are analyzed using the method of moments and CXTFIT to quantify fate and transport parameters in the system at various flow rates. The spatial distribution of the estimated fate and transport parameters for the tracers revealed high variability related to preferential flow heterogeneities and scale dependence. Results are integrated to define spatially-variable transport regions within the system and assess their fate and transport characteristics.
Contemporary Remotely Sensed Data Products Refine Invasive Plants Risk Mapping in Data Poor Regions.
Truong, Tuyet T A; Hardy, Giles E St J; Andrew, Margaret E
2017-01-01
Invasive weeds are a serious problem worldwide, threatening biodiversity and damaging economies. Modeling potential distributions of invasive weeds can prioritize locations for monitoring and control efforts, increasing management efficiency. Forecasts of invasion risk at regional to continental scales are enabled by readily available downscaled climate surfaces together with an increasing number of digitized and georeferenced species occurrence records and species distribution modeling techniques. However, predictions at a finer scale and in landscapes with less topographic variation may require predictors that capture biotic processes and local abiotic conditions. Contemporary remote sensing (RS) data can enhance predictions by providing a range of spatial environmental data products at fine scale beyond climatic variables only. In this study, we used the Global Biodiversity Information Facility (GBIF) and empirical maximum entropy (MaxEnt) models to model the potential distributions of 14 invasive plant species across Southeast Asia (SEA), selected from regional and Vietnam's lists of priority weeds. Spatial environmental variables used to map invasion risk included bioclimatic layers and recent representations of global land cover, vegetation productivity (GPP), and soil properties developed from Earth observation data. Results showed that combining climate and RS data reduced predicted areas of suitable habitat compared with models using climate or RS data only, with no loss in model accuracy. However, contributions of RS variables were relatively limited, in part due to uncertainties in the land cover data. We strongly encourage greater adoption of quantitative remotely sensed estimates of ecosystem structure and function for habitat suitability modeling. Through comprehensive maps of overall predicted area and diversity of invasive species, we found that among lifeforms (herb, shrub, and vine), shrub species have higher potential invasion risk in SEA. Native invasive species, which are often overlooked in weed risk assessment, may be as serious a problem as non-native invasive species. Awareness of invasive weeds and their environmental impacts is still nascent in SEA and information is scarce. Freely available global spatial datasets, not least those provided by Earth observation programs, and the results of studies such as this one provide critical information that enables strategic management of environmental threats such as invasive species.
Contemporary Remotely Sensed Data Products Refine Invasive Plants Risk Mapping in Data Poor Regions
Truong, Tuyet T. A.; Hardy, Giles E. St. J.; Andrew, Margaret E.
2017-01-01
Invasive weeds are a serious problem worldwide, threatening biodiversity and damaging economies. Modeling potential distributions of invasive weeds can prioritize locations for monitoring and control efforts, increasing management efficiency. Forecasts of invasion risk at regional to continental scales are enabled by readily available downscaled climate surfaces together with an increasing number of digitized and georeferenced species occurrence records and species distribution modeling techniques. However, predictions at a finer scale and in landscapes with less topographic variation may require predictors that capture biotic processes and local abiotic conditions. Contemporary remote sensing (RS) data can enhance predictions by providing a range of spatial environmental data products at fine scale beyond climatic variables only. In this study, we used the Global Biodiversity Information Facility (GBIF) and empirical maximum entropy (MaxEnt) models to model the potential distributions of 14 invasive plant species across Southeast Asia (SEA), selected from regional and Vietnam’s lists of priority weeds. Spatial environmental variables used to map invasion risk included bioclimatic layers and recent representations of global land cover, vegetation productivity (GPP), and soil properties developed from Earth observation data. Results showed that combining climate and RS data reduced predicted areas of suitable habitat compared with models using climate or RS data only, with no loss in model accuracy. However, contributions of RS variables were relatively limited, in part due to uncertainties in the land cover data. We strongly encourage greater adoption of quantitative remotely sensed estimates of ecosystem structure and function for habitat suitability modeling. Through comprehensive maps of overall predicted area and diversity of invasive species, we found that among lifeforms (herb, shrub, and vine), shrub species have higher potential invasion risk in SEA. Native invasive species, which are often overlooked in weed risk assessment, may be as serious a problem as non-native invasive species. Awareness of invasive weeds and their environmental impacts is still nascent in SEA and information is scarce. Freely available global spatial datasets, not least those provided by Earth observation programs, and the results of studies such as this one provide critical information that enables strategic management of environmental threats such as invasive species. PMID:28555147
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.
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.
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.
Signal to Noise Ratio for Different Gridded Rainfall Products of Indian Monsoon
NASA Astrophysics Data System (ADS)
Nehra, P.; Shastri, H. K.; Ghosh, S.; Mishra, V.; Murtugudde, R. G.
2014-12-01
Gridded rainfall datasets provide useful information of spatial and temporal distribution of precipitation over a region. For India, there are 3 gridded rainfall data products available from India Meteorological Department (IMD), Tropical Rainfall Measurement Mission (TRMM) and Asian Precipitation - Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE), these compile precipitation information obtained through satellite based measurement and ground station based data. The gridded rainfall data from IMD is available at spatial resolution of 1°, 0.5° and 0.25° where as TRMM and APHRODITE is available at 0.25°. Here, we employ 7 years (1998-2004) of common time period amongst the 3 data products for the south-west monsoon season, i.e., the months June to September. We examine temporal mean and standard deviation of these 3 products to observe substantial variation amongst them at 1° resolution whereas for 0.25° resolution, all the data types are nearly identical. We determine the Signal to Noise Ratio (SNR) of the 3 products at 1° and 0.25° resolution based on noise separation technique adopting horizontal separation of the power spectrum generated with the Fast Fourier Transformation (FFT). A methodology is developed for threshold based separation of signal and noise from the power spectrum, treating the noise as white. The variance of signal to that of noise is computed to obtain SNR. Determination of SNR for different regions over the country shows the highest SNR with APHRODITE at 0.25° resolution. It is observed that the eastern part of India has the highest SNR in all cases considered whereas the northern and southern most Indian regions have lowest SNR. An incremental linear trend is observed among the SNR values and the spatial variance of corresponding region. Relationship between the computed SNR values and the interpolation method used with the dataset is analyzed. The SNR analysis provides an effective tool to evaluate the gridded precipitation data products. However detailed analysis is needed to determine the processes that lead to these SNR distributions so that the quality of the gridded rainfall data products can be further improved and transferability of the gridding algorithms can be explored to produce a unified high-quality rainfall dataset.
NASA Astrophysics Data System (ADS)
McNeil, Mardi A.; Webster, Jody M.; Beaman, Robin J.; Graham, Trevor L.
2016-12-01
Halimeda bioherms occur as extensive geological structures on the northern Great Barrier Reef (GBR), Australia. We present the most complete, high-resolution spatial mapping of the northern GBR Halimeda bioherms, based on new airborne lidar and multibeam echosounder bathymetry data. Our analysis reveals that bioherm morphology does not conform to the previous model of parallel ridges and troughs, but is far more complex than previously thought. We define and describe three morphological sub-types: reticulate, annulate, and undulate, which are distributed in a cross-shelf pattern of reduced complexity from east to west. The northern GBR bioherms cover an area of 6095 km2, three times larger than the original estimate, exceeding the area and volume of calcium carbonate in the adjacent modern shelf-edge barrier reefs. We have mapped a 1740 km2 bioherm complex north of Raine Island in the Cape York region not previously recorded, extending the northern limit by more than 1° of latitude. Bioherm formation and distribution are controlled by a complex interaction of outer-shelf geometry, regional and local currents, coupled with the morphology and depth of continental slope submarine canyons determining the delivery of cool, nutrient-rich water upwelling through inter-reef passages. Distribution and mapping of Halimeda bioherms in relation to Great Barrier Reef Marine Park Authority bioregion classifications and management zones are inconsistent and currently poorly defined due to a lack of high-resolution data not available until now. These new estimates of bioherm spatial distribution and morphology have implications for understanding the role these geological features play as structurally complex and productive inter-reef habitats, and as calcium carbonate sinks which record a complete history of the Holocene post-glacial marine transgression in the northern GBR.
Spatial Distribution of Surface Soil Moisture in a Small Forested Catchment
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...
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.
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.
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
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
Schulze, Jule; Frank, Karin; Priess, Joerg A; Meyer, Markus A
2016-01-01
Meeting the world's growing energy demand through bioenergy production involves extensive land-use change which could have severe environmental and social impacts. Second generation bioenergy feedstocks offer a possible solution to this problem. They have the potential to reduce land-use conflicts between food and bioenergy production as they can be grown on low quality land not suitable for food production. However, a comprehensive impact assessment that considers multiple ecosystem services (ESS) and biodiversity is needed to identify the environmentally best feedstock option, as trade-offs are inherent. In this study, we simulate the spatial distribution of short rotation coppices (SRCs) in the landscape of the Mulde watershed in Central Germany by modeling profit-maximizing farmers under different economic and policy-driven scenarios using a spatially explicit economic simulation model. This allows to derive general insights and a mechanistic understanding of regional-scale impacts on multiple ESS in the absence of large-scale implementation. The modeled distribution of SRCs, required to meet the regional demand of combined heat and power (CHP) plants for solid biomass, had little or no effect on the provided ESS. In the policy-driven scenario, placing SRCs on low or high quality soils to provide ecological focus areas, as required within the Common Agricultural Policy in the EU, had little effect on ESS. Only a substantial increase in the SRC production area, beyond the regional demand of CHP plants, had a relevant effect, namely a negative impact on food production as well as a positive impact on biodiversity and regulating ESS. Beneficial impacts occurred for single ESS. However, the number of sites with balanced ESS supply hardly increased due to larger shares of SRCs in the landscape. Regression analyses showed that the occurrence of sites with balanced ESS supply was more strongly driven by biophysical factors than by the SRC share in the landscape. This indicates that SRCs negligibly affect trade-offs between individual ESS. Coupling spatially explicit economic simulation models with environmental and ESS assessment models can contribute to a comprehensive impact assessment of bioenergy feedstocks that have not yet been planted.
Schulze, Jule; Frank, Karin; Priess, Joerg A.; Meyer, Markus A.
2016-01-01
Meeting the world’s growing energy demand through bioenergy production involves extensive land-use change which could have severe environmental and social impacts. Second generation bioenergy feedstocks offer a possible solution to this problem. They have the potential to reduce land-use conflicts between food and bioenergy production as they can be grown on low quality land not suitable for food production. However, a comprehensive impact assessment that considers multiple ecosystem services (ESS) and biodiversity is needed to identify the environmentally best feedstock option, as trade-offs are inherent. In this study, we simulate the spatial distribution of short rotation coppices (SRCs) in the landscape of the Mulde watershed in Central Germany by modeling profit-maximizing farmers under different economic and policy-driven scenarios using a spatially explicit economic simulation model. This allows to derive general insights and a mechanistic understanding of regional-scale impacts on multiple ESS in the absence of large-scale implementation. The modeled distribution of SRCs, required to meet the regional demand of combined heat and power (CHP) plants for solid biomass, had little or no effect on the provided ESS. In the policy-driven scenario, placing SRCs on low or high quality soils to provide ecological focus areas, as required within the Common Agricultural Policy in the EU, had little effect on ESS. Only a substantial increase in the SRC production area, beyond the regional demand of CHP plants, had a relevant effect, namely a negative impact on food production as well as a positive impact on biodiversity and regulating ESS. Beneficial impacts occurred for single ESS. However, the number of sites with balanced ESS supply hardly increased due to larger shares of SRCs in the landscape. Regression analyses showed that the occurrence of sites with balanced ESS supply was more strongly driven by biophysical factors than by the SRC share in the landscape. This indicates that SRCs negligibly affect trade-offs between individual ESS. Coupling spatially explicit economic simulation models with environmental and ESS assessment models can contribute to a comprehensive impact assessment of bioenergy feedstocks that have not yet been planted. PMID:27082742
NASA Astrophysics Data System (ADS)
Hu, W.; Si, B. C.
2013-10-01
Soil water content (SWC) varies in space and time. The objective of this study was to evaluate soil water content distribution using a statistical model. The model divides spatial SWC series into time-invariant spatial patterns, space-invariant temporal changes, and space- and time-dependent redistribution terms. The redistribution term is responsible for the temporal changes in spatial patterns of SWC. An empirical orthogonal function was used to separate the total variations of redistribution terms into the sum of the product of spatial structures (EOFs) and temporally-varying coefficients (ECs). Model performance was evaluated using SWC data of near-surface (0-0.2 m) and root-zone (0-1.0 m) from a Canadian Prairie landscape. Three significant EOFs were identified for redistribution term for both soil layers. EOF1 dominated the variations of redistribution terms and it resulted in more changes (recharge or discharge) in SWC at wetter locations. Depth to CaCO3 layer and organic carbon were the two most important controlling factors of EOF1, and together, they explained over 80% of the variations in EOF1. Weak correlation existed between either EOF2 or EOF3 and the observed factors. A reasonable prediction of SWC distribution was obtained with this model using cross validation. The model performed better in the root zone than in the near surface, and it outperformed conventional EOF method in case soil moisture deviated from the average conditions.
Antunes, Ana Carolina Lopes; Halasa, Tariq; Lauritsen, Klara Tølbøl; Kristensen, Charlotte Sonne; Larsen, Lars Erik; Toft, Nils
2015-12-21
Porcine reproductive and respiratory syndrome (PRRS) has been a cause for great concern to the Danish pig industry since it was first diagnosed in 1992. The causative agent of PRRS is an RNA virus which is divided into different genotypes. The clinical signs, as well as its morbidity and mortality, is highly variable between herds and regions. Two different genotypes of PRRS virus (PRRSV) are found in Denmark: type 1 and type 2. Approximately 40% of Danish swine herds are seropositive for one or both PRRSV types. The objective of this study was to describe the temporal trend and spatial distribution of PRRSV in Danish swine herds from 2007 to 2010, based on type-specific serological tests from the PRRS surveillance and control program in Denmark using the results stored in the information management system at the National Veterinary Institute, Technical University of Denmark (DTU Vet). The average monthly seroprevalence of PRRSV type 1 was 9% (minimum of 5%; maximum of 13%) in breeding herds, and 20% (minimum of 14%; maximum of 26%) in production herds; PRRSV type 2 had an average seroprevalence of 3% (minimum of 1%; maximum of 9%) in breeding herds and of 9% (minimum of 5%; maximum of 13%) within production herds. The seroconversion rate followed a similar and consistent pattern, being higher for type 1 than for type 2 for both PRRSV types. Regarding the spatiotemporal results, the relative risk distribution maps changed over time as a consequence of the changes in PRRSV seroprevalence, suggesting a general decline in the extent of areas with higher relative risk for both type 1 and 2. Local spatial analysis results demonstrated the existence of statistically significant clusters in areas where the relative risk was higher for both herds. PRRSV type 1 seroprevalence was constantly higher than for PRRSV type 2 in both herd types. Significant spatial clusters were consistently found in Denmark, suggesting that PRRSV is endemic in these areas. Furthermore, relative risk distribution maps revealed different patterns over time as a consequence of the changes in seroprevalence.
Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao
2014-01-01
The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables. PMID:25317762
Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao
2014-10-14
The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables.
Effects of habitat fragmentation on passerine birds breeding in Intermountain shrubsteppe
Knick, S.T.; Rotenberry, J.T.
2002-01-01
Habitat fragmentation and loss strongly influence the distribution and abundance of passerine birds breeding in Intermountain shrubsteppe. Wildfires, human activities, and change in vegetation communities often are synergistic in these systems and can result in radical conversion from shrubland to grasslands dominated by exotic annuals at large temporal and spatial scales from which recovery to native conditions is unlikely. As a result, populations of 5 of the 12 species in our review of Intermountain shrubsteppe birds are undergoing significant declines; 5 species are listed as at-risk or as candidates for protection in at least one state. The process by which fragmentation affects bird distributions in these habitats remains unknown because most research has emphasized the detection of population trends and patterns of habitat associations at relatively large spatial scales. Our research indicates that the distribution of shrubland-obligate species, such as Brewer's Sparrows (Spizella breweri), Sage Sparrows (Amphispiza belli), and Sage Thrashers (Oreoscoptes montanus), was highly sensitive to fragmentation of shrublands at spatial scales larger than individual home ranges. In contrast, the underlying mechanisms for both habitat change and bird population dynamics may operate independently of habitat boundaries. We propose alternative, but not necessarily exclusive, mechanisms to explain the relationship between habitat fragmentation and bird distribution and abundance. Fragmentation might influence productivity through differences in breeding density, nesting success, or predation. However, local and landscape variables were not significant determinants either of success, number fledged, or probability of predation or parasitism (although our tests had relatively low statistical power). Alternatively, relative absence of natal philopatry and redistribution by individuals among habitats following fledging or post-migration could account for the pattern of distribution and abundance. Thus, boundary dynamics may be important in determining the distribution of shrubland-obligate species but insignificant relative to the mechanisms causing the pattern of habitat and bird distribution. Because of the dichotomy in responses, Intermountain shrubsteppe systems present a unique challenge in understanding how landscape composition, configuration, and change influence bird population dynamics.
A Bayesian Surrogate for Regional Skew in Flood Frequency Analysis
NASA Astrophysics Data System (ADS)
Kuczera, George
1983-06-01
The problem of how to best utilize site and regional flood data to infer the shape parameter of a flood distribution is considered. One approach to this problem is given in Bulletin 17B of the U.S. Water Resources Council (1981) for the log-Pearson distribution. Here a lesser known distribution is considered, namely, the power normal which fits flood data as well as the log-Pearson and has a shape parameter denoted by λ derived from a Box-Cox power transformation. The problem of regionalizing λ is considered from an empirical Bayes perspective where site and regional flood data are used to infer λ. The distortive effects of spatial correlation and heterogeneity of site sampling variance of λ are explicitly studied with spatial correlation being found to be of secondary importance. The end product of this analysis is the posterior distribution of the power normal parameters expressing, in probabilistic terms, what is known about the parameters given site flood data and regional information on λ. This distribution can be used to provide the designer with several types of information. The posterior distribution of the T-year flood is derived. The effect of nonlinearity in λ on inference is illustrated. Because uncertainty in λ is explicitly allowed for, the understatement in confidence limits due to fixing λ (analogous to fixing log skew) is avoided. Finally, it is shown how to obtain the marginal flood distribution which can be used to select a design flood with specified exceedance probability.
Spatio-temporal patterns of key exploited marine species in the Northwestern Mediterranean Sea.
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.
Obrist, Daniel; Pearson, Christopher; Webster, Jackson; Kane, Tyler; Lin, Che-Jen; Aiken, George R; Alpers, Charles N
2016-10-15
A synthesis of published vegetation mercury (Hg) data across 11 contiguous states in the western United States showed that aboveground biomass concentrations followed the order: leaves (26μgkg(-1))~branches (26μgkg(-1))>bark (16μgkg(-1))>bole wood (1μgkg(-1)). No spatial trends of Hg in aboveground biomass distribution were detected, which likely is due to very sparse data coverage and different sampling protocols. Vegetation data are largely lacking for important functional vegetation types such as shrubs, herbaceous species, and grasses. Soil concentrations collected from the published literature were high in the western United States, with 12% of observations exceeding 100μgkg(-1), reflecting a bias toward investigations in Hg-enriched sites. In contrast, soil Hg concentrations from a randomly distributed data set (1911 sampling points; Smith et al., 2013a) averaged 24μgkg(-1) (A-horizon) and 22μgkg(-1) (C-horizon), and only 2.6% of data exceeded 100μgkg(-1). Soil Hg concentrations significantly differed among land covers, following the order: forested upland>planted/cultivated>herbaceous upland/shrubland>barren soils. Concentrations in forests were on average 2.5 times higher than in barren locations. Principal component analyses showed that soil Hg concentrations were not or weakly related to modeled dry and wet Hg deposition and proximity to mining, geothermal areas, and coal-fired power plants. Soil Hg distribution also was not closely related to other trace metals, but strongly associated with organic carbon, precipitation, canopy greenness, and foliar Hg pools of overlying vegetation. These patterns indicate that soil Hg concentrations are related to atmospheric deposition and reflect an overwhelming influence of plant productivity - driven by water availability - with productive landscapes showing high soil Hg accumulation and unproductive barren soils and shrublands showing low soil Hg values. Large expanses of low-productivity, arid ecosystems across the western U.S. result in some of the lowest soil Hg concentrations observed worldwide. Copyright © 2015 Elsevier B.V. All rights reserved.
Wang, Xinbing; Zhou, Baoyuan; Sun, Xuefang; Yue, Yang; Ma, Wei; Zhao, Ming
2015-01-01
The spatial distribution of the root system through the soil profile has an impact on moisture and nutrient uptake by plants, affecting growth and productivity. The spatial distribution of the roots, soil moisture, and fertility are affected by tillage practices. The combination of high soil density and the presence of a soil plow pan typically impede the growth of maize (Zea mays L.).We investigated the spatial distribution coordination of the root system, soil moisture, and N status in response to different soil tillage treatments (NT: no-tillage, RT: rotary-tillage, SS: subsoiling) and the subsequent impact on maize yield, and identify yield-increasing mechanisms and optimal soil tillage management practices. Field experiments were conducted on the Huang-Huai-Hai plain in China during 2011 and 2012. The SS and RT treatments significantly reduced soil bulk density in the top 0-20 cm layer of the soil profile, while SS significantly decreased soil bulk density in the 20-30 cm layer. Soil moisture in the 20-50 cm profile layer was significantly higher for the SS treatment compared to the RT and NT treatment. In the 0-20 cm topsoil layer, the NT treatment had higher soil moisture than the SS and RT treatments. Root length density of the SS treatment was significantly greater than density of the RT and NT treatments, as soil depth increased. Soil moisture was reduced in the soil profile where root concentration was high. SS had greater soil moisture depletion and a more concentration root system than RT and NT in deep soil. Our results suggest that the SS treatment improved the spatial distribution of root density, soil moisture and N states, thereby promoting the absorption of soil moisture and reducing N leaching via the root system in the 20-50 cm layer of the profile. Within the context of the SS treatment, a root architecture densely distributed deep into the soil profile, played a pivotal role in plants' ability to access nutrients and water. An optimal combination of deeper deployment of roots and resource (water and N) availability was realized where the soil was prone to leaching. The correlation between the depletion of resources and distribution of patchy roots endorsed the SS tillage practice. It resulted in significantly greater post-silking biomass and grain yield compared to the RT and NT treatments, for summer maize on the Huang-Huai-Hai plain.
Wang, Xinbing; Zhou, Baoyuan; Sun, Xuefang; Yue, Yang; Ma, Wei; Zhao, Ming
2015-01-01
The spatial distribution of the root system through the soil profile has an impact on moisture and nutrient uptake by plants, affecting growth and productivity. The spatial distribution of the roots, soil moisture, and fertility are affected by tillage practices. The combination of high soil density and the presence of a soil plow pan typically impede the growth of maize (Zea mays L.).We investigated the spatial distribution coordination of the root system, soil moisture, and N status in response to different soil tillage treatments (NT: no-tillage, RT: rotary-tillage, SS: subsoiling) and the subsequent impact on maize yield, and identify yield-increasing mechanisms and optimal soil tillage management practices. Field experiments were conducted on the Huang-Huai-Hai plain in China during 2011 and 2012. The SS and RT treatments significantly reduced soil bulk density in the top 0–20 cm layer of the soil profile, while SS significantly decreased soil bulk density in the 20–30 cm layer. Soil moisture in the 20–50 cm profile layer was significantly higher for the SS treatment compared to the RT and NT treatment. In the 0-20 cm topsoil layer, the NT treatment had higher soil moisture than the SS and RT treatments. Root length density of the SS treatment was significantly greater than density of the RT and NT treatments, as soil depth increased. Soil moisture was reduced in the soil profile where root concentration was high. SS had greater soil moisture depletion and a more concentration root system than RT and NT in deep soil. Our results suggest that the SS treatment improved the spatial distribution of root density, soil moisture and N states, thereby promoting the absorption of soil moisture and reducing N leaching via the root system in the 20–50 cm layer of the profile. Within the context of the SS treatment, a root architecture densely distributed deep into the soil profile, played a pivotal role in plants’ ability to access nutrients and water. An optimal combination of deeper deployment of roots and resource (water and N) availability was realized where the soil was prone to leaching. The correlation between the depletion of resources and distribution of patchy roots endorsed the SS tillage practice. It resulted in significantly greater post-silking biomass and grain yield compared to the RT and NT treatments, for summer maize on the Huang-Huai-Hai plain. PMID:26098548
NASA Astrophysics Data System (ADS)
Li, J.; Menzel, W.; Sun, F.; Schmit, T.
2003-12-01
The Moderate-Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS) Aqua satellite will enable global monitoring of the distribution of clouds. MODIS is able to provide at high spatial resolution (1 ~ 5km) the cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud water path (CWP). AIRS is able to provide CTP, ECA, CPS, and CWP within the AIRS footprint with much better accuracy using its greatly enhanced hyperspectral remote sensing capability. The combined MODIS / AIRS system offers the opportunity for cloud products improved over those possible from either system alone. The algorithm developed was applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS cloud products, as well as with the Geostationary Operational Environmental Satellite (GOES) sounder cloud products, to demonstrate the advantage of synergistic use of high spatial resolution MODIS cloud products and high spectral resolution AIRS sounder radiance measurements for optimal cloud retrieval. Data from ground-based instrumentation at the Atmospheric Radiation Measurement (ARM) Program Cloud and Radiation Test Bed (CART) in Oklahoma were used for the validation; results show that AIRS improves the MODIS cloud products in certain cases such as low-level clouds.
MODIS 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region
NASA Technical Reports Server (NTRS)
Munchak, L. A.; Levy, R. C.; Mattoo, S.; Remer, L. A.; Holben, B. N.; Schafer, J. S.; Hostetler, C. A.; Ferrare, R. A.
2013-01-01
MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.
NASA Astrophysics Data System (ADS)
Zou, Li; Yao, Xiao; Yamaguchi, Hitomi; Guo, Xinyu; Gao, Huiwang; Wang, Kai; Sun, Mingyi
2018-04-01
In order to examine the seasonal and spatial distributions of benthic animals in the intertidal mudflat of the southern Yellow River Delta, field investigations were carried out in 2007 and 2008 and multiple methods were applied. Results showed that, the biomass of macro benthos ranged at 0.75-1151.00 g wet m-2 and averaged at 156.31 g wet m-2, in which Mactra veneriformis accounted for 75.6%-93.4% of the total macro benthic biomass. More than 90% of macro benthos inhabited in the middle and low tide lines, and higher biomass occurred in early summer and lower in winter. Statistical analysis showed that: 1) M. veneriformis growth was primarily favored at higher temperature and lower salinity; 2) after long time interaction, benthic bivalve grazers led to patching distributions of Chlorophyll a (Chl a); 3) macro benthic biomass positively related with Chl a when the concentration of Chl a was low, but they were negatively related when Chl a concentration was high; and 4) furthermore, the biomass of benthic bivalves peaked in the sediment with median grain size about 0.55 mm, but decreased gradually in coarse or fine sediments. The secondary productivity ranged at 0.37-283.68 g m-2yr-1 and averaged at 47.88 g m-2 yr-1, in which 69.7% was contributed by M. veneriformis It was estimated that primary production was transformed to secondary production at a rate of 6.87% approximately, which implies that there is a local sustainability of high bivalve production.
[Collaborative application of BEPS at different time steps.
Lu, Wei; Fan, Wen Yi; Tian, Tian
2016-09-01
BEPSHourly is committed to simulate the ecological and physiological process of vegetation at hourly time steps, and is often applied to analyze the diurnal change of gross primary productivity (GPP), net primary productivity (NPP) at site scale because of its more complex model structure and time-consuming solving process. However, daily photosynthetic rate calculation in BEPSDaily model is simpler and less time-consuming, not involving many iterative processes. It is suitable for simulating the regional primary productivity and analyzing the spatial distribution of regional carbon sources and sinks. According to the characteristics and applicability of BEPSDaily and BEPSHourly models, this paper proposed a method of collaborative application of BEPS at daily and hourly time steps. Firstly, BEPSHourly was used to optimize the main photosynthetic parameters: the maximum rate of carboxylation (V c max ) and the maximum rate of photosynthetic electron transport (J max ) at site scale, and then the two optimized parameters were introduced into BEPSDaily model to estimate regional NPP at regional scale. The results showed that optimization of the main photosynthesis parameters based on the flux data could improve the simulate ability of the model. The primary productivity of different forest types in descending order was deciduous broad-leaved forest, mixed forest, coniferous forest in 2011. The collaborative application of carbon cycle models at different steps proposed in this study could effectively optimize the main photosynthesis parameters V c max and J max , simulate the monthly averaged diurnal GPP, NPP, calculate the regional NPP, and analyze the spatial distribution of regional carbon sources and sinks.
NASA Astrophysics Data System (ADS)
Zhang, Z.; Zimmermann, N. E.; Poulter, B.
2015-11-01
Simulations of the spatial-temporal dynamics of wetlands are key to understanding the role of wetland biogeochemistry under past and future climate variability. Hydrologic inundation models, such as TOPMODEL, are based on a fundamental parameter known as the compound topographic index (CTI) and provide a computationally cost-efficient approach to simulate wetland dynamics at global scales. However, there remains large discrepancy in the implementations of TOPMODEL in land-surface models (LSMs) and thus their performance against observations. This study describes new improvements to TOPMODEL implementation and estimates of global wetland dynamics using the LPJ-wsl dynamic global vegetation model (DGVM), and quantifies uncertainties by comparing three digital elevation model products (HYDRO1k, GMTED, and HydroSHEDS) at different spatial resolution and accuracy on simulated inundation dynamics. In addition, we found that calibrating TOPMODEL with a benchmark wetland dataset can help to successfully delineate the seasonal and interannual variations of wetlands, as well as improve the spatial distribution of wetlands to be consistent with inventories. The HydroSHEDS DEM, using a river-basin scheme for aggregating the CTI, shows best accuracy for capturing the spatio-temporal dynamics of wetlands among the three DEM products. The estimate of global wetland potential/maximum is ∼ 10.3 Mkm2 (106 km2), with a mean annual maximum of ∼ 5.17 Mkm2 for 1980-2010. This study demonstrates the feasibility to capture spatial heterogeneity of inundation and to estimate seasonal and interannual variations in wetland by coupling a hydrological module in LSMs with appropriate benchmark datasets. It additionally highlights the importance of an adequate investigation of topographic indices for simulating global wetlands and shows the opportunity to converge wetland estimates across LSMs by identifying the uncertainty associated with existing wetland products.
Changes of the potential distribution area of French Mediterranean forests under global warming
NASA Astrophysics Data System (ADS)
Gaucherel, C.; Guiot, J.; Misson, L.
2008-11-01
This work aims at understanding future spatial and temporal distributions of tree species in the Mediterranean region of France under various climates. We focused on two different species (Pinus Halepensis and Quercus Ilex) and compared their growth under the IPCC-B2 climate scenario in order to quantify significant changes between present and future. The influence of environmental factors such as atmospheric CO2 increase and topography on the tree growth has also been quantified. We modeled species growth with the help of a process-based model (MAIDEN), previously calibrated over measured ecophysiological and dendrochronological series with a Bayesian scheme. The model was fed with the ARPEGE MeteoFrance climate model, combined with an explicit increase in CO2 atmospheric concentration. The main output of the model gives the carbon allocation in boles and thus tree production. Our results show that the MAIDEN model is correctly able to simulate pine and oak production in space and time, after detailed calibration and validation stages. Yet, these simulations, mainly based on climate, are indicative and not predictive. The comparison of simulated growth at end of 20th and 21st centuries, show a shift of the pine production optimum from about 650 to 950 m due to 2.5 K temperature increase, while no optimum has been found for oak. With the direct effect of CO2 increase taken into account, both species show a significant increase in productivity (+26 and +43% for pine and oak respectively) at the end of the 21st century. While both species have different growth mechanisms, they have a good chance to extend their spatial distribution and their elevation in the Alps during the 21st century under the IPCC-B2 climate scenario. This extension is mainly due to the CO2 fertilization effect.
NASA Astrophysics Data System (ADS)
French, David W.; Huguet, Carme; Wakeham, Stuart; Turich, Courtney; Carlson, Laura T.; Ingalls, Anitra E.
2015-04-01
Branched and isoprenoid glycerol dialkyl glycerol tetraethers (GDGTs) are used to reconstruct carbon flow from terrestrial landscapes to the ocean in a proxy called the branched vs isoprenoid tetraether index, or BIT Index. The index is based on analysis of core GDGTs from non-living material that originate from the cell membranes of bacteria living in soils and archaea living primarily in the marine environment. However, uncertainty in the identity and location of branched GDGTs (BrGDGTs) producing organisms and the likely production of isoprenoid GDGTs (IsoGDGTs) in terrestrial environments hinders interpretation of the BIT Index. Since BrGDGTs remain our only tool to study BrGDGT producing organisms, it is particularly important to use the intact form of BrGDGTs, present in living cells, to infer organism distributions. In situ production within riverine, lacustrine, and marine environments is currently thought to be possible, yet few measures of intact BrGDGTs (I-BrGDGTs) are available to confirm this. Here we assess the spatial distribution of both core and intact GDGTs throughout the Columbia River basin and nearby areas in Washington and Oregon in order to elucidate source environments for these lipids. The presence of I-BrGDGTs throughout the studied soils, rivers and estuaries suggests in situ production across the continuum from soil to marine environments. Likewise, intact crenarchaeol, the marine endmember isoprenoidal GDGT used in the BIT index, was present in all samples. Widespread production of each GDGT class along terrestrial carbon transport paths likely alters the BIT Index along this continuum. The core to intact GDGT ratios and the weak correlation between I-GDGT derived BIT values and carbon isotope signatures suggest a mixture of allocthonous and autochthonous sources of GDGTs in riverine and marine environments. Our findings highlight the need for further work into the provenance of GDGTs to improve the BIT index and other environmental proxies that rely on these compounds.
De Roos, J; Verce, M; Aerts, M; Vandamme, P; De Vuyst, L
2018-04-01
Few data have been published on the occurrence and functional role of acetic acid bacteria (AAB) in lambic beer production processes, mainly due to their difficult recovery and possibly unknown role. Therefore, a novel aseptic sampling method, spanning both the spatial and temporal distributions of the AAB and their substrates and metabolites, was combined with a highly selective medium and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) as a high-throughput dereplication method followed by comparative gene sequencing for their isolation and identification, respectively. The AAB ( Acetobacter species more than Gluconobacter species) proliferated during two phases of the lambic beer production process, represented by Acetobacter orientalis during a few days in the beginning of the fermentation and Acetobacter pasteurianus from 7 weeks until 24 months of maturation. Competitive exclusion tests combined with comparative genomic analysis of all genomes of strains of both species available disclosed possible reasons for this successive dominance. The spatial analysis revealed that significantly higher concentrations of acetic acid (from ethanol) and acetoin (from lactic acid) were produced at the tops of the casks, due to higher AAB counts and a higher metabolic activity of the AAB species at the air/liquid interface during the first 6 months of lambic beer production. In contrast, no differences in AAB species diversity occurred throughout the casks. IMPORTANCE Lambic beer is an acidic beer that is the result of a spontaneous fermentation and maturation process. Acidic beers are currently attracting attention worldwide. Part of the acidity of these beers is caused by acetic acid bacteria (AAB). However, due to their difficult recovery, they were never investigated extensively regarding their occurrence, species diversity, and functional role in lambic beer production. In the present study, a framework was developed for their isolation and identification using a novel aseptic sampling method in combination with matrix-assisted laser desorption ionization-time of flight mass spectrometry as a high-throughput dereplication technique followed by accurate molecular identification. The sampling method applied enabled us to take spatial differences into account regarding both enumerations and metabolite production. In this way, it was shown that more AAB were present and more acetic acid was produced at the air/liquid interface during a major part of the lambic beer production process. Also, two different AAB species were encountered, namely, Acetobacter orientalis at the beginning and Acetobacter pasteurianus in a later stage of the production process. This developed framework could also be applied for other fermentation processes. Copyright © 2018 American Society for Microbiology.
[Study on ecological suitability regionalization of Eucommia ulmoides in Guizhou].
Kang, Chuan-Zhi; Wang, Qing-Qing; Zhou, Tao; Jiang, Wei-Ke; Xiao, Cheng-Hong; Xie, Yu
2014-05-01
To study the ecological suitability regionalization of Eucommia ulmoides, for selecting artificial planting base and high-quality industrial raw material purchase area of the herb in Guizhou. Based on the investigation of 14 Eucommia ulmoides producing areas, pinoresinol diglucoside content and ecological factors were obtained. Using spatial analysis method to carry on ecological suitability regionalization. Meanwhile, combining pinoresinol diglucoside content, the correlation of major active components and environmental factors were analyzed by statistical analysis. The most suitability planting area of Eucommia ulmoides was the northwest of Guizhou. The distribution of Eucommia ulmoides was mainly affected by the type and pH value of soil, and monthly precipitation. The spatial structure of major active components in Eucommia ulmoides were randomly distributed in global space, but had only one aggregation point which had a high positive correlation in local space. The major active components of Eucommia ulmoides had no correlation with altitude, longitude or latitude. Using the spatial analysis method and statistical analysis method, based on environmental factor and pinoresinol diglucoside content, the ecological suitability regionalization of Eucommia ulmoides can provide reference for the selection of suitable planting area, artificial planting base and directing production layout.
Spatial entanglement patterns and Einstein-Podolsky-Rosen steering in Bose-Einstein condensates
NASA Astrophysics Data System (ADS)
Fadel, Matteo; Zibold, Tilman; Décamps, Boris; Treutlein, Philipp
2018-04-01
Many-particle entanglement is a fundamental concept of quantum physics that still presents conceptual challenges. Although nonclassical states of atomic ensembles were used to enhance measurement precision in quantum metrology, the notion of entanglement in these systems was debated because the correlations among the indistinguishable atoms were witnessed by collective measurements only. Here, we use high-resolution imaging to directly measure the spin correlations between spatially separated parts of a spin-squeezed Bose-Einstein condensate. We observe entanglement that is strong enough for Einstein-Podolsky-Rosen steering: We can predict measurement outcomes for noncommuting observables in one spatial region on the basis of corresponding measurements in another region with an inferred uncertainty product below the Heisenberg uncertainty bound. This method could be exploited for entanglement-enhanced imaging of electromagnetic field distributions and quantum information tasks.
Martinez, Edson Zangiacomi; Roza, Daiane Leite da; Caccia-Bava, Maria do Carmo Gullaci Guimarães; Achcar, Jorge Alberto; Dal-Fabbro, Amaury Lelis
2011-05-01
Teenage pregnancy is a common public health problem worldwide. The objective of this ecological study was to investigate the spatial association between teenage pregnancy rates and socioeconomic characteristics of municipalities in São Paulo State, Southeast Brazil. We used a Bayesian model with a spatial distribution following a conditional autoregressive (CAR) form based on Markov Chain Monte Carlo algorithm. We used data from the Live Birth Information System (SINASC) and the Brazilian Institute of Geography and Statistics (IBGE). Early pregnancy was more frequent in municipalities with lower per capital gross domestic product (GDP), higher poverty rate, smaller population, lower human development index (HDI), and a higher percentage of individuals with State social vulnerability index of 5 or 6 (more vulnerable). The study demonstrates a significant association between teenage pregnancy and socioeconomic indicators.
NASA Astrophysics Data System (ADS)
Tian, Qingjiu; Chen, Jing M.; Zheng, Guang; Xia, Xueqi; Chen, Junying
2006-09-01
Forest ecosystem is an important component of terrestrial ecosystem and plays an important role in global changes. Aboveground biomass (AGB) of forest ecosystem is an important factor in global carbon cycle studies. The purpose of this study was to retrieve the yearly Net Primary Productivity (NPP) of forest from the 8-days-interval MODIS-LAI images of a year and produce a yearly NPP distribution map. The LAI, DBH (diameter at breast height), tree height, and tree age field were measured in different 80 plots for Chinese fir, Masson pine, bamboo, broadleaf, mix forest in Liping County. Based on the DEM image and Landsat TM images acquired on May 14th, 2000, the geometric correction and terrain correction were taken. In addition, the "6S"model was used to gain the surface reflectance image. Then the correlation between Leaf Area Index (LAI) and Reduced Simple Ratio (RSR) was built. Combined with the Landcover map, forest stand map, the LAI, aboveground biomass, tree age map were produced respectively. After that, the 8-days- interval LAI images of a year, meteorology data, soil data, forest stand image and Landcover image were inputted into the BEPS model to get the NPP spatial distribution. At last, the yearly NPP spatial distribution map with 30m spatial resolution was produced. The values in those forest ecological parameters distribution maps were quite consistent with those of field measurements. So it's possible, feasible and time-saving to estimate forest ecological parameters at a large scale by using remote sensing.
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.
Spatial and temporal distribution of trunk-injected imidacloprid in apple tree canopies.
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.
NASA Astrophysics Data System (ADS)
Menenti, Massimo; Akdim, Nadia; Alfieri, Silvia Maria; Labbassi, Kamal; De Lorenzi, Francesca; Bonfante, Antonello; Basile, Angelo
2014-05-01
Frequent and contiguous observations of soil water content such as the ones to be provided by SMAP are potentially useful to improve distributed models of soil water balance. This requires matching of observations and model estimates provided both sample spatial patterns consistently. The spatial resolution of SMAP soil water content data products ranges from 3 km X 3 km to 40 km X 40 km. Even the highest spatial resolution may not be sufficient to capture the spatial variability due to terrain, soil properties and precipitation. We have evaluated the SMAP spatial resolution against spatial variability of soil water content in two Mediterranean landscapes: a hilly area dominated by vineyards and olive orchards in Central Italy and a large irrigation schemes (Doukkala) in Morocco. The "Valle Telesina" is a 20,000 ha complex landscape located in South Italy in the Campania region, which has a complex geology and geomorphology and it is characterised by an E-W elongated graben where the Calore river flows. The main crops are grapevine (6,448 ha) and olive (3,390 ha). Soil information was mainly derived from an existing soil map at 1:50 000 scale (Terribile et al., 1996). The area includes 47 SMUs (Soil Mapping Units) and about 60 soil typological units (STUs). (Bonfante et al., 2011). In Doukkala, the soil water retention and unsaturated capillary conductivity were estimated from grain size distribution of a number of samples (22 pilot points, each one sampled in 3 horizons of 20cm), and combined with a soil map. The land use classification was carried out using a NDVI time series at high spatial resolution (Landsat TM and SPOT HRV). We have calculated soil water content for each soil unit in each area in response to several climate cases generating daily maps of soil water content at different depths. To reproduce spatial sampling by SMAP we have filtered these spatial patterns by calculating box averages with grid sizes of 1 km X 1 km and 5 km X 5 km. We have repeated this procedure for soil water content in the 0 to 5 cm and 0 to 10 cm depths. For each case we have compared the variance of filtered soil water content with the expected accuracy of SMAP soil water content. The two areas are very different as regards morphology and soil formation. The Valle Telesina is characterized by a very significant variability of soil hydrological properties leading to complex patterns in soil water content. Contrariwise, the soil properties estimated for all soil mapping units in the Dhoukkala collapse into just two pairs of water retention and hydraulic conductivity characteristics, leading to smoother patterns of soil water content.
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
NASA Astrophysics Data System (ADS)
Park, Seonyoung; Im, Jungho; Park, Sumin; Rhee, Jinyoung
2017-04-01
Soil moisture is one of the most important keys for understanding regional and global climate systems. Soil moisture is directly related to agricultural processes as well as hydrological processes because soil moisture highly influences vegetation growth and determines water supply in the agroecosystem. Accurate monitoring of the spatiotemporal pattern of soil moisture is important. Soil moisture has been generally provided through in situ measurements at stations. Although field survey from in situ measurements provides accurate soil moisture with high temporal resolution, it requires high cost and does not provide the spatial distribution of soil moisture over large areas. Microwave satellite (e.g., advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR2), the Advanced Scatterometer (ASCAT), and Soil Moisture Active Passive (SMAP)) -based approaches and numerical models such as Global Land Data Assimilation System (GLDAS) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) provide spatial-temporalspatiotemporally continuous soil moisture products at global scale. However, since those global soil moisture products have coarse spatial resolution ( 25-40 km), their applications for agriculture and water resources at local and regional scales are very limited. Thus, soil moisture downscaling is needed to overcome the limitation of the spatial resolution of soil moisture products. In this study, GLDAS soil moisture data were downscaled up to 1 km spatial resolution through the integration of AMSR2 and ASCAT soil moisture data, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and Moderate Resolution Imaging Spectroradiometer (MODIS) data—Land Surface Temperature, Normalized Difference Vegetation Index, and Land cover—using modified regression trees over East Asia from 2013 to 2015. Modified regression trees were implemented using Cubist, a commercial software tool based on machine learning. An optimization based on pruning of rules derived from the modified regression trees was conducted. Root Mean Square Error (RMSE) and Correlation coefficients (r) were used to optimize the rules, and finally 59 rules from modified regression trees were produced. The results show high validation r (0.79) and low validation RMSE (0.0556m3/m3). The 1 km downscaled soil moisture was evaluated using ground soil moisture data at 14 stations, and both soil moisture data showed similar temporal patterns (average r=0.51 and average RMSE=0.041). The spatial distribution of the 1 km downscaled soil moisture well corresponded with GLDAS soil moisture that caught both extremely dry and wet regions. Correlation between GLDAS and the 1 km downscaled soil moisture during growing season was positive (mean r=0.35) in most regions.
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.
Quantifying discharge uncertainty from remotely sensed precipitation data products in Puerto Rico
NASA Astrophysics Data System (ADS)
Weerasinghe, H.; Raoufi, R.; Yoon, Y.; Beighley, E., II; Alshawabkeh, A.
2014-12-01
Preterm birth is a serious health issue in the United States that contributes to over one-third of all infant deaths. Puerto Rico being one of the hot spots, preliminary research found that the high preterm birth rate can be associated with exposure to some contaminants in water used on daily basis. Puerto Rico has more than 200 contaminated sites including 16 active Superfund sites. Risk of exposure to contaminants is aggravated by unlined landfills lying over the karst regions, highly mobile and dynamic nature of the karst aquifers, and direct contact with surface water through sinkholes and springs. Much of the population in the island is getting water from natural springs or artesian wells that are connected with many of these potentially contaminated karst aquifers. Mobility of contaminants through surface water flows and reservoirs are largely known and are highly correlated with the variations in hydrologic events and conditions. In this study, we quantify the spatial and temporal distribution of Puerto Rico's surface water stores and fluxes to better understand potential impacts on the distribution of groundwater contamination. To quantify and characterize Puerto Rico's surface waters, hydrologic modeling, remote sensing and field measurements are combined. Streamflow measurements are available from 27 U.S. Geological Survey (USGS) gauging stations with drainage areas ranging from 2 to 510 km2. Hillslope River Routing (HRR) model is used to simulate hourly streamflow from watersheds larger than 1 km2 that discharge to ocean. HRR model simulates vertical water balance, lateral surface and subsurface runoff and river discharge. The model consists of 4418 sub-catchments with a mean model unit area (i.e., sub-catchment) of 1.8 km2. Using gauged streamflow measurements for validation, we first assess model results for simulated discharge using three precipitation products: TRMM-3B42 (3 hour temporal resolution, 0.25 degree spatial resolution); NWS stage-III radar rainfall (~ 5 min temporal resolution and 4 km spatial resolution); and gauge measurements from 37 rainfall stations for the period 2000-2012. We then explore methods for combining each product to improve overall model performance. Effects of varied spatial and temporal rainfall resolutions on simulated discharge are also investigated.
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.
Thematic and spatial resolutions affect model-based predictions of tree species distribution.
Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei
2013-01-01
Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.
Thematic and Spatial Resolutions Affect Model-Based Predictions of Tree Species Distribution
Liang, Yu; He, Hong S.; Fraser, Jacob S.; Wu, ZhiWei
2013-01-01
Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution. PMID:23861828
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.
Wan, Jinhong; Yan, Denghua; Fu, Guobin; Hao, Lu; Yue, Yaojie; Li, Ruoxi; Li, Yunpeng; Liu, Jiangang; Deng, Jun
2016-01-01
In China, Zou Zhe (Memorials to the Throne, or Palace Memorials), an official communication to the emperors of China by local officials, offers an opportunity to reconstruct the spatial-temporal distributions of droughts at a high-resolution. A 223-year, 1689–1911, time series of drought events was reconstructed in this study based on 2494 pieces of Zou Zhe. The results show that: 1) on the temporal scale, the drought affected areas, i.e., number of affected counties, showed three peak periods during the last 223 years and nine extreme drought years with more than 300 counties affected have been identified; 2) on the spatial scale, there existed three drought-prone areas in China, i.e., Gansu province and Ningxia Hui Autonomous Region in Northwest China, Shandong, Hebei, and Henan provinces and Tianjin in the North China, and Anhui and Jiangsu provinces in Jianghuai area, respectively; 3) the drought-prone areas have been expanding from North China to South China since the second half of 19th century; 4) on the seasonal scale, summer witnessed the largest number of drought events. Meanwhile, the uncertainties of the results were also discussed, i.e. what caused the spatial-temporal distribution of drought. The results of this study can be used to mitigate the adverse effects of extreme weather events on food increasing and stable production. PMID:26836807
Wan, Jinhong; Yan, Denghua; Fu, Guobin; Hao, Lu; Yue, Yaojie; Li, Ruoxi; Li, Yunpeng; Liu, Jiangang; Deng, Jun
2016-01-01
In China, Zou Zhe (Memorials to the Throne, or Palace Memorials), an official communication to the emperors of China by local officials, offers an opportunity to reconstruct the spatial-temporal distributions of droughts at a high-resolution. A 223-year, 1689-1911, time series of drought events was reconstructed in this study based on 2494 pieces of Zou Zhe. The results show that: 1) on the temporal scale, the drought affected areas, i.e., number of affected counties, showed three peak periods during the last 223 years and nine extreme drought years with more than 300 counties affected have been identified; 2) on the spatial scale, there existed three drought-prone areas in China, i.e., Gansu province and Ningxia Hui Autonomous Region in Northwest China, Shandong, Hebei, and Henan provinces and Tianjin in the North China, and Anhui and Jiangsu provinces in Jianghuai area, respectively; 3) the drought-prone areas have been expanding from North China to South China since the second half of 19th century; 4) on the seasonal scale, summer witnessed the largest number of drought events. Meanwhile, the uncertainties of the results were also discussed, i.e. what caused the spatial-temporal distribution of drought. The results of this study can be used to mitigate the adverse effects of extreme weather events on food increasing and stable production.
Wiltshire, Serge W
2018-01-01
An agent-based computer model that builds representative regional U.S. hog production networks was developed and employed to assess the potential impact of the ongoing trend towards increased producer specialization upon network-level resilience to catastrophic disease outbreaks. Empirical analyses suggest that the spatial distribution and connectivity patterns of contact networks often predict epidemic spreading dynamics. Our model heuristically generates realistic systems composed of hog producer, feed mill, and slaughter plant agents. Network edges are added during each run as agents exchange livestock and feed. The heuristics governing agents' contact patterns account for factors including their industry roles, physical proximities, and the age of their livestock. In each run, an infection is introduced, and may spread according to probabilities associated with the various modes of contact. For each of three treatments-defined by one-phase, two-phase, and three-phase production systems-a parameter variation experiment examines the impact of the spatial density of producer agents in the system upon the length and size of disease outbreaks. Resulting data show phase transitions whereby, above some density threshold, systemic outbreaks become possible, echoing findings from percolation theory. Data analysis reveals that multi-phase production systems are vulnerable to catastrophic outbreaks at lower spatial densities, have more abrupt percolation transitions, and are characterized by less-predictable outbreak scales and durations. Key differences in network-level metrics shed light on these results, suggesting that the absence of potentially-bridging producer-producer edges may be largely responsible for the superior disease resilience of single-phase "farrow to finish" production systems.
Ecosystem classifications based on summer and winter conditions.
Andrew, Margaret E; Nelson, Trisalyn A; Wulder, Michael A; Hobart, George W; Coops, Nicholas C; Farmer, Carson J Q
2013-04-01
Ecosystem classifications map an area into relatively homogenous units for environmental research, monitoring, and management. However, their effectiveness is rarely tested. Here, three classifications are (1) defined and characterized for Canada along summertime productivity (moderate-resolution imaging spectrometer fraction of absorbed photosynthetically active radiation) and wintertime snow conditions (special sensor microwave/imager snow water equivalent), independently and in combination, and (2) comparatively evaluated to determine the ability of each classification to represent the spatial and environmental patterns of alternative schemes, including the Canadian ecozone framework. All classifications depicted similar patterns across Canada, but detailed class distributions differed. Class spatial characteristics varied with environmental conditions within classifications, but were comparable between classifications. There was moderate correspondence between classifications. The strongest association was between productivity classes and ecozones. The classification along both productivity and snow balanced these two sets of variables, yielding intermediate levels of association in all pairwise comparisons. Despite relatively low spatial agreement between classifications, they successfully captured patterns of the environmental conditions underlying alternate schemes (e.g., snow classes explained variation in productivity and vice versa). The performance of ecosystem classifications and the relevance of their input variables depend on the environmental patterns and processes used for applications and evaluation. Productivity or snow regimes, as constructed here, may be desirable when summarizing patterns controlled by summer- or wintertime conditions, respectively, or of climate change responses. General purpose ecosystem classifications should include both sets of drivers. Classifications should be carefully, quantitatively, and comparatively evaluated relative to a particular application prior to their implementation as monitoring and assessment frameworks.
Attributing Crop Production in the United States Using Artificial Neural Network
NASA Astrophysics Data System (ADS)
Ma, Y.; Zhang, Z.; Pan, B.
2017-12-01
Crop production plays key role in supporting life, economy and shaping environment. It is on one hand influenced by natural factors including precipitation, temperature, energy, and on the other hand shaped by the investment of fertilizers, pesticides and human power. Successful attributing of crop production to different factors can help optimize resources and improve productivity. Based on the meteorological records from National Center for Environmental Prediction and state-wise crop production related data provided by the United States Department of Agriculture Economic Research Service, an artificial neural network was constructed to connect crop production with precipitation and temperature anormlies, capital input, labor input, energy input, pesticide consumption and fertilizer consumption. Sensitivity analysis were carried out to attribute their specific influence on crop production for each grid. Results confirmed that the listed factors can generally determine the crop production. Different state response differently to the pertubation of predictands. Their spatial distribution is visulized and discussed.
Production and Distribution of NASA MODIS Remote Sensing Products
NASA Technical Reports Server (NTRS)
Wolfe, Robert
2007-01-01
The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board NASA's Earth Observing System (EOS) Terra and Aqua satellites make key measurements for understanding the Earth's terrestrial ecosystems. Global time-series of terrestrial geophysical parameters have been produced from MODIS/Terra for over 7 years and for MODIS/Aqua for more than 4 1/2 years. These well calibrated instruments, a team of scientists and a large data production, archive and distribution systems have allowed for the development of a new suite of high quality product variables at spatial resolutions as fine as 250m in support of global change research and natural resource applications. This talk describes the MODIS Science team's products, with a focus on the terrestrial (land) products, the data processing approach and the process for monitoring and improving the product quality. The original MODIS science team was formed in 1989. The team's primary role is the development and implementation of the geophysical algorithms. In addition, the team provided feedback on the design and pre-launch testing of the instrument and helped guide the development of the data processing system. The key challenges the science team dealt with before launch were the development of algorithms for a new instrument and provide guidance of the large and complex multi-discipline processing system. Land, Ocean and Atmosphere discipline teams drove the processing system requirements, particularly in the area of the processing loads and volumes needed to daily produce geophysical maps of the Earth at resolutions as fine as 250 m. The processing system had to handle a large number of data products, large data volumes and processing loads, and complex processing requirements. Prior to MODIS, daily global maps from heritage instruments, such as Advanced Very High Resolution Radiometer (AVHRR), were not produced at resolutions finer than 5 km. The processing solution evolved into a combination of processing the lower level (Level 1) products and the higher level discipline specific Land and Atmosphere products in the MODIS Science Investigator Lead Processing System (SIPS), the MODIS Adaptive Processing System (MODAPS), and archive and distribution of the Land products to the user community by two of NASA s EOS Distributed Active Archive Centers (DAACs). Recently, a part of MODAPS, the Level 1 and Atmosphere Archive and Distribution System (LAADS), took over the role of archiving and distributing the Level 1 and Atmosphere products to the user community.
The assessment of Global Precipitation Measurement estimates over the Indian subcontinent
NASA Astrophysics Data System (ADS)
Murali Krishna, U. V.; Das, Subrata Kumar; Deshpande, Sachin M.; Doiphode, S. L.; Pandithurai, G.
2017-08-01
Accurate and real-time precipitation estimation is a challenging task for current and future spaceborne measurements, which is essential to understand the global hydrological cycle. Recently, the Global Precipitation Measurement (GPM) satellites were launched as a next-generation rainfall mission for observing the global precipitation characteristics. The purpose of the GPM is to enhance the spatiotemporal resolution of global precipitation. The main objective of the present study is to assess the rainfall products from the GPM, especially the Integrated Multi-satellitE Retrievals for the GPM (IMERG) data by comparing with the ground-based observations. The multitemporal scale evaluations of rainfall involving subdaily, diurnal, monthly, and seasonal scales were performed over the Indian subcontinent. The comparison shows that the IMERG performed better than the Tropical Rainfall Measuring Mission (TRMM)-3B42, although both rainfall products underestimated the observed rainfall compared to the ground-based measurements. The analyses also reveal that the TRMM-3B42 and IMERG data sets are able to represent the large-scale monsoon rainfall spatial features but are having region-specific biases. The IMERG shows significant improvement in low rainfall estimates compared to the TRMM-3B42 for selected regions. In the spatial distribution, the IMERG shows higher rain rates compared to the TRMM-3B42, due to its enhanced spatial and temporal resolutions. Apart from this, the characteristics of raindrop size distribution (DSD) obtained from the GPM mission dual-frequency precipitation radar is assessed over the complex mountain terrain site in the Western Ghats, India, using the DSD measured by a Joss-Waldvogel disdrometer.
Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling
NASA Astrophysics Data System (ADS)
Sasai, T.; Murakami, K.; Kato, S.; Matsunaga, T.; Saigusa, N.; Hiraki, K.
2015-12-01
Global terrestrial carbon cycle largely depends on a spatial pattern in land cover type, which is heterogeneously-distributed over regional and global scales. However, most studies, which aimed at the estimation of carbon exchanges between ecosystem and atmosphere, remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. In this study, we show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. As methodology for computing the exchanges, we 1) developed a global 1km-grid climate and satellite dataset based on the approach in Setoyama and Sasai (2013); 2) used the satellite-driven biosphere model (Biosphere model integrating Eco-physiological And Mechanistic approaches using Satellite data: BEAMS) (Sasai et al., 2005, 2007, 2011); 3) simulated the carbon exchanges by using the new dataset and BEAMS by the use of a supercomputer that includes 1280 CPU and 320 GPGPU cores (GOSAT RCF of NIES). As a result, we could develop a global uniform system for realistically estimating terrestrial carbon exchange, and evaluate net ecosystem production in each community level; leading to obtain highly detailed understanding of terrestrial carbon exchanges.
Yang, Jinying; Li, Jing; Luan, Xiwu; Zhang, Yunbo; Gu, Guizhou; Xue, Rongrong; Zong, Mingyue; Klotz, Martin G.
2013-01-01
The South China Sea (SCS), the largest marginal sea in the Western Pacific Ocean, is a huge oligotrophic water body with very limited influx of nitrogenous nutrients. This suggests that sediment microbial N2 fixation plays an important role in the production of bioavailable nitrogen. To test the molecular underpinning of this hypothesis, the diversity, abundance, biogeographical distribution, and community structure of the sediment diazotrophic microbiota were investigated at 12 sampling sites, including estuarine, coastal, offshore, deep-sea, and methane hydrate reservoirs or their prospective areas by targeting nifH and some other functional biomarker genes. Diverse and novel nifH sequences were obtained, significantly extending the evolutionary complexity of extant nifH genes. Statistical analyses indicate that sediment in situ temperature is the most significant environmental factor influencing the abundance, community structure, and spatial distribution of the sediment nifH-harboring microbial assemblages in the northern SCS (nSCS). The significantly positive correlation of the sediment pore water NH4+ concentration with the nifH gene abundance suggests that the nSCS sediment nifH-harboring microbiota is active in N2 fixation and NH4+ production. Several other environmental factors, including sediment pore water PO43− concentration, sediment organic carbon, nitrogen and phosphorus levels, etc., are also important in influencing the community structure, spatial distribution, or abundance of the nifH-harboring microbial assemblages. We also confirmed that the nifH genes encoded by archaeal diazotrophs in the ANME-2c subgroup occur exclusively in the deep-sea methane seep areas, providing for the possibility to develop ANME-2c nifH genes as a diagnostic tool for deep-sea methane hydrate reservoir discovery. PMID:23064334
NASA and USGS ASTER Expedited Satellite Data Services for Disaster Situations
NASA Astrophysics Data System (ADS)
Duda, K. A.
2012-12-01
Significant international disasters related to storms, floods, volcanoes, wildfires and numerous other themes reoccur annually, often inflicting widespread human suffering and fatalities with substantial economic consequences. During and immediately after such events it can be difficult to access the affected areas and become aware of the overall impacts, but insight on the spatial extent and effects can be gleaned from above through satellite images. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on the Terra spacecraft has offered such views for over a decade. On short notice, ASTER continues to deliver analysts multispectral imagery at 15 m spatial resolution in near real-time to assist participating responders, emergency managers, and government officials in planning for such situations and in developing appropriate responses after they occur. The joint U.S./Japan ASTER Science Team has developed policies and procedures to ensure such ongoing support is accessible when needed. Processing and distribution of data products occurs at the NASA Land Processes Distributed Active Archive Center (LP DAAC) located at the USGS Earth Resources Observation and Science Center in South Dakota. In addition to current imagery, the long-term ASTER mission has generated an extensive collection of nearly 2.5 million global 3,600 km2 scenes since the launch of Terra in late 1999. These are archived and distributed by LP DAAC and affiliates at Japan Space Systems in Tokyo. Advanced processing is performed to create higher level products of use to researchers. These include a global digital elevation model. Such pre-event imagery provides a comparative basis for use in detecting changes associated with disasters and to monitor land use trends to portray areas of increased risk. ASTER imagery acquired via the expedited collection and distribution process illustrates the utility and relevancy of such data in crisis situations.
Burnet, Jean-Baptiste; Penny, Christian; Ogorzaly, Leslie; Cauchie, Henry-Michel
2014-02-15
Because of their significant public health impact, waterborne Cryptosporidium and Giardia have been monitored in surface water in order to assess microbial quality of water bodies used for drinking water production and/or for recreational purposes. In this context, sampling strategy is of key importance and should be representative enough to appropriately assess the related microbial risk. This, however, requires sound knowledge on the behaviour of both pathogens in water. In the present study, the spatial and temporal distribution of Cryptosporidium and Giardia was explored in the rural Upper-Sûre watershed used for drinking water production in Luxembourg. By subdividing it into three compartments including (i) sub-catchments, (ii) the Sûre River fed by the sub-catchments and (iii) the Upper-Sûre reservoir fed by the Sûre River, parasite distribution was assessed using sampling designs adapted to the hydro-dynamic characteristics of the respective compartments. Results highlighted the high spatial and temporal variability in parasite distribution at watershed scale, as well as the prevalence of Giardia over Cryptosporidium. Besides land use features and catchment characteristics, hydro-climatology appeared to be a major driver of parasite behaviour in the watershed. It introduced a seasonal trend in their occurrence, highest densities being detected during the wet season. Peaks of contamination triggered out by rainfall-induced runoff were further observed in the three compartments. In the Sûre River, Cryptosporidium and Giardia fluxes peaked at 10(9) and 10(10) (oo)cysts.d(-1), respectively, and were discharged into the drinking water reservoir, where they underwent a 2 to 3 log10 removal rate. Despite this, parasite fluxes entering the drinking water treatment plant were still high (10(6) to 10(7) (oo)cysts.d(-1)) and stressed on the need for improved watershed management upstream the water treatment barrier. The catchment-wide analysis described here constitutes a valuable tool for assessment of catchment microbial dynamics, especially within the framework of Water Safety Plans. © 2013.
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.
Spatial and Temporal Distribution of Weeviled Acorns within a Northern Red oak Seedling Orchard
D.R. Miller; S.E. Scharbaum
2004-01-01
Acorn insects can have a severe impact on mass production and regeneration. Gibson (1972) reported losses of 10 to 100 percent of acorn crops in stands of white oak, whereas Gibson (1982) reported losses of up to 96 percent in stands of northern red oak. Acorn insects can be divided into two groups: primary and secondary insects. The primary insects include the...
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.
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 ...
Dongjiao Liu; Hao Jiang; Robin Zhang; Kate S. He
2011-01-01
The spatial distribution of most invasive plants is poorly documented and studied. This project examined and compared the spatial distribution of a successful invasive plant, Japanese honeysuckle (Lonicera japonica), in two similar-sized but ecologically distinct watersheds in western Kentucky (Ledbetter Creek) and western Tennessee (Panther Creek)....
Zhu, Yumin; Zhang, Hua; Shao, Liming; He, Pinjing
2015-01-01
Excessive inter-contamination with heavy metals hampers the application of biological treatment products derived from mixed or mechanically-sorted municipal solid waste (MSW). In this study, we investigated fine particles of <2mm, which are small fractions in MSW but constitute a significant component of the total heavy metal content, using bulk detection techniques. A total of 17 individual fine particles were evaluated using synchrotron radiation-based micro-X-ray fluorescence and micro-X-ray diffraction. We also discussed the association, speciation and source apportionment of heavy metals. Metals were found to exist in a diffuse distribution with heterogeneous intensities and intense hot-spots of <10 μm within the fine particles. Zn-Cu, Pb-Fe and Fe-Mn-Cr had significant correlations in terms of spatial distribution. The overlapped enrichment, spatial association, and the mineral phases of metals revealed the potential sources of fine particles from size-reduced waste fractions (such as scraps of organic wastes or ceramics) or from the importation of other particles. The diverse sources of heavy metal pollutants within the fine particles suggested that separate collection and treatment of the biodegradable waste fraction (such as food waste) is a preferable means of facilitating the beneficial utilization of the stabilized products. Copyright © 2014. Published by Elsevier B.V.
NASA Astrophysics Data System (ADS)
Othman, A.; Sultan, M.; Becker, R.; Sefry, S.; Alharbi, T.; Alharbi, H.; Gebremichael, E.
2017-12-01
Land deformational features (subsidence, and earth fissures, etc.) are being reported from many locations over the Lower Mega Aquifer System (LMAS) in the central and northern parts of Saudi Arabia. We applied an integrated approach (remote sensing, geodesy, GIS, geology, hydrogeology, and geotechnical) to identify nature, intensity, spatial distribution, and factors controlling the observed deformation. A three-fold approach was adopted to accomplish the following: (1) investigate, identify, and verify the land deformation through fieldwork; (2) assess the spatial and temporal distribution of land deformation and quantify deformation rates using Interferometric Synthetic Aperture Radar (InSAR) and Persistent Scatterer Interferometry (PSI) methods (period: 2003 to 2012); (3) generate a GIS database to host all relevant data and derived products (remote sensing, geology, geotechnical, GPS, groundwater extraction rates, and water levels, etc.) and to correlate these spatial and temporal datasets in search of causal effects. The following observations are consistent with deformational features being caused by excessive groundwater extraction: (1) distribution of deformational features correlated spatially and temporally with increased agricultural development and groundwater extraction, and with the decline in groundwater levels and storage; (2) earthquake events (1.5 - 5.5 M) increased from one event at the beginning of the agricultural development program in 1980 (average annual extraction [ANE]: 1-2 km³/yr), to 13 events per year between 1995 to 2005, the decade that witnessed the largest expansion in groundwater extraction (ANE: >6.4 km³) and land reclamation using groundwater resources; and (3) earthquake epicenters and the deformation sites are found largely within areas bound by the Kahf fault system suggesting that faults play a key role in the deformation phenomenon. Findings from the PSI investigation revealed high, yet irregularly distributed, subsidence rates (-4 to -15 mm/yr) along a NW-SE trending graben within the Wadi As-Sirhan Basin in the northern part of LMAS with the highest subsidence rates being localized within elongated bowls, that are proximal to, or bound by, the major faults and that areas to the east and west of the bounding faults show no, or minimal subsidence.
Distributed visualization of gridded geophysical data: the Carbon Data Explorer, version 0.2.3
NASA Astrophysics Data System (ADS)
Endsley, K. A.; Billmire, M. G.
2016-01-01
Due to the proliferation of geophysical models, particularly climate models, the increasing resolution of their spatiotemporal estimates of Earth system processes, and the desire to easily share results with collaborators, there is a genuine need for tools to manage, aggregate, visualize, and share data sets. We present a new, web-based software tool - the Carbon Data Explorer - that provides these capabilities for gridded geophysical data sets. While originally developed for visualizing carbon flux, this tool can accommodate any time-varying, spatially explicit scientific data set, particularly NASA Earth system science level III products. In addition, the tool's open-source licensing and web presence facilitate distributed scientific visualization, comparison with other data sets and uncertainty estimates, and data publishing and distribution.
Rappaz, Benjamin; Cano, Elena; Colomb, Tristan; Kühn, Jonas; Depeursinge, Christian; Simanis, Viesturs; Magistretti, Pierre J; Marquet, Pierre
2009-01-01
Digital holography microscopy (DHM) is an optical technique which provides phase images yielding quantitative information about cell structure and cellular dynamics. Furthermore, the quantitative phase images allow the derivation of other parameters, including dry mass production, density, and spatial distribution. We have applied DHM to study the dry mass production rate and the dry mass surface density in wild-type and mutant fission yeast cells. Our study demonstrates the applicability of DHM as a tool for label-free quantitative analysis of the cell cycle and opens the possibility for its use in high-throughput screening.
Béland, Laurent Karim; Osetsky, Yuri N.; Stoller, Roger E.
2016-06-23
Previous experimental and theoretical studies suggest that the production of extended defect structures by collision cascades is inhibited in equiatomic NiFe, in comparison to pure Ni. It is also known that the production of such extend defect structures results from the formation of subcascades by high-energy recoils and their subsequent interaction. A detailed analysis of the ballistics of 40 keV cascades in Ni and NiFe is performed to identify the formation of such subcascades and to assess their spatial distribution. It is found that subcascades in Ni and NiFe are created with nearly identical energies and distributed similarly in space.more » This suggests that the differences in production of extended defect structures is not related to processes taking place in the ballistic phase of the collision cascade. Lastly, these results can be generalized to other, more chemically complex, concentrated alloys where the elements have similar atomic numbers, such as many high-entropy alloys.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Béland, Laurent Karim; Osetsky, Yuri N.; Stoller, Roger E.
Previous experimental and theoretical studies suggest that the production of extended defect structures by collision cascades is inhibited in equiatomic NiFe, in comparison to pure Ni. It is also known that the production of such extend defect structures results from the formation of subcascades by high-energy recoils and their subsequent interaction. A detailed analysis of the ballistics of 40 keV cascades in Ni and NiFe is performed to identify the formation of such subcascades and to assess their spatial distribution. It is found that subcascades in Ni and NiFe are created with nearly identical energies and distributed similarly in space.more » This suggests that the differences in production of extended defect structures is not related to processes taking place in the ballistic phase of the collision cascade. Lastly, these results can be generalized to other, more chemically complex, concentrated alloys where the elements have similar atomic numbers, such as many high-entropy alloys.« less
NASA Astrophysics Data System (ADS)
Ribera, M.
2016-02-01
Identification of biological hotspots may be a necessary step toward ecosystem-based management goals, as these often signal underlying processes that aggregate or stimulate resources in a particular location. However, previously used metrics to locate these hotspots are not easily adapted to local marine datasets, in part due to the high spatial and temporal variability of phytoplankton populations. While most fish species in temperate regions are well adapted to the seasonal variability of phytoplankton abundance, it is the variability beyond this predictable pattern (i.e. anomalies) that may heavily impact the abundance and spatial distribution of organisms higher up the food chain. The objective of this study was to identify local-scale biological hotspots in a region in the western side of the Gulf of Maine using remote sensing chlorophyll-a data (from MERIS sensor), and to study the spatial overlap between these hotspots and high concentrations of fish abundance (derived from VTR dataset). For this reason, we defined a new hotspot metric that identified as a hotspot any area that consistently exhibited high-magnitude anomalies through time, a sign of highly dynamic communities. We improved on previous indices by minimizing the effect that different means and variances across space may have on the results, a situation that often occurs when comparing coastal and offshore systems. Results show a significant spatial correlation between pelagic fish abundance and aggregations of primary productivity. Spatial correlations were also significant between benthic fish abundance and primary productivity hotspots, but only during spring months. We argue that this new hotspot index compliments existing global measures as it helps managers understand the dynamic characteristics of a complex marine system. It also provides a unique metric that is easily compared across space and between different trophic levels, which may facilitate future ecosystem-wide studies.
NASA Astrophysics Data System (ADS)
Ribera, M.
2016-12-01
Identification of biological hotspots may be a necessary step toward ecosystem-based management goals, as these often signal underlying processes that aggregate or stimulate resources in a particular location. However, previously used metrics to locate these hotspots are not easily adapted to local marine datasets, in part due to the high spatial and temporal variability of phytoplankton populations. While most fish species in temperate regions are well adapted to the seasonal variability of phytoplankton abundance, it is the variability beyond this predictable pattern (i.e. anomalies) that may heavily impact the abundance and spatial distribution of organisms higher up the food chain. The objective of this study was to identify local-scale biological hotspots in a region in the western side of the Gulf of Maine using remote sensing chlorophyll-a data (from MERIS sensor), and to study the spatial overlap between these hotspots and high concentrations of fish abundance (derived from VTR dataset). For this reason, we defined a new hotspot metric that identified as a hotspot any area that consistently exhibited high-magnitude anomalies through time, a sign of highly dynamic communities. We improved on previous indices by minimizing the effect that different means and variances across space may have on the results, a situation that often occurs when comparing coastal and offshore systems. Results show a significant spatial correlation between pelagic fish abundance and aggregations of primary productivity. Spatial correlations were also significant between benthic fish abundance and primary productivity hotspots, but only during spring months. We argue that this new hotspot index compliments existing global measures as it helps managers understand the dynamic characteristics of a complex marine system. It also provides a unique metric that is easily compared across space and between different trophic levels, which may facilitate future ecosystem-wide studies.
Spatial interactions among ecosystem services in an urbanizing agricultural watershed
Qiu, Jiangxiao; Turner, Monica G.
2013-01-01
Understanding spatial distributions, synergies, and tradeoffs of multiple ecosystem services (benefits people derive from ecosystems) remains challenging. We analyzed the supply of 10 ecosystem services for 2006 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked the following: (i) Where are areas of high and low supply of individual ecosystem services, and are these areas spatially concordant across services? (ii) Where on the landscape are the strongest tradeoffs and synergies among ecosystem services located? (iii) For ecosystem service pairs that experience tradeoffs, what distinguishes locations that are “win–win” exceptions from other locations? Spatial patterns of high supply for multiple ecosystem services often were not coincident; locations where six or more services were produced at high levels (upper 20th percentile) occupied only 3.3% of the landscape. Most relationships among ecosystem services were synergies, but tradeoffs occurred between crop production and water quality. Ecosystem services related to water quality and quantity separated into three different groups, indicating that management to sustain freshwater services along with other ecosystem services will not be simple. Despite overall tradeoffs between crop production and water quality, some locations were positive for both, suggesting that tradeoffs are not inevitable everywhere and might be ameliorated in some locations. Overall, we found that different areas of the landscape supplied different suites of ecosystem services, and their lack of spatial concordance suggests the importance of managing over large areas to sustain multiple ecosystem services. PMID:23818612
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Shaoqing; Zhuang, Qianlai; Chen, Min
Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO 2) concentration data at the global scale. However, high-precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 tomore » 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr –1 and 0.08 Pg C•yr –1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less
Spatial interactions among ecosystem services in an urbanizing agricultural watershed.
Qiu, Jiangxiao; Turner, Monica G
2013-07-16
Understanding spatial distributions, synergies, and tradeoffs of multiple ecosystem services (benefits people derive from ecosystems) remains challenging. We analyzed the supply of 10 ecosystem services for 2006 across a large urbanizing agricultural watershed in the Upper Midwest of the United States, and asked the following: (i) Where are areas of high and low supply of individual ecosystem services, and are these areas spatially concordant across services? (ii) Where on the landscape are the strongest tradeoffs and synergies among ecosystem services located? (iii) For ecosystem service pairs that experience tradeoffs, what distinguishes locations that are "win-win" exceptions from other locations? Spatial patterns of high supply for multiple ecosystem services often were not coincident; locations where six or more services were produced at high levels (upper 20th percentile) occupied only 3.3% of the landscape. Most relationships among ecosystem services were synergies, but tradeoffs occurred between crop production and water quality. Ecosystem services related to water quality and quantity separated into three different groups, indicating that management to sustain freshwater services along with other ecosystem services will not be simple. Despite overall tradeoffs between crop production and water quality, some locations were positive for both, suggesting that tradeoffs are not inevitable everywhere and might be ameliorated in some locations. Overall, we found that different areas of the landscape supplied different suites of ecosystem services, and their lack of spatial concordance suggests the importance of managing over large areas to sustain multiple ecosystem services.
Liu, Shaoqing; Zhuang, Qianlai; Chen, Min; ...
2016-07-25
Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO 2) concentration data at the global scale. However, high-precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 tomore » 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr –1 and 0.08 Pg C•yr –1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less
Characterization of water bodies for mosquito habitat using a multi-sensor approach
NASA Astrophysics Data System (ADS)
Midekisa, A.; Wimberly, M. C.; Senay, G. B.
2012-12-01
Malaria is a major health problem in Ethiopia. Anopheles arabiensis, which inhabits and breeds in a variety of aquatic habitats, is the major mosquito vector for malaria transmission in the region. In the Amhara region of Ethiopia, mosquito breeding sites are heterogeneously distributed. Therefore, accurate characterization of aquatic habitats and potential breeding sites can be used as a proxy to measure the spatial distribution of malaria risk. Satellite remote sensing provides the ability to map the spatial distribution and monitor the temporal dynamics of surface water. The objective of this study is to map the probability of surface water accumulation to identify potential vector breeding sites for Anopheles arabiensis using remote sensing data from sensors at multiple spatial and temporal resolutions. The normalized difference water index (NDWI), which is based on reflectance in the green and the near infrared (NIR) bands were used to estimate fractional cover of surface water. Temporal changes in surface water were mapped using NDWI indices derived from MODIS surface reflectance product (MOD09A1) for the period 2001-2012. Landsat TM and ETM+ imagery were used to train and calibrate model results from MODIS. Results highlighted interannual variation and seasonal changes in surface water that were observed from the MODIS time series. Static topographic indices that estimate the potential for water accumulation were generated from 30 meter Shuttle Radar Topography Mission (SRTM) elevation data. Integrated fractional surface water cover was developed by combining the static topographic indices and dynamic NDWI indices using Geographic Information System (GIS) overlay methods. Accuracy of the results was evaluated based on ground truth data that was collected on presence and absence of surface water immediately after the rainy season. The study provided a multi-sensor approach for mapping areas with a high potential for surface water accumulation that are potential breeding habitats for anopheline mosquitoes. The resulting products are useful for public health decision making towards effective prevention and control of the malaria burden in the Amhara region of Ethiopia.